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Introducing System One Models and Jev

typesafe.ai

251–260 of 512 posts

Re: Introducing System One Models and Jev

#251

Earlier quoted context omitted.

I'm biased but I wouldn't call it misleading - generating text is super awesome and flexible, (we describe that in the blog post - and I personally use string models all the time) but it's true you pay a high tax for autoregressive generation > Also "can't hallucinate" seems wrong? Sure, it can't emit an invalid type, but it can still emit a completely wrong valid value. that is likely true of all ML! perhaps we coul…

From a quick look at this it looks like it could easily generate natural language text by following a structured representation like UMR (Uniform Meaning Representation) or the similar representation the Abstract-Wikipedia folks will be working on for generic encyclopedic text (which will be heavily informed by Universal Dependencies). These are basically linguistically principled and frame-based counterparts to a pr…

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Re: Introducing System One Models and Jev

#252

Earlier quoted context omitted.

I dunno, I would consider Waymo and Tesla to have frontier models. I think AlphaFold and related are also frontier models. Being an LLM does not seem like the qualifier for frontier.

This is likely still an LLM (in the purest definition of a language model with relatively many parameters) since the inputs are natural language, just not a generative LLM as the output is something other than more language.

The inputs aren't natural language. https://docs.typesafe.ai/primitives

Re: Introducing System One Models and Jev

#253

This sounds good but so far all claims just sound like marketing terms. I'd love to see real proof. e.g. "RLCD" and "parallel sampling" have nothing to back it up. also "70-500ms vs 3-329 seconds" are apples-to-oranges unless the LLM baseline is doing comparable work (e.g., long chain-of-thought). If Jev is skipping generation entirely for a narrow structured task, of course it's faster. Nonetheless i want this to be…

> I really have to say that I like their manifesto

Their manifesto: "you only build on top of it if it's trustworthy." - the irony of this while putting out the most misleading, dishonest marketing campaign I've seen in months for their first public appearance doesn't exactly scream "trustworthy" to me.

Re: Introducing System One Models and Jev

#254

The Doom demo looks impressive but was it a fine-tuned model? It's the difference between a cool demo and revolutionary tech.

Shouldn't self-driving be a piece of cake if it works this well for Doom? Or what am I missing?

Driving is more complicated than Doom, and it doesn't look that great at Doom to me.

Re: Introducing System One Models and Jev

#255

I would love for things like this to be accessible via hubs like open router or AWS bedrock. It's hard to justify adding new model vendors directly with all the heightened concerns about privacy and security, but if bold new capabilities are added to a centralized already-vendor like AWS, technical people can adopt them without going through a whole compliance/purchasing/vendor review process. And an extra middleman…

I think the trouble is that Typesafe APIs don't fit into the normal OpenAI-style API that every other regular LLM provider users. You're not just providing unstructured text and getting unstructured text back. It would take a different request and response format than every other model on Open Router. Though you could shoe-horn it in some way, it'd be hacky.

But agreed it'd be very useful to see it deployed on other hubs, and it seems worth it to provide the bespoke API format. Perhaps Typesafe's API will end up becoming the standard for a new type of structured model, the way OpenAI's API did.

Re: Introducing System One Models and Jev

#256

This sounds good but so far all claims just sound like marketing terms. I'd love to see real proof. e.g. "RLCD" and "parallel sampling" have nothing to back it up. also "70-500ms vs 3-329 seconds" are apples-to-oranges unless the LLM baseline is doing comparable work (e.g., long chain-of-thought). If Jev is skipping generation entirely for a narrow structured task, of course it's faster. Nonetheless i want this to be…

> I really have to say that I like their manifesto Their manifesto: "you only build on top of it if it's trustworthy." - the irony of this while putting out the most misleading, dishonest marketing campaign I've seen in months for their first public appearance doesn't exactly scream "trustworthy" to me.

What do you find dishonest?

Re: Introducing System One Models and Jev

#257

I would love for things like this to be accessible via hubs like open router or AWS bedrock. It's hard to justify adding new model vendors directly with all the heightened concerns about privacy and security, but if bold new capabilities are added to a centralized already-vendor like AWS, technical people can adopt them without going through a whole compliance/purchasing/vendor review process. And an extra middleman…

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Re: Introducing System One Models and Jev

#258

There's a whole lot of information on this page that doesn't tell me anything about what this actually is. Can anyone spell out what the architecture is here? They claim it's not an LLM, which I read as "not an auto-regressive token generator". I assume they are still using a transformer, otherwise they would be talking about the thing that's not a transformer, instead of all the fluff on the linked page. But they em…

I would guess a tiny stripped down text diffusion model. It only has 32k context, and for choice mode it can only select from 10 choices.

Re: Introducing System One Models and Jev

#259

> [others] Output tokens: ~5x more expensive than input tokens. > [them] Output tokens: FREE (too cheap to meter). I'm very confused by this.

The output tokens are just responses to your inputed questions and their probability. So relatively few output tokens. No unstructured text back in the response.

Re: Introducing System One Models and Jev

#260

Doom demo is beyond impressive, even scary

It's very misleading. If I'm actually playing a game I don't get the coordinates of enemies sent back to me so that I can feed into my mouse to snap my crosshair to. It's looking through walls too, because it's working off structured state in text form. You could re-create this whole demo without using AI. Have an LLM generate the state machine for you and no model is required to run it.
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