Presumably RLHF (Reinforcement Learning from Human Feedback).
4,060 karma · joined July 29, 2020
Presumably RLHF (Reinforcement Learning from Human Feedback).
As an end user, security in game development seems to hit a minimum is the early 2000s.
I recall playing EverQuest and using ShowEQ on a Linux machine on the same network as a proxy to silently eavesdrop on the traffic to show a map of the game with all the hidden/obscured/visible stuff all present. They either never encrypted that traffic or I quit playing before they did.
As multiplayer games started to become the default, netcode improved quite a bit and basic encryption was implemented - but I don't recall a single multi-player game, ever, that was free of hackers when playing online.
It feels like over the years the issue moved from remote exploitation to hiding processes on the user's machine. That has lead to kernel-level anticheat systems. I'm unsure of the effectiveness as when they started to become common I moved all of my gaming to dedicated hosts because I wasn't willing to give that level of access to my "real" computers. That said, I've certainly not noticed a decrease in the perceived number of cheaters.
These days, as far as I know - and to be clear, this isn't an area of deep interest for me - I'm not worried about my gaming accounts being compromised through technical means. It feels like that sort of security is a solved issue overall, although I suppose it's also possible that other forms of exploits have simply gotten easier/cheaper.
These days we're generating multiple times more code than we were writing before. That means a similar multiple of opportunities for bugs to be introduced - so the ability to automate security review is more impactful in proportion to that.
Pre-AI, the advantage went to the entities with the largest budget to hire the best and brightest security engineers.
Post-AI, it'll go to the entities with the largest inference budget.
Right now we're in a transitionary period where it's kind of a tossup which approach is more practical, but at the end of the day - it's still all about how much money you can throw at the problem. I'm just hoping the threshold climbs high enough it's no longer practical for governments to be able to compromise individual actors' devices because doing so would waste a 0-day that's far, far more valuable than prosecuting one arbitrary person is worth.
I'm using open weights models on a privacy-focused provider right now, and that's adequate for my current usage, but I'm rapidly getting to the point where my agent's access level to my data (and to a lesser extent, my accounts) is becoming something I'm not comfortable sending outside my network at all.
My hope is that models that are roughly on par with Deepseek V4 Flash can be run on hardware that I can own for <~$5k in the near future. We're close, but not there yet as far as I know.
The only long-term solution to this is self-hosting.
I can absolutely prompt AI to following established patterns and produce nice, clean output in a legacy codebase. I also have a completely separate set of skill files that I’ve been building organically by allowing the agent to do make most decisions about conventions. The latter produces code that would be a nightmare to modify by hand, but I’m still able to iterate on it many times faster than I could in the codebase where code quality is a requirement.
“Code quality” is mostly “human readability”, and I’m simply not sure that’s a valuable attribute anymore.
That’s not at all my experience, and I’m in “2A” communities every day. A few months ago you’d have found a few people in support of it; now you’ll find a couple of cops say something inflammatory in the hopes of getting the other members banned, but otherwise they stay holed up in their little private law-enforcement-only subforums that everyone else isn’t allowed to access.
There’s at least one case of a Tennessee congressional candidate shooting multiple cameras: https://www.yahoo.com/news/politics/articles/tennessee-congr...
Where I am, deep in “Red State” territory, they’ve not started talking openly about it yet, but there are at least three separate people I’m aware of personally that are interfering with or destroying them.
What more would you have them do at this point?
No one who believed it definitely was not has changed their mind, they've just at most gotten quiet about it.
No one who believed it could have been but that the claim has not been proven have changed our minds, we've just decided that there's no way to know what actually happened.
There is no place for a young man who views masculinity through a traditional lens on the left.
There’s a place for a “decoder” for this stuff, and that should tell you something.
(just an example; it really can be framed from pretty much any angle)
That's a great example of selection bias: if they were intelligent enough to be capable of causing harm at that scale, they would have immediately realized the new guy suggesting targets and offering to buy them explosives was an FBI agent.
If Apple released a machine that would let me run, say, DeepSeek V4 Pro or GLM 5.2 locally at 100 tok/s for $10k, I might hurt myself running to get my credit card.
But then, I'm also posting this sitting in my truck while my family attends an event, with a Vision Pro on my face so I can monitor 7 Claude Code sessions without constantly switching screens on my laptop.
The general intent is fine, and I'm certainly not abandoning everything we've learned as an industry - but LLMs are not people, people are not LLMs, and there's no reason to believe that the coding practices we've found to be good for humans will be good for LLMs.
Each time we apply a practice like this, we should ask ourselves what problem it was intended to solve, whether that problem still exists for LLMs, and if the existing practice is the best fit for LLMs.
Cancer rates are significantly above baseline, especially neurological cancers.