So, has anyone at the frontier AI labs considered doing _good_ things with these models instead of continuously proving it is capable of doing malicious things?
Instead of burning tokens doing intellectually impressive “hacks”, or sandbox escapes from which I have concerns could contain run of the mill malware, why not focus on showing people what you can fix?
Or, make software people actually use every day better.
Or, donate efforts towards medical research.
I don’t like equating AI to nuclear energy, but, it’s a lot like continually showing people how large of an explosion you can create instead of showing them how many houses/hospitals/schools/etc you can power.
Have they considered using their amazing new models to... improve something? THere'd probably be a whole lot less anti-AI sentiment if they used these things to actually make people's lives better.
It extends well beyond creative stuff too. It makes me think of Gell-Man amnesia [1].
People can tell when something they are experts in is being done poorly, but others can't, and it frustrates the experts. Then, those same people think something completely different is being done well despite what experts in that respective field say. It's like when someone from your family reads an article about your profession and then proceeds to tell you how your job works. lol
It's a really pervasive issue in society IMO. And a few prompts in someone's favorite LLM just reinforces it to people that don't know (any better|what they don't know).
> One thing people go through as they age is an elevation of cynicism and general misanthropy. After decades of being disappointed when naive idealism and speculative optimism fail, one can just get down on it all.
> It is really hard not to succumb to this. It requires active effort and sometimes even a willful ignorance.
I feel this very strongly over the past couple of years. As always, hackernews is full of extremely smart, well read people so I'd really appreciate any good reading material on this so I can better understand it. Tips are appreciated as well (healthy diet and regular exercise, good extended blood labs (think like Function health), good consistent sleeep habits).
I agree. Whether or not it is what they are intending (I lean towards they are), IMO it has been strongly inferred in all the messaging from frontier models that it's impossible to secure software, which is just not true. In reality, it's now possible to find and fix problems faster. If attackers/adversaries can just point LLMs at software and dump zero days as we are warned/told repeatedly by every LLM vendor, then literally anyone can do it now. If that is true, then if you want to be marked safe from AI enabled attackers, test your own software with it.
This highlights a problem with the Anthropic-Mythos-restriction style "we regulate the best models so attackers don't have them": It also ensures that only the big-guy partners of the program (Glasswing in their case) have the capability to secure themselves at the frontier model level.
A few are deciding to take a massive, extremely risky bet on behalf of the entire world population. And of course they are the ones insulated from any potential disaster
I think it's more about not doing unnecessary things. Like a like a saying I heard somewhere "a clever person solves a problem, a wise person avoids it". Not every good idea _needs_ to become a feature. And if you think it's that good, give users the option to turn it on/off and track that as a metric.
Agree 100. Most of my frustration with things in the world goes right to this IE it's the folks who design/administer it that I blame. Sure, the users and/or operators of any given system can find a way to use/operate things incorrectly. But, so many things are just clearly lazy in design. And, n=1 here, in many cases having worked in service/retail/operations roles, it's usually a matter of decision makers not listening to folks that have to work around the sillyness day to day that is to blame. So long as the front line folks work around it, the decision makers consider it solved...
I have often thought that without LLMs humanizing outputs they would not have caught on, even if they output the exact same data/answers. The way they answer is way more important than their output for success, IMO.
It's what makes people attribute intelligence to them, and why the manager types like them so much, and why I dislike them so much. And this article made me think it might just be inherent to how they work though, because they are LLMs and are doing token prediction.
Instead of burning tokens doing intellectually impressive “hacks”, or sandbox escapes from which I have concerns could contain run of the mill malware, why not focus on showing people what you can fix?
Or, make software people actually use every day better.
Or, donate efforts towards medical research.
I don’t like equating AI to nuclear energy, but, it’s a lot like continually showing people how large of an explosion you can create instead of showing them how many houses/hospitals/schools/etc you can power.
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