41–50 of 65 posts
We're still in stealth, but I'll be able to share details and performance figures soon.
Our first product is a bet on transformers. If we're right, there's enormous upside - being transformer-specific lets you get an order of magnitude more compute than more flexible accelerators (GPUs, TPUs).
We're hiring - if the EV makes sense for you, reach out at gavin @ etched.ai
I am not buying this at all. But I’m not a hardware guy so maybe someone can help with why this is not true: - Crypto hardware needed SHA256 which is basically tons of bitwise operations. That’s way simpler than the tons of matrix ops transformers need. - NVidia wasn’t focused on crypto acceleration as a core competency. There are focussed on this, and are already years down the path. - One of the biggest bottlenecks…
Nvidia has devoted an astronomical amount of effort to supporting AI as their “next big thing”.
…and here is some information-free landing page showing perf which is an order of magnitude above what nvidia is offering.
…but no numbers. You can get called out for numbers.
A vague infographic is much safer.
When things seem to good to be true, they usually are.
I guess some custom hardware with some cherry picked metric here, but frankly the whole thing screams scam.
If it was that easy, Amazon, Google, etc would have already done it with their proven ability to make new silicon.
I don't have a good scrollwheel, not easy to browse the site. :(
Yeah I call BS on this. This does nothing to address the main issues with autoregressive transformer models (memory bandwidth). GPU compute units are mostly sitting idle these days waiting for chip cache to receive data fr VRAM. This does nothing to solve that.
Founder here! We're still in stealth, but I'll be able to share details and performance figures soon. Our first product is a bet on transformers. If we're right, there's enormous upside - being transformer-specific lets you get an order of magnitude more compute than more flexible accelerators (GPUs, TPUs). We're hiring - if the EV makes sense for you, reach out at gavin @ etched.ai
1. Do you have a working prototype?
2. Are the pictures real (or close), or entirely CGI?
That would win over a lot of people here on HN.
Founder here! We're still in stealth, but I'll be able to share details and performance figures soon. Our first product is a bet on transformers. If we're right, there's enormous upside - being transformer-specific lets you get an order of magnitude more compute than more flexible accelerators (GPUs, TPUs). We're hiring - if the EV makes sense for you, reach out at gavin @ etched.ai
Founder here! We're still in stealth, but I'll be able to share details and performance figures soon. Our first product is a bet on transformers. If we're right, there's enormous upside - being transformer-specific lets you get an order of magnitude more compute than more flexible accelerators (GPUs, TPUs). We're hiring - if the EV makes sense for you, reach out at gavin @ etched.ai
Yeah I call BS on this. This does nothing to address the main issues with autoregressive transformer models (memory bandwidth). GPU compute units are mostly sitting idle these days waiting for chip cache to receive data fr VRAM. This does nothing to solve that.
Not exactly idle but only at around 30% utilization on average (measured on a ~900 GPU cluster over ~25 days)
interesting how MCTS decoding is called out. that seems entirely like a software aspect, which doesn't depend on a particular chip design? and on the topic of MCTS decoding, I've heard lots of smart people suggest it, but I've yet to see any serious implementation of it. it seems like such an obviously good way to select tokens, you'd think it would be standard in vllm, TGI, llama.cpp, etc. But none of them seem to u…
Founder here! We're still in stealth, but I'll be able to share details and performance figures soon. Our first product is a bet on transformers. If we're right, there's enormous upside - being transformer-specific lets you get an order of magnitude more compute than more flexible accelerators (GPUs, TPUs). We're hiring - if the EV makes sense for you, reach out at gavin @ etched.ai