The Federal Trade Commission (FTC) said it is using \u201call the tools at its disposal\u201d to oversee the rise of artificial intelligence (AI) technologies.
\nThe commission made that statement Wednesday (July 31) when submitting comments to the Federal Communications Commission (FCC) about its efforts in the AI space.
\nThe FTC is working \u201cto address the rapid emergence of new technologies powered by AI and their potential risks to consumers and businesses,\u201d it said, taking \u201caction against companies that deceive users about their use of AI or use AI in unfair ways.\u201d
\nThe commission gives the example of its allegation that Amazon and Ring used private data \u2014 voice recordings collected by Amazon\u2019s Alexa voice assistant and videos collected by Ring\u2019s internet-connected home security cameras \u2014 to train their algorithms while violating customers\u2019 privacy.
\nRing reached a $5.8 million settlement with the FTC last year. The commission has also been investigating recent AI efforts by Big Tech companies, such as Amazon\u2019s relationship with the AI firm Adept and Microsoft\u2019s hiring of the leadership of Inflection AI.
\nThe FTC also pointed to its efforts to combat AI-powered voice cloning, noting that scammers are using this \u201ctechnology to impersonate family or friends, business executives or others to obtain money from consumers.\u201d
\nThe FCC in February voted to make it illegal for companies to use AI-generated voices in robocalls, a ruling that gives state attorneys general another tool to use against voice cloning scams: they can they can prosecute fraudsters for not only the scam but also for using AI to generate the voice in the robocall.
\n\u201cWe\u2019re putting the fraudsters behind these robocalls on notice,\u201d FCC Chairwoman Jessica Rosenworcel said in a news release. \u201cState Attorneys General will now have new tools to crack down on these scams and ensure the public is protected from fraud and misinformation.\u201d
\nLast week, the FTC joined its counterparts from the European Union and the United Kingdom in issuing a rare joint statement about potential antitrust issues in the AI field.
\nThe statement outlined concerns about market concentration and anti-competitive practices in generative AI \u2014 the technology fueling popular chatbots like ChatGPT.
\n\u201cThere are risks that firms may attempt to restrict key inputs for the development of AI technologies,\u201d the regulators warned, highlighting the need for quick action in the rapidly evolving sector.
\nThe post FTC Pledges \u2018All the Tools at Its Disposal\u2019 to Govern AI appeared first on PYMNTS.com.
\n", "content_text": "The Federal Trade Commission (FTC) said it is using \u201call the tools at its disposal\u201d to oversee the rise of artificial intelligence (AI) technologies.\nThe commission made that statement Wednesday (July 31) when submitting comments to the Federal Communications Commission (FCC) about its efforts in the AI space.\nThe FTC is working \u201cto address the rapid emergence of new technologies powered by AI and their potential risks to consumers and businesses,\u201d it said, taking \u201caction against companies that deceive users about their use of AI or use AI in unfair ways.\u201d\nThe commission gives the example of its allegation that Amazon and Ring used private data \u2014 voice recordings collected by Amazon\u2019s Alexa voice assistant and videos collected by Ring\u2019s internet-connected home security cameras \u2014 to train their algorithms while violating customers\u2019 privacy.\nRing reached a $5.8 million settlement with the FTC last year. The commission has also been investigating recent AI efforts by Big Tech companies, such as Amazon\u2019s relationship with the AI firm Adept and Microsoft\u2019s hiring of the leadership of Inflection AI.\nThe FTC also pointed to its efforts to combat AI-powered voice cloning, noting that scammers are using this \u201ctechnology to impersonate family or friends, business executives or others to obtain money from consumers.\u201d\nThe FCC in February voted to make it illegal for companies to use AI-generated voices in robocalls, a ruling that gives state attorneys general another tool to use against voice cloning scams: they can they can prosecute fraudsters for not only the scam but also for using AI to generate the voice in the robocall.\n\u201cWe\u2019re putting the fraudsters behind these robocalls on notice,\u201d FCC Chairwoman Jessica Rosenworcel said in a news release. \u201cState Attorneys General will now have new tools to crack down on these scams and ensure the public is protected from fraud and misinformation.\u201d\nLast week, the FTC joined its counterparts from the European Union and the United Kingdom in issuing a rare joint statement about potential antitrust issues in the AI field.\nThe statement outlined concerns about market concentration and anti-competitive practices in generative AI \u2014 the technology fueling popular chatbots like ChatGPT.\n\u201cThere are risks that firms may attempt to restrict key inputs for the development of AI technologies,\u201d the regulators warned, highlighting the need for quick action in the rapidly evolving sector.\nThe post FTC Pledges \u2018All the Tools at Its Disposal\u2019 to Govern AI appeared first on PYMNTS.com.", "date_published": "2024-07-31T18:33:34-04:00", "date_modified": "2024-07-31T23:05:59-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2023/07/FTC-6.jpg", "tags": [ "AI", "AI regulation", "artificial intelligence", "FCC", "Federal Communications Commission", "Federal Trade Commission", "FTC", "News", "PYMNTS News", "regulations", "TechREG", "What's Hot", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2020104", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/ai-integration-drives-revenue-streams-for-tech-giants/", "title": "AI Integration Drives Revenue Streams for Tech Giants", "content_html": "Major technology companies are embedding artificial intelligence (AI) into their core products and services, creating new revenue opportunities and enhancing user experiences.
\nIntegrating AI across various sectors marks a shift in how companies monetize technology and engage with users. From search engines and productivity tools to freelance marketplaces, AI is becoming a key differentiator and revenue driver. This trend is reshaping business models and consumer interactions while also raising questions about the future of work and the implications of AI deployment.
\n\u201cCompanies are increasingly focusing their AI spending on developing lightweight and compressed models, which are crucial for efficient deployment in resource-constrained environments,\u201d Jiahao Sun, CEO at Flock.io, told PYMNTS.
\nGoogle has been integrating AI capabilities into its search engine through initiatives like Search Generative Experience (SGE). Google CEO Sundar Pichai has emphasized, \u201cAI is the most profound technology we are working on today.\u201d
\nNot to be outdone, Microsoft has launched Copilot, an AI assistant embedded across its Office suite, charging enterprise users $30 per person per month. Microsoft CEO Satya Nadella noted, \u201cCopilot is already improving productivity for more than 40% of the Fortune 100 who participated in our early access program.\u201d
\nAmazon leverages AI for personalized product recommendations and search results. In a shareholder letter, Amazon CEO Andy Jassy stated, \u201cWe’re investing heavily in large language models and generative AI across our businesses.\u201d
\n\u201cGenerative AI will significantly impact how people discover topics on the internet, such as asking ChatGPT for recommendations rather than browsing through search rankings and reviews,\u201d Brad Null, head of AI at Reputation, told PYMNTS. He added, \u201cAI will consume all of the information out there about a business to make such recommendations, so brands will need to stay on top of those advancements, especially when it comes to their search strategy.\u201d
\nIndustry experts are expressing optimism about AI\u2019s potential in the commerce sector while warning of hurdles in its implementation. Their insights paint a picture of an industry on the cusp of major change, grappling with both excitement and caution.
\nSun highlighted AI\u2019s capabilities. \u201cAdvancements in AI, particularly in large language models [LLMs] and machine learning [ML], are poised to revolutionize the commerce sector by automating a wide range of processes,” he stated. This automation, Sun suggested, could streamline operations across the board, from inventory management to customer service.
\nAI could enhance customer insights. Null said, \u201cFor years, we have had tools that mine customer feedback data to surface insights about brands. With new advancements in AI, these tools are getting increasingly more powerful, helping us more quickly aggregate feedback, discover emerging themes, and surface more actionable insights.\u201d This improved ability to understand and respond to customer needs could give businesses a competitive edge.
\nHowever, both experts quickly pointed out that the road to AI integration is fraught with challenges. Sun highlighted the financial barriers, stating, \u201cThere are high API fees associated with using centralized AI services, which can quickly escalate as usage scales.\u201d
\nHe added, \u201cCompanies must frequently upgrade their hardware, particularly GPUs, to keep up with the latest AI developments and model requirements.\u201d These costs could prove prohibitive for smaller businesses or those operating on tight margins.
\nData management remains a critical issue, even as AI capabilities advance. \u201cThe biggest challenge today is the same as what it was five years ago, getting the most useful, actionable data and positioning it so that you can maximize value from that data,\u201d Null said. This sentiment underscores the importance of not just having data but also having it in a format that AI can effectively use.
\nHe elaborated on this point, saying, \u201cIf you don\u2019t already have the data you need, and have it formatted in a way that it is easy to leverage \u2014 meaning, if you haven\u2019t already applied AI and ML to your data \u2014 then you probably have a lot of work to do to gather and position this data before using it to find consumer insights.\u201d This suggests that many businesses face a preparatory phase before leveraging AI\u2019s capabilities.
\nThe post AI Integration Drives Revenue Streams for Tech Giants appeared first on PYMNTS.com.
\n", "content_text": "Major technology companies are embedding artificial intelligence (AI) into their core products and services, creating new revenue opportunities and enhancing user experiences.\nIntegrating AI across various sectors marks a shift in how companies monetize technology and engage with users. From search engines and productivity tools to freelance marketplaces, AI is becoming a key differentiator and revenue driver. This trend is reshaping business models and consumer interactions while also raising questions about the future of work and the implications of AI deployment.\n\u201cCompanies are increasingly focusing their AI spending on developing lightweight and compressed models, which are crucial for efficient deployment in resource-constrained environments,\u201d Jiahao Sun, CEO at Flock.io, told PYMNTS.\nTech Giants Lead AI Monetization\nGoogle has been integrating AI capabilities into its search engine through initiatives like Search Generative Experience (SGE). Google CEO Sundar Pichai has emphasized, \u201cAI is the most profound technology we are working on today.\u201d\nNot to be outdone, Microsoft has launched Copilot, an AI assistant embedded across its Office suite, charging enterprise users $30 per person per month. Microsoft CEO Satya Nadella noted, \u201cCopilot is already improving productivity for more than 40% of the Fortune 100 who participated in our early access program.\u201d\nAmazon leverages AI for personalized product recommendations and search results. In a shareholder letter, Amazon CEO Andy Jassy stated, \u201cWe’re investing heavily in large language models and generative AI across our businesses.\u201d\n\u201cGenerative AI will significantly impact how people discover topics on the internet, such as asking ChatGPT for recommendations rather than browsing through search rankings and reviews,\u201d Brad Null, head of AI at Reputation, told PYMNTS. He added, \u201cAI will consume all of the information out there about a business to make such recommendations, so brands will need to stay on top of those advancements, especially when it comes to their search strategy.\u201d\nIndustry experts are expressing optimism about AI\u2019s potential in the commerce sector while warning of hurdles in its implementation. Their insights paint a picture of an industry on the cusp of major change, grappling with both excitement and caution.\nSun highlighted AI\u2019s capabilities. \u201cAdvancements in AI, particularly in large language models [LLMs] and machine learning [ML], are poised to revolutionize the commerce sector by automating a wide range of processes,” he stated. This automation, Sun suggested, could streamline operations across the board, from inventory management to customer service.\nAI could enhance customer insights. Null said, \u201cFor years, we have had tools that mine customer feedback data to surface insights about brands. With new advancements in AI, these tools are getting increasingly more powerful, helping us more quickly aggregate feedback, discover emerging themes, and surface more actionable insights.\u201d This improved ability to understand and respond to customer needs could give businesses a competitive edge.\nHowever, both experts quickly pointed out that the road to AI integration is fraught with challenges. Sun highlighted the financial barriers, stating, \u201cThere are high API fees associated with using centralized AI services, which can quickly escalate as usage scales.\u201d\n He added, \u201cCompanies must frequently upgrade their hardware, particularly GPUs, to keep up with the latest AI developments and model requirements.\u201d These costs could prove prohibitive for smaller businesses or those operating on tight margins.\nData management remains a critical issue, even as AI capabilities advance. \u201cThe biggest challenge today is the same as what it was five years ago, getting the most useful, actionable data and positioning it so that you can maximize value from that data,\u201d Null said. This sentiment underscores the importance of not just having data but also having it in a format that AI can effectively use.\nHe elaborated on this point, saying, \u201cIf you don\u2019t already have the data you need, and have it formatted in a way that it is easy to leverage \u2014 meaning, if you haven\u2019t already applied AI and ML to your data \u2014 then you probably have a lot of work to do to gather and position this data before using it to find consumer insights.\u201d This suggests that many businesses face a preparatory phase before leveraging AI\u2019s capabilities.\nThe post AI Integration Drives Revenue Streams for Tech Giants appeared first on PYMNTS.com.", "date_published": "2024-07-31T18:10:59-04:00", "date_modified": "2024-07-31T18:10:59-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2024/07/Google-AI-overviews-1.jpg", "tags": [ "AI", "AI search", "Amazon", "Andy Jassy", "artificial intelligence", "Brad Null", "Copilot", "data analysis", "data management", "FLock.io", "GenAI", "generative AI", "Google", "Jiahao Sun", "machine learning", "Microsoft", "ML", "News", "PYMNTS News", "reputation", "Satya Nadella", "Sundar Pichai", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2019684", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/apples-ai-makeover-begins-with-developer-beta-release-and-siri/", "title": "Apple\u2019s AI Makeover Begins With Developer Beta Release and Siri", "content_html": "Apple launched its first wave of artificial intelligence-enhanced software betas for developers on Monday (July 29), marking its push into AI-driven mobile commerce and potentially reshaping how millions of users interact with their devices.
\nThe release of developer betas for iOS 18.1, iPadOS 18.1, and macOS Sequoia 15.1 introduces many of the Apple Intelligence capabilities previewed at WWDC 2024. This move signals Apple\u2019s intent to transform the mobile commerce landscape, altering how consumers search for products, make purchasing decisions and communicate with brands.
\n\u201cApple\u2019s been a bit behind in the AI race,\u201d Bob Rogers, data scientist and CEO of Oii.ai, told PYMNTS. \u201cBy enhancing Siri and summaries with AI, I think users will be able to take advantage of \u2018conversational\u2019 searching.\u201d
\nThe new betas include writing tools, natural language search capabilities for Photos, priority message sorting for Mail and Siri improvements across iPhone, iPad and Mac platforms. Future updates are expected to include some anticipated features, such as Image Playground and Genemoji.
\nThe advancement in voice search capabilities could significantly streamline the shopping process. Steven Athwal, CEO and founder of The Big Phone Store, told PYMNTS, \u201cUsers can speak naturally and conversationally, meaning searches are less focused on hitting keywords. So it\u2019s faster and easier to find what they need, and search is done quicker.\u201d
\nThis improvement addresses current limitations in Siri\u2019s capabilities. Rogers pointed out, \u201cRight now, Siri is a tad lacking, often answering \u2018here\u2019s what I found on the web\u2019 when you ask it anything more complex than the current time or weather.\u201d
\nThe potential for more personalized shopping experiences is a key feature of the new AI capabilities. \u201cSiri\u2019s contextual awareness understands follow-up questions and gives accurate results based on previous searches, so a more personalized experience and targeted ads can be implemented,\u201d Athwal said.
\nAI-generated summaries could also streamline product comparisons. Rogers said, \u201cThe AI-generated summaries will help consumers compare products they\u2019re searching for via Siri much easier since it can aggregate product details, reviews, pricing, and more.\u201d Athwal noted this could drive companies to offer more competitive prices to be suggested first by AI\u2019s comparative pricing.
\nThese advancements could improve business communication. \u201cAI-driven responses are personal to customers based on their data, preferences, and previous interactions … so you get more advanced and relevant offers,\u201d Athwal said. He also highlighted the potential for \u201cmulti-lingual capabilities through AI translation,\u201d allowing businesses to \u201cexpand globally much easier.\u201d
\nIntegrating AI in customer service could also lead to more consistent support. Athwal noted, \u201cSupport is available 24/7 with a consistent tone and high standard of service, ensuring that real people are not subjected to potential verbal abuse from customers.\u201d
\nThese tools could also provide valuable insights. \u201cBy collecting and analyzing customer interactions and speech patterns, businesses can find out what customers are really looking for, what are the trends and needs?\u201d Athwal said.
\nThis separate x. 1 beta confirms the staggered release of Apple Intelligence features, which aligns with recent reports that these capabilities won\u2019t be part of the initial iOS 18, iPadOS 18, and macOS Sequoia releases. Instead, they\u2019re slated for subsequent updates, likely following public betas expected later this summer.
\nAs Apple ventures further into the AI realm, the impact on mobile commerce and customer interactions could be profound. However, concerns about potential e-waste issues have been raised. Athwal warned, \u201cAs new features are introduced, the demand for older models will dwindle, and we’ll have an even bigger e-waste problem than we already do.\u201d
\nYet, the promise of increased productivity may drive upgrades. \u201cNew features can increase productivity, and with smarter organizational tools, workflow, and efficiency will be increased in those who choose to upgrade,\u201d Athwal said.
\nThe rollout of these features not only reshapes the digital marketplace landscape but also raises questions about consumer behavior, device longevity and the pace of technological advancement. Athwal pondered, \u201cAn upgrade may seem like a long-term investment but how long before the latest models become outdated? A few years or just a few months?\u201d
\nAs Apple\u2019s AI push unfolds, the mobile commerce landscape is clearly on the brink of significant change, with implications that reach far beyond simple software updates.
\nFor all PYMNTS AI coverage, subscribe to the daily\u00a0AI\u00a0Newsletter.
\nThe post Apple\u2019s AI Makeover Begins With Developer Beta Release and Siri appeared first on PYMNTS.com.
\n", "content_text": "Apple launched its first wave of artificial intelligence-enhanced software betas for developers on Monday (July 29), marking its push into AI-driven mobile commerce and potentially reshaping how millions of users interact with their devices.\nThe release of developer betas for iOS 18.1, iPadOS 18.1, and macOS Sequoia 15.1 introduces many of the Apple Intelligence capabilities previewed at WWDC 2024. This move signals Apple\u2019s intent to transform the mobile commerce landscape, altering how consumers search for products, make purchasing decisions and communicate with brands.\n\u201cApple\u2019s been a bit behind in the AI race,\u201d Bob Rogers, data scientist and CEO of Oii.ai, told PYMNTS. \u201cBy enhancing Siri and summaries with AI, I think users will be able to take advantage of \u2018conversational\u2019 searching.\u201d\nAI Features Debut in Beta\nThe new betas include writing tools, natural language search capabilities for Photos, priority message sorting for Mail and Siri improvements across iPhone, iPad and Mac platforms. Future updates are expected to include some anticipated features, such as Image Playground and Genemoji.\nThe advancement in voice search capabilities could significantly streamline the shopping process. Steven Athwal, CEO and founder of The Big Phone Store, told PYMNTS, \u201cUsers can speak naturally and conversationally, meaning searches are less focused on hitting keywords. So it\u2019s faster and easier to find what they need, and search is done quicker.\u201d\nThis improvement addresses current limitations in Siri\u2019s capabilities. Rogers pointed out, \u201cRight now, Siri is a tad lacking, often answering \u2018here\u2019s what I found on the web\u2019 when you ask it anything more complex than the current time or weather.\u201d\nThe potential for more personalized shopping experiences is a key feature of the new AI capabilities. \u201cSiri\u2019s contextual awareness understands follow-up questions and gives accurate results based on previous searches, so a more personalized experience and targeted ads can be implemented,\u201d Athwal said.\nAI-generated summaries could also streamline product comparisons. Rogers said, \u201cThe AI-generated summaries will help consumers compare products they\u2019re searching for via Siri much easier since it can aggregate product details, reviews, pricing, and more.\u201d Athwal noted this could drive companies to offer more competitive prices to be suggested first by AI\u2019s comparative pricing.\nReshaping Business Communication\nThese advancements could improve business communication. \u201cAI-driven responses are personal to customers based on their data, preferences, and previous interactions … so you get more advanced and relevant offers,\u201d Athwal said. He also highlighted the potential for \u201cmulti-lingual capabilities through AI translation,\u201d allowing businesses to \u201cexpand globally much easier.\u201d\nIntegrating AI in customer service could also lead to more consistent support. Athwal noted, \u201cSupport is available 24/7 with a consistent tone and high standard of service, ensuring that real people are not subjected to potential verbal abuse from customers.\u201d\nThese tools could also provide valuable insights. \u201cBy collecting and analyzing customer interactions and speech patterns, businesses can find out what customers are really looking for, what are the trends and needs?\u201d Athwal said.\nThis separate x. 1 beta confirms the staggered release of Apple Intelligence features, which aligns with recent reports that these capabilities won\u2019t be part of the initial iOS 18, iPadOS 18, and macOS Sequoia releases. Instead, they\u2019re slated for subsequent updates, likely following public betas expected later this summer.\nAs Apple ventures further into the AI realm, the impact on mobile commerce and customer interactions could be profound. However, concerns about potential e-waste issues have been raised. Athwal warned, \u201cAs new features are introduced, the demand for older models will dwindle, and we’ll have an even bigger e-waste problem than we already do.\u201d\nYet, the promise of increased productivity may drive upgrades. \u201cNew features can increase productivity, and with smarter organizational tools, workflow, and efficiency will be increased in those who choose to upgrade,\u201d Athwal said.\nThe rollout of these features not only reshapes the digital marketplace landscape but also raises questions about consumer behavior, device longevity and the pace of technological advancement. Athwal pondered, \u201cAn upgrade may seem like a long-term investment but how long before the latest models become outdated? A few years or just a few months?\u201d\nAs Apple\u2019s AI push unfolds, the mobile commerce landscape is clearly on the brink of significant change, with implications that reach far beyond simple software updates.\n\nFor all PYMNTS AI coverage, subscribe to the daily\u00a0AI\u00a0Newsletter.\n\nThe post Apple\u2019s AI Makeover Begins With Developer Beta Release and Siri appeared first on PYMNTS.com.", "date_published": "2024-07-31T09:00:19-04:00", "date_modified": "2024-07-31T08:45:01-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2024/07/Apple-AI-beta.png", "tags": [ "AI", "Apple", "Apple Intelligence", "artificial intelligence", "iPhones", "mobile commerce", "News", "Oii.ai", "PYMNTS News", "search engines", "Technology", "The Big Phone Store", "voice search", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2019568", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/microsoft-bets-big-on-ai-as-demand-surges-across-cloud-and-software-businesses/", "title": "Microsoft Bets Big on AI as Demand Surges Across Cloud and Software Businesses", "content_html": "Microsoft is doubling down on artificial intelligence (AI) as a driver of growth. During the company\u2019s fiscal fourth-quarter earnings call on Tuesday (July 30), executives described surging demand for AI services across its cloud and software portfolio.
\nThe tech giant reported that Azure AI, its cloud-based AI platform, grew 30% year-over-year and now accounts for 8 percentage points of Azure\u2019s overall growth. This comes as Microsoft grapples with capacity constraints in meeting the explosive demand for AI services.
\n\u201cAzure growth included eight points from AI services, where demand remained higher than our available capacity,\u201d said Amy Hood, Microsoft\u2019s chief financial officer. She added that the company expects \u201cAzure growth to accelerate as our capital investments create an increase in available AI capacity to serve more of the growing demand\u201d in the second half of fiscal year 2025.
\nTo meet this demand, Microsoft is ramping up its capital expenditures. Hood revealed that about half of the company\u2019s capital spending is on \u201cland and builds and finance leases\u201d for data centers, investments that will \u201cbe monetized over 15 years and beyond.\u201d The other half is dedicated to \u201cCPUs and GPUs to serve customers based on demand signals.\u201d
\nThe company stated it expects capital expenditures to increase in fiscal year 2025 to support growing AI and cloud demand but did not give a precise figure.
\nSatya Nadella, Microsoft\u2019s CEO, emphasized the company\u2019s focus on capturing the AI opportunity: \u201cWe are investing for the long term in our fundamentals, in our innovation, and in our people.\u201d He likened the current AI transition to the earlier shift to cloud computing, describing both as \u201cknowledge and capital-intensive investments.\u201d
\nMicrosoft saw revenue soaring 15% to $64.7 billion and net income jumping 10% to $22 billion. The company\u2019s cloud juggernaut, Azure, led the charge with a 29% revenue surge. Executives touted AI leadership and highlighted record bookings, with Microsoft Cloud revenue hitting $36.8 billion. The Intelligent Cloud segment was the star performer, growing 19% to $28.5 billion. Even gaming got a boost, with Xbox content and services revenue skyrocketing 61%, thanks largely to the Activision acquisition. With these results, Microsoft wrapped up the fiscal year 2024 boasting $245.1 billion in revenue and $88.1 billion in net income, both up over 20% year-over-year.
\nThe impact of AI is being felt across Microsoft\u2019s product lines. Nadella highlighted the success of Copilot for Microsoft 365, the company\u2019s AI-powered assistant for productivity software.
\n\u201cThe number of people who use Copilot daily at work nearly doubled quarter over quarter,\u201d he said, adding that \u201cCopilot customers increased more than 60% quarter over quarter.\u201d
\nPerhaps most telling was Nadella\u2019s revelation about GitHub Copilot, the company\u2019s AI pair programming tool: \u201cCopilot accounted for over 40% of GitHub revenue growth this year, and is already a larger business than all of GitHub was when we acquired it.\u201d
\nThis success in developer tools appears to be a blueprint for Microsoft\u2019s broader AI strategy. Nadella explained, \u201cWhat used to be line of business applications to us are Copilot extensions going forward. So we think of this as really a new design system for knowledge and frontline work to drive productivity, which will be very akin to what has happened in software engineering.\u201d
\nThe company sees potential for AI to transform various business functions. \u201cWhen you think about marketing or finance or sales or customer service, we\u2019ll effectively replicate what you just said, which is the type of productivity we\u2019ve seen in developers will come to all of these functions,\u201d Nadella predicted.
\nMicrosoft\u2019s AI push extends to its Dynamics 365 business applications as well. Nadella pointed to the contact center as an area ripe for AI-driven transformation: \u201cWe ourselves are … on a course to save hundreds of millions of dollars in our own customer support and contact center operations. I think we can drive that value to our customers.\u201d
\nDespite the heavy investments in AI infrastructure, Microsoft remains focused on maintaining financial discipline. Hood stated, \u201cWe will remain disciplined on operating expense management,\u201d and projected that operating expenses would grow in the single digits for fiscal year 2025.
\nThe company\u2019s ability to leverage its existing cloud infrastructure for AI workloads appears to be paying dividends. Hood explained, \u201cBecause we\u2019re building to one Azure AI stack, we don\u2019t have to have multiple infrastructure investments. … It does, in fact, make margins start off better and obviously scale consistently.\u201d
\nTo address near-term capacity constraints, Microsoft has formed partnerships with other tech companies. \u201cWe\u2019ve signed up with third parties to help us, as we are behind with some leases on AI capacity,\u201d Hood said. Nadella added that these partnerships are \u201cno different than leases that we would have done in the past\u201d and may even be \u201cmore efficient leases because they\u2019re even shorter dates.\u201d
\nLooking ahead, Microsoft expects its AI investments to drive growth across its cloud and software businesses. The company is betting that AI will not only enhance existing products but also create new categories of software and services.
\nAs Nadella put it, \u201cAt the end of the day, GenAI is just software.\u201d But it\u2019s software that Microsoft believes will reshape the technology landscape and drive the next wave of productivity gains across industries.
\nWith its deep pockets, vast cloud infrastructure, and broad software portfolio, Microsoft appears well-positioned to capitalize on the AI boom. However, the company will need to navigate challenges such as capacity constraints, potential regulatory scrutiny, and competition from other tech giants also investing heavily in AI.
\nAs the race to dominate the AI era heats up, investors and industry observers will closely watch Microsoft\u2019s ability to execute its ambitious AI strategy while maintaining financial discipline.
\nThe post Microsoft Bets Big on AI as Demand Surges Across Cloud and Software Businesses appeared first on PYMNTS.com.
\n", "content_text": "Microsoft is doubling down on artificial intelligence (AI) as a driver of growth. During the company\u2019s fiscal fourth-quarter earnings call on Tuesday (July 30), executives described surging demand for AI services across its cloud and software portfolio.\nThe tech giant reported that Azure AI, its cloud-based AI platform, grew 30% year-over-year and now accounts for 8 percentage points of Azure\u2019s overall growth. This comes as Microsoft grapples with capacity constraints in meeting the explosive demand for AI services.\n\u201cAzure growth included eight points from AI services, where demand remained higher than our available capacity,\u201d said Amy Hood, Microsoft\u2019s chief financial officer. She added that the company expects \u201cAzure growth to accelerate as our capital investments create an increase in available AI capacity to serve more of the growing demand\u201d in the second half of fiscal year 2025.\nTo meet this demand, Microsoft is ramping up its capital expenditures. Hood revealed that about half of the company\u2019s capital spending is on \u201cland and builds and finance leases\u201d for data centers, investments that will \u201cbe monetized over 15 years and beyond.\u201d The other half is dedicated to \u201cCPUs and GPUs to serve customers based on demand signals.\u201d\nThe company stated it expects capital expenditures to increase in fiscal year 2025 to support growing AI and cloud demand but did not give a precise figure.\nSatya Nadella, Microsoft\u2019s CEO, emphasized the company\u2019s focus on capturing the AI opportunity: \u201cWe are investing for the long term in our fundamentals, in our innovation, and in our people.\u201d He likened the current AI transition to the earlier shift to cloud computing, describing both as \u201cknowledge and capital-intensive investments.\u201d\nMicrosoft saw revenue soaring 15% to $64.7 billion and net income jumping 10% to $22 billion. The company\u2019s cloud juggernaut, Azure, led the charge with a 29% revenue surge. Executives touted AI leadership and highlighted record bookings, with Microsoft Cloud revenue hitting $36.8 billion. The Intelligent Cloud segment was the star performer, growing 19% to $28.5 billion. Even gaming got a boost, with Xbox content and services revenue skyrocketing 61%, thanks largely to the Activision acquisition. With these results, Microsoft wrapped up the fiscal year 2024 boasting $245.1 billion in revenue and $88.1 billion in net income, both up over 20% year-over-year.\nCopilot Drives Growth Across Products\nThe impact of AI is being felt across Microsoft\u2019s product lines. Nadella highlighted the success of Copilot for Microsoft 365, the company\u2019s AI-powered assistant for productivity software.\n \u201cThe number of people who use Copilot daily at work nearly doubled quarter over quarter,\u201d he said, adding that \u201cCopilot customers increased more than 60% quarter over quarter.\u201d\nPerhaps most telling was Nadella\u2019s revelation about GitHub Copilot, the company\u2019s AI pair programming tool: \u201cCopilot accounted for over 40% of GitHub revenue growth this year, and is already a larger business than all of GitHub was when we acquired it.\u201d\nThis success in developer tools appears to be a blueprint for Microsoft\u2019s broader AI strategy. Nadella explained, \u201cWhat used to be line of business applications to us are Copilot extensions going forward. So we think of this as really a new design system for knowledge and frontline work to drive productivity, which will be very akin to what has happened in software engineering.\u201d\nThe company sees potential for AI to transform various business functions. \u201cWhen you think about marketing or finance or sales or customer service, we\u2019ll effectively replicate what you just said, which is the type of productivity we\u2019ve seen in developers will come to all of these functions,\u201d Nadella predicted.\nMicrosoft\u2019s AI push extends to its Dynamics 365 business applications as well. Nadella pointed to the contact center as an area ripe for AI-driven transformation: \u201cWe ourselves are … on a course to save hundreds of millions of dollars in our own customer support and contact center operations. I think we can drive that value to our customers.\u201d\nDespite the heavy investments in AI infrastructure, Microsoft remains focused on maintaining financial discipline. Hood stated, \u201cWe will remain disciplined on operating expense management,\u201d and projected that operating expenses would grow in the single digits for fiscal year 2025.\nThe company\u2019s ability to leverage its existing cloud infrastructure for AI workloads appears to be paying dividends. Hood explained, \u201cBecause we\u2019re building to one Azure AI stack, we don\u2019t have to have multiple infrastructure investments. … It does, in fact, make margins start off better and obviously scale consistently.\u201d\nTo address near-term capacity constraints, Microsoft has formed partnerships with other tech companies. \u201cWe\u2019ve signed up with third parties to help us, as we are behind with some leases on AI capacity,\u201d Hood said. Nadella added that these partnerships are \u201cno different than leases that we would have done in the past\u201d and may even be \u201cmore efficient leases because they\u2019re even shorter dates.\u201d\nFuture of AI and Microsoft\nLooking ahead, Microsoft expects its AI investments to drive growth across its cloud and software businesses. The company is betting that AI will not only enhance existing products but also create new categories of software and services.\nAs Nadella put it, \u201cAt the end of the day, GenAI is just software.\u201d But it\u2019s software that Microsoft believes will reshape the technology landscape and drive the next wave of productivity gains across industries.\nWith its deep pockets, vast cloud infrastructure, and broad software portfolio, Microsoft appears well-positioned to capitalize on the AI boom. However, the company will need to navigate challenges such as capacity constraints, potential regulatory scrutiny, and competition from other tech giants also investing heavily in AI.\nAs the race to dominate the AI era heats up, investors and industry observers will closely watch Microsoft\u2019s ability to execute its ambitious AI strategy while maintaining financial discipline.\nThe post Microsoft Bets Big on AI as Demand Surges Across Cloud and Software Businesses appeared first on PYMNTS.com.", "date_published": "2024-07-30T21:24:08-04:00", "date_modified": "2024-07-30T21:24:08-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2024/07/Microsoft-AI-2.jpg", "tags": [ "AI", "Amy Hood", "artificial intelligence", "Azure", "Azure AI", "Copilot", "Earnings", "GenAI", "generative AI", "github", "Microsoft", "News", "PYMNTS News", "Satya Nadella", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2019476", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/openai-debuts-advanced-voice-ai-for-subscribers/", "title": "OpenAI Debuts Advanced Voice AI for Subscribers", "content_html": "Artificial intelligence (AI) company OpenAI has begun rolling out an advanced voice feature for its ChatGPT platform.
\nThe feature, which utilizes the company\u2019s GPT-4o model, offers hyper-realistic audio responses, according to a Tuesday (July 30) TechCrunch report. The new audio capabilities supposedly enable users to have real-time, delay-free conversations with ChatGPT and even interrupt it mid-sentence, addressing key challenges in achieving realistic AI interactions.
\nThe alpha version of Advanced Voice Mode is being released to a select group of ChatGPT Plus subscribers, with plans for a broader rollout to all premium users in this fall. This cautious approach comes after controversy surrounding the technology\u2019s initial demonstration in May.
\nDuring that showcase, the voice capability, dubbed \u201cSky,\u201d drew attention for its uncanny resemblance to actress Scarlett Johansson\u2019s voice, even as the actress said she had repeatedly denied OpenAI permission to use her voice.
\nJohansson, who had a starring role in the AI-themed film \u201cHer,\u201d subsequently sought legal counsel to protect her likeness. OpenAI denied using Johansson\u2019s voice but removed the controversial demo, highlighting the complex legal landscape surrounding AI and celebrity likeness rights.
\nTo mitigate potential misuse, OpenAI has limited the system to four preset voices created in collaboration with paid voice actors. The company emphasized that ChatGPT cannot impersonate specific individuals or public figures, a measure designed to prevent the creation of deceptive deepfakes \u2014 a growing concern in the AI industry.
\n\u201cWe tested GPT-4o\u2019s voice capabilities with 100+ external red teamers across 45 languages,\u201d the company wrote on X, formerly Twitter, in a series of posts on Tuesday to announce the new offering. \u201cTo protect people\u2019s privacy, we\u2019ve trained the model to only speak in the four preset voices, and we built systems to block outputs that differ from those voices. We\u2019ve also implemented guardrails to block requests for violent or copyrighted content.\u201d
\n\n\n\nWe tested GPT-4o\u2019s voice capabilities with 100+ external red teamers across 45 languages. To protect people\u2019s privacy, we\u2019ve trained the model to only speak in the four preset voices, and we built systems to block outputs that differ from those voices. We\u2019ve also implemented\u2026
\n\u2014 OpenAI (@OpenAI) July 30, 2024
OpenAI has also implemented filters to block requests for generating music or copyrighted audio, a move likely influenced by recent legal actions against AI companies for alleged copyright infringement.
\nThe music industry, in particular, has been proactive in challenging AI-generated content, with lawsuits already filed against AI song-generators Suno and Udio.
\nThe post OpenAI Debuts Advanced Voice AI for Subscribers appeared first on PYMNTS.com.
\n", "content_text": "Artificial intelligence (AI) company OpenAI has begun rolling out an advanced voice feature for its ChatGPT platform.\nThe feature, which utilizes the company\u2019s GPT-4o model, offers hyper-realistic audio responses, according to a Tuesday (July 30) TechCrunch report. The new audio capabilities supposedly enable users to have real-time, delay-free conversations with ChatGPT and even interrupt it mid-sentence, addressing key challenges in achieving realistic AI interactions.\nThe alpha version of Advanced Voice Mode is being released to a select group of ChatGPT Plus subscribers, with plans for a broader rollout to all premium users in this fall. This cautious approach comes after controversy surrounding the technology\u2019s initial demonstration in May.\nDuring that showcase, the voice capability, dubbed \u201cSky,\u201d drew attention for its uncanny resemblance to actress Scarlett Johansson\u2019s voice, even as the actress said she had repeatedly denied OpenAI permission to use her voice.\nJohansson, who had a starring role in the AI-themed film \u201cHer,\u201d subsequently sought legal counsel to protect her likeness. OpenAI denied using Johansson\u2019s voice but removed the controversial demo, highlighting the complex legal landscape surrounding AI and celebrity likeness rights.\nTo mitigate potential misuse, OpenAI has limited the system to four preset voices created in collaboration with paid voice actors. The company emphasized that ChatGPT cannot impersonate specific individuals or public figures, a measure designed to prevent the creation of deceptive deepfakes \u2014 a growing concern in the AI industry.\n\u201cWe tested GPT-4o\u2019s voice capabilities with 100+ external red teamers across 45 languages,\u201d the company wrote on X, formerly Twitter, in a series of posts on Tuesday to announce the new offering. \u201cTo protect people\u2019s privacy, we\u2019ve trained the model to only speak in the four preset voices, and we built systems to block outputs that differ from those voices. We\u2019ve also implemented guardrails to block requests for violent or copyrighted content.\u201d\n\nWe tested GPT-4o\u2019s voice capabilities with 100+ external red teamers across 45 languages. To protect people\u2019s privacy, we\u2019ve trained the model to only speak in the four preset voices, and we built systems to block outputs that differ from those voices. We\u2019ve also implemented\u2026\n\u2014 OpenAI (@OpenAI) July 30, 2024\n\nOpenAI has also implemented filters to block requests for generating music or copyrighted audio, a move likely influenced by recent legal actions against AI companies for alleged copyright infringement.\nThe music industry, in particular, has been proactive in challenging AI-generated content, with lawsuits already filed against AI song-generators Suno and Udio.\nThe post OpenAI Debuts Advanced Voice AI for Subscribers appeared first on PYMNTS.com.", "date_published": "2024-07-30T17:59:25-04:00", "date_modified": "2024-07-30T17:59:25-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2024/07/OpenAI-ChatGPT-voice-tech-AI.jpg", "tags": [ "AI", "artificial intelligence", "chatbots", "ChatGPT", "GenAI", "generative AI", "News", "OpenAI", "PYMNTS News", "Voice Tech", "What's Hot", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2019327", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/ai-regulations-eu-probes-unilever-prepares-utah-innovates/", "title": "AI Regulations: EU Probes, Unilever Prepares, Utah Innovates", "content_html": "Artificial intelligence (AI) regulation takes center stage as the EU investigates X\u2019s (formerly Twitter) data practices, Unilever adopts a proactive stance and Utah targets mental health chatbots.
\nThese moves signal a shifting landscape in AI governance across the tech, business and healthcare sectors.
\nThe Irish Data Protection Commission (DPC) has reportedly launched an inquiry into X\u2019s latest privacy rule, which caught European regulators off guard. The social media giant, formerly known as Twitter, quietly introduced a new setting that has stirred the data protection community.
\nAt the heart of the controversy is a default-enabled option allowing X to harvest users\u2019 public posts for Grok, an AI system developed by xAI \u2014 another venture by Elon Musk. This move, implemented without fanfare, potentially affects data on millions of EU citizens.
\nUsers face significant hurdles when opting out of this data collection scheme. Currently, the option to disable the setting is only available through X\u2019s web interface, leaving mobile users without recourse. While X has promised a mobile solution in the future, critics argue that this vague timeline is inadequate and potentially violates EU data protection principles.
\nThe DPC, X\u2019s primary EU regulator, expressed dismay at the sudden rollout and stressed the lack of proper consultation. This stealth approach has raised serious questions about user consent and data protection practices.
\nThis latest controversy adds to X\u2019s mounting regulatory challenges in the EU. The company is reportedly already under scrutiny for at least five other investigations related to data protection violations. Each case carries the potential for substantial fines, which could significantly impact X\u2019s financial standing.
\nAs the regulatory storm brews, xAI continues its aggressive expansion. Recently, after securing a staggering $6 billion in funding, the company is constructing what it claims will be a revolutionary AI training supercomputer. This digital powerhouse, boasting 100,000 GPUs, aims to push the boundaries of AI capabilities.
\nConsumer goods giant Unilever has implemented an AI assurance process, positioning itself ahead of impending European Union regulations on AI use.
\nAt the core of Unilever\u2019s approach is a cross-functional team of experts who scrutinize potential AI projects before they are greenlit. This team, which includes external partners such as Holistic AI, assesses proposals for potential risks and develops mitigation strategies.
\nUnilever\u2019s Chief Data Officer Andy Hill wrote on the company\u2019s website that the AI assurance process has become integral to Unilever\u2019s operations, with the company recently surpassing 150 \u2018projects assured.\u2019 Unilever currently employs over 500 AI systems worldwide, spanning areas from research and development to inventory management and marketing.
\n\u201cWe see potential in the use of AI to drive productivity, creativity, and growth at Unilever,\u201d Hill wrote. He emphasized the importance of responsible implementation as AI deployments expand within the company.
\nThe program\u2019s development comes as the EU prepares to enforce the AI Act, widely regarded as the world\u2019s first comprehensive AI legislation. Unilever\u2019s Chief Privacy Officer Christine Lee noted that regulatory compliance is a key component of the firm\u2019s framework, with the company actively monitoring and addressing upcoming legal developments that may impact its operations.
\nUnilever\u2019s initiative addresses various AI-related concerns, including intellectual property rights, data privacy, transparency and potential bias. The company reports that its approach is designed to be adaptable, allowing it to keep pace with evolving regulations in different jurisdictions.
\nAs global discussions on AI governance intensify, Unilever executives said they are committed to aligning with legal developments affecting their businesses and brands. This proactive stance, they said, enables the company to pursue digital innovation while maintaining responsible AI use and proper data governance.
\nUtah\u2019s newly minted Office of Artificial Intelligence is taking aim at mental health chatbots, marking a first in state-level AI regulation.
\nThe office plans to introduce legislation by year-end to oversee AI use in mental health services, Fierce Healthcare reported. This initiative focuses on AI chatbots employed in licensed medical practice, addressing concerns over reliability and potential legal pitfalls. Key issues include information accuracy and the risk of unlicensed medical practice.
\nThe office is collaborating with a diverse group of stakeholders, from local health providers to national mental health companies and startups, to shape the proposed regulations. Their primary concern is the impact of AI chatbots on patient well-being and the integrity of mental health care delivery.
\nUtah\u2019s move could spark a domino effect, potentially leading to a patchwork of state regulations and spurring federal action on AI governance in healthcare. As the first state to establish a permanent AI regulatory body, Utah is setting a precedent in navigating the complex intersection of AI technology and mental health policy.
\nThe post AI Regulations: EU Probes, Unilever Prepares, Utah Innovates appeared first on PYMNTS.com.
\n", "content_text": "Artificial intelligence (AI) regulation takes center stage as the EU investigates X\u2019s (formerly Twitter) data practices, Unilever adopts a proactive stance and Utah targets mental health chatbots.\nThese moves signal a shifting landscape in AI governance across the tech, business and healthcare sectors.\nEU Regulator Probes X\u2019s Covert AI Data Collection\nThe Irish Data Protection Commission (DPC) has reportedly launched an inquiry into X\u2019s latest privacy rule, which caught European regulators off guard. The social media giant, formerly known as Twitter, quietly introduced a new setting that has stirred the data protection community.\nAt the heart of the controversy is a default-enabled option allowing X to harvest users\u2019 public posts for Grok, an AI system developed by xAI \u2014 another venture by Elon Musk. This move, implemented without fanfare, potentially affects data on millions of EU citizens.\nUsers face significant hurdles when opting out of this data collection scheme. Currently, the option to disable the setting is only available through X\u2019s web interface, leaving mobile users without recourse. While X has promised a mobile solution in the future, critics argue that this vague timeline is inadequate and potentially violates EU data protection principles.\nThe DPC, X\u2019s primary EU regulator, expressed dismay at the sudden rollout and stressed the lack of proper consultation. This stealth approach has raised serious questions about user consent and data protection practices.\nThis latest controversy adds to X\u2019s mounting regulatory challenges in the EU. The company is reportedly already under scrutiny for at least five other investigations related to data protection violations. Each case carries the potential for substantial fines, which could significantly impact X\u2019s financial standing.\nAs the regulatory storm brews, xAI continues its aggressive expansion. Recently, after securing a staggering $6 billion in funding, the company is constructing what it claims will be a revolutionary AI training supercomputer. This digital powerhouse, boasting 100,000 GPUs, aims to push the boundaries of AI capabilities.\nUnilever Rolls Out AI Governance Program\nConsumer goods giant Unilever has implemented an AI assurance process, positioning itself ahead of impending European Union regulations on AI use.\nAt the core of Unilever\u2019s approach is a cross-functional team of experts who scrutinize potential AI projects before they are greenlit. This team, which includes external partners such as Holistic AI, assesses proposals for potential risks and develops mitigation strategies.\nUnilever\u2019s Chief Data Officer Andy Hill wrote on the company\u2019s website that the AI assurance process has become integral to Unilever\u2019s operations, with the company recently surpassing 150 \u2018projects assured.\u2019 Unilever currently employs over 500 AI systems worldwide, spanning areas from research and development to inventory management and marketing.\n\u201cWe see potential in the use of AI to drive productivity, creativity, and growth at Unilever,\u201d Hill wrote. He emphasized the importance of responsible implementation as AI deployments expand within the company.\nThe program\u2019s development comes as the EU prepares to enforce the AI Act, widely regarded as the world\u2019s first comprehensive AI legislation. Unilever\u2019s Chief Privacy Officer Christine Lee noted that regulatory compliance is a key component of the firm\u2019s framework, with the company actively monitoring and addressing upcoming legal developments that may impact its operations.\nUnilever\u2019s initiative addresses various AI-related concerns, including intellectual property rights, data privacy, transparency and potential bias. The company reports that its approach is designed to be adaptable, allowing it to keep pace with evolving regulations in different jurisdictions.\nAs global discussions on AI governance intensify, Unilever executives said they are committed to aligning with legal developments affecting their businesses and brands. This proactive stance, they said, enables the company to pursue digital innovation while maintaining responsible AI use and proper data governance.\nUtah Targets AI Mental Health Chatbots\nUtah\u2019s newly minted Office of Artificial Intelligence is taking aim at mental health chatbots, marking a first in state-level AI regulation.\nThe office plans to introduce legislation by year-end to oversee AI use in mental health services, Fierce Healthcare reported. This initiative focuses on AI chatbots employed in licensed medical practice, addressing concerns over reliability and potential legal pitfalls. Key issues include information accuracy and the risk of unlicensed medical practice.\nThe office is collaborating with a diverse group of stakeholders, from local health providers to national mental health companies and startups, to shape the proposed regulations. Their primary concern is the impact of AI chatbots on patient well-being and the integrity of mental health care delivery.\nUtah\u2019s move could spark a domino effect, potentially leading to a patchwork of state regulations and spurring federal action on AI governance in healthcare. As the first state to establish a permanent AI regulatory body, Utah is setting a precedent in navigating the complex intersection of AI technology and mental health policy.\nThe post AI Regulations: EU Probes, Unilever Prepares, Utah Innovates appeared first on PYMNTS.com.", "date_published": "2024-07-30T14:51:40-04:00", "date_modified": "2024-07-30T14:51:40-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2024/07/X-Twitter-xAI-Grok-DPC-data-privacy.jpg", "tags": [ "AI", "AI regulations", "artificial intelligence", "chatbots", "data privacy", "EMEA", "EU", "GenAI", "generative AI", "Grok", "Healthcare", "Irish Data Protection Commission", "mental health", "News", "PYMNTS News", "twitter", "unilever", "Utah", "X", "xAI", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2018743", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/metas-open-source-ai-model-sparks-industry-debate-on-commerces-future/", "title": "Meta\u2019s Open-Source AI Model Sparks Industry Debate on Commerce\u2019s Future", "content_html": "Industry experts are debating the business impact of Meta\u2019s free artificial intelligence (AI) model Llama 3.1, weighing its potential against practical implementation challenges.
\nBoasting 405 billion parameters, the AI model claims performance comparable to proprietary competitors like GPT-4 and Claude 3.5 Sonnet. As Meta expands its reach, with CEO Mark Zuckerberg predicting it will become the most widely used AI assistant by year\u2019s end, businesses are weighing the implications of access to powerful, cost-free AI against the challenges of implementation and security.\u00a0
\n\u201cThese models can be used to communicate with customers and provide instant 24/7 assistance with simple queries that do not require human intervention,\u201d Ilia Badeev, head of data science at Trevolution Group, told PYMNTS. \u201cWith LLMs [large language models], marketing campaigns and recommendations can be truly personalized for individual customers.\u201d\u00a0
\nSome experts predict a fundamental shift in customer service. \u201cIf you think about the cost of intelligence effectively going to zero over time for customer relations, call centers will not exist in the future. AI systems will manage huge volumes of customer inbound in a meaningful and satisfactory way to the end user,\u201d Mike Conover, CEO of the AI company Brightwave, told PYMNTS.
\nThe potential for businesses to customize these models is significant. \u201cBy fine-tuning Llama on their specific domain data, companies can create powerful natural language interfaces that understand customer queries, provide intelligent recommendations, and automate tasks like product categorization and content generation,\u201d Hamza Tahir, CTO and co-founder of ZenML, an open-source machine learning operations (MLOps) startup, told PYMNTS.
\nThe availability of powerful, open-source AI models could level the playing field for smaller businesses. \u201cOpen-source models like Llama have the potential to democratize AI-powered commerce tools for small businesses and startups,\u201d Tahir said.
\n\u201cEven small teams can leverage state-of-the-art natural language processing capabilities to build intelligent chatbots, product recommenders and content generators.\u201d\u00a0
\nOpen-source AI also offers advantages in regulatory compliance. \u201cProcessing data with in-house models keeps user data private and compliant with regulatory laws (such as GDPR),\u201d Badeev pointed out, referring to the EU\u2019s General Data Protection Regulation. This contrasts with proprietary models that may require sending user data to third-party services.
\nThe introduction of Llama 3.1 is stirring debate about its potential to disrupt the commercial AI market. Conover said that the 405 billion-parameter model from Llama is comparable in its reasoning quality to OpenAI\u2019s GPT-4. \u201cThis means commercial providers do not have some secret sauce that would lead to vendor lock-in \u2014 business owners are the masters of their own destiny,\u201d he added.\u00a0
\nTahir predicted that the introduction of the new model may presage a shift toward a service-based model, where AI companies differentiate themselves through their domain expertise, data assets and ability to customize and deploy open-source models for specific use cases.
\nThe economic impact could be substantial. \u201cFor business owners like eCommerce platforms and customer service providers, you\u2019re going to see improving unit economics for these services because of the competitive pressures that open-source technologies place on the commercial providers,\u201d Conover added.
\nDespite the opportunities, businesses face challenges in implementing open-source AI. \u201cOpen-source AI models give SMEs [small to mid-sized enterprises] the advantage of doing more and reaching a wider audience, but this comes at the cost of both talent and security, Harry Toor, chief of staff at OpenSSF, which promotes open-source software, told PYMNTS.\u00a0
\nHe added, \u201cOpen-source AI models need to be consumed securely to ensure outputs aren\u2019t manipulated, which could sink any SME operating in a cost-constrained environment.\u201d\u00a0
\nSecurity measures are crucial. \u201cSecure open-source AI models should be built from a secured development environment, cryptographically signed, and follow best practices already in place for open-source software development. This can be achieved by leveraging existing open-source tools from OpenSSF and elsewhere to secure open-source AI models,\u201d Toor said.
\nPotential supply chain issues also pose a risk. \u201cThe commercial AI market needs to evaluate the supply chain for open-source AI models. Recent global cyber issues like XZ Utils and the Microsoft Blue Screen of Death have shown that widely used software components can cripple industries,\u201d Toor warned.
\nAs businesses consider adopting open-source AI, they face a complex set of considerations. The long-term implications for eCommerce, customer service and marketing strategies are still unfolding. While some predict a radical transformation of these sectors, others caution that the technology’s impact will depend on factors beyond mere availability.
\nOpen-source models could lead to more effective feedback collection. \u201cUser feedback/reactions can be effectively gathered from various sources such as reviews, social media mentions, and customer support interactions. These can be massively processed using AI to extract insights and analytics instantly,\u201d Badeev noted.
\nFor all PYMNTS AI coverage, subscribe to the daily AI\u00a0Newsletter.
\nThe post Meta’s Open-Source AI Model Sparks Industry Debate on Commerce’s Future appeared first on PYMNTS.com.
\n", "content_text": "Industry experts are debating the business impact of Meta\u2019s free artificial intelligence (AI) model Llama 3.1, weighing its potential against practical implementation challenges.\nBoasting 405 billion parameters, the AI model claims performance comparable to proprietary competitors like GPT-4 and Claude 3.5 Sonnet. As Meta expands its reach, with CEO Mark Zuckerberg predicting it will become the most widely used AI assistant by year\u2019s end, businesses are weighing the implications of access to powerful, cost-free AI against the challenges of implementation and security.\u00a0\n\u201cThese models can be used to communicate with customers and provide instant 24/7 assistance with simple queries that do not require human intervention,\u201d Ilia Badeev, head of data science at Trevolution Group, told PYMNTS. \u201cWith LLMs [large language models], marketing campaigns and recommendations can be truly personalized for individual customers.\u201d\u00a0\nSome experts predict a fundamental shift in customer service. \u201cIf you think about the cost of intelligence effectively going to zero over time for customer relations, call centers will not exist in the future. AI systems will manage huge volumes of customer inbound in a meaningful and satisfactory way to the end user,\u201d Mike Conover, CEO of the AI company Brightwave, told PYMNTS.\nThe potential for businesses to customize these models is significant. \u201cBy fine-tuning Llama on their specific domain data, companies can create powerful natural language interfaces that understand customer queries, provide intelligent recommendations, and automate tasks like product categorization and content generation,\u201d Hamza Tahir, CTO and co-founder of ZenML, an open-source machine learning operations (MLOps) startup, told PYMNTS.\nOpportunity for Small Businesses?\nThe availability of powerful, open-source AI models could level the playing field for smaller businesses. \u201cOpen-source models like Llama have the potential to democratize AI-powered commerce tools for small businesses and startups,\u201d Tahir said. \n\u201cEven small teams can leverage state-of-the-art natural language processing capabilities to build intelligent chatbots, product recommenders and content generators.\u201d\u00a0\nOpen-source AI also offers advantages in regulatory compliance. \u201cProcessing data with in-house models keeps user data private and compliant with regulatory laws (such as GDPR),\u201d Badeev pointed out, referring to the EU\u2019s General Data Protection Regulation. This contrasts with proprietary models that may require sending user data to third-party services.\nThe introduction of Llama 3.1 is stirring debate about its potential to disrupt the commercial AI market. Conover said that the 405 billion-parameter model from Llama is comparable in its reasoning quality to OpenAI\u2019s GPT-4. \u201cThis means commercial providers do not have some secret sauce that would lead to vendor lock-in \u2014 business owners are the masters of their own destiny,\u201d he added.\u00a0\nTahir predicted that the introduction of the new model may presage a shift toward a service-based model, where AI companies differentiate themselves through their domain expertise, data assets and ability to customize and deploy open-source models for specific use cases.\nThe economic impact could be substantial. \u201cFor business owners like eCommerce platforms and customer service providers, you\u2019re going to see improving unit economics for these services because of the competitive pressures that open-source technologies place on the commercial providers,\u201d Conover added.\nDespite the opportunities, businesses face challenges in implementing open-source AI. \u201cOpen-source AI models give SMEs [small to mid-sized enterprises] the advantage of doing more and reaching a wider audience, but this comes at the cost of both talent and security, Harry Toor, chief of staff at OpenSSF, which promotes open-source software, told PYMNTS.\u00a0\nHe added, \u201cOpen-source AI models need to be consumed securely to ensure outputs aren\u2019t manipulated, which could sink any SME operating in a cost-constrained environment.\u201d\u00a0\nSecurity measures are crucial. \u201cSecure open-source AI models should be built from a secured development environment, cryptographically signed, and follow best practices already in place for open-source software development. This can be achieved by leveraging existing open-source tools from OpenSSF and elsewhere to secure open-source AI models,\u201d Toor said.\nFuture of AI in Commerce\nPotential supply chain issues also pose a risk. \u201cThe commercial AI market needs to evaluate the supply chain for open-source AI models. Recent global cyber issues like XZ Utils and the Microsoft Blue Screen of Death have shown that widely used software components can cripple industries,\u201d Toor warned.\nAs businesses consider adopting open-source AI, they face a complex set of considerations. The long-term implications for eCommerce, customer service and marketing strategies are still unfolding. While some predict a radical transformation of these sectors, others caution that the technology’s impact will depend on factors beyond mere availability.\nOpen-source models could lead to more effective feedback collection. \u201cUser feedback/reactions can be effectively gathered from various sources such as reviews, social media mentions, and customer support interactions. These can be massively processed using AI to extract insights and analytics instantly,\u201d Badeev noted.\nFor all PYMNTS AI coverage, subscribe to the daily AI\u00a0Newsletter.\nThe post Meta’s Open-Source AI Model Sparks Industry Debate on Commerce’s Future appeared first on PYMNTS.com.", "date_published": "2024-07-29T19:15:40-04:00", "date_modified": "2024-07-29T19:15:40-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2024/07/open-source-AI-Meta-Llama.jpg", "tags": [ "AI", "artificial intelligence", "Brightwave", "customer relations", "data processing", "data security", "digital transformation", "ecommerce", "GenAI", "generative AI", "Hamza Tahir", "Harry Toor", "Ilia Badeev", "LLAMA", "machine learning", "Meta", "Mike Conover", "ML", "natural-language processing", "News", "nlp", "open source", "open source AI", "OpenSSF", "PYMNTS News", "small business", "SMBs", "Trevolution Group", "ZenML", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2018707", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/openai-board-member-agi-is-five-to-15-years-away/", "title": "OpenAI Director Says Artificial General Intelligence May Be 5 Years Out", "content_html": "How long will it take for artificial intelligence to be as smart as human beings?
\nAccording to OpenAI board member Adam D\u2019Angelo, that milestone is likely to happen \u201cwithin five to 15 years,\u201d Seeking Alpha reported Monday (July 29).
\nD\u2019Angelo, CEO and co-founder of Quora, made that prediction during an event last week, the report added. He said the advent of artificial general intelligence (AGI) will be a \u201cvery, very important change in the world when we get there.\u201d
\nHis comments follow reports from earlier this month that OpenAI had developed a way to track its progress toward building AGI, with the company sharing a new five-level classification system with employees.
\nThe company believes it is now at Level 1, where AI that can interact in a conversational way with people, and is approaching Level 2, or systems that can solve problems as well as a human with a doctorate-level education.
\nThe next levels involve AI systems that can spend several days acting on a user\u2019s behalf, develop innovations, and finally \u2014 at level five \u2014 do the work of an organization.
\nOpenAI CEO Sam Altman and Chief Technology Officer (CTO) Mira Murati said last fall that AGI will be reached within the next 10 years.
\n\u201cWe\u2019re big believers that you give people better tools, and they do things that astonish you,\u201d Altman said. \u201cAnd I think AGI will be the best tool humanity has yet created.\u201d
\nAs PYMNTS wrote recently, the reports of these efforts have sparked buzz in the business world of the possibility of AI-powered commerce that could rewrite the rules of global trade, assuming the technology can live up to the hype.
\n\u201cOpenAI\u2019s pursuit of human-level reasoning isn\u2019t just a technological marvel; it\u2019s a narrative of pushing boundaries and sparking new possibilities in every sector,\u201d Ghazenfer Mansoor, founder and CEO of Technology Rivers, told PYMNTS. \u201cIn business, AI can dramatically change how supply chains are managed, forecast market trends with great accuracy, and make customer experiences very personal on a big scale.\u201d
\nEarlier this year, OpenAI staffers reportedly showed demos of AI models that could answer tricky science and math questions, with one model scoring more than 90% on a championship math dataset. The company also recently showcased a project with new human-like reasoning skills at an internal meeting.
\n\u201cThe way such an algorithm can work is by creating multiple options, following a tree of possibilities, and then reasoning about the outcome and choosing the best path,\u201d SmythOS CTO Alexander De Ridder told PYMNTS. \u201cThis is similar to how chess players think different steps ahead before choosing to move their piece.\u201d
\nHe suggested that OpenAI\u2019s innovation likely involves \u201can algorithmic breakthrough in how to do this efficiently and scalably,\u201d potentially combining \u201cautonomous web research and tool usage to arrive at a reasoning breakthrough.\u201d
\nThe post OpenAI Director Says Artificial General Intelligence May Be 5 Years Out appeared first on PYMNTS.com.
\n", "content_text": "How long will it take for artificial intelligence to be as smart as human beings?\nAccording to OpenAI board member Adam D\u2019Angelo, that milestone is likely to happen \u201cwithin five to 15 years,\u201d Seeking Alpha reported Monday (July 29).\nD\u2019Angelo, CEO and co-founder of Quora, made that prediction during an event last week, the report added. He said the advent of artificial general intelligence (AGI) will be a \u201cvery, very important change in the world when we get there.\u201d\nHis comments follow reports from earlier this month that OpenAI had developed a way to track its progress toward building AGI, with the company sharing a new five-level classification system with employees.\nThe company believes it is now at Level 1, where AI that can interact in a conversational way with people, and is approaching Level 2, or systems that can solve problems as well as a human with a doctorate-level education.\nThe next levels involve AI systems that can spend several days acting on a user\u2019s behalf, develop innovations, and finally \u2014 at level five \u2014 do the work of an organization.\nOpenAI CEO Sam Altman and Chief Technology Officer (CTO) Mira Murati said last fall that AGI will be reached within the next 10 years.\n\u201cWe\u2019re big believers that you give people better tools, and they do things that astonish you,\u201d Altman said. \u201cAnd I think AGI will be the best tool humanity has yet created.\u201d\nAs PYMNTS wrote recently, the reports of these efforts have sparked buzz in the business world of the possibility of AI-powered commerce that could rewrite the rules of global trade, assuming the technology can live up to the hype.\n\u201cOpenAI\u2019s pursuit of human-level reasoning isn\u2019t just a technological marvel; it\u2019s a narrative of pushing boundaries and sparking new possibilities in every sector,\u201d Ghazenfer Mansoor, founder and CEO of Technology Rivers, told PYMNTS. \u201cIn business, AI can dramatically change how supply chains are managed, forecast market trends with great accuracy, and make customer experiences very personal on a big scale.\u201d\nEarlier this year, OpenAI staffers reportedly showed demos of AI models that could answer tricky science and math questions, with one model scoring more than 90% on a championship math dataset. The company also recently showcased a project with new human-like reasoning skills at an internal meeting.\n\u201cThe way such an algorithm can work is by creating multiple options, following a tree of possibilities, and then reasoning about the outcome and choosing the best path,\u201d SmythOS CTO Alexander De Ridder told PYMNTS. \u201cThis is similar to how chess players think different steps ahead before choosing to move their piece.\u201d\nHe suggested that OpenAI\u2019s innovation likely involves \u201can algorithmic breakthrough in how to do this efficiently and scalably,\u201d potentially combining \u201cautonomous web research and tool usage to arrive at a reasoning breakthrough.\u201d\nThe post OpenAI Director Says Artificial General Intelligence May Be 5 Years Out appeared first on PYMNTS.com.", "date_published": "2024-07-29T18:39:36-04:00", "date_modified": "2024-07-29T22:19:07-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2024/07/AI-AGI-artificial-general-intelligence.jpg", "tags": [ "Adam D'Angelo", "AGI", "AI", "Artificial General Intelligence", "artificial intelligence", "digital transformation", "News", "OpenAI", "PYMNTS News", "What's Hot", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2018571", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/ai-giants-unleash-new-models-with-more-business-capabilities/", "title": "GenAI Giants Unleash New Models With More Business Capabilities", "content_html": "In a move that\u2019s sending ripples through the tech and business worlds, Meta Platforms has unveiled its most advanced AI models yet, challenging industry leaders OpenAI and Google.
\nThe release of Meta\u2019s Llama 3 family of models, mostly available for free, marks a significant escalation in the AI arms race and could redefine how businesses operate across sectors.
\nMeta\u2019s flagship Llama 3 model, boasting 405 billion parameters, demonstrates multilingual prowess in eight languages and improved capabilities in code generation and problem-solving. This launch follows closely on the heels of OpenAI\u2019s GPT-4o mini and Google\u2019s upgraded Gemini.
\nThe Llama 3 family includes three models of varying sizes: 8 billion, 70 billion and 405 billion parameters. All three models feature expanded \u201ccontext windows,\u201d allowing them to process larger amounts of information and handle more complex, multi-step requests.
\nOpenAI has recently added to its lineup the GPT-4o mini, a smaller version of the GPT-4o model that was introduced in May.
\n\u201cWe expect GPT-4o mini will significantly expand the range of applications built with AI by making intelligence much more affordable,\u201d OpenAI said in a release announcing its launch.
\nThis model maintains much of the functionality of its larger counterpart, including a context window of 128,000 tokens, which is eight times that of GPT-3.5 Turbo.
\nGoogle\u2019s Gemini, released in three versions \u2014 Ultra, Pro and Nano \u2014 is designed to be more efficient and perform better across various tasks. Gemini Ultra has shown strong performance in complex reasoning and multimodal tasks, rivaling human experts in certain benchmarks.
\nThese models are pushing the boundaries of what\u2019s possible in artificial intelligence, with each company claiming superior performance in various benchmarks.
\nOpenAI reports that GPT-4o mini outperforms competitors on several standard tests, including the massive multitask language understanding (MMLU) benchmark, where it scored 82% compared to Google\u2019s Gemini Flash at 77.9% and Anthropic\u2019s Claude Haiku at 73.8%.
\nGoogle has also unveiled significant upgrades to its Gemini AI platform, enhancing its capabilities and expanding its reach. The company is rolling out Gemini 1.5 Flash, a faster and more capable version, to users of the free tier in over 230 countries and territories. This update quadruples the context window to 32,000 tokens, allowing for longer conversations and more complex queries. Additionally, Google is introducing a new feature to combat AI hallucinations by displaying related content links within Gemini\u2019s responses.
\nThe tech giant is also broadening Gemini\u2019s accessibility. The Gemini mobile app is being introduced to more countries, while integration with Google Messages is expanding to the European Economic Area, U.K. and Switzerland. In a move to engage younger users, Google plans to extend Gemini access to teenagers globally in over 40 languages, implementing additional safeguards and partnering with child safety experts.
\nThe implications for commerce are far-reaching.
\nOpenAI suggests that GPT-4o mini\u2019s larger context window and improved capabilities make it \u201cespecially useful for processing big documents or linking multiple interactions with the AI model.\u201d
\nThis could lead to enhanced recommendations in online stores, faster real-time text responses for customer service and more accurate and detailed answers for students.
\nFrom Main Street to Wall Street, businesses are eyeing these AI advancements as potential game-changers. With AI-powered chatbots offering more nuanced, round-the-clock support, customer service will likely see an immediate impact. eCommerce giants are poised to leverage these models for hyper-personalized product recommendations and dynamic pricing strategies.
\nSupply chain management, a persistent pain point for many industries, could see a significant overhaul. AI models promise to optimize inventory levels and distribution networks with unprecedented accuracy, potentially slashing operational costs and boosting responsiveness to market fluctuations.
\nIn the financial sector, risk assessment and fraud detection are prime targets for AI enhancement. Robo-advisors powered by these advanced models could democratize access to sophisticated financial planning, disrupting traditional wealth management services.
\nHealthcare isn\u2019t far behind, with AI poised to accelerate drug discovery and enhance diagnostic accuracy. These models\u2019 ability to analyze vast amounts of medical data could lead to breakthroughs in personalized medicine and treatment protocols.
\nFor marketing departments, AI-generated content could be a double-edged sword. While it promises to streamline content production, concerns about AI-generated misinformation loom large, challenging brands to maintain authenticity and trust.
\nMeta\u2019s strategy of offering Llama 3 largely for free could democratize access to cutting-edge AI capabilities, potentially leveling the playing field for startups and smaller enterprises. Similarly, OpenAI\u2019s introduction of GPT-4o mini at \u201cjust over half the price per token of GPT-3.5 Turbo\u201d aims to make AI more accessible to a broader range of businesses.
\nAs these AI models evolve, their impact on commerce is expected to accelerate. Future iterations, including multimodal versions incorporating image, video and speech capabilities, could spark a new wave of innovation across industries. OpenAI has already hinted at expanding GPT-4o mini\u2019s capabilities to include \u201cimage, video and audio inputs and outputs.\u201d
\nThe post GenAI Giants Unleash New Models With More Business Capabilities appeared first on PYMNTS.com.
\n", "content_text": "In a move that\u2019s sending ripples through the tech and business worlds, Meta Platforms has unveiled its most advanced AI models yet, challenging industry leaders OpenAI and Google.\nThe release of Meta\u2019s Llama 3 family of models, mostly available for free, marks a significant escalation in the AI arms race and could redefine how businesses operate across sectors.\nMeta\u2019s flagship Llama 3 model, boasting 405 billion parameters, demonstrates multilingual prowess in eight languages and improved capabilities in code generation and problem-solving. This launch follows closely on the heels of OpenAI\u2019s GPT-4o mini and Google\u2019s upgraded Gemini.\nThe Llama 3 family includes three models of varying sizes: 8 billion, 70 billion and 405 billion parameters. All three models feature expanded \u201ccontext windows,\u201d allowing them to process larger amounts of information and handle more complex, multi-step requests.\nA New Era of AI Capabilities\nOpenAI has recently added to its lineup the GPT-4o mini, a smaller version of the GPT-4o model that was introduced in May.\n\u201cWe expect GPT-4o mini will significantly expand the range of applications built with AI by making intelligence much more affordable,\u201d OpenAI said in a release announcing its launch.\nThis model maintains much of the functionality of its larger counterpart, including a context window of 128,000 tokens, which is eight times that of GPT-3.5 Turbo.\nGoogle\u2019s Gemini, released in three versions \u2014 Ultra, Pro and Nano \u2014 is designed to be more efficient and perform better across various tasks. Gemini Ultra has shown strong performance in complex reasoning and multimodal tasks, rivaling human experts in certain benchmarks.\nThese models are pushing the boundaries of what\u2019s possible in artificial intelligence, with each company claiming superior performance in various benchmarks.\nOpenAI reports that GPT-4o mini outperforms competitors on several standard tests, including the massive multitask language understanding (MMLU) benchmark, where it scored 82% compared to Google\u2019s Gemini Flash at 77.9% and Anthropic\u2019s Claude Haiku at 73.8%.\nGoogle has also unveiled significant upgrades to its Gemini AI platform, enhancing its capabilities and expanding its reach. The company is rolling out Gemini 1.5 Flash, a faster and more capable version, to users of the free tier in over 230 countries and territories. This update quadruples the context window to 32,000 tokens, allowing for longer conversations and more complex queries. Additionally, Google is introducing a new feature to combat AI hallucinations by displaying related content links within Gemini\u2019s responses.\nThe tech giant is also broadening Gemini\u2019s accessibility. The Gemini mobile app is being introduced to more countries, while integration with Google Messages is expanding to the European Economic Area, U.K. and Switzerland. In a move to engage younger users, Google plans to extend Gemini access to teenagers globally in over 40 languages, implementing additional safeguards and partnering with child safety experts.\nTransforming Business Across Sectors\nThe implications for commerce are far-reaching.\nOpenAI suggests that GPT-4o mini\u2019s larger context window and improved capabilities make it \u201cespecially useful for processing big documents or linking multiple interactions with the AI model.\u201d\nThis could lead to enhanced recommendations in online stores, faster real-time text responses for customer service and more accurate and detailed answers for students.\nFrom Main Street to Wall Street, businesses are eyeing these AI advancements as potential game-changers. With AI-powered chatbots offering more nuanced, round-the-clock support, customer service will likely see an immediate impact. eCommerce giants are poised to leverage these models for hyper-personalized product recommendations and dynamic pricing strategies.\nSupply chain management, a persistent pain point for many industries, could see a significant overhaul. AI models promise to optimize inventory levels and distribution networks with unprecedented accuracy, potentially slashing operational costs and boosting responsiveness to market fluctuations.\nIn the financial sector, risk assessment and fraud detection are prime targets for AI enhancement. Robo-advisors powered by these advanced models could democratize access to sophisticated financial planning, disrupting traditional wealth management services.\nHealthcare isn\u2019t far behind, with AI poised to accelerate drug discovery and enhance diagnostic accuracy. These models\u2019 ability to analyze vast amounts of medical data could lead to breakthroughs in personalized medicine and treatment protocols.\nChallenges and Opportunities Ahead\nFor marketing departments, AI-generated content could be a double-edged sword. While it promises to streamline content production, concerns about AI-generated misinformation loom large, challenging brands to maintain authenticity and trust.\nMeta\u2019s strategy of offering Llama 3 largely for free could democratize access to cutting-edge AI capabilities, potentially leveling the playing field for startups and smaller enterprises. Similarly, OpenAI\u2019s introduction of GPT-4o mini at \u201cjust over half the price per token of GPT-3.5 Turbo\u201d aims to make AI more accessible to a broader range of businesses.\nAs these AI models evolve, their impact on commerce is expected to accelerate. Future iterations, including multimodal versions incorporating image, video and speech capabilities, could spark a new wave of innovation across industries. OpenAI has already hinted at expanding GPT-4o mini\u2019s capabilities to include \u201cimage, video and audio inputs and outputs.\u201d\nThe post GenAI Giants Unleash New Models With More Business Capabilities appeared first on PYMNTS.com.", "date_published": "2024-07-29T15:54:09-04:00", "date_modified": "2024-07-30T22:27:40-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2024/04/AI-artificial-intelligence.jpg", "tags": [ "AI", "artificial intelligence", "B2B", "B2B Payments", "ChatGPT", "commercial payments", "Featured News", "Gemini", "GenAI", "generative AI", "Google", "Google Gemini", "GPT-4o", "GPT-4o Mini", "large language models", "Llama 3", "LLMs", "Meta", "News", "OpenAI", "PYMNTS News", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2018410", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/ai-ethics-tackles-issues-arising-from-machines-making-decisions/", "title": "AI Ethics Tackles Issues Arising From Machines Making Decisions", "content_html": "Imagine a world where machines make life-altering decisions about your health, your job prospects and even your freedom. That world isn\u2019t science fiction \u2014 it\u2019s already here. As artificial intelligence (AI) reshapes our lives, a new frontier is emerging: AI ethics.
\nThis rapidly evolving field tackles a crucial question: How do we ensure that intelligent machines serve humanity\u2019s best interests? From privacy concerns to racial bias, from job displacement to existential risks, AI ethics grapples with the moral implications of our increasingly automated world.
\nAI ethics encompasses a wide range of concerns, including privacy, bias, transparency, accountability, and the long-term societal impacts of artificial intelligence. As AI systems become more sophisticated and autonomous, the ethical questions surrounding their development and deployment grow increasingly complex and urgent.
\nOne of the primary areas of focus in AI ethics is algorithmic bias. AI systems are only as unbiased as the data they\u2019re trained on and the humans who design them. The consequences can be far-reaching and profound when these systems reflect or amplify existing societal biases.
\nA stark example of this issue emerged in 2018 when Amazon scrapped an AI recruiting tool that showed bias against women. The system, which was designed to review resumes and identify top talent, had been trained on patterns in resumes submitted to the company over a 10-year period. Because tech industry applicants were predominantly male then, the AI learned to penalize resumes that included the word \u201cwomen\u2019s\u201d or mentioned all-women\u2019s colleges.
\nThis case highlighted the potential for AI to perpetuate and even exacerbate existing inequalities if not carefully designed and monitored. It also underscored the need for diverse teams in AI development to help identify and mitigate such biases.
\nThe problem of algorithmic bias extends far beyond hiring practices. A study published in Science\u00a0found that a widely used algorithm in U.S. hospitals was systematically discriminating against black patients. The algorithm, used to identify patients who would benefit from extra medical care, was unintentionally programmed to use health costs as a proxy for health needs. Because less money has historically been spent on black patients due to socioeconomic factors and disparities in access to care, the algorithm incorrectly concluded that black patients were healthier than equally sick white patients.
\nAnother critical concern in AI ethics is privacy. As AI systems become more adept at collecting, analyzing and utilizing personal data, questions arise about the appropriate limits of such capabilities. The use of facial recognition technology by law enforcement agencies has sparked particular controversy, with critics arguing that it represents an unacceptable intrusion into personal privacy and civil liberties.
\nThe privacy implications of AI extend beyond facial recognition. In 2019, it was revealed that Google\u2019s AI assistant could eavesdrop on private conversations through its Nest security system. The incident highlighted the potential for AI-powered smart home devices to become surveillance tools, raising questions about the balance between convenience and privacy in an increasingly connected world.
\nTransparency and explainability represent another key pillar of AI ethics. As AI systems become more complex and make decisions that significantly impact people\u2019s lives \u2014 from loan approvals to medical diagnoses \u2014 there\u2019s a growing demand for them to explain their reasoning in terms that humans can understand.
\nThis issue arose in the healthcare sector when IBM\u2019s Watson for Oncology, an AI system designed to assist in cancer treatment recommendations, faced criticism for its lack of transparency. Oncologists expressed concern that they couldn\u2019t understand how the system arrived at its recommendations, making it difficult to trust and implement its advice in critical care situations.
\nAs AI systems become more autonomous, questions of accountability also come to the forefront. When an AI makes a decision that results in harm, who bears responsibility \u2014 the developers, the company deploying the system or the AI itself?
\nThis question has practical implications in areas like autonomous vehicles. In 2018, an Uber self-driving car struck and killed a pedestrian in Arizona, raising questions about liability and the ethical considerations in programming such vehicles. Should an autonomous car prioritize the safety of its passengers or pedestrians in unavoidable accident scenarios? These \u201ctrolley problem\u201d type dilemmas have moved from philosophical thought experiments to real-world engineering challenges.
\nSimilar ethical dilemmas arise in the field of autonomous weapons systems. The prospect of \u201ckiller robots\u201d capable of selecting and engaging targets without human intervention has sparked intense debate. While proponents argue that such systems could reduce military casualties and potentially be more precise than human soldiers, critics warn of the moral hazard of delegating life-or-death decisions to machines.
\nGoogle faced significant employee backlash over its involvement in Project Maven, a U.S. Department of Defense initiative using AI for drone footage analysis. The controversy led to Google deciding not to renew the contract and establishing AI principles that preclude the development of AI for weapons.
\nLooking ahead, the field of AI ethics must also grapple with long-term existential questions. As AI capabilities continue to advance rapidly, some experts warn that artificial general intelligence (AGI) or artificial superintelligence (ASI) could pose existential risks to humanity if not developed with robust ethical safeguards.
\nOrganizations like the Future of Humanity Institute\u00a0at Oxford University and the Center for Human-Compatible AI at UC Berkeley are dedicated to researching ways to ensure that advanced AI systems remain aligned with human values and interests. These efforts involve complex technical challenges, such as developing reliable methods to specify and encode human values in AI systems, as well as philosophical questions about the nature of intelligence, consciousness and morality.
\nIn response to these myriad challenges, governments and organizations worldwide are working to establish ethical guidelines and regulatory frameworks for AI development and deployment. The European Union\u2019s AI Act, which aims to create the world\u2019s first comprehensive AI regulations, represents a significant step in this direction.
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\nThe post AI Ethics Tackles Issues Arising From Machines Making Decisions appeared first on PYMNTS.com.
\n", "content_text": "Imagine a world where machines make life-altering decisions about your health, your job prospects and even your freedom. That world isn\u2019t science fiction \u2014 it\u2019s already here. As artificial intelligence (AI) reshapes our lives, a new frontier is emerging: AI ethics.\nThis rapidly evolving field tackles a crucial question: How do we ensure that intelligent machines serve humanity\u2019s best interests? From privacy concerns to racial bias, from job displacement to existential risks, AI ethics grapples with the moral implications of our increasingly automated world.\nAI ethics encompasses a wide range of concerns, including privacy, bias, transparency, accountability, and the long-term societal impacts of artificial intelligence. As AI systems become more sophisticated and autonomous, the ethical questions surrounding their development and deployment grow increasingly complex and urgent.\nThe Bias Blind Spot: When AI Amplifies Inequality\nOne of the primary areas of focus in AI ethics is algorithmic bias. AI systems are only as unbiased as the data they\u2019re trained on and the humans who design them. The consequences can be far-reaching and profound when these systems reflect or amplify existing societal biases.\nA stark example of this issue emerged in 2018 when Amazon scrapped an AI recruiting tool that showed bias against women. The system, which was designed to review resumes and identify top talent, had been trained on patterns in resumes submitted to the company over a 10-year period. Because tech industry applicants were predominantly male then, the AI learned to penalize resumes that included the word \u201cwomen\u2019s\u201d or mentioned all-women\u2019s colleges.\nThis case highlighted the potential for AI to perpetuate and even exacerbate existing inequalities if not carefully designed and monitored. It also underscored the need for diverse teams in AI development to help identify and mitigate such biases.\nThe problem of algorithmic bias extends far beyond hiring practices. A study published in Science\u00a0found that a widely used algorithm in U.S. hospitals was systematically discriminating against black patients. The algorithm, used to identify patients who would benefit from extra medical care, was unintentionally programmed to use health costs as a proxy for health needs. Because less money has historically been spent on black patients due to socioeconomic factors and disparities in access to care, the algorithm incorrectly concluded that black patients were healthier than equally sick white patients.\nAnother critical concern in AI ethics is privacy. As AI systems become more adept at collecting, analyzing and utilizing personal data, questions arise about the appropriate limits of such capabilities. The use of facial recognition technology by law enforcement agencies has sparked particular controversy, with critics arguing that it represents an unacceptable intrusion into personal privacy and civil liberties.\nThe privacy implications of AI extend beyond facial recognition. In 2019, it was revealed that Google\u2019s AI assistant could eavesdrop on private conversations through its Nest security system. The incident highlighted the potential for AI-powered smart home devices to become surveillance tools, raising questions about the balance between convenience and privacy in an increasingly connected world.\nTransparency and explainability represent another key pillar of AI ethics. As AI systems become more complex and make decisions that significantly impact people\u2019s lives \u2014 from loan approvals to medical diagnoses \u2014 there\u2019s a growing demand for them to explain their reasoning in terms that humans can understand.\nThis issue arose in the healthcare sector when IBM\u2019s Watson for Oncology, an AI system designed to assist in cancer treatment recommendations, faced criticism for its lack of transparency. Oncologists expressed concern that they couldn\u2019t understand how the system arrived at its recommendations, making it difficult to trust and implement its advice in critical care situations.\nThe Trolley Problem 2.0: Ethics in Autonomous Systems\nAs AI systems become more autonomous, questions of accountability also come to the forefront. When an AI makes a decision that results in harm, who bears responsibility \u2014 the developers, the company deploying the system or the AI itself?\nThis question has practical implications in areas like autonomous vehicles. In 2018, an Uber self-driving car struck and killed a pedestrian in Arizona, raising questions about liability and the ethical considerations in programming such vehicles. Should an autonomous car prioritize the safety of its passengers or pedestrians in unavoidable accident scenarios? These \u201ctrolley problem\u201d type dilemmas have moved from philosophical thought experiments to real-world engineering challenges.\nSimilar ethical dilemmas arise in the field of autonomous weapons systems. The prospect of \u201ckiller robots\u201d capable of selecting and engaging targets without human intervention has sparked intense debate. While proponents argue that such systems could reduce military casualties and potentially be more precise than human soldiers, critics warn of the moral hazard of delegating life-or-death decisions to machines.\nGoogle faced significant employee backlash over its involvement in Project Maven, a U.S. Department of Defense initiative using AI for drone footage analysis. The controversy led to Google deciding not to renew the contract and establishing AI principles that preclude the development of AI for weapons.\nLooking ahead, the field of AI ethics must also grapple with long-term existential questions. As AI capabilities continue to advance rapidly, some experts warn that artificial general intelligence (AGI) or artificial superintelligence (ASI) could pose existential risks to humanity if not developed with robust ethical safeguards.\nOrganizations like the Future of Humanity Institute\u00a0at Oxford University and the Center for Human-Compatible AI at UC Berkeley are dedicated to researching ways to ensure that advanced AI systems remain aligned with human values and interests. These efforts involve complex technical challenges, such as developing reliable methods to specify and encode human values in AI systems, as well as philosophical questions about the nature of intelligence, consciousness and morality.\nIn response to these myriad challenges, governments and organizations worldwide are working to establish ethical guidelines and regulatory frameworks for AI development and deployment. The European Union\u2019s AI Act, which aims to create the world\u2019s first comprehensive AI regulations, represents a significant step in this direction.\n\nFor all PYMNTS AI coverage, subscribe to the daily\u00a0AI\u00a0Newsletter.\n\nThe post AI Ethics Tackles Issues Arising From Machines Making Decisions appeared first on PYMNTS.com.", "date_published": "2024-07-29T13:52:28-04:00", "date_modified": "2024-07-29T15:14:07-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/f05cc0fdcc9e387e4f3570c17158c503?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2024/03/AI-ethics.jpg", "tags": [ "AI", "AI Act", "AI ethics", "AI regulation", "AI risks", "Amazon", "artificial intelligence", "Center for Human-Compatible AI at UC Berkeley", "Editor's Picks", "Ethics", "Future of Humanity Institute", "Google", "IBM", "News", "privacy", "PYMNTS News", "Technology", "artificial intelligence" ] } ] }