ashu garg

Most companies are still in the equivalent of the cars-on-dirt-roads phase of AI. Early automobiles entered streets built for pedestrians and horses. The full gains of the car came later, when roads were paved, highways were built, and urban life was reorganized around the assumption of widespread car ownership. Today, AI is at the same inflection point. Individuals are moving faster, but faster individuals don’t automatically add up to a more productive company. It’s time to rebuild our processes from the ground up. More in my newsletter: ashugarg.substack.com/p/what-it-take…

I think this is an unfair and incorrect characterization of @narendramodi but I celebrate their right to do so. That’s what democracy and freedom of speech are all about!

I remember when people were saying "It's useless to open-source big models because nobody will be able to run them fast"....

Getting AI pilots into production is the real challenge. Without the real mess of real life and real users with unexpected inputs, pilots are almost always too pristine to matter. Knowing which use cases to pilot matters just as much as how you run them. To identify which AI use cases are ready to deploy, look for 5 things: bounded scope, high-quality data that’s easy to connect to models, a measurable and precise outcome, human judgment in the loop, and a workflow with significant cognitive repetition. If a business maps their use cases against these criteria, the ones that check every box will be obvious wins. More insights from Arsalan Tavakoli (co-founder of @Databricks) and Rajat Taneja (President of Technology at @Visa) at our recent CEO dinner in my newsletter: foundationcapital.com/ideas/what-it-…

@smehmood @jerrychen @bilalfarooqui @GreylockVC @cerebras at @FoundationCap by my partner @vassallo

@bilalfarooqui Palo Alto Networks at @GreylockVC

biggest vc incubated companies ever: - openai (yc) - snowflake (sutter hill) what else?

@dr_alphalyrae What is the definition of “non-transactional” ? IMO, in order to build a long lasting and deep friendship you need shared context and experiences. That can from a shared hobby or a shared professional interest possibly a mutual friend.

but seriously has anyone in the bay area figured out how to make net new, non-transactional friendships as an adult?

In April 2016, I threatened to climb over @andrewdfeldman's fence to give him his first term sheet for @cerebras. It was April Fool’s day, but I wasn’t fooling around. The story started in October 2007, when Andrew and his co-founder Gary Lauterbach had just started SeaMicro. Even then, Andrew was a force of nature. He was extremely intense and miswired in all the right ways. You could feel the sparks flying off him. We didn't invest in SeaMicro, but we stayed in touch. Andrew and the team built SeaMicro then sold it to AMD in 2012. When AMD acquired SeaMicro, I had a hunch Andrew wouldn't last long inside a big company. He has, as I've said many times, immense ambition and a heart full of disobedience. By early 2014, he was looking for an escape hatch. Over the next year and a half, Andrew and I met 6 or 7 times. Sometimes in our office. Sometimes at a coffee shop in Portola Valley. Sometimes at our local tennis and swim club. We kept coming back to one thing: deep learning workloads were growing exponentially, and traditional compute architectures couldn't keep up. GPUs had become the default for neural network training, mainly because researchers had accidentally discovered they were less terrible than CPUs. Andrew, Gary and Sean saw the GPU for what it was: a battlefield promotion of a chip optimized for graphics. Better than a CPU, but not what anyone would design starting from a blank sheet of paper. Their key insight was that memory bandwidth, not raw compute, was the real constraint on what neural networks could achieve. So Andrew, Sean Lie, Gary Lauterbach, Jean-Philippe Fricker and Michael James set out to do something nobody had pulled off in the 75-year history of semiconductors: Build a wafer-scale chip the size of a dinner plate. In April 2016, I asked Andrew if we could be his first term sheet. @ericvishria at Benchmark and I co-led the round along with Pierre Lamond from Eclipse. Then the hard work began. In the 75-year history of computing, no one had made wafer scale work. Which meant no one had ever had to solve the problems that came from trying. How do you power a chip that large? How do you cool one? How do you maintain electrical continuity across tens of thousands of connection points on a single piece of silicon? To get there, Cerebras had to invent in nearly every modern computing discipline at once: semiconductors, systems, data fabric, software, algorithms. Each was a startup in its own right. Their first wafer self-destructed on initial power-up and Andrew and the team were back in the lab the next morning, identifying what didn’t work and coming up with approaches to solving it. Yesterday, Cerebras went public. 19 years after our first meeting, 10 years after that April Fool's term sheet, they’ve built a generational AI company. From a coffee shop in Portola Valley to ringing the bell at the NASDAQ. What a journey. Proud to have been Andrew's first partner in Cerebras. Even prouder to call him my friend.

@cerebras @andrewdfeldman @vassallo More from Steve on a decade with Cerebras: foundationcapital.com/ideas/reinvent…

Today, @Cerebras rang the bell at NASDAQ. It’s a huge milestone for @andrewdfeldman and his co-founders, and for my partner @vassallo, who backed them at the very start. Foundation wrote Cerebras's first term sheet, and for the company's initial stretch, they set up shop on the second floor of our old office at 250 Middlefield. My favorite memory from those early years is watching Steve take walk after walk up and down Middlefield with early engineering candidates, selling them on Cerebras's vision and team. He believed in what they were building before most of the industry had caught on, and he showed up: not just in board meetings, but in the day-to-day work of helping a company come together, one hire at a time. I'm immensely proud to call Steve my partner. Congratulations to Andrew and everyone at Cerebras!

We founded @cerebras with a vision to forever change AI compute. Yesterday we went public on the @Nasdaq, an important step towards that goal. Today our AI super computer solution was the centerpiece of a collaboration between the Governments of the UAE and India. We are honored and humbled.

@saarth_ @cerebras @andrewdfeldman @vassallo 🙏

@ashugarg @cerebras @andrewdfeldman @vassallo Congrats guys!

@tanayj @cerebras @andrewdfeldman @vassallo 🙏

@ashugarg @cerebras @andrewdfeldman @vassallo congrats to the Foundation team!

@kevaldesai @cerebras @andrewdfeldman @vassallo 🙏

@ashugarg @cerebras @andrewdfeldman @vassallo So awesome!! Congrats to all!!

@nitinsharma1 @ericvishria @benchmark @FoundationCap 🙏

Today, @Cerebras rang the bell at NASDAQ. We wrote their first term sheet in 2016, when our partner @vassallo led Foundation's investment in @andrewdfeldman and his co-founders Sean Lie, Gary Lauterbach, Michael James, and JP Fricker. To get to wafer scale, Cerebras had to invent new approaches to nearly every facet of modern computing at once: semiconductors, systems, data fabric, software, and algorithms. Each was a startup in its own right. Realizing this mission took ten years of relentless engineering. Congratulations to Andrew and the entire Cerebras team! More from Steve on a decade with Cerebras: foundationcapital.com/ideas/reinvent…

So excited to see @Cerebras go public. What an amazing journey. I'm so proud of my partner @vassallo who backed the team from day one. The story is just getting started!