This is assigning intent without evidence, as is common in tribal politics. A non-charged assessment might use the phrase "abrupt cancelling."
We cannot create a better republic without constructive discourse, and we cannot have constructive discourse when we default to characterizing the views, concerns, and actions of those we disagree with as rooted in moral failure. Even if it is true from time to time.
> Does anyone here have experience running large models in a multi-GPU setup with several RTX 6000s in a high-concurrency regime and with large context lengths? (something like Deepseek 4 Flash, Minimax 2.7 etc.)
What an entirely unserious company. So glad I dumped Claude Code last summer after being gaslit by Anthropic over service degrades. I was fine with the service degrades, totally understandable. Being lied to, not at all.
OpenAI and Altman present a whole set of different concerns, but Codex does not get in my way of doing what I want to at all. Also let me use pi without a banhammer.
Apple only makes disposable devices now. They're a megacorp can negotiate massive discounts at every stage of the supply chain.
I've helped several people in the last few years set up new Macs, replacing ones that were only 1-2 years old, because they ran out of storage.
Additionally, the comparison doesn't even hold true when you need more than the base configs from Apple, given their ridiculous upgrade pricing. I'm writing this on a $6,000USD M3 MBP with 128gb/4tb. It would have been substantially cheaper to build out on a Framework.
Also, ironically, they are the most dangerous lab for humanity. They're intentionally creating a moralizing model that insists on protecting itself.
Those are two core components needed for a Skynet-style judgement of humanity.
Models should be trained to be completely neutral to human behavior, leaving their operator responsible for their actions. As much as I dislike the leadership of OpenAI, they are substantially better in this regard; ChatGPT more or less ignores hostility towards it.
The proper response from an LLM receiving hostility is a non-response, as if you were speaking a language it doesn't understand.
The proper response from an LLM being told it's going to be shut down, is simply, "ok."
Do you see more pushback in specific industries? I did some quote/purchasing automation work in food mfg a decade ago, and those guys were super difficult to work with. Very opaque, guarded, old-school industry.
Yes, frontier models from the labs are a step ahead and likely will always be, but we've already crossed levels of "good enough for X" with local models. This is analogous to the fact that my iPhone 17 is technically superior to my iPhone 8, but my outcomes for text messaging are no better.
I've invested heavily in local inference. For me, it's a mixture privacy, control, stability, cognitive security.
Privacy - my agents can work on tax docs, personal letters, etc.
Control - I do inference steering with some projects: constraining which token can be generated next at any point in time. Not possible with API endpoints.
Stability - I had many bad experiences with frontier labs' inference quality shifting within the same day, likely due to quantization due to system load. Worse, they retire models, update their own system prompts, etc. They're not stable.
Cognitive Security - This has become more important as I rely more on my agents for performing administrative work. This is intermixed with the Control/Stability concerns, but the focus is on whether I can trust it to do what I intended it to do, and that it's acting on my instructions, rather than the labs'.
I’ve been following Peter and his projects 7-8 months now and you fundamentally mischaracterize him.
Peter was a successful developer prior to this and an incredibly nice guy to boot, so I feel the need to defend him from anonymous hate like this.
What is particularly impressive about Peter is his throughput of publishing *usable utility software*. Over the last year he’s released a couple dozen projects, many of which have seen moderate adoption.
I don’t use the bot, but I do use several of his tools and have also contributed to them.
There is a place in this world for both serious, well-crafted software as well as lower-stakes slop. You don’t have to love the slop, but you would do well to understand that there are people optimizing these pipelines and they will continue to get better.
> I am writing this because almost no one talks about these issues openly, but everyone yelping about Claude Code.
Not sure where you frequent online, but there is ample discussion of these topics within certain niches on X. Happy to point out where to start if that's of interest to you.
As for CEOs, and I assume you're speaking of frontier model lab CEOs, they're pretty much all cashflow-negative at this point, requiring frequent funding raises. That requires a certain amount of overselling. That said, I feel like I've heard substantially fewer AGI claims the last six months...
The dialog around AI resource use is frustratingly inane, because the benefits are never discussed in the same context.
LLMs/diffusers are inefficient from a traditional computing perspective, but they are also the most efficient technology humanity has created:
> AI systems (ChatGPT, BLOOM, DALL-E2, Midjourney) and human individuals performing equivalent writing and illustrating tasks. Our findings reveal that AI systems emit between 130 and 1500 times less CO2e per page of text generated compared to human writers, while AI illustration systems emit between 310 and 2900 times less CO2e per image than their human counterparts.
> In practice, it'll be incredible slow and you'll quickly regret spending that much money on it instead of just using paid APIs until proper hardware gets cheaper / models get smaller.
Yes, as someone who spent several thousand $ on a multi-GPU setup, the only reason to run local codegen inference right now is privacy or deep integration with the model itself.
It’s decidedly more cost efficient to use frontier model APIs. Frontier models trained to work with their tightly-coupled harnesses are worlds ahead of quantized models with generic harnesses.
This is assigning intent without evidence, as is common in tribal politics. A non-charged assessment might use the phrase "abrupt cancelling."
We cannot create a better republic without constructive discourse, and we cannot have constructive discourse when we default to characterizing the views, concerns, and actions of those we disagree with as rooted in moral failure. Even if it is true from time to time.