451–460 of 534 posts
They have a silent nerfing system for their models and say so openly. The obvious question is how much it is being used already. Competitor companies being nerfed? Non Americans getting worse code? Punishing and rewarding users to maximize engagement, like online games do affecting victories through matchmaking?
$$$$$$: no nerf $$$$: a little nerf $$$: more nerf $$: are you poor? $: be permanent underclass
I spend a lot of time telling Opus 4.8 to search for security bugs in the code it wrote, and it spends a lot of time finding them, and then fixing them. Fable wont let me fix the security issues that Opus 4.8 created.
Can you elaborate what you mean by "won't let me fix"? What happens when you try to?
Wow, this is like saying: > If you buy a car from us, you agree not use it driving to and from work that involves automotive R&D that might compete with our product. And if our (heavily spying) car detects you are violating this, it will slow down to 20mph and cannot be made to go any faster, until we are sure the violation has ceased. Or > If you buy a laptop from us, you agree not to use it to study or acquire any…
If your car slows down to 20mph you'd instantly know. If Claude silently switches to dumb mode, you might not even realize.
Given the high rate of false positives people are reporting for the non-silent cybersecurity, biological, etc., safeguards, there is a strong likelihood that you will encounter silently nerfed behavior even if you are _not_ violating their TOS. Ultimately this will be evident in the way customers / external benchmarkers experience Fable. Hopefully competition will drive future models toward a lower false positive rat…
Having said that, on this query I've seen very little difference in the quality, there's nothing to be "2x as good on" for the "2x quota usage", so shrugs?
Here's a question that is still bothering me: what happens if you put something into CC /goal and it thinks this is related to LLM work? Will it just continue to spend your money until you're bankrupt? Did Anthropic unlock a legal way to steal people's money and call it saving the world AND get away with it? Just how much of that infinite money goes into Anthropic's PR department that they're able to pull this off an…
There is a possibility this may not end at simply nerfing the model. The idea of manipulating the behavior of a model depending on the prompt given to it can extend to 1. Detecting if employees from competing companies are using it and sabatoge their work, even not LLM-training related 2. Direct users to outcomes that would justify higher compute spend. Deliberately coding a project to 95% completion but designed to…
Anthropic: were commiting to being ad free. Also Anthropic: if you use our models in any way that might negatively impact our revenue we'll sabotage you. Can I pick the ads please?
Earlier quoted context omitted.
> But, history says the supercomputer of today will fit in your pocket in a few years. I don't think this will be true in the same time span anymore. Each miniaturization is costing more and more money. Perhaps they'll come up with exotic fundamental improvements, but I don't think the rate of improvement of compute/watt will match the previous decades.
Yeah, that's probably true, but we're also seeing that there's still tons of inefficiencies in how LLMs are being run. Seems like every couple months there's some new technique to squeeze more performance out of less hardware. KV caching improvements, fast attention, speculative decoding, dynamic quantization, quantization aware training, etc. That said, I recently replaced my five year old self-built PC (with a top-…
As that transition happens, hardware evolves from general purpose (because nobody knows what's needed and hardware design is slow) to fixed function high performance (once requirements are better defined).
GPUs (and TPUs) are a weird middle-ground here, as they're already fairly specialized, but I wouldn't bet against next gen AI inference-optimized hardware architectures dominating that use case in ~10 years if the pace of AI arch tweaking slows.
The efficiency/power/cost gains from fixed function optimization are always too great, and the only thing that holds that approach back is rapidly mutating requirements.
Earlier quoted context omitted.
> But, history says the supercomputer of today will fit in your pocket in a few years. I don't think this will be true in the same time span anymore. Each miniaturization is costing more and more money. Perhaps they'll come up with exotic fundamental improvements, but I don't think the rate of improvement of compute/watt will match the previous decades.
In five years I think you will be able to train a frontier modem for much less money than today and the power hungry hardware of today will be cheap second hand due to the power usage.
My biggest problem with Fable is that it includes health into its biology restrictions. Which means half the use I'd get from it ... doesn't exist. I'm not as bitter as I could be. I'm actually quite surprised at the sanity of not avoiding the health topic completely - I think only OpenAI had a few months where ChatGPT was tip toeing in any health related conversation. Otherwise it's been almost completely ungated, a…
it has also done the opposite, including affirming a mentally ill person's suicidal ideations.
The moat looks deep today but it's going to become more shallow every year. Training a new model from scratch takes serious resources. Post-training/fine-tuning an existing model, dramatically less. The knowledge for the process was esoteric two years ago, now you can ask a current model (one of several) to walk you through it, while building the tools to do it as you go. Several of my recent weekend projects have be…
The moat is not the model, it's the harness. I wager that's one of the main reasons why Google made Antigravity closed source.