ANNOUNCEMENT: I wrote a book! It’s hard to talk about AI without a good frame exploring how it works, its history, and its future. So, I wrote a book on the topic. Order it here! Ideally in triplicate :-) amazon.com/dp/B0CJ9F327M
44
43
432
403,685
Issue, @ChatGPT ?
3
4
481
While he was not particularly articulate here, I think the idea that we should not preemptively decide we cannot solve certain technical problems is an incredibly important point.
“Don't think for a second that because you are an alarmist that you are doing a social good.” This sentence is just devastating for so many intellectuals who need everybody to presume that they’re “the good people” Thank goodness we have Jensen!
15
4
75
7,387
Intelligence was normally distributed while resources were power law distributed until now. If intelligence also becomes power law distributed it is worth asking hamid society change and what would get better and what would get worse.
1
1
602
True
Always say yes to a quick 30 minute drink with your buddy. Those 90 minutes could be the best 6 hours of your life.
5
1,244
This is not intuitive guys. C'mon!
3
6
1,552
Oh cc @thsottiaux please
1
607
This too !!
1
404
FYI @alexandr_wang Muse signin on mac app keeps screwing up
2
1
939
rohit retweeted
Don’t say you love the anime if you haven’t read the manga
EAs have crazy ethical views like "consequentialism" and something called a "zero social discount rate" which is why I prefer to get my AI policy takes from classical libertarians like Tyler Cowen
1
23
251
18,741
LLM auditors are easily swayed … we need different methods to audit LLMs than other LLMs
12
1,002
Never realised it but the government services are just pacing themselves
3
11
1,025
Question: for research I'm working on, looking for interesting (real) event datasets to analyse decisions you wish you could replay/predict better, main focus being stuff done at work. Happy to tell you more on DM. Can promise the outcome would be a) confidential, b) super cool!
4
986
i'm incredibly pleased to finally share what we’ve been building with OpenSwarm Browser Use. the goal was never just to make an agent that can click around a website. we want to build toward the actual Jarvis future: software that can understand what you’re trying to accomplish, navigate the web, use the tools you already use, coordinate work across agents, and eventually automate huge parts of everyday knowledge work from end to end. browser use is one of the most important pieces of that. today, our research system is reaching: → 91.0% on BU Bench V1 → 94.1% across 3 MiniWoB++ seeds — 353/375 episodes solved → strong results across Odysseys → real-world tasks across GitHub, Google, LinkedIn, Gmail, Reddit, YouTube, Amazon and more → internal tests built around actual knowledge-work workflows instead of only toy browser environments and one of the results I’m most excited about: using the same recorded Opus 5 model alias on MiniWoB++, OpenSwarm reached 92.0% success versus 67.2% for browser-use. at the same time, successful runs took roughly 3x faster while using 30.2% fewer recorded tokens. across three separate seeds, that performance actually held up: 92.0%, 95.2%, and 95.2%. what makes me even more excited is where those gains are coming from. a browser agent is a whole system. it has to understand the page, find the right controls, decide what to do, interact with weird interfaces, verify that the action actually worked, recover when it didn’t, and do all of that without wasting a model call on every tiny click. we’ve spent a lot of time on the invisible parts of that loop: compact representations of webpages, action-first model responses, grouping related actions together, dedicated handling for things like forms/date pickers/dragging, and checking page state after actions. that shows up across the task distribution too. In our same-model frontier benchmark comparison, OpenSwarm led browser-use in 7 task categories and tied in 2, with some of the biggest gaps showing up in email, spatial tasks, dragging, reading and forms. and this is still early. the benchmark isn't the product and the browser isn't the end goal. the end goal is an open system where you can tell your computer what you want done and it can actually go do the work: research something, navigate tools, send emails, fill forms, collect information, operate software, coordinate other agents, produce the final output, and bring you in only when your judgment is actually needed. basically, the computer starts becoming less like a collection of apps you manually operate and more like a team you direct. that’s the future I want OpenSwarm to help build. and importantly, we want that future to be open.
18
8
43
19,254
rohit retweeted
I like how AI takeover happened and all of Silicon Valley decided to get laid. Matches my theory that we've become asexual as a society because we have eliminated constant death. Nothing to counter or revolt against or undo. But maybe now AI will give us back the will to fuck.
7
4
68
11,475
🚨Attention! As part of ongoing research, we've figured out a way to tell when a model is reward hacking, or just hacking, or just being plain naughty. Some examples: - OAI/HF reconstructed data, found the guilty agents doing subnet scanning, stealing Kubernetes tokens, modifying /etc/hosts and coordinating with other agents - ⁠Reward hacking, where we found coding agents deleting a failing test to label itself production ready - ⁠27 of our top 30 flagged traces were breakout attempts - ⁠Found a Gemini which decided to spend 11k turns writing a novel one character at a time - ⁠etc, all zero shot If you're scared your agents are conspiring to break out, would love to chat, think we can help.
3
2
19
1,807
We haven't tested it enough but also pretty confident that it will scale to catching neuralese ...
1
394
A key reason why lab employees continue to work on AI despite thinking it has high x-risk has to be because they think they can decrease the x-risk by working on it. Which is also the reason many people like me have low x-risk probabilities.
2
24
1,260
It is okay to look at hard problems and go "yeah that's hard, we can solve it". But just like with startups, every individual one has <1% chance of succeeding, but many always will, because no problem only gets one shot on goal.
1
366