Generative AI Digest 14: A roundup of latest breakthroughs and developments
Nick is a Managing Analyst with S&P Global Market Intelligence 451 Research, with responsibility for 451 Research’s coverage of Data, AI, Analytics, Information Security and Risk. As a co-founder of 451 Research and its lead analyst for AI and machine learning, Nick has been researching and exploring the use cases for machine learning since the company's inception in 2000. He is a sought-after speaker and advisor, known for his expertise in the drivers of AI adoption, industry use cases, and the infrastructure behind its development and deployment. Nick rejoined the team in 2015 after a successful three-year stint as a product marketing lead at Recommind (now part of OpenText), a machine learning-driven eDiscovery software company. Since 2000 he has held multiple senior management positions at 451 Research, with experience in both New York and London. Prior to starting 451 Research, Nick was a financial and technology journalist with ComputerWire (now part of Informa) in London and New York. Nick has an MSc in Computing Science from the University of London, and a BA in Philosophy and Music from Middlesex University.
The startup continues to cultivate its image as an independent European "underdog," taking on Silicon Valley giants by building efficient open-source AI systems. Recent product announcements showcase the tension between Mistral AI's commercial viability and its commitment to open-source, especially as the world awaits the economic stability of generative AI.
The hyperscaler brings a wealth of assets to the challenge of getting AI ideas to fruition. Google is infusing the capabilities of its multimodal Gemini LLM into its developer, productivity, database and security suites to attract net-new customers and partners to its ecosystem, and improve its traction in the enterprise.
While generative AI models have been in development for years, the wide-scale productization of these models is a recent phenomenon, with many vendors included in our analysis currently in the beta or initial launch stage with their commercial products.
While generative AI models have been in development for years, the wide-scale productization of these models is a recent phenomenon, with many vendors included in our analysis currently in the beta or initial launch stage with their commercial products.
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