Birbla

Join the discussion

Write your take first — we'll ask for email only when you're ready to publish.

Sign in
  • Hacker News
  • Their corporate sound system is sick!
    by madebylaw
  • the intentions may be good but it looks like a boost to surveillance tech in the wrong hands, time to react
    by oldfuture
  • Very cool tech. I think people are underrating how this will be used.
    by nasreddin
  • Really really cool. If they can serve this efficiently it would disrupt a lot of things.
    by Nimitz14
  • This does feel like where things should be going for more natural human-AI interaction patterns. Nice write up and demos.
    by monkeydust
  • I see that a lot of demos involve moving components from external harness into the model itself, but would this really be a flexible way to do things?

    It seems that in a lot of cases you would be able to iterate faster on the user interaction harness if it's an external harness rather than a full-blown model. For example, if there's a UI standing between the user and the model that needs to change (perhaps by the user customizing it themselves).

    IMO flexibility is mandatory because for fixed use cases like live translation or a straight-up voice bot, sure a model like this helps, but in each of those cases you'd just be outcompeted by even more specialized alternatives down the line.

    by 2001zhaozhao
  • That's neat and definitely the next step. But to be honest, I don't want an AI talk to me like that.
    by emsign
  • Same here.

    Presumably it will be possible to adjust that behavior with settings, the system prompt, etc. Not that most users will make such adjustments, though.

    I'm currently teaching a class on AI-related issues at a university in Tokyo. Many of the students were surprised when I showed them that they can change the response behavior of chatbots to make them more or less verbose, sycophantic, etc. It shifted the direction of our discussions on the possible impacts of AI on the people who use it.

    by tkgally
  • Very cool! The demos felt fairly contrived - e.g., count things while I talk. I wonder what more useful or commercial applications look like.
    by tedsanders
  • Yes! This is a big thing ive noticed in all AI demos. If the best use case you can think of to show off yor tech is to book a holiday, that I could easily do myself, does your service really add much value? Or is it simply because the real uses will be nuanced and specialsed, and not suited for a quick general audience demo? I'm not sure.
    by haritha-j
  • In theory I would expect it to do everything the current frontier models are capable of but with the added benefit of real time interactivity for better collaboration. The biggest benefit may be the real time video input so it can take in that input in parallel with producing outputs steered by the input rather than taking in a video or all images at once and then producing a single output for all of that.
    by alyxya
  • One of the most interesting things to me about AI is that it seems no one has a clear use for intelligence (besides for programming which has taken off)

    Every demo by openai showing of their models is "tell me how tall the statue of liberty is divided by the year the inventor of steam engines was born". It's cool but it's so hard to find an actual use. As a personal answer machine I find it very useful but if someone told me 5 years ago; here's a natural language computer as smart as at least every 15 year old, it costs a few bucks per million words. I would have thought that the applications would just scream out but till this day - outside of programming (a big deal tbc) - no one has found a good use for intelligence. It's so so weird.

    I guess even a company can't just automatically make more money by hiring more people but I'm still confused

    by FergusArgyll
  • A lot of people use AI to write things, from mundane emails over blog posts and news articles all the way to full novels and non-fiction books. I'm not saying the results are any good, I'm just saying people find use for it. Another common use-case is summarizing or proofreading.
    by Timwi
  • Aside from how impressive the model is, the demos here are very well done! Quirky and short, unlike what we're used to from Anthropic and OpenAI.
    by rohitpaulk
  • Agree that this is interesting/impressive, and the demos are nice.

    But I completely cracked up at the unexpected physical comedy of the woman in the "slouching" demo, haha omg that was comedy gold, no notes...

    I do appreciate less of that flavor of demo that we get from OpenAI/Anthropic, and more of this "human"-feeling vibe. Dare I go as far as calling this an example of "human-centered design" even (https://en.wikipedia.org/wiki/Human-centered_design)?

    by strgcmc
  • The noteworthy things to me are that the architecture is a transformer that takes in text, image, and audio input and produces text and audio output, all trained together, and it works in near real-time through interleaving inputs and outputs rather than pure generation of the output from a given prompt.

    > Time-Aligned Micro-Turns. The interaction model works with micro-turns continuously interleaving the processing of 200ms worth of input and generation of 200ms worth of output. Rather than consuming a complete user-turn and generating a complete response, both input and output tokens are treated as streams. Working with 200ms chunks of these streams enables near real-time concurrency of multiple input and output modalities.

    That's probably the main thing that distinguishes it from the multimodal models from other frontier labs as far as I can tell.

    by alyxya
  • > interleaving the processing of 200ms worth of input and generation of 200ms worth of output.

    How does this work? Don't LLMs/transformers need whole context to output next chunk of tokens?

    by throwaw12
  • What's really interesting for me about multimodal architectures from the ground up is that we might start to see applications where different modalities are "facets" of the same thing. Like a coding agent that sees "code" + "IDE" + "memory mapping" + feedback from different plugins as different modalities. And it gets to output in them as well - text where it needs to, actions (not <action>call_something(params)</action> like we have today) and so on. Being able to "sit still" until one of the modalities triggers is really interesting.

    We can do these things today, but they're "bolted on" as afterthoughts. Yet they work remarkably well. I wonder how well they'd work if trained int his combined regime, from the ground up.

    by NitpickLawyer
  • These videos are worth a watch. There are tons of impressive moments, but they had me at the very first one where a woman says: "I'm going to tell you a story," and then pauses for a long, luxurious sip from a cup of coffee, and the model ... does nothing, just waits. Take my money.

    Speaking of taking my money, what's the economic model for a company like this? They've published a fair amount about their architecture - enough that I imagine frontier labs could implement. Patents? Trade secrets? It's hard for me to understand how you'd be able to beat that training compute and knowhow at Anthropic/GOOG/oAI/Meta without some sort of legal protection.

    I can't wait to see what these model architectures do with like 30-40% lower latency and more model intelligence. Very appealing. For reference, these look to be roughly 1/10 the size of Opus 4.7 / GPT 5.x series -- 275B, 12B active. So there's lots of room to add intelligence, and lots of hope that we could see lower latency.

    by vessenes
  • hasn't the economic model always been enterprise llms?

    tinker - for fine tuning a custom enterprise model,

    interaction models - for working as a digital paired employee (as opposed to a company having to reinvent their entire process around ai agents)

    by htrp
  • they hire leading researchers, and leading researchers won't work for you unless they're able to publish
    by babelfish
  • In China it's become well known that promising new companies will get an offer from either Alibaba or Tencent. In the US, it's probably simmilar. Everything that's out in the open can get acquired or simply copied. Maybe that is what Thinking Machines is hoping as well?
    by edg5000
  • > They've published a fair amount about their architecture - enough that I imagine frontier labs could implement.

    i think the real ones know this is the tip of the iceberg? hparam tuning, data recipes, data collection, custom kernels, rl/eval infra, all immensely deep topics that would condense multiple decades of phd lifetimes to produce SOTA performance (in both senses of the word) like this.

    i would also calibrate what you are impressed by. simply waiting is a posttrain thing - the fact that gemini and oai have not prioritized it is not something you should overindex on as hard. what they showed with full duplex is technically far far harder to achieve

    by swyx