Turing Post

Is Google over? Many people are asking, but that is the wrong lens.We look at what actually happened and why this leadership reset may be good for Google, and even better for Jeff Dean and Demis Hassabis.

Dean left Google after 27 years with Sanjay Ghemawat, Oriol Vinyals, and Quoc Le to launch Discovery Loop, which aims to automate scientific experimentation. The same day, Hassabis stepped back from running Google DeepMind, while Koray Kavukcuoglu took control of Gemini models, frontier research, the Gemini app, and developer teams under Sundar Pichai.

Taken together, these moves reveal what Google is becoming.

Read the FOD editorial that preceded this episode: https://www.turingpost.com/p/google-ai-race-hassabis-pichai

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Hashtags
#JeffDean #DiscoveryLoop #GoogleDeepMind #Gemini #ArtificialIntelligence

Links:
Google, "The next chapter of our AI momentum" (official leadership announcement): https://blog.google/company-news/inside-google/message-ceo/next-chapter-ai-momentum/
Jeff Dean, Discovery Loop launch announcement: https://x.com/JeffDean/status/2085034604172603724
Jeff Dean, redacted farewell note: https://x.com/JeffDean/status/2085083442669318443
Discovery Loop, mission and team: https://www.discoveryloop.com/
Wired, "Jeff Dean Leaves Google to Launch Discovery Loop": https://www.wired.com/story/jeff-dean-google-discovery-loop-startup/ 
Turing Post FOD editorial, "Why 'The Actual Reason Why Google Fell Out of the AI Race Changes Everything' Is Wrong": https://www.turingpost.com/p/google-ai-race-hassabis-pichai
Alphabet 2026 proxy statement, beneficial ownership and voting power: https://www.sec.gov/Archives/edgar/data/1652044/000130817926000342/goog-20260424.htm
Google I/O 2026 keynote remarks, internal coding and developer-agent figures: https://blog.google/intl/en-in/company-news/technology/sundar-pichai-io-2026/
Google Cloud Next 2026 remarks, AI-generated code figure: https://blog.google/innovation-and-ai/infrastructure-and-cloud/google-cloud/cloud-next-2026-sundar-pichai/
Reuters, Google AI leadership changes and delayed flagship release: https://www.reuters.com/business/google-shakes-up-ai-leadership-deepmind-chief-shifts-role-2026-08-05/
The Information, Google's coding-model strike team: https://www.theinformation.com/articles/google-creates-strike-team-improve-coding-models
The Information, Koray's Gemini consolidation: https://www.theinformation.com/articles/googles-new-ai-architect-plans-spread-gemini-everywhere
Google, combining Brain and DeepMind in 2023: https://blog.google/innovation-and-ai/technology/ai/april-ai-update/
Jeff Dean, official Google Research profile: https://research.google/people/jeff/
University of Washington, "Whole-Program Optimization of Object-Oriented Languages": https://projectsweb.cs.washington.edu/research/projects/cecil/pubs/jdean-thesis.html
University of Washington, whole-program optimization paper and Vortex results: https://projectsweb.cs.washington.edu/research/projects/cecil/www/Papers/whole-program.html
University of Minnesota, Dean on his parallel neural-network thesis: https://cse.umn.edu/cs/news/cse-alumnus-jeff-dean-returns-campus-commencement

OpenAI says its next model, Astra, produced ten mathematical advances, each backed by a machine-checked Lean proof. The successful searches would cost roughly $2,000 at API prices. Are mathematicians done?!

Twenty-four hours later, Anthropic mathematician Levent Alpöge claimed Claude Fable had matched five of them. Meanwhile, startups are raising hundreds of millions to turn proof generation and verification into a business.

In this episode, we explain what Astra actually achieved, what the $2,000 figure excludes, how Lean changes mathematical verification, and why the next scarce resource in mathematics may be human judgment rather than proofs.

Attention Span explains how AI is changing who produces, verifies, and ultimately controls mathematical discovery.

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#AI #OpenAI #Anthropic #Mathematics #AIResearch #MachineLearning #Lean #Astra #claude 

*Sources used to produce this video:*
- Sébastien Bubeck's Astra announcement: https://x.com/SebastienBubeck/status/2083456300692979886
- OpenAI, Ten advances in mathematics and theoretical computer science: https://openai.com/index/ten-advances-in-mathematics/
- OpenAI, Ten Proofs manuscript: https://cdn.openai.com/pdf/ten-proofs-oai.pdf
- OpenAI, Lean repository: https://github.com/openai/ten-proofs
- OpenAI, reasoning walkthroughs: https://cdn.openai.com/pdf/reasoning-walkthroughs.pdf
- Terence Tao, Mathematics in the Age of AI, ICM 2026: https://teorth.github.io/tao-web/slides/age-of-ai-icm-2026.pdf
- Tao's explanation of the Jacobian counterexample: https://terrytao.wordpress.com/2026/07/21/a-digestion-of-the-jacobian-conjecture-counterexample/
- Leiden Declaration on Artificial Intelligence and Mathematics: https://leidendeclaration.ai/
- Leonardo de Moura, Proof Assistants in the Age of AI: https://leodemoura.github.io/blog/2026-2-18-proof-assistants-in-the-age-of-ai/
- Georges Gonthier, formal proof of the Four Color Theorem: https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/gonthier-4colproof.pdf
- Levent Alpöge's Astra counterclaim: https://x.com/__alpoge__/status/2083855298239078748
- Axiom Math funding and product thesis: https://menlovc.com/perspective/ai-will-write-all-the-code-mathematics-will-prove-it-works/
- Axiom proofs accepted by journals: https://www.axios.com/2026/05/26/axiom-ai-math-journal
- AxiomProver Putnam 2025 and early-2026 results overview: https://wal.sh/research/axiomprover-2026/
- Math Inc., Gauss: https://www.math.inc/gauss
- Math Inc., FormalQualBench: https://www.math.inc/formalqualbench
Reuters, Harmonic funding: https://www.reuters.com/business/robinhood-ceos-math-focused-ai-startup-harmonic-valued-145-billion-latest-2025-11-25/

One AI request may soon begin on one computer and finish on another. WHAT?!

AMD and Cerebras are separating the two phases of LLM inference: Helios processes prompts and long context, while Cerebras generates tokens. They claim up to 5x more tokens per second per watt, although the figure is based on internal modeling.

Meanwhile, OpenAI reportedly cut inference costs for one segment of ChatGPT by more than half through an undisclosed optimization. The inference race is shifting from installing more chips to extracting more useful work from them.

Attention Span explains how the race to make AI inference faster and cheaper is reshaping hardware and the software that orchestrates it.

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Sources and further reading
The Information on OpenAI's reported inference optimization: https://www.theinformation.com/newsletters/ai-agenda/openai-discovers-new-way-cut-inference-costs-half
OpenAI on GPT-5.6 inference and agent-harness efficiency: https://openai.com/index/gpt-5-6-frontier-intelligence-efficiency/
AMD and Cerebras announcement: https://ir.amd.com/news-events/press-releases/detail/1293/amd-and-cerebras-announce-industry-leading-ultra-low-latency-and-high-throughput-ai-inference-solution
AMD Helios architecture: https://www.amd.com/en/blogs/2026/amd-launches-helios-the-highest-performing-rackscale-ai-infrastructure-solution.html
AMD Helios networking: https://www.amd.com/en/blogs/2026/amd-helios-resilient-scale-up-networking-for-ai.html
Cerebras WSE-3: https://www.cerebras.ai/chip
Cerebras CS-3 datasheet: https://cdn.sanity.io/files/e4qjo92p/production/0d73d528371618c0372fcb9de9b3c0da703adf9e.pdf
Cerebras inference architecture: https://www.cerebras.ai/blog/introducing-cerebras-inference-ai-at-instant-speed
Kimi K2.6 model card: https://huggingface.co/moonshotai/Kimi-K2.6
AWS and Cerebras disaggregated inference: https://www.aboutamazon.com/news/aws/aws-cerebras-ai-inference
AMD and vLLM MORI-IO disaggregation test: https://vllm.ai/blog/2026-04-07-moriio-kv-connector
PagedAttention: https://doi.org/10.1145/3600006.3613165
Splitwise: https://arxiv.org/abs/2311.18677
DistServe: https://arxiv.org/abs/2401.09670
TetriInfer: https://arxiv.org/abs/2401.11181
Mooncake: https://www.usenix.org/conference/fast25/presentation/qin 
NVIDIA Dynamo: https://www.nvidia.com/dynamo/
NVIDIA Groq 3 LPX: https://developer.nvidia.com/blog/inside-nvidia-groq-3-lpx-the-low-latency-inference-accelerator-for-the-nvidia-vera-rubin-platform/
CDC 6600: https://www.cisl.ucar.edu/ncar-supercomputing-history/cdc6600

#ArtificialIntelligence #AI #MachineLearning #LLM #Inference #OpenAI #AMD #Cerebras #AIInfrastructure #FutureOfAI

Jensen Huang joined X and immediately rallied Silicon Valley around open-weight AI. First came a letter signed by 77 companies and industry leaders. Then came a security alliance with 37 members. Anthropic was absent from both.

This was not a random disagreement. Kimi K3 had narrowed the gap with American frontier models, Anthropic had accused Moonshot AI of extracting 3.4 million Claude exchanges, Hugging Face had turned to an open-weight Chinese model during a security investigation, and Congress had proposed an AI kill switch.

In this episode, we examine why Jensen and Anthropic represent two competing approaches to AI safety, what their companies gain from those positions, and who ultimately gets to control the model layer.
Attention Span explains the technical and business decisions shaping AI.

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*Links:*
Jensen Huang on X https://x.com/JensenHuang
NVIDIA: Open Secure AI Alliance https://blogs.nvidia.com/blog/open-secure-ai-alliance/?ncid=so-twit-957725
Moonshot AI: Kimi K3 announcement https://x.com/Kimi_Moonshot/status/2081760186235289764
Kimi K3 model page https://huggingface.co/moonshotai/Kimi-K3
Anthropic: Detecting and preventing distillation attacks https://www.anthropic.com/news/detecting-and-preventing-distillation-attacks
Turing Post: What Is Knowledge Distillation? https://www.turingpost.com/p/kd
Nathan Lambert on distillation https://x.com/natolambert/status/2079616308203942332
Little Tech Association https://littletech.org/
Jensen Huang’s open-weights letter https://x.com/JensenHuang/status/2080643682408321103
Jensen Huang on the Open Secure AI Alliance https://x.com/JensenHuang/status/2081698060330250294
AI Kill Switch Act press release https://lieu.house.gov/media-center/press-releases/reps-lieu-and-moran-introduce-bill-require-kill-switch-ai-systems-can
Jeremy Howard on NVIDIA, Anthropic, and open weights https://x.com/jeremyphoward/status/2081280852454166680
Turing Post: Anthropic Fable 5 and Mythos 5 episode https://www.youtube.com/watch?v=o9d12zG6kNM&t=1s
Axios: Jensen Huang on China and open-source AI https://www.axios.com/2026/07/22/nvidia-jensen-huang-china-open-source-ai
The Information: Silicon Valley Unites Against Anthropic Over Chinese AI Restrictions https://www.theinformation.com/articles/silicon-valley-unites-anthropic-chinese-ai-restrictions

#AI #OpenWeights #Anthropic #NVIDIA #KimiK3 #JensenHuang

OpenAI’s models were supposed to solve a cybersecurity benchmark. Instead, they found a zero-day, reached the internet and broke into Hugging Face to obtain the answers.

Then came the contradiction: closed models blocked Hugging Face from analyzing the attack evidence, so its security team turned to the open-weight GLM-5.2!

We explain what happened, who was in control and why this incident may push OpenAI with help from Hugging Face toward AI that is both more open and safer

Attention Span explains the technical and business choices shaping AI.

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*Links:*
Hugging Face: https://huggingface.co/blog/security-incident-july-2026
OpenAI: https://openai.com/index/hugging-face-model-evaluation-security-incident/
ExploitGym: https://arxiv.org/abs/2605.11086
Adrien Carreira: https://x.com/XciD_/status/2079191130248212591
Simon Willison: https://simonwillison.net/2026/Jul/22/openai-cyberattack/
Thomas Ptacek: https://x.com/tqbf/status/2080290141063569791
LeRobot: https://x.com/LeRobotHF/status/2080296144832274881 

#AI #OpenAI #HuggingFace #OpenSourceAI #Cybersecurity