Vanguard增持TSLA翻倍 技术支撑位受关注

The practical solution here would be closing the feedback loop with customers. The business does want happy customers, it's important they return to purchase in 5 years. The problem with car companies is that they don't get immediate feedback (telemetry, tickets, etc) when they do push an issue. And they obviously don't have gradual roll outs the way tesla does. Rather than ham…

> there are companies with amazing software experience, Rivian, Tesla, Nio, Lucid I own a Tesla, and a Ford. Amazing is not how I would describe the Tesla software experience. It lacks features like iMessage for group and for non-phone recipients that I am able to use in my Ford. Even though many people would say the Ford software is otherwise inferior. And if history is anythi…

Why wait? People are already doing their work on OpenAI and Anthropic's servers, Apple Intelligence servers could quickly subsume any "local" model work that you want to do. That way everyone has access, even with older devices, and it's a subscription! Then Apple can tie their APIs into the ecosystem you love at a flat cost you can afford. No need to support local model integr…

I am aware of it, and I dabble with Unsloth Studio and use the llama-server approach. I would obviously prefer an open source, open weights stack. But I guess a paradox is that as long as there are open source options I could use, a solid agentic environment that I can use with my own open weights is something I might pay for, in a similar sort of way to paying for a Mac when I…

groq did an ASIC for llama and now for nvidia. Their cloud service is fast. > NVIDIA Groq 3 LPU Inference Accelerator > The NVIDIA Groq 3 LPU is the next generation of Groq’s innovative language processing unit. Each LPX rack features 256 interconnected LPU accelerators that, together with the NVIDIA Vera Rubin platform, supercharge inference. Each LPU accelerator delivers 500 …

I'm not sure where "so much less resources" comes from. Training the best model has nothing to do with having the most NVIDIA GPUs around. If that were true then xAI would have the best model. It comes down to the quality of data, research, and financial backing.

It's the same reason Meta open sourced Llama and AMD open sourced FSR. When you're behind it is a prudent strategy because it undermines investment in the private frontier. Once you're on top you pull the rug and go closed source. There are no morals in this anywhere to be found. > 100s of Millions That is utter peanuts given the stakes. This is competition between two super po…

AMD had an interesting take on this around a decade ago. Never went anywhere but very cool tech.

For fun, I took that image and put it into a few models and asked it "what is wrong with this genAI image?" Grok fast came up with a lot of minor quibbles and missed the issue. Grok expert touched on it with a "Limbs/anatomy ambiguity / This creates a slight "how many legs does this cat actually have?" moment." but then moved on to complain about texturing . Later it summarized…

There is actually an interrupt mode in NotebookLM now. Overall I've found it the best AI product Google have. Only complaint I have about it is the hyper positive US corporate accents get pretty annoying pretty quickly. The realtime voice in ChatGPT is excellent, the newer model is a big step up too.

But some (Meta, Anthropic) suggested that optimizing and extending the "<think>" process can produce extra value. (I do not know if that requires an improved underlying architecture - frontier models architectures are sometimes not public.)