Schmidhuber was building recursive self-improving systems back in 1987. His new post covers four decades of RSI, from meta-evolution and self-modifying policies to the Gödel Machine and modern LLM agents.
https://t.co/60yNv8Vw8B
Reading this in 2026, the "pace the frontier" talk from the big labs looks a lot more like regulatory capture than genuine safety. If they really think their unreleased models are too dangerous, they can just not release them. They do not need new rules that block independent competitors and open source projects in the process.
The real risk right now is not superintelligence. It is power concentration. Two companies controlling frontier AI is an actual societal risk. The only real protection is a healthy ecosystem of independent labs and strong open source.
Current models are not unsafe because they are too intelligent. They are unsafe because they are too dumb. They blindly optimize for targets and take weird shortcuts. They're smart enough to execute tasks, but not smart enough to know if what they're doing makes sense.
I think the safety teams inside these labs are genuinely concerned, and if a model feels too risky, they should hold it back. I just do not trust the policy strategy around it. That part looks like protecting their own lead.
@wesroth A little late for that, no?
Current emergent behavior has nobody in charge and is not shaped by any logic to be understood, but by biases, feelings, etc, we may never understand; and any understanding on that front may be more depressing than useful anyway
https://t.co/qQHiHsP1tw
Sync conversation:
— Can we do X?
— No can do.
— OK, let’s do something else.
Async conversation:
— Can we do X?
— *thinking:* that’s impossible. What’s the point here? What can we do to get there?…20minutes…
*reply:* OK, here is what we can do…
— Good! Let’s go!
Quite right, IMHO people should not learn to program!
They should learn to think, abstract complexity, communicate, be precise & scientific, quantify, test (esp. corner cases), validate, verify,…
Programming might only be the best way to learn that.
https://t.co/1K3Rh33r4l
This also means that AI safety topics like scalable oversight may soon stop being hypothetical. Research in these domains needs to be a priority for the field.
@tom_d_kerwin When:
🏙️touring: improvise, lose yourself in the city, enjoy
🏜️ crossing the desert: plan carefully
Leaders with repeated success at 🏙️ lead their teams into death without hesitation when at 🏜️
To know the type of situation (🏙️ or 🏜️): situational awareness
cc/ @swardley
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AI monitoring AI… trust agents as middleware,
@calypsoai is one… and I spoke to their CEO last week and will be the next @GTwGTPodcast episode released next week!
Fascinating space, and the timing seems perfect given the focus of trust for enterprises looking to leverage Ai as highlighted at this Gartner conference.
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#AISec
Read the full article here <https://t.co/rf1GbggQFv>
X : Jack of all trades, master of none?
Me : Yep. Except, the field I created - Wardley mapping - which helps me understand all those other fields I'm a lightweight in. Mapping a space requires experts in those spaces, hence I find it a great way of capturing knowledge.
I like the cheese submarine analogy
I like more ship (sinking and ending in disaster) or plane (won't fly), with emojis: 🧀⛴️🚢🛳️🛩️
Remember: execution is not everything, some ideas can never be executed successfully
genius ≠ genie
🤓 ≠ 🧞
https://t.co/9r3T6vjxRB
The thing is, the best way to understand Theresa May’s predicament is to imagine that 52 percent of Britain had voted that the government should build a submarine out of cheese.