331–340 of 340 posts
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what are you working on? I only hit the guardrails twice after burning through two weeks of 20x max plan, both times on ML stuff; still more than I'd want to, but not unusable
Lucky for you. I, along with everyone else on the fable guardrail thread have been hitting guardrails with Fable for boring normal shit and getting downgraded.
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what are you working on? I only hit the guardrails twice after burning through two weeks of 20x max plan, both times on ML stuff; still more than I'd want to, but not unusable
very mundane web app and networking security (vpn etc.), nowhere near redteaming
I think any security-related task triggers it to think about the threat model and thus hit the guardrails
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why would you need a local fable at that point? AGI will surely solve all the problems in the world at that point
I’m kidding but.. it’ll be great if in 10 years we look back on this and your joke has become a prophecy.
I personally don't think the weight efficiency will improve that much; if anything big does happen, I expect it to be about scalable architectures and continual learning
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The fact that you're even saying this it is probably an admission that you do think it's making you dumber. Most people I know, who are honest with themselves, have admitted to me that they feel like it's making them dumber or "zombifying" them. This is also well studied already, https://arxiv.org/abs/2506.08872 LLMs are poison for the brain, I'm almost certain of it, at least when used in the way most people are usi…
It's pretty easy to generalize this, but it doesn't match my perception. People who are using llms to do things they could have already done, but faster, probably have atrophying skill sets. People who are using these tools to accomplish significantly more difficult or complex work than they used to are absolutely finding new ways to push themselves. The problems are just much bigger. The average Joe can easily vibe…
This line: "this is my main argument against the valuation of frontier labs. It’s not that AI won’t create that much value, it’s that they won’t capture it." That is a very astute and concise way to explain everything about how the frontier labs are behaving and how they're trying to push more people to pay token rates for the best models. At the current subscription prices ($100 or $200 a month for a generous, thoug…
The funny thing about Fable, is we all but know it will be obsolete in a month or two. Between their embargo shenanigans (which IMO they could have avoided just by not pretending it was dangerous) and continuing to give access, whatever marginal advantage it had was essentially wasted. It would have been an interesting experiment to charge more for it right away and see what the market would bear, rather than tease i…
I love LLMs too, but I am concerned about their cost. They are all still very subsidised. Is there any guarantee that I'll be able to run a Opus 4.8-level model on my personal computer before the big AI labs decide to hike up the prices?
> They are all still very subsidised. I think the opposite: I think the frontier labs have good margins on their inference unit costs. We can already see what it costs to run near frontier-size models. There are independent business pivoting to serving these models at reasonable prices and they're competing on OpenRouter for costs much lower than frontier labs. > Is there any guarantee that I'll be able to run a Opus…
Interesting. Good enough to make up for training costs?
Also, where can I read more about this?
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While I do agree there will be disruption we haven't seen yet, my company is already spending >$40k/day for a "frontier model", so who knows. Then again, they're not using that for coding
What are they / you using it for in such quantities?
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Typing prompts isn't the equivalent of baking bread. Typing prompts would be like measuring ingredients.
putting ingredients into the bread maker and pressing "on"
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Well, we did do similar stuff back then. All it takes is money ;)
You're talking about going from a single gigabyte to 16 terabytes in a low-power consumer form factor, which is 1600x. A generous estimate of the factor of the RAM sizes for low-power consumer devices between 1990 and 2000 would still be a few orders of magnitude short, if I'm doing my math right. Examples of what exactly you're claiming is precedent for this would be helpful.
Not sure where the 1Gb number comes from? A standard laptop now is ~16Gb of RAM, so 1000x (and 1Gb -> 16Tb would be 16000x not 1600x). We went from Kb to Mb and then Mb to Gb of memory roughly every ten years from ~1990 -> ~2010. Each of those jumps is 1000x
Talking this over with claude, though, it pointed out that the need in dealing with LLMs is bandwidth and read-only storage, since the weights aren't dynamic. So we're not necessarily looking at 1Tb of RAM, we could be looking at 256Gb of faster RAM, and multi-TB of (much cheaper) flash storage, with extensive caching built in at OS level. This is all technically do-able with current tech, so it'll be interesting to see if it happens.