Jonathan Ross

Jonathan Ross

@jonathan-ross.bsky.social

CEO + Founder @ Groq, the Most Popular API for Fast Inference | Creator of the TPU and LPU, Two of the World’s Most Important AI Chips | On a Mission to Double the World's AI Compute by 2027

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What can you do with Llama quality and Groq speed? Instant. That's what. 3 months back: Llama 8B running at 750 Tokens/sec Now: Llama 70B model running at 3,200 Tokens/sec We're still going to get a liiiiiiitle bit faster, but this is our V1 14nm LPU - how fast will V2 be? 😉

Jonathan Ross reposted

Founder Tip #2: You have to spend time to make time. Hiring, re-organizing, calendar clean up (across the team), preparation for meetings (internal and external), etc. Half my day is available for whatever I find important - because the other half is spent freeing up time.

Clearly China doesn't have enough compute for scaled AI today: - GPT-OSS, Llama [US]: optimized for cheaper inference - R1, Kimi K2, Qwen [China]: optimized for cheaper training With China's population reducing inference costs is more important, and that means more training.

I spent the weekend hanging out with a group of friends. A question we asked was what dreams did we have that we gave up on? When I was 18, I had two dreams: 1) Be an astronaut 2) Build AI chips I didn’t give up on one of them. 😀

Jonathan Ross reposted

Big news! Mistral AI Saba 24B is on GroqCloud! The specialized regional language model is perfect for Middle East and South Asia-based devs and enterprises building AI solutions that need fast inference. Learn more: groq.com/mistral-saba...

hubs.laMistral Saba Added to GroqCloud™ Model Suite - Groq is Fast AI InferenceGroqCloud™ has added another openly-available model to our suite – Mistral Saba. Mistral Saba is Mistral AI’s first specialized regional language model,

It was a pleasure being back on 20VC with Harry Stebbings. His craft of interviewing is second to none and we went deep. This is the interview after we just launched 19,000 LPUs in Saudi Arabia. We built the largest inference cluster in the region. Link to the interview in the comments below!

We built the region’s largest inference cluster in Saudi Arabia in 51 days and we just announced a $1.5B agreement for Groq to expand our advanced LPU-based AI inference infrastructure. Build fast.

When you make compute cheaper do people buy more? Yes. It's called Jevons Paradox and it's a big part of our business thesis. In the 1860s, an Englishman wrote a treatise on coal where he noted that every time steam engines got more efficient people bought more coal. 🧵(1/5)

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Over the last 60 years, almost like clockwork, every decade compute gets about 1000x cheaper, people buy 100,000x as much of it, spending 100x times more overall.  Our mission at Groq is to drive the cost of compute towards zero;The cheaper we make compute the more people spend. 🧵(4/5)

When you make compute cheaper do people buy more? Yes. It's called Jevons Paradox and it's a big part of our business thesis. In the 1860s, an Englishman wrote a treatise on coal where he noted that every time steam engines got more efficient people bought more coal. 🧵(1/5)

- The answer is when you make a steam engine more efficient, it reduces the OpEx; - When you reduce the OpEx, it increases the number of activities that are profitable; - Therefore, people will do more things using steam engines and coal demand rises. The same paradox applies to compute. 🧵(3/5)

This is insane, Groq is the #4 API on this list! 😮 OpenAI, Anthropic, and Azure are the top 3 LLM API providers on LangChain Groq is #4, and close behind Azure Google, Amazon, Mistral, and Hugging Face are the next 4. Ollama is for local development. Now add three more 747's worth of LPUs 😁

(1/5) One of the reasons why chips are so hard to innovate in is because if you're asking someone to put up a 10 million, 100 million, or a billion dollar check they need to know that what they're buying is going to work.

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(1/5) One of the reasons why chips are so hard to innovate in is because if you're asking someone to put up a 10 million, 100 million, or a billion dollar check they need to know that what they're buying is going to work.

(2/5) That makes it almost impossible to do counterintuitive things. Like, “Try this new chip called an LPU", when everything in the zeitgeist is talking about GPUs. And if you're a startup? Forget it. That realization is why we made the strategic decision to put up our own cloud.

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(4/5) It's also significantly less expensive and faster than the larger model. Meta continues to push the lead in open weight innovations, and is keeping the pressure high for proprietary model providers to attempt to keep ahead of the giant wave of open.

(5/5) The new Llama-3.3-70B model launched and is now available to all 645,000 GroqCloud™ developers as of this morning. Go cook, and don't forget to share what you build here. Thank you for making GroqCloud™ the #1 API for fast inference! This is only just the beginning.

(2/5) Today, our partner Meta released its latest version of Llama-3.3-70B-Instruct. And to all those who speculated that the industry had hit the wall - maybe some have, but Meta hasn’t yet. 😉 This is a big deal.

(3/5) Though ~1/5th the size of Llama 3.1-405B, benchmarking shows Llama-3.3-70B performing neck and neck, and in many crucial cases substantially out performing the larger model (Instruction Following, Coding, Math, etc.), a suitable replacement for a majority of workloads.

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(4/5) When you look at something that's rapidly becoming that grand, that vast, and that capable it makes you feel small and afraid. Over time we've gotten used to this idea that the universe is large and that we're small. If anything we now see the beauty in how vast the universe is.

(2/5) He got in trouble because he made a telescope, pointed it at the stars, and using data from other astronomers he put together a pretty convincing case that human beings weren't the center of the universe. They locked him in a tower.

(3/5) They did that because they were afraid. If people weren't the center of the universe that made us feel small. Large language models are the telescope of the mind. They give us this view of an intelligence that is quickly becoming larger and more vast than any single human being.

(1/5) Everyone at Groq has one of these challenge coins on them. It’s how we create alignment. One side says its 25 million, because we're going to get to 25 million tokens per second by the end of the year On the other side, it says, “Make it real. Make it now. Make it wow.”

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(4/5) The reason for that number? 25 million? If we do 25 million tokens per second then we're going to have as much compute capacity as a hyperscaler had at the start of this year. And from that point forward, we'll just ramp.

(5/5) That's why we expect that by the start of next year, we will be one of the most significant players in our space. And by the end of next year, we will provide more than half the world's generative AI inference compute.

(1/5) Everyone at Groq has one of these challenge coins on them. It’s how we create alignment. One side says its 25 million, because we're going to get to 25 million tokens per second by the end of the year On the other side, it says, “Make it real. Make it now. Make it wow.”

(2/5) Okay fine, cute prop. But how does a challenge coin create alignment? Well, if someone makes a proposal and it doesn't help with these priorities, anyone can just put their coin on the table and ask “how does it help with this?”

(3/5) It may sound silly to distill our north star down to such a simple message but that is the hardest part about leadership. Getting alignment is finding that singular thing, that if you do it well, you're going to be successful.

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