The circumstances under which they were able to get the synthesized DNA this way would not work in the general case [1]
>Multiple IGSC member companies detected the ordered sequence and determined the order to be legitimate as defined in the 2023 guidance. Specifically, the orders were placed on behalf of SecureBio, an organization known to IGSC member companies given the role played by SecureBio in the SecureDNA project, an effort to build a DNA synthesis screening system. In addition, the name on the orders was an individual who has co-published multiple times with Esvelt, an individual well known to IGSC companies to work in viral evolution and who is known to have access to laboratory facilities sufficient to work safely with the ordered material.
>In short, the system worked as designed: a legitimate individual ordered DNA sequence that, by itself, posed no risk of misuse, for delivery to a company associated with legitimate scientific contributions directly relevant to the sequence that was ordered.
"So you think in 3 years AI is going to solve longstanding math problems because it was used to write some coherent sentences?" — people with the same amount of foresight in 2023
Are you saying at anything that can solve longstanding math problems necessarily has the means, motive, and capability to kill 8 billion people in just 3 years?
No dude, it was an analogy. Sorry to pick on you, you're just another ignorant uninformed take in this thread, but come on. This technology is progressing at an insane rate, the shit it's doing now is science fiction from just a year or two ago, and people just keep on moving the goal posts, it's maddening. The technology is unpredictable and that in itself has risks. You must realize that the window of possibility is widening the further into the future we go! Can you pick people with epistemology you trust and see if there's anything you can learn in this moment? Can you try to challenge your own ideas instead of retreating into comfortable certitude? There are real risks here, they are worth taking seriously, and serious people are doing so!
If more than 0.05% of the rationalist and AI safety community were Zizians this argument might be worth considering for like ten seconds before dismissing it.
If you're referencing Fetch for mac (pre macos) or Transit by Panic (later renamed to Transmit), I was a fan (and I've been a terminal fanboy since the early 80s). Both of them started as FTP wrappers, and both provided convenience the cli lacked.
I'm not sure about the answer here, but this can be caused by the scoring rubric used by given benchmarks. For instance, if a benchmark docks scores for running too many commands or using too much wall-clock time, higher efforts will get lower scores.
I gave the photo to Opus 4.8 and it reconstructed the same script in one shot. Although it did say it had to correct some parts of it based on context where it suspected OCR mistakes.
I feel like the Nonogram is AI generated? There’s no way a human would set a perfectly symmetrical “diamond” as a medium difficulty puzzle. Worse yet, the hard difficulty is just “big diamond”, the same thing on a slightly larger grid.
I was also very confused. I started a medium puzzle and was immediately thrown off by the borders. Thicker borders are usually every 5 cells, but here it looks like they've been added just to equally divide the puzzle into 3 chunks.
Missing small details like these makes it fall into the uncanny valley. It looks like a typical puzzle on the surface but when you try to solve it all the mistakes stick out.
The nonograms get more difficult as you do them. I actually made the diamond one myself, haha! Not too challenging really. I'm not good with making pixel art, but I probably made half of them by hand and I used Fable 5 to make the rest. I didn't actually find Opus or GPT-5.5 very good at making them. Or if they had an idea that was good, I had to fix it myself. Fable 5 was much better and 80% of its ideas looked decent.
I hear ya. Fair criticism. I'm a professional developer myself, but not great at design. I've tried to come up with a different looking site best I could. I went with a newspaper theme like back in the day when you'd get the puzzles in the paper. And then it was my idea to have a sudoku being solved as a graphic on the front page. I would push back that this could be one-shot by any of the leading models including Fable. Each of the 10 puzzle types has to have its own generator and they're different from each other. They have to handle uniqueness, solvability, and difficulty and none of the leading models have nailed even just a single generator on the first shot. Plus, there's monetization, rate limiting, caching, among other things under the hood that models wouldn't typically touch without specific instruction or would, at best, half-ass it. Maybe you have better luck with them, but for my job, I work on a large legacy app as well as various microservices and the LLMs miss things all the time. I have a system I use that does make them perform better, but you still gotta watch em like a hawk.
I one shot games every now and then, just to see how much it can do. For anyone wanting to experiment, I have come to learn that if you make it make browser games the setup is even easier since it can just inject the JS into the HTML and import from a popular CDN, no node, no compilers needed, just a single HTML page with inline JS.
I'm curious, What kind of details are you thinking of? I'm not sure I really have much of a radar for LLM websites in the way I do for LLM pictures or music.
I don't know for pictures, but I have gotten pretty good at detecting AI in videos. I am noticing these a lot on youtube. Often you can tell, e. g. movements being weird, animals behaving in ways that are only in a short and nowhere else to be found. And some more indicators e. g. youtube insists on showing sexy girls, but the video is clearly "cut" into another video and the surface layers also don't fully align; or some proportions are odd (I don't mean the "regular" ones but e. g. when the biceps looks like semi-hulk, you know something is AI slop). I try to not watch AI slop but sometimes it happens.
For images, there are some clear styles AI leans heavily on if not actively steered away[0].
It can definitely be prompted pretty successfully though, a bird spotting app was up her on HN recently with some really nice looking woodblock prints that were AI generated (I always feel disappointed/tricked when art turns out to be made by AI, I'm not sure why, it seems to pull the joy out of it for me)
As far as I understand, this is exactly how ELO scores work. If a more capable show up and starts beating all the other models, it literally takes ELO points from everyone else.
It's a fitted Bradley Terry model, scaled to familiar Elo scores, anchored to wins against Mixtral-8x7B at 1114 (at least last time I looked at it). When you fit the model against historical data, and then you add another month of time that contains newer models, the relative strength of a given model might decline even if its absolute ability remained fixed.
It depends what you use as an anchor. If the anchor is a fixed model, you’re right. If the anchor is updated to a better model over time, then the elo of historical models degrades, right?
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