OpenAI is exploring making its own AI chips

Note Sam Altman is a Cerebras investor.

Given the cost of gpus it would be negligent if they weren’t at least looking for alternatives. A story like this could also help negotiate prices with their suppliers. And everyone is looking at the success Apple had with custom silicon. But I suspect they’d prefer to partner or find alternative (cheaper) suppliers

It’s interesting to think, when a company starts to vertically integrate, how deep do you go?<p>Seems like OpenAI is exploring its own devices&#x2F;OS as well, which makes sense to me, but it’s a vertical integration bet. This seems to be another big bet, but they could benefit from having their own optimized chips regardless of whether the device&#x2F;OS bet wins out.<p>Extremely exciting times for OpenAI!

This makes a lot of sense. When ChatGPT initially broke the mold, I was hoping someone would find a way to repurpose all the silicon the crypto-bros&#x27; nonsense has commandeered -- alas, the problems are too different.<p>Making specialized chips to run LLMs is the logical next step.

It means Microsoft is involved too. From consumer perspective, following the performance of Apple silicon, I am excited for this news.

Meta was rumored to want to layoff its chip fab team for VR. I wonder if OpenAI will work out a deal with them.

When building out an initiative like this, how do companies avoid IP issues? They are looking to build technology that competes with the best in class to make it worth the effort without having to reinvent the wheel.

My guess is that this leak is in response to the announcement from Anthropic that they will be using Amazon&#x27;s custom AI silicon.

This is not answering question, on what OpenAI will earn money. As even using only Nvidia chips, industry need somewhere gather ~$1000B (half of this is OpenAI share now), but with custom chips will be at least 3-4 times larger numbers.

The economy is in an interesting place when in house chip making efforts or startups are popping up now. It used to be a task like landing on the moon. Still a difficult effort but it looks like this industry is expanding. It speaks to the rapid nature of technology in general where insurmountable tasks over time become closer to trivial.

I said a while back that I expect the major cloud vendors (Azure, AWS, GCP, etc) to start trying to develop their own chips for AI work. Google already does to some extent with their tpus. At the very least, this is saber rattling trying to convince nvidia to lower prices.

I think that endgame for generative language models is models embedded directly into chips. Computers that run english language instead of machine code and for which CPU, GPU and what is currently known as PC is more like a peripheral IO device.

Am I the only person who thinks OpenAI just doesn&#x27;t know where to go from here?

I was just thinking the inference cost could be reduced by making hardware with less error correction in specific areas to get higher density, and let the NN work around the limitations.

As soon as the investors and boardmembers realize that chips mean &quot;hardware design&quot; they will quickly put an end to any of these efforts.

Wish I could buy stock in Tenstorrent.

Masayoshi Son is funding them so you know they’re gonna lose a ton of money

I&#x27;m so tired of all this vertical integration.<p>Can&#x27;t we have hardware companies that make hardware, software (AI) companies that make software, and data companies (or government institutions) that run the software on the hardware and deal with our data?

they should also buy reddit