Anyone have any idea what the architecture/vendors they are using for inference/compute?
Getting the compute to run inference for multi-trillion parameter models at any sort of scale and performance is daunting. There are a handful of vendors that have systems that can do this (~ Nvidia NVl-72 class) that pretty much only the frontier labs and hyperscalers effectively have access to.
That statement means nothing. You could say the exact same thing about Rails and have an equally defensible position. What about its architecture makes it better?
Apple was on the USB Implementers Forum that designed USB-C so.. I would say they could definitely be credited as a co-inventor of USB-C, they also introduced one of the first devices that used USB-C.
There are some studies that suggest human brain sizes have been shrinking over the last 20,000 years. The theory is that as civilization developed the demand for individual humans to be independently intelligent has weakened because we developed a "collective brain" and also self-domesticated to be more cooperative.
We use headless browser providers because the companies we interact with don't and won't create a proper API for us to use. Lots of legacy web apps/portals. Saves thousands of man hours.
Everything is obvious in hindsight, but the data (and theory) at the time was that this had a really good shot at being the next big thing in a world where >90% of drugs never make it past clinical trials. 10% probability of success * $200B in lifetime sales (assuming a Keytruda level smash hit) means an EV of ~$20B or more. Not a surprise more than a few companies wanted a shot at it.
How so? Most of these companies will take a hit but will be fine Alphabet, Amazon, Google, etc can write off their entire investments in AI and will be a-OK. The pure AI companies will obviously be dead.
What do you mean? Pandoras box has already been opened. Even if OpenAI disappears, there will be another one to take its marketshare. The tech is too useful to die
Absolutely dumb take. There are plenty of very bright and talented people that would have made excellent teachers but chose different career paths because - surprise surprise - the pay is better.
Getting the compute to run inference for multi-trillion parameter models at any sort of scale and performance is daunting. There are a handful of vendors that have systems that can do this (~ Nvidia NVl-72 class) that pretty much only the frontier labs and hyperscalers effectively have access to.