in 2023 i wouldve said gpt could pass the turing test. today i could figure out it was an llm in a few turns no problem. llms cannot pass the turing test now that we’re accustomed to them
they are definitely not agi as it was ever defined. they’re only a bit more capable than they were a year ago. they crossed over from interesting crap to useful tool recently but really only for software
I feel like i've seen less hype about "the next model will be agi". GPT-6 is supposed to be coming this summer, and nobody is expecting AGI now. Not sure how they're going to keep the hype cycle going
so are buybacks. you choose to sign the contract. there's no way they didn't have an escape clause, although likely it meant not using the cloud provider anymore
I use a gemma4 model locally to extract content from messages to a personal agent I'm building for its memory graph (to break the message up into the topic, source (assistant or owner), facts, entities, etc. in the message content (all getting thrown into a magma-esque graph using NLEmbeddings for memory search). This is for a custom personal agent that targets deepseek-v4 flash. The local model is too slow in my setup for a chat agent, but for memory extraction it works pretty well, saving API usage on every chat turn.
for many purposes they're good enough now. If I had an opus 4.8 class model on a box next to me that could produce tokens at rates like 5000/s, i don't know if i'd need a new one for a long time. I think we might be underestimating how powerful very very fast LLMs could be, since they could iterate on tons of small variations on tasks. paired with deterministic guardrails that gate "doneness", you could loop on tasks for a long time having the agent try different strategies until the goal was reached, in ways that are just impractical now (and very expensive)
the distinction may be between using the coding agents vs using models for products. for example where i work we're talking about dropping opus for a chinese model for the in-app agent (which is very expensive to run)
If AGI comes to exist it won't be "priced" at all, since the lab that creates it will either quickly be seized by the gov't for national security, or they will become the most powerful organization in the world and have no need to sell services to other corporations. they will become the only corporation.
if deepseek cost twice as much to train it would prove the same thing: the american companies have no monopoly on state of the art llms, and commoditization is happening
cost has nothing to do with why deepseek was disruptive, the fact that it means there is zero moat around anthropic or openai is what's disruptive about it. it means in the mid-term LLMs will be commoditized and customers will flock to the cheapest inference wherever they can find it. there's no reason to stick to the "frontier" labs
i pirated a ton but i also ripped all my cds and all my friends cds (and their parents cds). i took my macbook around everywhere and ripped every cd in could find