Google is aggressively pushing the boundaries of what its AI models can do and how easy it is to use them.
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Like a heavyweight fight, the large AI research labs continue to duke it out over improvements to their models.
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For a brief moment last week, the AI video community was buzzing about a mysterious model, codenamed “David,” rising to the top of the leaderboards.
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Ilya Sutskever, the former Chief Scientist of OpenAI and a central figure in the modern AI revolution, recently opened up about his new venture, Safe Superintelligence (SSI).
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AI Music Startup Suno has announced a strategic partnership with major label Warner Music Group (WMG) that will require Suno to use licensed songs to train its models.
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As companies race to integrate artificial intelligence into their operations, a critical safety net might be quietly disappearing in the process.
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The “AI 2027” report, a project that originally predicted Artificial General Intelligence (AGI) could arrive in two years, has been updated by its authors. The new consensus? It will arrive around 2030.
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For years, the conventional wisdom has been this: The best performing chips for training and running AI models come from Nvidia (GPUs). An alternative is Google’s custom chips, Tensor Processing Units (TPUs), available through Google Cloud.
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OpenAI just rolled out “shopping research,” a new ChatGPT experience designed to automate the creation of personalized buyer guides.
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