![\"AI](\"https://www.pymnts.com/wp-content/uploads/2024/09/AI-carmakers.jpg\")
In a whirlwind week for AI, OpenAI co-founder Ilya Sutskever\u2019s new venture secured $1 billion for \u2018safe\u2019 superintelligence, while AI-driven drug discovery hit roadblocks in clinical trials. Meanwhile, tech giants raced to perfect multilingual chatbots, researchers mined big data for insights, and a breakthrough in \u201cpersonhood credentials\u201d promised to distinguish humans from AI online.
\nOpenAI co-founder Ilya Sutskever\u2019s new venture, Safe Superintelligence (SSI), has secured a cool $1 billion in funding, valuing the startup at a whopping $5 billion. With backing from tech heavyweights like Andreessen Horowitz and Sequoia, SSI is gearing up for a \u201cstraight shot to safe superintelligence,\u201d prioritizing R&D over rapid commercialization. This move follows Sutskever\u2019s dramatic OpenAI exit, where boardroom drama \u201cdiminished\u201d his role and dissolved his AI safety team.
\nAI is also reshaping drug discovery, but recent clinical trials reveal both its promise and challenges. Recursion Pharmaceuticals, a self-described \u201cTechBio company,\u201d recently announced mixed results from its AI-driven Phase 2 SYCAMORE trial for REC-994, targeting a rare brain disorder. While meeting safety endpoints, efficacy results were inconclusive, highlighting AI\u2019s potential and limitations in pharmaceutical research.
\n\u201cWhile artificial intelligence excels at analyzing vast datasets, the scarcity of information on uncommon neurological conditions poses a major challenge,\u201d \u00a0Keaun Amani, CEO of\u00a0Neurosnap, told PYMNTS.
\nTech giants are racing to develop multilingual AI chatbots for cross-border eCommerce, with Google\u2019s Gemini and other projects like OpenBuddy\u00a0and Cohere\u2019s Aya 23 leading the charge. These AI assistants aim to break down language barriers, potentially shifting how businesses engage with international customers.
\n\u201cMultilingual AI chatbots hold significant potential for SMBs looking to expand into international markets,\u201d Tim Peters, CMO of\u00a0Enghouse Systems, said. However, experts cautioned that while AI excels at general communication, it may stumble on nuanced cultural contexts and complex negotiations.
\nIn today\u2019s digital gold rush, AI-powered data mining is the high-tech prospector, sifting through vast information reserves to unearth valuable insights. Unlike cryptocurrency mining, this process extracts business intelligence from big data, revolutionizing industries and driving corporate decision-making. Companies leverage these advanced techniques to predict consumer behavior and optimize operations, gaining a sharp competitive edge.
\nResearchers from OpenAI and MIT have unveiled \u201cpersonhood credentials,\u201d a system to prove you\u2019re human online without sacrificing privacy. This cryptographic solution creates unique digital badges, allowing users to verify their humanity while keeping personal details under wraps. As AI renders traditional verification tools like CAPTCHAs obsolete, this innovation could drive eCommerce trust, social media authenticity and fraud prevention.
\nThe post The Week in AI: \u2018Safe\u2019 Superintelligence, Research Hurdles and Digital ID Badges appeared first on PYMNTS.com.
\n", "content_text": "In a whirlwind week for AI, OpenAI co-founder Ilya Sutskever\u2019s new venture secured $1 billion for \u2018safe\u2019 superintelligence, while AI-driven drug discovery hit roadblocks in clinical trials. Meanwhile, tech giants raced to perfect multilingual chatbots, researchers mined big data for insights, and a breakthrough in \u201cpersonhood credentials\u201d promised to distinguish humans from AI online.\nAI Whiz Raises $1B to Build \u2018Safe\u2019 Superintelligence\nOpenAI co-founder Ilya Sutskever\u2019s new venture, Safe Superintelligence (SSI), has secured a cool $1 billion in funding, valuing the startup at a whopping $5 billion. With backing from tech heavyweights like Andreessen Horowitz and Sequoia, SSI is gearing up for a \u201cstraight shot to safe superintelligence,\u201d prioritizing R&D over rapid commercialization. This move follows Sutskever\u2019s dramatic OpenAI exit, where boardroom drama \u201cdiminished\u201d his role and dissolved his AI safety team.\nAI Drug Discovery Faces Reality Check in Clinical Trial\nAI is also reshaping drug discovery, but recent clinical trials reveal both its promise and challenges. Recursion Pharmaceuticals, a self-described \u201cTechBio company,\u201d recently announced mixed results from its AI-driven Phase 2 SYCAMORE trial for REC-994, targeting a rare brain disorder. While meeting safety endpoints, efficacy results were inconclusive, highlighting AI\u2019s potential and limitations in pharmaceutical research.\n\u201cWhile artificial intelligence excels at analyzing vast datasets, the scarcity of information on uncommon neurological conditions poses a major challenge,\u201d \u00a0Keaun Amani, CEO of\u00a0Neurosnap, told PYMNTS.\nAI Chatbots Speak Your Language, But Can They Close the Deal?\nTech giants are racing to develop multilingual AI chatbots for cross-border eCommerce, with Google\u2019s Gemini and other projects like OpenBuddy\u00a0and Cohere\u2019s Aya 23 leading the charge. These AI assistants aim to break down language barriers, potentially shifting how businesses engage with international customers.\n\u201cMultilingual AI chatbots hold significant potential for SMBs looking to expand into international markets,\u201d Tim Peters, CMO of\u00a0Enghouse Systems, said. However, experts cautioned that while AI excels at general communication, it may stumble on nuanced cultural contexts and complex negotiations.\nAI Strikes Gold in Data Rush, Mining Insights\nIn today\u2019s digital gold rush, AI-powered data mining is the high-tech prospector, sifting through vast information reserves to unearth valuable insights. Unlike cryptocurrency mining, this process extracts business intelligence from big data, revolutionizing industries and driving corporate decision-making. Companies leverage these advanced techniques to predict consumer behavior and optimize operations, gaining a sharp competitive edge.\nDigital ID Breakthrough: Humans Get AI-Proof Badges\nResearchers from OpenAI and MIT have unveiled \u201cpersonhood credentials,\u201d a system to prove you\u2019re human online without sacrificing privacy. This cryptographic solution creates unique digital badges, allowing users to verify their humanity while keeping personal details under wraps. As AI renders traditional verification tools like CAPTCHAs obsolete, this innovation could drive eCommerce trust, social media authenticity and fraud prevention.\nThe post The Week in AI: \u2018Safe\u2019 Superintelligence, Research Hurdles and Digital ID Badges appeared first on PYMNTS.com.", "date_published": "2024-09-06T12:35:44-04:00", "date_modified": "2024-09-06T12:35:44-04:00", "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/2024/06/Artificial-Intelligence-AI-1.jpg", "tags": [ "AI", "AI investments", "artificial intelligence", "data analysis", "ecommerce", "funding", "Ilya Sutskever", "Investments", "News", "OpenAI", "pharmaceuticals", "PYMNTS News", "Retail", "Safe Superintelligence", "This Week in AI", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2095027", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/ai-startups-1b-windfall-signals-potential-shake-up-in-global-business-landscape/", "title": "AI Startup\u2019s $1B Windfall Signals Potential Shake-up in Global Business Landscape", "content_html": "A three-month-old artificial intelligence (AI) startup\u2019s eye-popping $1 billion funding round could signal a shift in how the technology affects commerce.
\nSafe Superintelligence (SSI), co-founded by former OpenAI chief scientist Ilya Sutskever, has secured this massive investment with only 10 employees. The company, launched in June by Sutskever along with Daniel Gross, a former Y Combinator partner who previously led AI efforts at Apple, and Daniel Levy, a former colleague of Sutskever’s at OpenAI, is focusing on developing artificial general intelligence (AGI) with an emphasis on safety.
\n\u201cAt the end of the day, it\u2019s all about increasing profits, reducing losses, and mitigating risk. In many use cases where AI can model the problem or historical data, it can provide significant benefits,\u201d Shoab Khan, chancellor of the Sir Syed CASE Institute of Technology, told PYMNTS.
\nThe funding round saw participation from NFDG, a venture capital firm run by Gross and Nat Friedman, alongside tech investment heavyweights Andreessen Horowitz, Sequoia Capital, DST Global and SV Angel. This substantial investment in such a young company underscores the growing interest and high stakes in the race to develop advanced AI systems.
\nThe company plans to use the funds partly for hiring, seeking to assemble what it calls \u201ca lean, cracked team of the world\u2019s best engineers and researchers.\u201d
\nThe 37-year-old Sutskever brings considerable experience to the venture. After completing his Ph.D. under renowned AI academic Geoffrey Hinton at the University of Toronto, he joined Google in 2013 before co-founding OpenAI in 2015. His departure from OpenAI followed a tumultuous period involving him in CEO Sam Altman\u2019s brief ousting.
\nWhile SSI has not yet partnered with any cloud providers or chipmakers, a significant portion of the investment is earmarked for building up computing power. Sutskever has indicated that SSI\u2019s approach to scaling will differ from that of OpenAI, though specifics remain undisclosed.
\nThe focus on safety in AI development comes at a time of increasing discourse about advanced AI systems\u2019 potential risks and rewards. Sutskever\u2019s experience leading a safety team at OpenAI that oversaw AI\u2019s existential risks may inform SSI\u2019s approach, although that team was disbanded shortly after his departure.
\nAccording to Khan, AI in commerce has limitations: \u201cThis depends on accurately modeling data probability distribution. In cases where data doesn’t follow a clear distribution or depends on many factors \u2014 some of which are difficult to measure, such as predicting bitcoin prices \u2014 AI\u2019s effectiveness is limited.\u201d
\nDespite challenges, there is optimism about AI\u2019s potential in business. \u201cI see substantial advantages for investors in supporting AI for decision-making in commerce by building complex models, incorporating all relevant factors and data, and reshaping the role of human oversight and trust,\u201d Khan said.
\nCompanies pushing the boundaries of AI capabilities increase the potential for transforming business practices. The substantial investment in SSI and similar ventures signals a growing recognition of the potential transformative power of advanced AI systems in the business world.
\nThe $5 billion valuation of SSI, a company just three months old, reflects the high expectations and potential that investors see in advanced AI technologies. This valuation puts SSI in the upper echelons of AI startups, competing with more established players.
\nResearch and development efforts at SSI are just beginning, and the broader implications for commerce and industry remain to be seen. The company\u2019s focus on safety in AGI development could set new standards for the industry, potentially influencing how other companies approach AI development and implementation.
\nFor all PYMNTS AI coverage, subscribe to the daily\u00a0AI\u00a0Newsletter.
\nThe post AI Startup\u2019s $1B Windfall Signals Potential Shake-up in Global Business Landscape appeared first on PYMNTS.com.
\n", "content_text": "A three-month-old artificial intelligence (AI) startup\u2019s eye-popping $1 billion funding round could signal a shift in how the technology affects commerce.\nSafe Superintelligence (SSI), co-founded by former OpenAI chief scientist Ilya Sutskever, has secured this massive investment with only 10 employees. The company, launched in June by Sutskever along with Daniel Gross, a former Y Combinator partner who previously led AI efforts at Apple, and Daniel Levy, a former colleague of Sutskever’s at OpenAI, is focusing on developing artificial general intelligence (AGI) with an emphasis on safety.\n\u201cAt the end of the day, it\u2019s all about increasing profits, reducing losses, and mitigating risk. In many use cases where AI can model the problem or historical data, it can provide significant benefits,\u201d Shoab Khan, chancellor of the Sir Syed CASE Institute of Technology, told PYMNTS.\nThe funding round saw participation from NFDG, a venture capital firm run by Gross and Nat Friedman, alongside tech investment heavyweights Andreessen Horowitz, Sequoia Capital, DST Global and SV Angel. This substantial investment in such a young company underscores the growing interest and high stakes in the race to develop advanced AI systems.\nA Billion-Dollar Bet on Safety-Focused AGI\nThe company plans to use the funds partly for hiring, seeking to assemble what it calls \u201ca lean, cracked team of the world\u2019s best engineers and researchers.\u201d\nThe 37-year-old Sutskever brings considerable experience to the venture. After completing his Ph.D. under renowned AI academic Geoffrey Hinton at the University of Toronto, he joined Google in 2013 before co-founding OpenAI in 2015. His departure from OpenAI followed a tumultuous period involving him in CEO Sam Altman\u2019s brief ousting.\nWhile SSI has not yet partnered with any cloud providers or chipmakers, a significant portion of the investment is earmarked for building up computing power. Sutskever has indicated that SSI\u2019s approach to scaling will differ from that of OpenAI, though specifics remain undisclosed.\nThe focus on safety in AI development comes at a time of increasing discourse about advanced AI systems\u2019 potential risks and rewards. Sutskever\u2019s experience leading a safety team at OpenAI that oversaw AI\u2019s existential risks may inform SSI\u2019s approach, although that team was disbanded shortly after his departure.\nBalancing Potential and Limitations\nAccording to Khan, AI in commerce has limitations: \u201cThis depends on accurately modeling data probability distribution. In cases where data doesn’t follow a clear distribution or depends on many factors \u2014 some of which are difficult to measure, such as predicting bitcoin prices \u2014 AI\u2019s effectiveness is limited.\u201d\nDespite challenges, there is optimism about AI\u2019s potential in business. \u201cI see substantial advantages for investors in supporting AI for decision-making in commerce by building complex models, incorporating all relevant factors and data, and reshaping the role of human oversight and trust,\u201d Khan said.\nCompanies pushing the boundaries of AI capabilities increase the potential for transforming business practices. The substantial investment in SSI and similar ventures signals a growing recognition of the potential transformative power of advanced AI systems in the business world.\nThe $5 billion valuation of SSI, a company just three months old, reflects the high expectations and potential that investors see in advanced AI technologies. This valuation puts SSI in the upper echelons of AI startups, competing with more established players.\nResearch and development efforts at SSI are just beginning, and the broader implications for commerce and industry remain to be seen. The company\u2019s focus on safety in AGI development could set new standards for the industry, potentially influencing how other companies approach AI development and implementation.\n\nFor all PYMNTS AI coverage, subscribe to the daily\u00a0AI\u00a0Newsletter.\n\nThe post AI Startup\u2019s $1B Windfall Signals Potential Shake-up in Global Business Landscape appeared first on PYMNTS.com.", "date_published": "2024-09-06T09:50:19-04:00", "date_modified": "2024-09-06T09:50:19-04:00", "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/2024/09/AI-startup-business.png", "tags": [ "AI", "Artificial General Intelligence", "artificial intelligence", "funding", "Ilya Sutskever", "Investments", "News", "OpenAI", "PYMNTS News", "Safe Superintelligence", "startups", "Technology", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2094712", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/ai-drug-discovery-trial-reveals-promise-and-challenges-of-using-the-tech/", "title": "AI Drug Discovery Trial Reveals Promise and Challenges of Using the Tech", "content_html": "As artificial intelligence (AI) promises to remake drug discovery, recent clinical trial results reveal its potential and challenges.
\nRecursion Pharmaceuticals, a self-described \u201cclinical stage TechBio company,\u201d recently announced results from its Phase 2 SYCAMORE trial for REC-994, a drug candidate targeting cerebral cavernous malformation (CCM), a rare brain disorder. The trial met its primary safety endpoint but showed mixed efficacy results, illustrating the complexities of translating AI-driven discoveries into clinical success.
\nThe company\u2019s Recursion OS platform uses machine-learning algorithms to analyze vast datasets, aiming to identify new drug candidates more efficiently than traditional methods. This approach represents a growing trend in the pharmaceutical industry to leverage AI in drug discovery. It also shows the challenges.
\n\u201cWhile artificial intelligence excels at analyzing vast datasets, the scarcity of information on uncommon neurological conditions poses a major challenge,\u201d Keaun Amani, CEO of Neurosnap, an AI platform used by labs, told PYMNTS. \u201cLimited patient populations make it difficult to gather sufficient data for training accurate AI models.\u201d
\nProgress in AI-driven drug discovery is evident. Alister Campbell, VP of science and technology at Dotmatics, told PYMNTS that since 2015, AI-native biotechnology companies and their partners have brought 75 candidates to clinical trials, with numbers growing yearly.
\n\u201cAI use in drug discovery comes in many shapes and forms, from drug repurposing to predicting structures of anti-bodies and proteins using algorithms like AlphaFold, designing small molecule drugs using generative AI methods, using AI to mine vast OMIC datasets providing valuable insights into disease biology, druggable targets, and biomarkers,\u201d Campbell said.
\nJo Varshney, founder and CEO of AI drug discovery company VeriSIM Life, told PYMNTS: \u201cNeurological conditions often lack clear, easily measurable indicators in lab tests or clinical assessments, resulting in a data scarcity that limits the effectiveness of AI systems.\u201d
\nRecursion\u2019s SYCAMORE clinical trial for CCM, which affects approximately 360,000 symptomatic individuals in the U.S. and EU, illustrates these challenges. Dr. Najat Khan, chief R&D officer at Recursion, noted \u201cpromising trends in exploratory efficacy endpoints,\u201d particularly at the highest dose. However, the company acknowledged that \u201cimprovements in either patient or physician-reported outcomes were not yet seen at the 12 month time point.\u201d
\nThe trial\u2019s outcome reflects broader industry challenges. According to Amani, \u201cMixed results in clinical studies reveal that while AI has great potential to revolutionize drug discovery, it still faces significant hurdles in accurately predicting drug efficacy. One major challenge is the complexity of biological systems, which AI models often struggle to fully capture.\u201d
\nExperts suggest various approaches to advance AI in drug discovery. Amani envisions developing more complex models capable of analyzing larger biological systems. He suggests \u201cdeveloping all-atom models capable of analyzing larger, more complex biological systems. These models, combined with a growing trend of blending machine learning and physics-based methods, offer the potential to simulate molecular interactions with unprecedented accuracy.\u201d
\nCampbell proposes combining AI with traditional techniques to identify relevant biological targets and develop drug candidates more efficiently. He suggests a multi-pronged approach to identify clinically relevant biological targets, develop ideal candidates more quickly and cheaply, and reduce the chances of failure due to safety, efficacy and cost issues.
\nAccessibility of AI tools is also crucial. Amani notes that platforms like Neurosnap have streamlined the process, making it easier for scientists to use these tools. \u201cAccessing AI-based tools for drug discovery can often be technically prohibitive to researchers,\u201d Amani said. \u201cPlatforms like Neurosnap have greatly streamlined this process making it easier for scientists to efficiently utilize the tools they need.\u201d
\nVarshney said developing more sophisticated \u201cknowledge\u201d or mechanistic systems that intricately incorporate detailed aspects of biology could yield more accurate and reliable predictions when integrated with AI.
\nFor all PYMNTS AI coverage, subscribe to the daily\u00a0AI\u00a0Newsletter.
\nThe post AI Drug Discovery Trial Reveals Promise and Challenges of Using the Tech appeared first on PYMNTS.com.
\n", "content_text": "As artificial intelligence (AI) promises to remake drug discovery, recent clinical trial results reveal its potential and challenges.\nRecursion Pharmaceuticals, a self-described \u201cclinical stage TechBio company,\u201d recently announced results from its Phase 2 SYCAMORE trial for REC-994, a drug candidate targeting cerebral cavernous malformation (CCM), a rare brain disorder. The trial met its primary safety endpoint but showed mixed efficacy results, illustrating the complexities of translating AI-driven discoveries into clinical success.\nThe company\u2019s Recursion OS platform uses machine-learning algorithms to analyze vast datasets, aiming to identify new drug candidates more efficiently than traditional methods. This approach represents a growing trend in the pharmaceutical industry to leverage AI in drug discovery. It also shows the challenges.\n\u201cWhile artificial intelligence excels at analyzing vast datasets, the scarcity of information on uncommon neurological conditions poses a major challenge,\u201d Keaun Amani, CEO of Neurosnap, an AI platform used by labs, told PYMNTS. \u201cLimited patient populations make it difficult to gather sufficient data for training accurate AI models.\u201d\nAI\u2019s Growing Role in Drug Discovery\nProgress in AI-driven drug discovery is evident. Alister Campbell, VP of science and technology at Dotmatics, told PYMNTS that since 2015, AI-native biotechnology companies and their partners have brought 75 candidates to clinical trials, with numbers growing yearly.\n\u201cAI use in drug discovery comes in many shapes and forms, from drug repurposing to predicting structures of anti-bodies and proteins using algorithms like AlphaFold, designing small molecule drugs using generative AI methods, using AI to mine vast OMIC datasets providing valuable insights into disease biology, druggable targets, and biomarkers,\u201d Campbell said.\nJo Varshney, founder and CEO of AI drug discovery company VeriSIM Life, told PYMNTS: \u201cNeurological conditions often lack clear, easily measurable indicators in lab tests or clinical assessments, resulting in a data scarcity that limits the effectiveness of AI systems.\u201d\nRecursion\u2019s SYCAMORE clinical trial for CCM, which affects approximately 360,000 symptomatic individuals in the U.S. and EU, illustrates these challenges. Dr. Najat Khan, chief R&D officer at Recursion, noted \u201cpromising trends in exploratory efficacy endpoints,\u201d particularly at the highest dose. However, the company acknowledged that \u201cimprovements in either patient or physician-reported outcomes were not yet seen at the 12 month time point.\u201d\nThe trial\u2019s outcome reflects broader industry challenges. According to Amani, \u201cMixed results in clinical studies reveal that while AI has great potential to revolutionize drug discovery, it still faces significant hurdles in accurately predicting drug efficacy. One major challenge is the complexity of biological systems, which AI models often struggle to fully capture.\u201d\nNavigating the Path Forward\nExperts suggest various approaches to advance AI in drug discovery. Amani envisions developing more complex models capable of analyzing larger biological systems. He suggests \u201cdeveloping all-atom models capable of analyzing larger, more complex biological systems. These models, combined with a growing trend of blending machine learning and physics-based methods, offer the potential to simulate molecular interactions with unprecedented accuracy.\u201d\nCampbell proposes combining AI with traditional techniques to identify relevant biological targets and develop drug candidates more efficiently. He suggests a multi-pronged approach to identify clinically relevant biological targets, develop ideal candidates more quickly and cheaply, and reduce the chances of failure due to safety, efficacy and cost issues.\nAccessibility of AI tools is also crucial. Amani notes that platforms like Neurosnap have streamlined the process, making it easier for scientists to use these tools. \u201cAccessing AI-based tools for drug discovery can often be technically prohibitive to researchers,\u201d Amani said. \u201cPlatforms like Neurosnap have greatly streamlined this process making it easier for scientists to efficiently utilize the tools they need.\u201d\nVarshney said developing more sophisticated \u201cknowledge\u201d or mechanistic systems that intricately incorporate detailed aspects of biology could yield more accurate and reliable predictions when integrated with AI.\n\nFor all PYMNTS AI coverage, subscribe to the daily\u00a0AI\u00a0Newsletter.\n\nThe post AI Drug Discovery Trial Reveals Promise and Challenges of Using the Tech appeared first on PYMNTS.com.", "date_published": "2024-09-05T16:56:23-04:00", "date_modified": "2024-09-05T16:56:23-04:00", "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/2024/09/AI-drug-discovery-trial.png", "tags": [ "AI", "artificial intelligence", "Dotmatics", "drug trials", "Neurosnap", "News", "pharmaceuticals", "PYMNTS News", "Recursion Pharmaceuticals", "research and development", "Technology", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2094654", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/report-openai-considers-2000-monthly-subscription-prices-for-new-llms/", "title": "Report: OpenAI Considers $2,000 Monthly Subscription Prices for New LLMs", "content_html": "OpenAI executives are reportedly considering subscription prices as high as $2,000 per month for the company\u2019s upcoming large language models (LLMs) like Strawberry and Orion.
\nThe executives have discussed higher prices in early internal talks regarding these LLMs, Reuters reported Thursday (Sept. 5), citing a paywalled article by The Information that is based on an unnamed source.
\nOpenAI did not immediately reply to PYMNTS\u2019 request for comment.
\nThe company\u2019s ChatGPT Plus currently costs $20 a month, and hundreds of millions of users access the model\u2019s free tier, according to the report.
\nIt was reported Aug. 27 that OpenAI aims to release Strawberry, its next-level artificial intelligence\u00a0(AI) product, in the fall.
\nStrawberry will be able to solve problems and tasks that are beyond the capabilities of current AI models. It will be able to solve math problems it has never encountered; perform high-level tasks like developing market strategies and solving complex word puzzles; and perform \u201cdeep research.\u201d
\nThis news comes at a time when OpenAI is reportedly considering changing its corporate structure to make that structure simpler and more attractive to financial backers.
\nThe company currently issues investors equity from its for-profit subsidiary, which is governed by its non-profit board whose \u201cprincipal beneficiary is humanity, not OpenAI investors.\u201d
\nResponding to claims about the company changing its corporate structure, OpenAI told the Financial Times: \u201cWe remain focused on building AI that benefits everyone and as we\u2019ve previously shared we\u2019re working with our board to ensure that we\u2019re best positioned to succeed in our mission. The non-profit is core to our mission and will continue to exist.\u201d
\nIt has also been reported that OpenAI aims to raise \u201cseveral billion dollars\u201d in a funding round that would value it at above $100 billion.
\nWhen employees sold shares in late 2023, the company was valued at $86 billion.
\nOpenAI\u2019s ChatGPT remains the market leader in the AI space with hundreds of millions of monthly users at a time when there is fierce competition among companies offering AI tools.
\nPotential investors in the company\u2019s upcoming funding round reportedly include Apple, Nvidia, Microsoft and Thrive Capital, which is said to be leading the round.
\nThe post Report: OpenAI Considers $2,000 Monthly Subscription Prices for New LLMs appeared first on PYMNTS.com.
\n", "content_text": "OpenAI executives are reportedly considering subscription prices as high as $2,000 per month for the company\u2019s upcoming large language models (LLMs) like Strawberry and Orion.\nThe executives have discussed higher prices in early internal talks regarding these LLMs, Reuters reported Thursday (Sept. 5), citing a paywalled article by The Information that is based on an unnamed source.\nOpenAI did not immediately reply to PYMNTS\u2019 request for comment.\nThe company\u2019s ChatGPT Plus currently costs $20 a month, and hundreds of millions of users access the model\u2019s free tier, according to the report.\nIt was reported Aug. 27 that OpenAI aims to release Strawberry, its next-level artificial intelligence\u00a0(AI) product, in the fall.\nStrawberry will be able to solve problems and tasks that are beyond the capabilities of current AI models. It will be able to solve math problems it has never encountered; perform high-level tasks like developing market strategies and solving complex word puzzles; and perform \u201cdeep research.\u201d\nThis news comes at a time when OpenAI is reportedly considering changing its corporate structure to make that structure simpler and more attractive to financial backers.\nThe company currently issues investors equity from its for-profit subsidiary, which is governed by its non-profit board whose \u201cprincipal beneficiary is humanity, not OpenAI investors.\u201d\nResponding to claims about the company changing its corporate structure, OpenAI told the Financial Times: \u201cWe remain focused on building AI that benefits everyone and as we\u2019ve previously shared we\u2019re working with our board to ensure that we\u2019re best positioned to succeed in our mission. The non-profit is core to our mission and will continue to exist.\u201d\nIt has also been reported that OpenAI aims to raise \u201cseveral billion dollars\u201d in a funding round that would value it at above $100 billion.\nWhen employees sold shares in late 2023, the company was valued at $86 billion.\nOpenAI\u2019s ChatGPT remains the market leader in the AI space with hundreds of millions of monthly users at a time when there is fierce competition among companies offering AI tools.\nPotential investors in the company\u2019s upcoming funding round reportedly include Apple, Nvidia, Microsoft and Thrive Capital, which is said to be leading the round.\nThe post Report: OpenAI Considers $2,000 Monthly Subscription Prices for New LLMs appeared first on PYMNTS.com.", "date_published": "2024-09-05T15:32:04-04:00", "date_modified": "2024-09-05T15:32:04-04:00", "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/2024/01/OpenAI-3.jpg", "tags": [ "AI", "artificial intelligence", "ChatGPT", "digital transformation", "large language models", "LLMs", "News", "PYMNTS News", "subscriptions", "Technology", "What's Hot", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2094549", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/google-adds-dresses-to-ai-powered-virtual-try-on-offering/", "title": "Google Adds Dresses to AI-Powered Virtual Try-On Offering", "content_html": "Google\u2019s\u00a0virtual try-on tool now lets shoppers see how they\u2019d look in dresses.
\nThe tech giant on Thursday (Sept. 5)\u00a0announced it is expanding the artificial intelligence (AI)-powered offering to cover dresses, one of its most-searched apparel categories.
\n\u201cThis feature is made possible thanks to a generative AI technology we created specifically for\u00a0virtual try-on\u00a0(VTO), which uses a technique based on diffusion,\u201d the company wrote on its blog. \u201cDiffusion lets us generate every pixel from scratch to produce high-quality, realistic images of tops and blouses on models.\u201d
\nHowever, testing the diffusion technique for dresses uncovered a pair of challenges. For one, dresses in many cases feature highly detailed designs. Google compared it to trying to paint an image on a small canvas.
\n\u201cYou can think of our VTO challenge in the same way: Our existing VTO AI model successfully diffused using low-resolution images, but in our testing with dresses, this approach often resulted in the loss of a dress\u2019s critical details \u2014 and simply switching to high-resolution didn\u2019t help,\u201d the company said.
\nTo address this, Google researchers employed a \u201cprogressive training strategy\u201d for VTO, where diffusion starts with lower-resolution images and gradually trains in higher resolutions to reflect finer details.
\nIn addition, because dresses cover more of a person\u2019s body than tops, Google found that \u201cerasing\u201d and \u201creplacing\u201d the dress on a person would \u201csmudge\u201d their features or obscure important details of their body. Google remedied this problem with a new technique called the VTO-UNet Diffusion Transformer, \u201cwhich isolates and preserves a person\u2019s important features.\u201d
\nThe news comes as other major players in the eCommerce world are stepping up their virtual try-on programs. For example,\u00a0Walmart\u00a0in July released its first annual \u201cAdaptive Retail Report,\u201d featuring results from a survey that looked at consumer interest in technologies such as virtual try-ons and other tools to see how items would appear in the real world.
\n\u201cThis focus on\u00a0virtual try-on and visualization\u00a0technologies suggests that Walmart may be looking to step up its existing presence in the space, with its beauty, apparel and accessories digital trial offerings,\u201d PYMNTS wrote at the time.
\nAnd as covered here earlier in the year, virtual try-on can help shoppers make sure they get their\u00a0clothing purchases\u00a0right the first time, thus eliminating a headache for retailers.
\n\u201cVirtual try-on helps to reduce returns because you get the\u00a0best product, which you like [the most],\u201d\u00a0Wayne Liu, president and chief growth officer at AI and augmented reality (AR) beauty technology company\u00a0Perfect Corp., told PYMNTS in February.
\nThe post Google Adds Dresses to AI-Powered Virtual Try-On Offering appeared first on PYMNTS.com.
\n", "content_text": "Google\u2019s\u00a0virtual try-on tool now lets shoppers see how they\u2019d look in dresses.\nThe tech giant on Thursday (Sept. 5)\u00a0announced it is expanding the artificial intelligence (AI)-powered offering to cover dresses, one of its most-searched apparel categories.\n\u201cThis feature is made possible thanks to a generative AI technology we created specifically for\u00a0virtual try-on\u00a0(VTO), which uses a technique based on diffusion,\u201d the company wrote on its blog. \u201cDiffusion lets us generate every pixel from scratch to produce high-quality, realistic images of tops and blouses on models.\u201d\nHowever, testing the diffusion technique for dresses uncovered a pair of challenges. For one, dresses in many cases feature highly detailed designs. Google compared it to trying to paint an image on a small canvas.\n\u201cYou can think of our VTO challenge in the same way: Our existing VTO AI model successfully diffused using low-resolution images, but in our testing with dresses, this approach often resulted in the loss of a dress\u2019s critical details \u2014 and simply switching to high-resolution didn\u2019t help,\u201d the company said.\nTo address this, Google researchers employed a \u201cprogressive training strategy\u201d for VTO, where diffusion starts with lower-resolution images and gradually trains in higher resolutions to reflect finer details.\nIn addition, because dresses cover more of a person\u2019s body than tops, Google found that \u201cerasing\u201d and \u201creplacing\u201d the dress on a person would \u201csmudge\u201d their features or obscure important details of their body. Google remedied this problem with a new technique called the VTO-UNet Diffusion Transformer, \u201cwhich isolates and preserves a person\u2019s important features.\u201d\nThe news comes as other major players in the eCommerce world are stepping up their virtual try-on programs. For example,\u00a0Walmart\u00a0in July released its first annual \u201cAdaptive Retail Report,\u201d featuring results from a survey that looked at consumer interest in technologies such as virtual try-ons and other tools to see how items would appear in the real world.\n\u201cThis focus on\u00a0virtual try-on and visualization\u00a0technologies suggests that Walmart may be looking to step up its existing presence in the space, with its beauty, apparel and accessories digital trial offerings,\u201d PYMNTS wrote at the time.\nAnd as covered here earlier in the year, virtual try-on can help shoppers make sure they get their\u00a0clothing purchases\u00a0right the first time, thus eliminating a headache for retailers.\n\u201cVirtual try-on helps to reduce returns because you get the\u00a0best product, which you like [the most],\u201d\u00a0Wayne Liu, president and chief growth officer at AI and augmented reality (AR) beauty technology company\u00a0Perfect Corp., told PYMNTS in February.\nThe post Google Adds Dresses to AI-Powered Virtual Try-On Offering appeared first on PYMNTS.com.", "date_published": "2024-09-05T13:48:00-04:00", "date_modified": "2024-09-05T13:48:00-04:00", "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/2024/09/Google-dresses-virtual-try.png", "tags": [ "AI", "apparel", "artificial intelligence", "digital transformation", "ecommerce", "generative AI", "Google", "News", "PYMNTS News", "Retail", "Technology", "virtual try-on", "VTO", "What's Hot", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2081221", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/75percent-of-automakers-plan-to-integrate-genai-into-vehicles-this-year/", "title": "75% of Automakers Plan to Integrate GenAI Into Vehicles This Year", "content_html": "Generative AI is revolutionizing the automotive industry, pushing the boundaries of vehicle design, manufacturing and customer experience. The technology, which harnesses advanced algorithms to create novel solutions and streamline processes, is reshaping how carmakers approach R&D and interact with consumers.
\nA \u00a0PYMNTS Intelligence report, \u201cHow Generative AI Is Boosting Innovation for Carmakers and Drivers,\u201d examines generative AI\u2019s advancements, along with substantial hurdles, ranging from technical skill shortages to ethical concerns.
\nGenerative artificial intelligence (AI) is emerging as a key driver of innovation in automotive design and development. The technology allows engineers to quickly explore numerous design variations, optimizing everything from vehicle aesthetics to performance attributes. This shift is supported by compelling industry data.
\n
Consider 93% of automotive stakeholders agree that generative AI will significantly impact the industry and 75% plan to integrate it into their operations within the year. The generative AI market in the automotive sector is projected to surge from $335 million in 2023 to $2.6 billion by 2033, reflecting a compound annual growth rate (CAGR) of 23%. This anticipated growth underscores a commitment to the technology among research and development departments, with nearly 70% of decision-makers prioritizing its adoption.
\nIn practical terms, generative AI enhances efficiency by automating design iterations and virtual testing. For instance, one German supplier reported a 70% increase in productivity for test vector generation due to AI integration. Additionally, generative AI has driven a 20% to 30% increase in efficiency for testing processes by automating reporting and scenario simulations. These improvements not only speed up product development but also help in meeting stringent regulatory requirements more effectively.
\nGenerative AI is transforming the in-car experience by personalizing interactions and anticipating driver needs. This technology is set to redefine how drivers engage with their vehicles, moving beyond traditional performance metrics to include highly tailored user experiences.
\nGeneral Motors (GM) has spearheaded efforts to integrate generative AI into in-vehicle systems, leveraging Microsoft Azure and OpenAI technologies to develop a chatbot designed to assist with real-time vehicle issues. This system will provide drivers with step-by-step instructions for common problems and potentially schedule maintenance, all through natural language interactions. Similarly, Cerence and Nvidia are collaborating on an automotive-specific large language model (LLM) to facilitate more intuitive human-vehicle communication.
\nAudi is also making strides by integrating Cerence\u2019s Chat Pro, powered by ChatGPT, across its product lineup to enhance conversational interfaces. Stellantis plans to extend its use of generative AI to voice assistance systems in 17 countries, with capabilities spanning 12 languages. These advancements promise to revolutionize driver-vehicle relationships by making interactions more responsive and contextually aware, potentially leading to vehicles that learn from individual driving behaviors to improve safety and efficiency.
\nDespite the promising prospects, the road to widespread generative AI adoption in the automotive industry is fraught with challenges. Key obstacles include a shortage of skilled professionals, complex regulatory environments, and significant ethical concerns.
\nAccording to the report, 63% of automotive industry stakeholders identify a lack of skilled staff as a major barrier to implementing generative AI. The need for expertise in both automotive engineering and advanced AI technologies is critical, yet finding and retaining such talent remains difficult. Integrating AI with existing legacy systems poses its own set of challenges, requiring both technical adjustments and cultural shifts within organizations.
\nEthical and data privacy issues are also paramount. Ensuring that generative AI systems are secure, protect user privacy and adhere to regulatory standards is crucial, given the sensitive nature of vehicle data and the safety-critical applications of the technology. Addressing these concerns is essential for the industry to fully realize the benefits of generative AI and avoid potential pitfalls.
\nAs the automotive industry accelerates toward a future driven by generative AI, it must navigate these technical and ethical challenges. The road ahead is set to transform vehicle design, manufacturing and user experience, creating new benchmarks for innovation and personalization in the automotive industry.
\nFor all PYMNTS AI coverage, subscribe to the daily\u00a0AI\u00a0Newsletter.
\nThe post 75% of Automakers Plan to Integrate GenAI Into Vehicles This Year appeared first on PYMNTS.com.
\n", "content_text": "Generative AI is revolutionizing the automotive industry, pushing the boundaries of vehicle design, manufacturing and customer experience. The technology, which harnesses advanced algorithms to create novel solutions and streamline processes, is reshaping how carmakers approach R&D and interact with consumers.\nA \u00a0PYMNTS Intelligence report, \u201cHow Generative AI Is Boosting Innovation for Carmakers and Drivers,\u201d examines generative AI\u2019s advancements, along with substantial hurdles, ranging from technical skill shortages to ethical concerns.\nAccelerating Innovation in Automotive Design\nGenerative artificial intelligence (AI) is emerging as a key driver of innovation in automotive design and development. The technology allows engineers to quickly explore numerous design variations, optimizing everything from vehicle aesthetics to performance attributes. This shift is supported by compelling industry data.\n\nConsider 93% of automotive stakeholders agree that generative AI will significantly impact the industry and 75% plan to integrate it into their operations within the year. The generative AI market in the automotive sector is projected to surge from $335 million in 2023 to $2.6 billion by 2033, reflecting a compound annual growth rate (CAGR) of 23%. This anticipated growth underscores a commitment to the technology among research and development departments, with nearly 70% of decision-makers prioritizing its adoption.\nIn practical terms, generative AI enhances efficiency by automating design iterations and virtual testing. For instance, one German supplier reported a 70% increase in productivity for test vector generation due to AI integration. Additionally, generative AI has driven a 20% to 30% increase in efficiency for testing processes by automating reporting and scenario simulations. These improvements not only speed up product development but also help in meeting stringent regulatory requirements more effectively.\nEnhancing the Driver Experience Through AI\nGenerative AI is transforming the in-car experience by personalizing interactions and anticipating driver needs. This technology is set to redefine how drivers engage with their vehicles, moving beyond traditional performance metrics to include highly tailored user experiences.\nGeneral Motors (GM) has spearheaded efforts to integrate generative AI into in-vehicle systems, leveraging Microsoft Azure and OpenAI technologies to develop a chatbot designed to assist with real-time vehicle issues. This system will provide drivers with step-by-step instructions for common problems and potentially schedule maintenance, all through natural language interactions. Similarly, Cerence and Nvidia are collaborating on an automotive-specific large language model (LLM) to facilitate more intuitive human-vehicle communication.\nAudi is also making strides by integrating Cerence\u2019s Chat Pro, powered by ChatGPT, across its product lineup to enhance conversational interfaces. Stellantis plans to extend its use of generative AI to voice assistance systems in 17 countries, with capabilities spanning 12 languages. These advancements promise to revolutionize driver-vehicle relationships by making interactions more responsive and contextually aware, potentially leading to vehicles that learn from individual driving behaviors to improve safety and efficiency.\nOvercoming Obstacles in AI Adoption\nDespite the promising prospects, the road to widespread generative AI adoption in the automotive industry is fraught with challenges. Key obstacles include a shortage of skilled professionals, complex regulatory environments, and significant ethical concerns.\nAccording to the report, 63% of automotive industry stakeholders identify a lack of skilled staff as a major barrier to implementing generative AI. The need for expertise in both automotive engineering and advanced AI technologies is critical, yet finding and retaining such talent remains difficult. Integrating AI with existing legacy systems poses its own set of challenges, requiring both technical adjustments and cultural shifts within organizations.\nEthical and data privacy issues are also paramount. Ensuring that generative AI systems are secure, protect user privacy and adhere to regulatory standards is crucial, given the sensitive nature of vehicle data and the safety-critical applications of the technology. Addressing these concerns is essential for the industry to fully realize the benefits of generative AI and avoid potential pitfalls.\nAs the automotive industry accelerates toward a future driven by generative AI, it must navigate these technical and ethical challenges. The road ahead is set to transform vehicle design, manufacturing and user experience, creating new benchmarks for innovation and personalization in the automotive industry.\n\nFor all PYMNTS AI coverage, subscribe to the daily\u00a0AI\u00a0Newsletter.\n\nThe post 75% of Automakers Plan to Integrate GenAI Into Vehicles This Year appeared first on PYMNTS.com.", "date_published": "2024-09-05T04:00:33-04:00", "date_modified": "2024-09-05T09:05:26-04:00", "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/2024/09/automakers-GenAI.png", "tags": [ "AI", "artificial intelligence", "Audi", "automotive", "Cerence", "connected cars", "general motors", "generative AI", "GM", "Microsoft", "News", "NVIDIA", "OpenAI", "PYMNTS News", "Stellantis", "Technology", "The Data Point", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2094191", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/c3-ai-sees-accelerating-growth-as-enterprise-ai-demand-surges/", "title": "C3.AI Sees Accelerating Growth as Enterprise AI Demand Surges", "content_html": "Artificial intelligence (AI) software company C3.AI reported better-than-expected quarterly results and highlighted surging demand for enterprise AI applications as businesses and government agencies rush to adopt the transformative technology.
\nThe Redwood City, California, company said revenue grew 21% year over year to $87.2 million in its fiscal first quarter ending July 31, beating analyst expectations. Subscription revenue, which is the bulk of C3.AI\u2019s business, increased 20% to $73.5 million.
\n\u201cWe\u2019re off to a solid start for fiscal year 25,\u201d said CEO Thomas Siebel on the company\u2019s earnings call. \u201cThis quarter marked our sixth consecutive quarter of accelerating revenue growth, reflecting our high levels of customer satisfaction and increasing demand for enterprise AI applications.\u201d
\nC3.AI, which provides AI software for large organizations across industries like energy, manufacturing and financial services, has positioned itself as a pioneer in the enterprise AI market. The company was founded in 2009, long before the current AI boom, with a vision of developing a software platform to help organizations leverage cloud computing, the Internet of Things, big data and predictive analytics.
\n\u201cC3.AI is the original enterprise AI, hard stop,\u201d Siebel declared. \u201cWe invested thousands of person-years over a decade building the C3 AI platform, the first reference architecture platform for enterprise AI.\u201d
\nThe company offers over 90 prebuilt enterprise AI applications addressing various industry-specific use cases. Siebel said C3.AI is seeing \u201cincredible results\u201d and high customer satisfaction scores as businesses derive tangible value from its AI solutions.
\nNotably, C3.AI reported strong traction in the public sector, signing 25 agreements with state and local government agencies in the quarter. \u201cWe just fell into a gold mine there,\u201d Siebel said, adding that the public sector opportunity was largely unanticipated.
\nThe company closed 71 agreements in Q1, including 52 new pilot projects \u2014 a 117% year-over-year increase in pilot count. C3.AI\u2019s model typically involves starting with a three- to six-month paid pilot before converting to a full production contract.
\nSiebel highlighted success stories with customers like Shell, which he said has over 100 C3.AI applications in development or deployment and estimates $2 billion in annual benefits from the partnership. Another client, Con Edison, is projecting over $3 billion in benefits over 20 years from its smart grid project with C3.AI.
\nThe company is also seeing strong demand for its new generative AI offerings, launched earlier this year. In the quarter, C3.AI signed 40 agreements related to generative AI with cloud partner Google.\u00a0
\n\u201cOur generative AI business is surprisingly diverse, with many candidly unanticipated use cases across the board in a wide range of industries,\u201d Siebel noted.
\nC3.AI maintained its full-year revenue guidance of $370-390 million, implying 19-27% growth. The company\u2019s stock has been volatile this year amid the broader AI frenzy as investors debate the long-term winners in enterprise AI.
\nC3.AI faces competition from major cloud providers and other enterprise software vendors rushing to embed AI capabilities. But Siebel argued that many legacy software companies are simply \u201crebranding their 20th-century software stacks with AI on the box\u201d without truly re-architecting for AI.
\nHe positioned C3.AI\u2019s prebuilt AI applications as a key differentiator, allowing customers to quickly configure and deploy proven solutions rather than undertaking long, complex development projects.
\n\u201cIn this current cacophony of AI market hype, C3.AI is achieving among the highest levels of customer satisfaction for value realized in the enterprise software world,\u201d Siebel claimed.
\nThe company still posted a non-GAAP operating loss of $16.6 million in Q1 as it invests heavily in growth. But Siebel said profitability is now \u201csimply a function of scale\u201d as revenue growth outpaces expense growth.
\nC3.AI projected it would be cash flow positive in Q4 and for the full fiscal year 2025. The company ended Q1 with $762.5 million in cash and investments.
\nLooking ahead, Siebel said C3.AI is focused on expanding sales capacity and growing in North America, Europe, and the public sector. However, he cautioned that modeling the business remains challenging given the rapidly evolving AI landscape.
\n\u201cIt\u2019s very difficult for people who are assessing these companies to really understand the complexity of what\u2019s going on in the AI market,\u201d Siebel said. \u201cThis is not a simple business, where in this new world of AI, it\u2019s really complex.\u201d
\nFor all PYMNTS AI coverage, subscribe to the daily AI\u00a0Newsletter.
\nThe post C3.AI Sees Accelerating Growth as Enterprise AI Demand Surges appeared first on PYMNTS.com.
\n", "content_text": "Artificial intelligence (AI) software company C3.AI reported better-than-expected quarterly results and highlighted surging demand for enterprise AI applications as businesses and government agencies rush to adopt the transformative technology.\nThe Redwood City, California, company said revenue grew 21% year over year to $87.2 million in its fiscal first quarter ending July 31, beating analyst expectations. Subscription revenue, which is the bulk of C3.AI\u2019s business, increased 20% to $73.5 million.\n\u201cWe\u2019re off to a solid start for fiscal year 25,\u201d said CEO Thomas Siebel on the company\u2019s earnings call. \u201cThis quarter marked our sixth consecutive quarter of accelerating revenue growth, reflecting our high levels of customer satisfaction and increasing demand for enterprise AI applications.\u201d\nC3.AI, which provides AI software for large organizations across industries like energy, manufacturing and financial services, has positioned itself as a pioneer in the enterprise AI market. The company was founded in 2009, long before the current AI boom, with a vision of developing a software platform to help organizations leverage cloud computing, the Internet of Things, big data and predictive analytics.\n\u201cC3.AI is the original enterprise AI, hard stop,\u201d Siebel declared. \u201cWe invested thousands of person-years over a decade building the C3 AI platform, the first reference architecture platform for enterprise AI.\u201d\nThe company offers over 90 prebuilt enterprise AI applications addressing various industry-specific use cases. Siebel said C3.AI is seeing \u201cincredible results\u201d and high customer satisfaction scores as businesses derive tangible value from its AI solutions.\nNotably, C3.AI reported strong traction in the public sector, signing 25 agreements with state and local government agencies in the quarter. \u201cWe just fell into a gold mine there,\u201d Siebel said, adding that the public sector opportunity was largely unanticipated.\nThe company closed 71 agreements in Q1, including 52 new pilot projects \u2014 a 117% year-over-year increase in pilot count. C3.AI\u2019s model typically involves starting with a three- to six-month paid pilot before converting to a full production contract.\nSiebel highlighted success stories with customers like Shell, which he said has over 100 C3.AI applications in development or deployment and estimates $2 billion in annual benefits from the partnership. Another client, Con Edison, is projecting over $3 billion in benefits over 20 years from its smart grid project with C3.AI.\nThe company is also seeing strong demand for its new generative AI offerings, launched earlier this year. In the quarter, C3.AI signed 40 agreements related to generative AI with cloud partner Google.\u00a0\n\u201cOur generative AI business is surprisingly diverse, with many candidly unanticipated use cases across the board in a wide range of industries,\u201d Siebel noted.\nC3.AI maintained its full-year revenue guidance of $370-390 million, implying 19-27% growth. The company\u2019s stock has been volatile this year amid the broader AI frenzy as investors debate the long-term winners in enterprise AI.\nC3.AI faces competition from major cloud providers and other enterprise software vendors rushing to embed AI capabilities. But Siebel argued that many legacy software companies are simply \u201crebranding their 20th-century software stacks with AI on the box\u201d without truly re-architecting for AI.\nHe positioned C3.AI\u2019s prebuilt AI applications as a key differentiator, allowing customers to quickly configure and deploy proven solutions rather than undertaking long, complex development projects.\n\u201cIn this current cacophony of AI market hype, C3.AI is achieving among the highest levels of customer satisfaction for value realized in the enterprise software world,\u201d Siebel claimed.\nThe company still posted a non-GAAP operating loss of $16.6 million in Q1 as it invests heavily in growth. But Siebel said profitability is now \u201csimply a function of scale\u201d as revenue growth outpaces expense growth.\nC3.AI projected it would be cash flow positive in Q4 and for the full fiscal year 2025. The company ended Q1 with $762.5 million in cash and investments.\nLooking ahead, Siebel said C3.AI is focused on expanding sales capacity and growing in North America, Europe, and the public sector. However, he cautioned that modeling the business remains challenging given the rapidly evolving AI landscape.\n\u201cIt\u2019s very difficult for people who are assessing these companies to really understand the complexity of what\u2019s going on in the AI market,\u201d Siebel said. \u201cThis is not a simple business, where in this new world of AI, it\u2019s really complex.\u201d\nFor all PYMNTS AI coverage, subscribe to the daily AI\u00a0Newsletter.\nThe post C3.AI Sees Accelerating Growth as Enterprise AI Demand Surges appeared first on PYMNTS.com.", "date_published": "2024-09-04T22:06:56-04:00", "date_modified": "2024-09-04T22:06:56-04:00", "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/2024/09/C3.ai-1.jpg", "tags": [ "AI", "artificial intelligence", "c3", "C3.ai", "Earnings", "enterprise AI", "GenAI", "generative AI", "News", "PYMNTS News", "Thomas Siebel", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2081370", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/intuit-debuts-major-updates-to-generative-ai-operating-system/", "title": "Intuit Debuts \u2018Major\u2019 Updates to Generative AI Operating System", "content_html": "TurboTax maker Intuit has released \u201cmajor\u201d updates to its generative artificial intelligence (AI) operating system, GenOS.
\nThe system now includes GenOS AI Workbench, a \u201cdedicated development environment for end-to-end application development,\u201d along with enhancements to GenStudio, GenRuntime, and GenUX components, the company said Wednesday (Sept. 4).
\n\u201cIntuit\u2019s proprietary GenOS is the key to unlocking new opportunities to fuel consumer and small and mid-market business success with GenAI,\u201d Alex Balazs, Intuit\u2019s chief technology officer, said in a news release.
\n\u201cOver the past year, we\u2019ve increased our pace of innovation by enabling product teams to turn new ideas into live customer experiments in just days, and built out our GenOS to speed time-to-market for ideas that rise to the top.\u201d
\nAccording to the release, Intuit introduced GenOS last year and has since continued to invest in the platform, with the company\u2019s software developers, product managers, data scientists, machine learning engineers, and data analysts experimenting with new uses.
\n\u201cFor example, Intuit\u2019s GenOS enabled new capabilities with easy-to-understand explanations of tax calculations, backed by real-time accuracy checks, with Intuit Assist for TurboTax, boosting confidence for millions of individual tax filers this tax season,\u201d the release said.
\nIntuit, whose other products include QuickBooks, CreditKarma and MailChimp, announced in July it was cutting 1,800 jobs \u2014 10% of its workforce. The company also said in a securities filing about the layoffs that it plans to \u201chire a nearly equivalent number of employees\u201d during the next year to support its growth areas.\u00a0
\nAnd in a message to employees included in the company\u2019s securities filing, CEO Sasan Goodarzi said the cuts come as Intuit is increasing its investments in AI.
\n\u201cWe were early to bet on and invest in AI, building one of the largest AI-driven expert platforms to fuel the success of consumers, small and mid-market businesses, and important partners like accountants, financial institutions and marketing agencies who rely on us daily to prosper,\u201d Goodarzi wrote.\u00a0
\n\u201cWith the introduction of GenAI, we are now delivering even more compelling customer experiences, increasing monetization potential and driving efficiencies in how the work gets done within Intuit.\u201d
\nEarlier this year, the company unveiled its new AI-powered \u201crevenue intelligence\u201d technology, which employs what it called \u201calways-on\u201d predictive and generative AI models.
\n\u201cIntuit\u2019s move is the latest example of a technology company tapping AI to try to make its products more useful and attract customers,\u201d PYMNTS wrote at the time. \u201cAI has been one of the hottest areas of technology investment in recent years as startups and big companies alike race to capitalize on its potential to automate tasks and provide new insights from data.\u201d
\nFor all PYMNTS AI coverage, subscribe to the daily AI\u00a0Newsletter.
\nThe post Intuit Debuts ‘Major’ Updates to Generative AI Operating System appeared first on PYMNTS.com.
\n", "content_text": "TurboTax maker Intuit has released \u201cmajor\u201d updates to its generative artificial intelligence (AI) operating system, GenOS.\nThe system now includes GenOS AI Workbench, a \u201cdedicated development environment for end-to-end application development,\u201d along with enhancements to GenStudio, GenRuntime, and GenUX components, the company said Wednesday (Sept. 4).\n\u201cIntuit\u2019s proprietary GenOS is the key to unlocking new opportunities to fuel consumer and small and mid-market business success with GenAI,\u201d Alex Balazs, Intuit\u2019s chief technology officer, said in a news release.\n\u201cOver the past year, we\u2019ve increased our pace of innovation by enabling product teams to turn new ideas into live customer experiments in just days, and built out our GenOS to speed time-to-market for ideas that rise to the top.\u201d\nAccording to the release, Intuit introduced GenOS last year and has since continued to invest in the platform, with the company\u2019s software developers, product managers, data scientists, machine learning engineers, and data analysts experimenting with new uses.\n\u201cFor example, Intuit\u2019s GenOS enabled new capabilities with easy-to-understand explanations of tax calculations, backed by real-time accuracy checks, with Intuit Assist for TurboTax, boosting confidence for millions of individual tax filers this tax season,\u201d the release said.\nIntuit, whose other products include QuickBooks, CreditKarma and MailChimp, announced in July it was cutting 1,800 jobs \u2014 10% of its workforce. The company also said in a securities filing about the layoffs that it plans to \u201chire a nearly equivalent number of employees\u201d during the next year to support its growth areas.\u00a0\nAnd in a message to employees included in the company\u2019s securities filing, CEO Sasan Goodarzi said the cuts come as Intuit is increasing its investments in AI.\n\u201cWe were early to bet on and invest in AI, building one of the largest AI-driven expert platforms to fuel the success of consumers, small and mid-market businesses, and important partners like accountants, financial institutions and marketing agencies who rely on us daily to prosper,\u201d Goodarzi wrote.\u00a0\n\u201cWith the introduction of GenAI, we are now delivering even more compelling customer experiences, increasing monetization potential and driving efficiencies in how the work gets done within Intuit.\u201d\nEarlier this year, the company unveiled its new AI-powered \u201crevenue intelligence\u201d technology, which employs what it called \u201calways-on\u201d predictive and generative AI models.\n\u201cIntuit\u2019s move is the latest example of a technology company tapping AI to try to make its products more useful and attract customers,\u201d PYMNTS wrote at the time. \u201cAI has been one of the hottest areas of technology investment in recent years as startups and big companies alike race to capitalize on its potential to automate tasks and provide new insights from data.\u201d\nFor all PYMNTS AI coverage, subscribe to the daily AI\u00a0Newsletter.\nThe post Intuit Debuts ‘Major’ Updates to Generative AI Operating System appeared first on PYMNTS.com.", "date_published": "2024-09-04T19:52:13-04:00", "date_modified": "2024-09-04T19:52:13-04:00", "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/2024/09/Intuit-AI.jpg", "tags": [ "AI", "artificial intelligence", "CreditKarma", "GenAI", "generative AI", "GenOS", "GenOS AI Workbench", "GenRuntime", "GenStudio", "GenUX", "Intuit", "News", "QuickBooks", "Sasan Goodarzi", "TurboTax", "What's Hot", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2081300", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/report-openais-building-of-ai-infrastructure-to-begin-in-us/", "title": "Report: OpenAI\u2019s Building of AI Infrastructure to Begin in US", "content_html": "OpenAI reportedly plans to bring together global investors to spend tens of billions of dollars on artificial intelligence (AI) infrastructure in the United States.
\nThe planned projects include data centers, turbines and generators, and semiconductor manufacturing, Bloomberg\u00a0reported Wednesday (Sept. 4), citing unnamed sources.
\nThe scope of the planned investment was reported earlier, but details are coming to light, according to the report.
\nAsked by Bloomberg about the company\u2019s plans for infrastructure spending, an OpenAI spokesperson said that the company believes such facilities are critical for advanced AI and making it more widely available.
\n\u201cWe are exploring opportunities with this goal in mind and look forward to sharing more details at a later date,\u201d the spokesperson said, per the report.
\nOpenAI has been working to form a coalition of global investors, including other private companies, and to get the U.S. government\u2019s blessing for this effort, according to the report.
\nSam Altman, CEO of OpenAI, has said that other companies and other countries allied with the U.S. would benefit from the building of additional AI infrastructure, per the report.
\nAt the same time, the U.S. could have national security concerns regarding investors that have ties to China, the report said.
\nIt was reported in February that Altman was seeking approval from the U.S. government for an initiative aimed at enhancing the global manufacturing of\u00a0AI chips.
\nWhile Altman was already actively engaging with potential investors and partners in the U.S., Middle East\u00a0and Asia, he emphasized the importance of obtaining approval from Washington before proceeding.
\nAltman aims to collaborate with the U.S. government on matters of approvals, timing\u00a0and the structure of the venture.
\nIn April, it was reported that Altman was meeting with government and industry officials in several countries in an effort to support the building of\u00a0AI infrastructure that would meet the need for chips, energy and data centers.
\nOpenAI believe that one of the biggest challenges facing the tech industry is the amount of energy it takes to power AI systems.
\nAt that time, Altman had spoken with official in several Western countries and in the United Arab Emirates (UAE).
\nThe post Report: OpenAI\u2019s Building of AI Infrastructure to Begin in US appeared first on PYMNTS.com.
\n", "content_text": "OpenAI reportedly plans to bring together global investors to spend tens of billions of dollars on artificial intelligence (AI) infrastructure in the United States.\nThe planned projects include data centers, turbines and generators, and semiconductor manufacturing, Bloomberg\u00a0reported Wednesday (Sept. 4), citing unnamed sources.\nThe scope of the planned investment was reported earlier, but details are coming to light, according to the report.\nAsked by Bloomberg about the company\u2019s plans for infrastructure spending, an OpenAI spokesperson said that the company believes such facilities are critical for advanced AI and making it more widely available.\n\u201cWe are exploring opportunities with this goal in mind and look forward to sharing more details at a later date,\u201d the spokesperson said, per the report.\nOpenAI has been working to form a coalition of global investors, including other private companies, and to get the U.S. government\u2019s blessing for this effort, according to the report.\nSam Altman, CEO of OpenAI, has said that other companies and other countries allied with the U.S. would benefit from the building of additional AI infrastructure, per the report.\nAt the same time, the U.S. could have national security concerns regarding investors that have ties to China, the report said.\nIt was reported in February that Altman was seeking approval from the U.S. government for an initiative aimed at enhancing the global manufacturing of\u00a0AI chips.\nWhile Altman was already actively engaging with potential investors and partners in the U.S., Middle East\u00a0and Asia, he emphasized the importance of obtaining approval from Washington before proceeding.\nAltman aims to collaborate with the U.S. government on matters of approvals, timing\u00a0and the structure of the venture.\nIn April, it was reported that Altman was meeting with government and industry officials in several countries in an effort to support the building of\u00a0AI infrastructure that would meet the need for chips, energy and data centers.\nOpenAI believe that one of the biggest challenges facing the tech industry is the amount of energy it takes to power AI systems.\nAt that time, Altman had spoken with official in several Western countries and in the United Arab Emirates (UAE).\nThe post Report: OpenAI\u2019s Building of AI Infrastructure to Begin in US appeared first on PYMNTS.com.", "date_published": "2024-09-04T14:08:54-04:00", "date_modified": "2024-09-04T14:08:54-04:00", "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/2024/09/OpenAI-AI-infrastructure.png", "tags": [ "AI", "AI funding", "AI infrastructure", "AI investments", "artificial intelligence", "funding", "Investments", "News", "OpenAI", "PYMNTS News", "What's Hot", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=2080537", "url": "https://www.pymnts.com/artificial-intelligence-2/2024/tech-firms-pursue-ai-chatbots-to-bridge-global-ecommerce-divide/", "title": "Tech Firms Pursue AI Chatbots to Bridge Global eCommerce Divide", "content_html": "Technology giants are racing to develop sophisticated, multilingual artificial intelligence (AI) chatbots for cross-border eCommerce and could reshape how businesses engage with international customers.\u00a0
\nGoogle\u2019s recent expansion of its Gemini AI in India exemplifies the industry\u2019s focus on multilingual capabilities. It\u2019s one of many companies trying to allow chatbots to communicate in different languages.
\n\u201cMultilingual AI chatbots hold significant potential for SMBs looking to expand into international markets,\u201d Tim Peters, CMO of Enghouse Systems, told PYMNTS. \u201cBy providing real-time, accurate translations, these chatbots can help businesses overcome language barriers, making it easier to connect with customers globally.\u201d
\nGoogle\u2019s AI assistant, Gemini, has expanded its reach in India by launching a mobile app and multilingual support for nine Indian languages. The move, catering to the country\u2019s mobile-first culture, allows users to interact with Gemini through text, voice or images. The enhanced Gemini Advanced features capabilities like document uploads and data analysis, enabling users to summarize lengthy documents and analyze complex datasets.\u00a0
\nGemini is one of many multilingual chatbots that are under development. The OpenBuddy project has launched a multilingual chatbot aimed at global users. Built on established models like Falcon and LLaMA, OpenBuddy offers a range of AI assistants, from 3 billion to 70 billion parameters, capable of conversing in multiple languages, including English, Chinese and several European and Asian languages. The project emphasizes offline capability and device-level operation and is freely available on popular AI platforms such as HuggingFace and ModelScope.\u00a0
\nCohere recently introduced Aya 23, a new set of multilingual large language models (LLMs) available in 23 languages. Developed by its nonprofit division, Cohere for AI, Aya 23 comes in two versions \u2014 8 billion and 35 billion parameters \u2014 and is designed to democratize AI by supporting diverse languages and communities.
\nThese models outperform others in tasks like summarization and translation and are more accessible to developers thanks to their open weights. Aya 23 represents a shift toward inclusivity in multilingual AI, offering broader language support and better performance across various natural language tasks.
\nSuch multilingual chatbots could allow businesses to engage with customers in their native languages, breaking down communication barriers that have traditionally limited market expansion, Philip Alves, founder and CEO of DevSquad, a software development company, told PYMNTS.\u00a0
\n\u201cBy providing 24/7 multilingual support, SMBs can enhance their global presence without the need for large, multilingual teams,\u201d he said.
\nWhile the potential benefits are substantial, experts caution about AI\u2019s limitations in nuanced communication. Peters said, \u201cWhile AI-powered translation can be effective for general communication, there are inherent challenges in using these tools for sensitive business negotiations or complex customer service interactions.\u201d\u00a0To ensure accuracy and cultural sensitivity, he suggested businesses consider involving human translators or customer service representatives in critical conversations.
\nAlves elaborated on these concerns: \u201cFor me, the biggest concern is the nuance and cultural context that AI may not fully grasp. Misinterpretations in these contexts could lead to misunderstandings or even damage business relationships.\u201d\u00a0This highlights the need for businesses to develop strategies that combine AI efficiency with human expertise, especially in high-stakes scenarios.
\nAs multilingual AI chatbots continue to evolve, they promise to lower entry barriers for businesses venturing into international markets. However, as these industry experts suggest, success in global eCommerce will likely depend on a balanced approach that leverages AI\u2019s efficiency while preserving the irreplaceable elements of human communication and cultural understanding.
\nThe job market impact of this technology is also a subject of debate. Alves suggested a shift rather than a wholesale replacement: \u201cWhile chatbots may handle routine inquiries and transactions, there will still be a demand for human translators and customer service reps, particularly for more complex or sensitive interactions.\u201d\u00a0
\nPeters added that there may be \u201can increased demand for higher-skilled roles that involve training, managing and refining these AI systems,\u201d\u00a0pointing to potential new career opportunities in the AI-augmented workforce.
\nFor all PYMNTS AI coverage, subscribe to the daily AI\u00a0Newsletter.
\nThe post Tech Firms Pursue AI Chatbots to Bridge Global eCommerce Divide appeared first on PYMNTS.com.
\n", "content_text": "Technology giants are racing to develop sophisticated, multilingual artificial intelligence (AI) chatbots for cross-border eCommerce and could reshape how businesses engage with international customers.\u00a0\nGoogle\u2019s recent expansion of its Gemini AI in India exemplifies the industry\u2019s focus on multilingual capabilities. It\u2019s one of many companies trying to allow chatbots to communicate in different languages.\n\u201cMultilingual AI chatbots hold significant potential for SMBs looking to expand into international markets,\u201d Tim Peters, CMO of Enghouse Systems, told PYMNTS. \u201cBy providing real-time, accurate translations, these chatbots can help businesses overcome language barriers, making it easier to connect with customers globally.\u201d\nGoogle\u2019s AI assistant, Gemini, has expanded its reach in India by launching a mobile app and multilingual support for nine Indian languages. The move, catering to the country\u2019s mobile-first culture, allows users to interact with Gemini through text, voice or images. The enhanced Gemini Advanced features capabilities like document uploads and data analysis, enabling users to summarize lengthy documents and analyze complex datasets.\u00a0\nAI\u2019s Promise for Global Trade\nGemini is one of many multilingual chatbots that are under development. The OpenBuddy project has launched a multilingual chatbot aimed at global users. Built on established models like Falcon and LLaMA, OpenBuddy offers a range of AI assistants, from 3 billion to 70 billion parameters, capable of conversing in multiple languages, including English, Chinese and several European and Asian languages. The project emphasizes offline capability and device-level operation and is freely available on popular AI platforms such as HuggingFace and ModelScope.\u00a0\nCohere recently introduced Aya 23, a new set of multilingual large language models (LLMs) available in 23 languages. Developed by its nonprofit division, Cohere for AI, Aya 23 comes in two versions \u2014 8 billion and 35 billion parameters \u2014 and is designed to democratize AI by supporting diverse languages and communities. \nThese models outperform others in tasks like summarization and translation and are more accessible to developers thanks to their open weights. Aya 23 represents a shift toward inclusivity in multilingual AI, offering broader language support and better performance across various natural language tasks.\nSuch multilingual chatbots could allow businesses to engage with customers in their native languages, breaking down communication barriers that have traditionally limited market expansion, Philip Alves, founder and CEO of DevSquad, a software development company, told PYMNTS.\u00a0\n\u201cBy providing 24/7 multilingual support, SMBs can enhance their global presence without the need for large, multilingual teams,\u201d he said.\nWhile the potential benefits are substantial, experts caution about AI\u2019s limitations in nuanced communication. Peters said, \u201cWhile AI-powered translation can be effective for general communication, there are inherent challenges in using these tools for sensitive business negotiations or complex customer service interactions.\u201d\u00a0To ensure accuracy and cultural sensitivity, he suggested businesses consider involving human translators or customer service representatives in critical conversations.\nAlves elaborated on these concerns: \u201cFor me, the biggest concern is the nuance and cultural context that AI may not fully grasp. Misinterpretations in these contexts could lead to misunderstandings or even damage business relationships.\u201d\u00a0This highlights the need for businesses to develop strategies that combine AI efficiency with human expertise, especially in high-stakes scenarios.\nHuman Touch in AI Communication\nAs multilingual AI chatbots continue to evolve, they promise to lower entry barriers for businesses venturing into international markets. However, as these industry experts suggest, success in global eCommerce will likely depend on a balanced approach that leverages AI\u2019s efficiency while preserving the irreplaceable elements of human communication and cultural understanding.\nThe job market impact of this technology is also a subject of debate. Alves suggested a shift rather than a wholesale replacement: \u201cWhile chatbots may handle routine inquiries and transactions, there will still be a demand for human translators and customer service reps, particularly for more complex or sensitive interactions.\u201d\u00a0\nPeters added that there may be \u201can increased demand for higher-skilled roles that involve training, managing and refining these AI systems,\u201d\u00a0pointing to potential new career opportunities in the AI-augmented workforce.\nFor all PYMNTS AI coverage, subscribe to the daily AI\u00a0Newsletter.\nThe post Tech Firms Pursue AI Chatbots to Bridge Global eCommerce Divide appeared first on PYMNTS.com.", "date_published": "2024-09-03T19:33:23-04:00", "date_modified": "2024-09-03T19:33:23-04:00", "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/2024/09/Gemini-AI-chatbots.jpg", "tags": [ "AI", "artificial intelligence", "Aya 23", "chatbots", "Cohere", "cross-border commerce", "customer service", "DevSquad", "digital transformation", "ecommerce", "Enghouse Systems", "Gemini AI", "GenAI", "generative AI", "Google", "large language models", "LLMs", "multilingual chatbots", "News", "OpenBuddy", "Philip Alves", "PYMNTS News", "Tim Peters", "artificial intelligence" ] } ] }