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

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

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"

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'.

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/

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

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

given recent news, I am convinced that AI more intelligent than any human is coming in the next few years, and given that most people are not aware of this, that would put us ahead of the curve. But how can we profit from this?

Hello everyone,

I've been thinking about this for a while now and I'm curious what everyone else thinks.

Am I the only one who feels like gaming has kind of stopped evolving? Don't get me wrong, games look incredible now. Graphics, ray tracing, bigger worlds, all that stuff is amazing. But when I actually sit down and play them, it still feels like I'm playing the same games I was 10 years ago, just with prettier visuals.

The NPCs still stand in the same place waiting for you. Dialogue is still scripted. Quests are still basically go here, kill this, come back. Open worlds are huge, but after a while you realize they're just filled with the same repetitive activities.

Meanwhile, AI has been improving at an insane pace over the last few years.

So it got me wondering when do you guys think AI will actually become part of games, not just a tool developers use behind the scenes?

Imagine NPCs that actually remember you. You insult someone early in the game, and 30 hours later they still hold a grudge. Or you help a random character, and months later they show up to help you without the game having a scripted event for it.

Imagine walking into a city where every NPC has their own goals, routines, opinions, and memories. You could have an actual conversation instead of choosing between three dialogue options. No two playthroughs would ever be the same because the world would constantly react to what you do.

I don't even care if the graphics stay where they are today. I'd rather have a world that actually feels alive than another game with "the most realistic water physics ever."

Honestly, this is the first time in years I've felt genuinely excited about the future of gaming. It feels like we're finally getting close to the next real leap instead of just another graphics upgrade. If AI keeps improving at this pace and if we eventually get something close to AGI I think video games could change more in the next 10 years than they have in the last 30.

Imagine games where you aren't following a script anymore. You're actually living in a world that evolves with you.

Maybe I'm being too optimistic, but I honestly think that's the future, and I can't wait to see it.

What do you guys think? Are we closer than I think, or is this still decades away?

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

With how rapidly things are progressing, I am curious where the average person thinks we currently stand.

Source

At the risk of coming across as a Google shill, this is my hot take.

When it comes to smaller coding tasks like iterating on front end design or fixing smaller bugs, the experience of using Gemini flash in Antigravity is WAY better than GPT 5.6 in codex.

I'm mostly comparing Flash 3.5 High to 5.6 Luna (across the effort spectrum), though I'd say flash is better for this work than terra or sol as well.

The sheer speed and tasteful constraint of flash makes it excellent to go back and forth with when building. It might take more steering to finish a problem, but you'll end up with a product much closer to your initial vision in less time if you get good with this workflow.

The main problem with GPT 5.6 is the slow speed and ridiculous tendency to over-engineer every single feature you ask for. It has a higher ceiling of intelligence, but even Luna at lower effort levels can't help itself from overthinking all the time.

Sol is great to throw at a problem too big foot gemini flash to handle, but for everything else, i find myself going to antigravity. If I send 5.6 on smaller tasks, the output is slower, and I end up having to do several iterations removing all the unnecessary complexity it shoved in without me asking for it.

Now with the launch of Flash 3.6, I'm actually feeling quite optimistic for Google. I know it looks unimpressive on benchmarks, but seriously give it a try yourself on some of your more simple day to day tasks. The speed and simplicity is so underrated. Also I think Antigravity's usage limits are more generous if you don't count the free codex resets.

I'm mostly working on fairly simple game dev and web development, so maybe my perspective is skewed because most people's tasks are beyond this. But if you haven't given flash a fair shot, take this as your sign to try and let me know.