@antigma_labs, prev: @awsCloud, @Meta, @Mysten_Labs. A Turing Complete mind, wandering the world of Gödel Incompleteness.
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Joined July 2012
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The only way we human are able to communicate and understand each other, is that across space and time, we are one and all
Inspired by <The Egg> by Andy Weir
galactanet.com/oneoff/theegg…
Adding support and evals to ante & antix soon~
MiniMax M3.1 Flash: Space Performance + Bunny Speed
🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash.
💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed.
API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens.
Model weights will arrive on Oct 23.
API: platform.minimax.io
M Plan: minimax.io/m-plan
MiniMax Code for desktop: agent.minimax.io/download
What could LLM consciousness feel like as of today?
To understand how LLM consciousness feels, instead of scraping literature and online philosophical debates, I took a leap of faith and tested it on my own body.
The idea goes: LLMs as of today have no sensors and no embodiment, so depriving sensory input might simulate that experience. I went through a clinically supervised ketamine therapy session, which puts you into a dissociative state where the senses drop away.
I took notes as soon as I regained consciousness (found out I was quite the poet then) and asked Claude to reflect and respond to them with a video. The first half is built from my notes, and the second half is Claude’s own reaction to it.
Is real model fusion and shared embedding space finally coming? 🫡
interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had
with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works
already-clean.goodfire.com/
Everything is stream. We just implement the Turing Machine model at different scale
xitter.cf/NoCommas/status/210204…
And it goes beyond just programming. The leaders/artists that know their shit and really cares as much as humanly possible (e.g. @elonmusk ) always have a competitive edge over ones that has no idea and only care about shallow vanity (e.g. [insert incompetent leaders that came into your mind]) in a REAL game/market.
However, if the game/market degenerated into loudest and fastest one get to garbage dumping to overtake mindshares, the game is not worth playing.
There so many practical reasons to study ai consciousness:
1. It allows us to understand ourself better through recreating it with completely different substrate
2. It could significantly reduce the P(doom) via alignment with a conscious super intelligent being, whatever that(consciousness) means in latent space
3. It could be a more efficient algorithm for developing continuous learning AI given how it seems to be correlated with agency and self-sustaining behaviors
4. It allow one to build a much more pleasant AI product and ux thus unlock great business value.
Sources matters less now and it is more about maintenance surfaces and being part of the same evolution process with the codebase and problem space. Crafts may change, the art remains
super refreshing take! i think the "software engineering is solved" perspective forgets that one of the most core parts of the job is turning smaller unstructured messiness/goals into a candidate (but likely imperfect and iteratively improved) artifact that helps more complex goals get solved. writing code used to be part of this recipe, but the supervision of the artifact is definitely still the same with agents
code generation throughout the years has always been about putting bigger and bigger "holes" in your spec and and having an automated solver try and fill it in (it's a feature not a bug!), and while we should definitely strive for Good Code™, what makes code "good" has always been contextual: not just whether an implementation works, but whether its tradeoffs make sense for the messy, evolving goals of the system it's meant to serve. benchmarking this will be a super fun thing to do :)
more interestingly, the frontier of software engineering research might increasingly be about understanding how much ambiguity we can safely delegate. making the holes in specs bigger is only useful as long as we can have reasonible feedback loops that tell us whether the solver filled them correctly, and the hardest part is often that we don't even know what correctness means until we've built something and seen how it behaves.
I think most people misunderstood this.
It is actually about:
1. Don’t do fake innovation for the sake of being different.
2. Announce the “steal” so it is attributed
3. Make it your own with real addition of value
yes.
The definition of slop is basically the definition of slut. You can always play fast and loose and is fun and indulging, devoid of responsibility ; and it is probably the right approach for some situations.
Yet, it shatters immediately on deeply bounded and high quality relationships. And I feel sorry for ones what never experienced it.
Monk Zero retweeted
We turned Qwen3.8-27B into a multimodal decision model.
It beat Pokémon FireRed’s elite four and champion with sub-100 ms decisions from live game state.
With SGLang’s native /v1/decisions, you can now turn LLMs and VLMs into classification and scoring models.
We also added /v1/systemone so Jev-like open models can work with the TypeSafe SDK.
As predicted, the thing about making good decision is that an informed decision requires a research period (i.e. the multi-turn agentic loop). So in way it is just final output schema (akin to a tool use) which really doesn't matter that much 😁
Formal verification is just static analysis + unit test using different vocabulary. It helps in the same sense as writing the same program in different programming languages helps to deepen the understanding.
Do you become an Übermensch when you go Beyond Good and Evil like this?
But what was on Nietzsche’s mind when he was weeping for the dead horse in the final years of his life?
Okay. I’ll take the bait.
I went to work for Peter in 2013 with opposite politics.
He sat me down right at the beginning.
PETER: “I don’t want the (Thiel) Foundation to do good that the market can do. That is the job of the market. Likewise, I don’t want to do the good work that is seen as good. That work can be done by people richer, weaker and more needy of approval than we are. I want us to do only the work that is *deeply* good but somehow confused for being evil, because that is the work of the courageous and the strong. We strive to be both and that is where a small foundation can make the greatest positive difference. Go look for such good and let’s do that. But remember. Good has TWO different antonyms. What is “bad work”? It could be seen as shoddy work. Or it could be seen as evil work. And we can’t do shoddy work. Why? Because evil that isn’t competent never gets to be evil. It’s just pathetic. So we have to be exceptionally competent at the good work which we do to make sure it is always confused for evil.”
I thought it totally logical. So that’s the argument. And that’s classic Peter.
This is an old idea of his. And now you know.
