Occam’s razor tells me it’s probably because it’s not good. Perhaps running a company like survivor in a pressure cooker is not an effective management strategy.
I'm guessing both openai and anthropic have transitioned to prompt magic and fine tuning rather than try to keep building LLMs at scale. The fact that QWEN and other models are impressive, small and perfectly suitable for most work means every dollar you're spending on trying to train larger models is a losing prop.
> every dollar you're spending on trying to train larger models is a losing prop
You probably don’t know how smaller models are trained then. Most of them are knowledge distilled or trained using data generated from larger models. If larger models are stopped there is no magical way smaller models will keep getting better.
0-60 in 2.5s — faster than a GT3RS, but slower than a 911 turbo S. I guess for north of half a million, you should be able to keep up with the german top dog.
This is exactly what I was looking for in the original post. For those who think this is expensive but spend most of your waking hours at a desk, think of it as an investment in yourself.
Today changed my opinion on them completely. Was willing to give them the benefit of the doubt that they're growing fast, but now seeing that they've failed to scale properly, and are missing little things that become big things later. I can't take that risk.
I think it’s good people are making IaaS platforms, but have dealt with enough firefighter hero bullshit to have seen this coming a mile away. Uptime and redundancy are strongly correlated.
This was kind of my read as well. We are increasing our AI usage but not in a way that meaningfully affects our ability to deliver on our product roadmap, so the solution is to cut opex on people so we can devote more to compute. The last bit is obviously speculation but it doesn’t feel like a far leap.
My charitable company strategy take: this is companies skating to where they think the puck will be
Given the rapid progress in LLM capability in recent history, it's reasonable to expect that continues... at least to some degree.
Consequently, companies are going to need to continue to cut, and delaying those cuts will only leave them in a worse position.
Devil's advocate counterpoint: it's currently unclear where AI does and doesn't provide efficiency gains in a business, so some companies are making headcount reductions without knowing where they should target them
would that someone were inclined to get ahead of such legislation, what are some of the most dangerous 3D printers, just so i know which ones to avoid...
