@PalantirTech 's Alex Karp @CNBC rant is exactly what I’ve been yelling for months. Privately now publicly.
@chamathhas also been bagging the drums.
Frontier Labs tokenizing while you offered your IP, Data, and in exchange, you get filtered, gated super intelligence?
Don’t complain, we all volunteered, nobody forced us. Now we are here. Done.
Now do something about it. Learn, adopt, evolve. Private and local AI is the move.
Control your models, your IP, your data, your weights. Don’t outsource your brain to the cloud. Lots of folks have been saying it. The rest are just catching up.
Palantir CEO Alex Karp on what customers actually want, the real business of frontier labs, and the importance of open source models:
“What the technical customers want is control over their compute, their models, their data stack, and their alpha. They want to know they own the means of production, and it's not being transferred to someone else.”
"Who owns the data? Are the prompts secure? Is this being transferred to you?"
"If it was so valuable, and I can make you a billion dollars, wouldn't I say I'll make you a billion dollars and I want 30%? Why are they charging for tokens if it's so valuable?"
Qwen3.8 is launching and going open-weight soon!🌐
With a massive 2.4T parameters, this model is continuously evolving. We believe it’s one of the most powerful model available today, compatible to leading frontier AI models , second only to Fable 5.
You don't have to wait to test it. Just now, the Qwen3.8-Max-Preview made its debut on Alibaba’s Token Plan, Qoder, and QoderWork. Be among the very first to try it out.
Can't wait to hear what you build. Stay tuned! 🚀
Token Plan
international:https://t.co/YRvcGdB9Bv
China:https://t.co/PKMUNwUuRp
With about 4 to 5 different frontier LLMs coming out in the span of just 10 days, it makes business sense that they’re doing this.
In fact, to retain their customers, they were forced to do this @AnthropicAI
Competition is good as it forces change. Don’t get distracted by claims that the Chinese are beating us or stealing from us. Focus on building.
You got this.
Big news: Kimi-K3 by @Kimi_Moonshot is now #1 in the Frontend Code Arena with 1679 pts, surpassing Claude Fable 5.
This is a 17-place jump from Kimi-k2.6 (#18 -> #1).
In Frontend, Kimi-K3 ranked #1 in 6 of 7 domains: Brand & Marketing, Reference-Based Design, Data & Analytics, Consumer Product, Simulations, and Content Creation Tools, landing #2 only in Gaming behind Fable 5.
The full model weights will be released by July 27.
Congrats to the @Kimi_Moonshot team on this major milestone!
Today, we’re announcing Bonsai 27B: the first 27B-class model to run on a phone.
Bonsai 27B is the new multimodal flagship of the Bonsai family. Based on Qwen3.6 27B, it brings a new capability tier to local AI: multi-step reasoning, structured tool use, long-context workflows, and coherent agentic loops.
Until now, models in this class have been impractical to deploy locally. A 27B model occupies roughly 54 GB in 16-bit precision, and even a strong 4-bit build is around 18GB - too large for a phone and for most laptops.
Bonsai 27B changes that.
It comes in two variants:
• Ternary Bonsai 27B: 5.9 GB, 1.71 effective bits per weight, optimized for laptop-class quality.
• 1-bit Bonsai 27B: 3.9 GB, 1.125 effective bits per weight, optimized for phone-class footprint.
Everything is open-sourced today under the Apache 2.0 license.
We gave a coding agent a goal and a time budget: build a training environment and teach a vision model to count colored stars.
Using autoresearch with NeMo RL, NeMo Gym, and reusable skills, the agent set up, trained and evaluated the model while the researcher steered the work.
Qwen3-VL-2B went from 25% to 96.9% accuracy, and the agent even proposed the next experiment on its own.
True.
As a precautionary measure, all user data that was uploaded to SpaceXAI before now will be completely and utterly deleted. Zero anything whatsoever will remain.