billypilgrim

It should be called the Chuck Palahniuk neuron.

It’s been going on for far longer, people want to believe all OpenAI and Anthropic are doing is pure marketing. When the first Fable results were released, everybody was skeptical (which is rational), but with every third party confirmation of the capabilities they doubled down that this must be even more marketing instead of admitting that they were wrong. To the point that they are no longer skeptical but in pure denial about what is happening.

Thank you for linking that. I distinctly remember this moment as an important point in time, played around with emulating a terminal for hours, couldn’t believe how realistic it was, it even remembered when I changed a file earlier etc. Another point was when people on twitter with early access were like “oh my god it can write code too! I asked it to design a website and it just works!”, programming wasn’t even what LLMs were about, and now it’s one of the main use cases. Another revelation was when it could kinda play chess. A single model that can one shot a huge array of different problems, still mind blown how well all of this works to this day.

Or, you know, you could just pay for a service that you enjoy. I watch a lot more YouTube and see a bigger need to keep it alive than Netflix, HBO and co for which I am paying good money already, why should YouTube be exempt from that? Also if Netflix goes away tomorrow, you’ll find their content on torrents easily, but if YouTube goes away, we will lose decades of videos that no one has backups of. Expecting them to offer this service for free and without ads is crazy.

That was always true according to an old saying in software cracking circles: „everything is open source if you know reverse engineering“

It really is very common here in Germany to get an alarm that a WW2 bomb was found somewhere near you, telling people close by to evacuate. Like every couple of months. It doesn’t even register with people, I don’t know if the news even report it.

Not the one you asked but I genuinely think it’s possible that a part of the answer is the psychological effect of getting used to models performing well and picking up more if they fail, but also … If you have a product that works well for 95% of software engineering tasks (for the sake of this argument), with a large number of users there will inevitably be some poor schmucks who get bad results multiple times in a row. It would be highly unlikely if that _didn’t_ happen at all. Now assuming you have millions of users, there will always be groups of thousands that experience this, and if those people go online to complain, it will look like an actual issue when it can just be explained by randomness and large numbers.

Similar use case here! Combining AI with fuzzers is so powerful, especially for creating a special fuzzing harness, or generating seeds for hard to reach code. That was taking hours/days and was frustratingly boring work before. Unfortunately the Codex models refuse a lot for me, I’m mostly using the cheapest models because they refuse the least, have you found Kimi to be a good alternative? Any other you tested that you can recommend? Thinking of switching.

I honestly do not understand why we let it continue when we have been seeing the drastic negative effects for years now. The recommendation algorithm and the data it relies on must be opened up to to some kind of elected agency, and they need to be vetted for negative health effects just as we do now with drugs. Any algorithm that is addictive enough to keep users mindlessly scrolling for hours needs adjustment or needs to be banned. This would put a stop to infinite scrolling. Give the user more agency in deciding if they want to continue or stop there. We should no longer allow for-profit companies to hijack our attention for long periods and abuse our brains need for digital sugar.

„The depressing thing about tennis is that no matter how good I get, I'll never be as good as a wall.“ -Mitch Hedberg

idalib with Claude Code already works really well. But honestly, despite what people have been saying, LLMs have been very good at decompiling for at least two years now, I have been using it for that purpose regularly. Even just copying disassembly from the current function and all nested called functions from IDA into ChatGPT is already unexpectedly good.

The thoughts you are having about this show me that you are at a local maximum, but you will find your way out if you keep trying everything. There is no single thing that will help. Read novels, copy them word by word, translate them, write short stories, dissect stories, stop movies halfway and ask yourself how you would continue them. Read a ton of writing advice, try them out but don’t take it as gospel.

Even if you don’t improve for 100 days straight, small successes accumulate. In a decade you will have transformed yourself.

There is just no way you won’t improve significantly if you keep trying new things and bring yourself to fail ever day.

What helped me was the saying “your first million words are gonna be shit”. I still distinctly remember, four or five years into writing every day, when things finally clicked, my voice came through, and my sentences became fun. It is delayed gratification to the max.

That’s too bad because I think the last episode is brilliant. I think about it a lot even years after seeing it.

I must say I expected an actual poisoning of the data used to train the LLM and was excited, but the examples indicate that the LLM just searched the web and reported what it found? When you create a website with fake information and search Google for that information, it will of course bring up your site, not because it’s factually correct but because it’s related to what you searched for. What am I missing?