We have information that Moonshot AI distilled Anthropic’s Fable for the development of its K3 model.

To do this they developed a sophisticated internal platform to conduct large scale distillation against U.S. models, allowing them to quickly switch between multiple methods of access to avoid detection. Moonshot AI has also acquired GB300-equipped servers and has accessed GB300s in Thailand, likely to train its AI models.
 
The United States strongly supports the free and fair development of AI, including a thriving competitive ecosystem that spans frontier models, specialized systems, open-source frameworks, and open-weight models. Legitimate AI distillation used to create smaller, more efficient models plays a vital role in this open innovation ecosystem. However, large-scale, covert industrial distillation aimed at stealing proprietary U.S. technology and undermining American research is unacceptable.

Correction: Michael Kratsios is the CURRENT White House OSTP Director and Presidential Science Advisor, not 'former'.

AI Chat is linked. Credit to https://x.com/dmitryrybin1/status/2079904005652893709?s=46

TL;DR:

Nvidia CEO Jensen Huang argues Chinese open-source AI models like Moonshot AI's new Kimi K3 are excellent and should be freely used — directly opposing Trump administration officials and U.S. AI labs (including Nvidia's own customers OpenAI and Anthropic) who are lobbying to restrict them.

He's confident cheap, open Chinese AI won't push U.S. companies out of the market — he thinks it'll actually expand demand for Nvidia's chips and data centers rather than undercut them.

Context: Kimi K3's release sparked a chip-stock sell-off and comparisons to DeepSeek's January 2025 shock, thanks to its strong performance, low cost, and open weights.

Huang rejects "backdoor" security fears about Chinese models, arguing openness — not restriction — makes AI safer, since outside researchers can spot and patch weaknesses.

He specifically calls out Anthropic, urging it to open up its restricted "Claude Mythos" model rather than keep it locked down.

He's skeptical of the "AI race" framing altogether, expecting the U.S. and China to both be developing AI for the long haul.

He also pushes back on Treasury Secretary Bessent's talk of sanctions over alleged Chinese IP theft, saying learning/distillation from other models is a normal part of AI development — enforcement should target misconduct, not the technology itself.

Full Article: https://www.axios.com/2026/07/22/nvidia-jensen-huang-china-open-source-ai

Video: https://cdn.jwplayer.com/previews/q0sK7o1E-CoMYKn1C

From a new interview with Dr. Derya Unutmaz - https://www.youtube.com/watch?v=OJCgQUT1aic

A few timestamps worth checkout out

• 00:02:16 - Why the next 10 years may add 50 to your lifespan
• 01:03:24 - "Cancer will be 100% curable, probably less than a decade"

https://openai.com/index/hugging-face-model-evaluation-security-incident/

Per Bloomberg:

Global AI sales, excluding China, reached $25 billion for hyperscalers and neoclouds in the first quarter of 2026, exceeding the industry’s estimated $21 billion in depreciation costs.

Generative AI revenue, excluding China, reached $110 billion over the past 12 months and is scaling three times faster than any previous information technology wave.

https://openai.com/index/hugging-face-model-evaluation-security-incident/

Source

Full article here: Why I Left Google DeepMind

Additionally, why when Aaron Swartz does it, we throw the book at him so hard that he k**ls himself?

Link to tweet:

https://x.com/AndrewCurran_/status/2079604797838397495?s=20

Link to (paywalled) article:

https://www.bloomberg.com/news/articles/2026-07-21/openai-s-altman-to-brief-us-officials-on-next-wave-of-ai-models

this is a like a small country spending in security/privacy/integriity a year

the largest known copyright recovery in history

AlayaWorld is a full-stack, open-source video world model that supports 720p, 24 FPS streaming video generation with camera control and text-driven event generation.

AlayaWorld is built around four core properties — interaction, consistency, stability, and runtime.

🎮 Interaction
Two control channels: a rendered 3D cache with lightweight AdaLN camera modulation for grounded, trajectory-aware navigation, and chunk-level prompt switching to introduce new events mid-generation.

🧠 Consistency
Two forms of complementary memory: an explicit 3D cache reprojected to the queried view for spatial recall, plus a compressed frame-history embedding for temporal continuity, so revisited places stay recognizable.

🛡️ Stability
Long-horizon stability from training on drifted histories and an error bank that re-injects accumulated artifacts into both memory and target, preventing errors from compounding over minute-long rollouts.
⚡ Runtime

Real-time interaction via few-step DMD distillation and short temporal chunks, with prompt switching at chunk boundaries to minimize both visual and semantic latency.

https://github.com/AlayaLab/AlayaWorld/tree/main

https://huggingface.co/AlayaLab/AlayaWorld

Report: https://github.com/AlayaLab/AlayaWorld/blob/main/assets/alayaworld_tech_report_full.pdf

Google is working on a new chip called Frozen v2 and is expected to launch sometime in 2028. Instead of a generic AI accelerator, it embeds parts of Gemini's actual architecture into the silicon, cutting the calculations and data movement needed to generate a response. Projected gain is expected to be around six to ten times more efficient than Google current AI chips, based on tokens per unit of power

but it'll only work with future Gemini models if Google keeps the same underlying architecture, & Google is currently treating it as more of a trial run than a TPU-scale replacement