It's so curious to me, doesn't look like Google is serious about AI. They've been investing in Anthropic for years, selling them TPUs, and basically diverting resources from Gemini while it is cracking under capacity constraints. Imagine OpenAI selling capacity to their core
GENERATIVE AI
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Gemma4 INT4 Models Now Available on Hugging Face
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🚩Gemma4 INT4 models are now available! @huggingface @GoogleAI @IntelAI huggingface.co/Intel/gemma-4… huggingface.co/Intel/gemma-4…
→ View original post on X — @clementdelangue, 2026-04-06 22:50 UTC
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Generative AI will enable sophisticated creative rewrites in six years
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Lisez bien. Dans moins de 6 ans, les IA génératives seront tellement puissantes que vous pourrez prompter 20 fois "procède à la réécriture du livre de Victor Hugo « Les Misérables » et fait en sorte que ça se finisse bien pour Fantine Gavroche Éponine, ajoute des détails
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Gary Marcus Challenges Claims of Near-Zero LLM Hallucination Rates
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This ML Prof told me that the hallucination rate for frontier reasoning LLMs is “next to nil” And then gave me data, only after I pushed him, showing a best-case rate of 4.6% (which of course is benchmark specific). 4.6% is not “next to nil”. Imagine if your accountant hallucinated 4.6% of the time. Or worse, your pilot. Aran Nayebi (@aran_nayebi) Have you had a chance to try the latest reasoning models? You'll see their hallucination rate is next to nil. In fact, there’s a big difference between frontier reasoning models & the base LLMs that're freely available to the public, see e.g. here: nitter.net/aran_nayebi/status/202… — https://nitter.net/aran_nayebi/status/2041249684698648922#m
→ View original post on X — @garymarcus, 2026-04-06 22:25 UTC
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AI Hallucinations Remain Unsolved According to Gary Marcus
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The plot gets wilder: the prof's evidence for hallucinations has been allegedly solved is a chart from OpenAI showing that all models test hallucinated at least 4.6% of the time on known (therefore somewhat gameable) benchmark. That certainly isn't "solved". Imagine if your accountant hallucinated 4.6% of the time. Or your pilot. [Translated from EN to English]
→ View original post on X — @garymarcus, 2026-04-06 22:21 UTC
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LLM Hallucination Rates Remain Critical Barrier for Production
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Your best data are still a 4.6% hallucination rate, and on a handpicked benchmark at that. Game over. 4.6% isn’t even close to zero. And for many applications that’s deadly. Thanks for playing, and goodbye.
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Anthropic Reaches $30B ARR in Explosive Monthly Growth
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Breaking: Anthropic is now at $30B ARR. Up from $19B in February. That's $11B ARR added in one month. WAT.
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Symbolic Learning vs Curve-Fitting: Reverse-Engineering Generative Programs
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With curve-fitting, you are recording a lossy approximation of the output of some generative program. With symbolic learning, you are losslessly reverse-engineering the source code of the generative program. Symbolic learning won't be the best fit for all problems, but for the ones where the latent program is reasonably simple, it will outperform by many orders of magnitude.
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Anthropic’s Run-Rate Revenue Surpasses $30 Billion with Google Partnership
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Our run-rate revenue has surpassed $30 billion, up from $9 billion at the end of 2025, as demand for Claude continues to accelerate. This partnership gives us the compute to keep pace. Read more: anthropic.com/news/google-br…
→ View original post on X — @ceobillionaire, 2026-04-06 22:03 UTC
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Anthropic Signs Agreement with Google and Broadcom for TPUs
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We've signed an agreement with Google and Broadcom for multiple gigawatts of next-generation TPU capacity, coming online starting in 2027, to train and serve frontier Claude models. [Translated from EN to English]
→ View original post on X — @anthropicai, 2026-04-06 22:03 UTC