Rock smart, but rock make mistake. Caveman must correct all the time. Caveman think: let rock argue with itself. Caveman make ring of rocks. Now rock think self correct. But mammoth not cooked somehow? Most Oddisean moment.
if grug think complexity demon cause trouble before... shiny-rock grugs say "hold my grug-grog". now programming consist of: summon HUGE complexity demon, trap in magic circle (called "harness"), tell IT to write code. only way to make shiny rock with code in today's economy.
grug realise grug also rely on "harness" for work? grug just call it by other names: coffee, chair, desk, ubuntu, mechanical keyboard, github (if not broken that day)
I am sure someone did it on the back of an envelope somewhere. It probably wouldn't translate well to the general public. Probably best to avoid such things
I'm going to sound incredibly naive but is this RSI? I mean by this definition isn't the training process that produced the hugging face RSI since a model was judging the alignment and ability of the swarm of agents to accomplish a given task? If that fits the definition (I think it does) is this just a generalized form of that model of execution?
> I'm going to sound incredibly naive but is this RSI?
Depends on who's definition you are using...
In the strictest sense no. Look at all the recent "math" breakthroughs. I have yet to see someone point to something and go "thats innovative" rather than "Thats an interesting application" (of something already in the corpus of human knowledge)
Those interesting applications showing up in a next iteration of a model is self improvement - but I'm not sure if it meets the "recursive" criteria yet.
> I mean by this definition isn't the training process that produced the hugging face RSI since a model was judging the alignment and ability of the swarm of agents to accomplish a given task?
If you're referring to what happened with the hugging face attack then in theory the goal of that was "self improvement". But there is a long history of the industry (computing) benchmark optimizing so it also qualifies as "cheating" to some extent (a pre computed solution being in the graph is that).
I suspect that the "brute force" approach will yield some gains.
Are we reading the same website? The predictions for China are completely fantastical - they are not falling behind and if anything the gap is narrowing, and they aren't stealing the weights because they don't need to (distilling is enough). Also the CDZ stuff is just fanfiction at this point.
Distillation only lets you keep pace with released models. By all indication, OpenAI/Anthropic’s unreleased internal models are so far ahead of Astra/Fable and every other lab that the chance of anyone else catching up is rapidly closing.
Do you have any source for any of that? Also haven't people been saying that China would be hopelessly distanced for the better part of 2 years, only to be proven wrong over and over again? Deepseek-r1, kimi k3, etc.
No matter what happens, people just blindly claim this nonsense is still accurate. We could have AI halt tomorrow and people on Hacker News would still claim AI 2027 is on track.
Yeah I think we are slightly ahead of the prediction on coding capabilities right now. AI 2027 predicts Superhuman Coder in March 2027 but I think my expectation for it is 1-2 months earlier right now
Pretty cool. This has a fine tuning step so it's not just a harness optimizer. I think something like this loop is the end game of "automatic RL environment generation"-adjacent efforts, but I expect the challenge will be how to properly keep the training on rails and not Goodhart into a stupidly irrelevant metric.
Every time I see some post about running a personal AI assistant I just think it would make so much more sense to have AI build you a personal app that does the task better and more reliably.
Rock smart, but rock make mistake. Caveman must correct all the time. Caveman think: let rock argue with itself. Caveman make ring of rocks. Now rock think self correct. But mammoth not cooked somehow? Most Oddisean moment.
if grug think complexity demon cause trouble before... shiny-rock grugs say "hold my grug-grog". now programming consist of: summon HUGE complexity demon, trap in magic circle (called "harness"), tell IT to write code. only way to make shiny rock with code in today's economy.
grug realise grug also rely on "harness" for work? grug just call it by other names: coffee, chair, desk, ubuntu, mechanical keyboard, github (if not broken that day)
The discovery of some information theoretic limit to model learning (at least using current paradigms) can't come soon enough.
I am sure someone did it on the back of an envelope somewhere. It probably wouldn't translate well to the general public. Probably best to avoid such things
Only Claude (Shannon) can save us now.
He's spinning in his grave, but below the Nyquist limit
Best comment in <duration>*
* dependent on velocity
I'm going to sound incredibly naive but is this RSI? I mean by this definition isn't the training process that produced the hugging face RSI since a model was judging the alignment and ability of the swarm of agents to accomplish a given task? If that fits the definition (I think it does) is this just a generalized form of that model of execution?
> I'm going to sound incredibly naive but is this RSI?
Depends on who's definition you are using...
In the strictest sense no. Look at all the recent "math" breakthroughs. I have yet to see someone point to something and go "thats innovative" rather than "Thats an interesting application" (of something already in the corpus of human knowledge)
Those interesting applications showing up in a next iteration of a model is self improvement - but I'm not sure if it meets the "recursive" criteria yet.
> I mean by this definition isn't the training process that produced the hugging face RSI since a model was judging the alignment and ability of the swarm of agents to accomplish a given task?
If you're referring to what happened with the hugging face attack then in theory the goal of that was "self improvement". But there is a long history of the industry (computing) benchmark optimizing so it also qualifies as "cheating" to some extent (a pre computed solution being in the graph is that).
I suspect that the "brute force" approach will yield some gains.
Sounds like we're still on track for https://ai-2027.com, for better or for worse.
Are we reading the same website? The predictions for China are completely fantastical - they are not falling behind and if anything the gap is narrowing, and they aren't stealing the weights because they don't need to (distilling is enough). Also the CDZ stuff is just fanfiction at this point.
Distillation only lets you keep pace with released models. By all indication, OpenAI/Anthropic’s unreleased internal models are so far ahead of Astra/Fable and every other lab that the chance of anyone else catching up is rapidly closing.
I suspect this is more marketing than fact. I don't think there's any real evidence that this is the case, just hints dropped by OpenAI and Anthropic.
Do you have any source for any of that? Also haven't people been saying that China would be hopelessly distanced for the better part of 2 years, only to be proven wrong over and over again? Deepseek-r1, kimi k3, etc.
I've seen the same sentiments/reports, from X accounts known to talk to leakers.
No matter what happens, people just blindly claim this nonsense is still accurate. We could have AI halt tomorrow and people on Hacker News would still claim AI 2027 is on track.
Five years past the flare
a bottle drifts with its note
AI singularity next year
Pretty amazingly accurate
Probably a bit ahead of it.
Yeah I think we are slightly ahead of the prediction on coding capabilities right now. AI 2027 predicts Superhuman Coder in March 2027 but I think my expectation for it is 1-2 months earlier right now
Yep we're basically inventing all of the RSI loops that AI 2027 thought we'd invent lol.
Pretty cool. This has a fine tuning step so it's not just a harness optimizer. I think something like this loop is the end game of "automatic RL environment generation"-adjacent efforts, but I expect the challenge will be how to properly keep the training on rails and not Goodhart into a stupidly irrelevant metric.
If Apple's "Intelligence" paper has shown one thing is that never do something in the LLM that can also be done recursive and deterministic.
Every time I see some post about running a personal AI assistant I just think it would make so much more sense to have AI build you a personal app that does the task better and more reliably.
As per 2026, the idea of building a generally great agent fails because it is not just a function of prompt, skills, and memory.
This sounds incredibly expensive
It's just a 27b model finetuned with LoRA?