I would've hoped the company stayed independent instead of being engulfed into a behemoth. I'd like to see more diversity in the hardware ecosystem, but I guess the economics of hardware manufacturing aren't there.
AMD acquires Taalas to boost inference performance by etching models in silicon
311–320 of 712 posts
Re: AMD acquires Taalas to boost inference performance by etching models in silicon
#312I've been eagerly awaiting their 2nd gen HC2, which uses multiple chips to host a "mid sized reasoning" [1] model. Its due in summer according to the article, I wonder if it will ever be released in that form now.
[1] https://www.forbes.com/sites/karlfreund/2026/02/19/taalas-la...
Re: AMD acquires Taalas to boost inference performance by etching models in silicon
#313Earlier quoted context omitted.
People already buy new phones every year, this just creates even more reason to do so
Your location/income bias is showing. Most people do not buy new phones every year.
I live in the bay area and buy a phone maybe every 3 years? Why do people waste so much money :D
Re: AMD acquires Taalas to boost inference performance by etching models in silicon
#314Earlier quoted context omitted.
I don't think this works out from a cost/silicon perspective. Small models already run pretty well in software (since the weights fit in cache) and big models require silicon area proportional to the size of weights. On a mobile device putting a chip like this is competing directly in BOM and power against a whole lot more l3 cache, and the l3 cache makes everything faster
What, even if it means you can run models without relying on the currently backlogged DRAM production?
The size of model we're talking about running doesn't need much if any dram.
Re: AMD acquires Taalas to boost inference performance by etching models in silicon
#315Earlier quoted context omitted.
If it is capable today why would a new model change this?
I think it’s tongue in cheek. When I first got access to Sonnet 4.5 I remember thinking to myself “y’know if they never got any better and I just had access to this forever then that would be pretty okay”. Turns out my expectations have changed since then and I would like a higher baseline now.
Interesting. I've yet to find a model I consider sufficiently intelligent.
Fable is nice, but still requires a lot of guidance for large scope tasks.
Re: AMD acquires Taalas to boost inference performance by etching models in silicon
#316Earlier quoted context omitted.
Considering the rate of model development and rail hopping, seems like baking models into silicon is speed-running obsolescence.
Depends on how much it costs the consumer. If I could buy a "cartridge" of Kimi K3 for 300 bucks I 100% would buy that shit asap. Even if it's "no good" after lets say 4 months still would be worth it IMO.
That's definitely super-enthousiast territory. Paying 80 bucks a month for AI is more than 99.99% of people would be willing to do
Re: AMD acquires Taalas to boost inference performance by etching models in silicon
#317Re: AMD acquires Taalas to boost inference performance by etching models in silicon
#318Earlier quoted context omitted.
My question is what changes about LLM use cases when you’re getting 1000 tok/s? Models in silicon might dramatically change how we think about them.
Did you use chatjimmy? It's somewhat terrifying to use when you think of the potential results with a better model. Ok, real life example: I now spend most of my time, as a developer, waiting for the agent to do its thing (after careful prompting, I'm also thinking about work stuff, don't worry I'm not useless). What if it gave back the same excellent results, but instantaneously? Why, then, I certainly would become…
> I now spend most of my time, as a developer, waiting for the agent to do its thing (after careful prompting, I'm also thinking about work stuff, don't worry I'm not useless).
you need to launch 10-15 more terminals, who is waiting these days? :)
Re: AMD acquires Taalas to boost inference performance by etching models in silicon
#319I've had an endgame idea in mind for a while. Models, probably first open weight ones like Kimi K3 class, are etched into silicon like this and sold as cartridges almost like old school game cartridges. You buy a USB-C dongle that the cartridge goes into, or for data centers you have PCI cards that take these in slots.
Each cartridge costs $1,000. Do you still want it?
Yeah. I have 3 max20 plans.
Re: AMD acquires Taalas to boost inference performance by etching models in silicon
#320Earlier quoted context omitted.
I'm not sure inference speed is always the slowest thing for me right now. The agent is running tests, loading webpages, etc, which all take time. I don't know if a fast agent would speed things up in all cases. That said, it obviously depends on the project.
> " The agent is running tests, loading webpages, etc, which all take time " A frustrating vision of the future would be when we've been asking for faster loading lighter web pages for years and then companies start caring about it and improving it not for us humans but for LLMs.
It's already kind of that way with MCP servers popping up everywhere. The JIRA MCP server is like a couple orders of magnitude faster to work with than the website itself.