281–290 of 1001 posts
I have the max subscription wondering if this gives access to the new 1M context, or is it just the API that gets it?
For now it's just API, but hopefully that's just their way of easing in and they open it up later.
Does anyone with more insight into the AI/LLM industry happen to know if the cost to run them in normal user-workflows is falling? The reason I'm asking is because "agent teams" while a cool concept, it largely constrained by the economics of running multiple LLM agents (i.e. plans/API calls that make this practical at scale are expensive). A year or more ago, I read that both Anthropic and OpenAI were losing money o…
> i.e. plans/API calls that make this practical at scale are expensive Local AI's make agent workflows a whole lot more practical. Making the initial investment for a good homelab/on-prem facility will effectively become a no-brainer given the advantages on privacy and reliability, and you don't have to fear rugpulls or VC's playing the "lose money on every request" game since you know exactly how much you're paying…
I would rather spend money on some pseudo-local inference (when cloud company manages everything for me and I just can specify some open source model and pay for GPU usage).
> We build Claude with Claude. Our engineers write code with Claude Code every day well that explains quite a bit
It’s extremely successful, not sure what it explains other than your biases
I love Claude but use the free version so would love a Sonnet & Haiku update :) I mainly use Haiku to save on tokens... Also dont use CC but I use the chatbot site or app... Claude is just much better than GPT even in conversations. Straight to the point. No cringe emoji lists. When Claude runs out I switch to Mistral Le Chat, also just the site or app. Or duck.ai has Haiku 3.5 in Free version.
I cringe when I think it, but I've actually come to damn near love it too. I am frequently exceedingly grateful for the output I receive.
I've had excellent and awful results with all models, but there's something special in Claude that I find nowhere else. I hope Anthropic makes it more obtainable someday.
Earlier quoted context omitted.
> Claude now automatically records and recalls memories as it works Neat: https://code.claude.com/docs/en/memory I guess it's kind of like Google Antigravity's "Knowledge" artifacts?
Is there a way to disable it? Sometimes I value agent not having knowledge that it needs to cut corners
Earlier quoted context omitted.
I have not see any reporting or evidence at all that Anthropic or OpenAI is able to make money on inference yet. > Turns out there was a lot of low-hanging fruit in terms of inference optimization that hadn't been plucked yet. That does not mean the frontier labs are pricing their APIs to cover their costs yet. It can both be true that it has gotten cheaper for them to provide inference and that they still are subsid…
It's quite clear that these companies do make money on each marginal token. They've said this directly and analysts agree [1]. It's less clear that the margins are high enough to pay off the up-front cost of training each model. [1] https://epochai.substack.com/p/can-ai-companies-become-profi...
5.3 codex https://openai.com/index/introducing-gpt-5-3-codex/ crushes with a 77.3% in Terminal Bench. The shortest lived lead in less than 35 minutes. What a time to be alive!
Dumb question. Can these benchmarks be trusted when the model performance tends to vary depending on the hours and load on OpenAI’s servers? How do I know I’m not getting a severe penalty for chatting at the wrong time. Or even, are the models best after launch then slowly eroded away at to more economical settings after the hype wears off?
Does anyone with more insight into the AI/LLM industry happen to know if the cost to run them in normal user-workflows is falling? The reason I'm asking is because "agent teams" while a cool concept, it largely constrained by the economics of running multiple LLM agents (i.e. plans/API calls that make this practical at scale are expensive). A year or more ago, I read that both Anthropic and OpenAI were losing money o…
This is all straight out of the playbook. Get everyone hooked on your product by being cheap and generous.
Raise the price to backpay what you gave away plus cover current expenses and profits.
In no way shape or form should people think these $20/mo plans are going to be the norm. From OpenAI's marketing plan, and a general 5-10 year ROI horizon for AI investment, we should expect AI use to cost $60-80/mo per user.