Ayush Ranjan (@gpuayush) header
Ayush Ranjan (@gpuayush) profile picture

Co-founder @huddle01com

San Francisco, CA
Joined July 2012
Photo by Ayush Ranjan (@gpuayush)Photo by Ayush Ranjan (@gpuayush)Photo by Ayush Ranjan (@gpuayush)Photo by Ayush Ranjan (@gpuayush)Photo by Ayush Ranjan (@gpuayush)Photo by Ayush Ranjan (@gpuayush)Photo by Ayush Ranjan (@gpuayush)Photo by Ayush Ranjan (@gpuayush)Photo by Ayush Ranjan (@gpuayush)
Ayush Ranjan retweeted
The benefits of abundant intelligence will accrue far outside of San Fransisco. Spent the last year writing about capital, sovereignty, and the coming reordering of economic power. THE COMMANDING HEIGHTS Commanding-Heights.com
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Ayush Ranjan retweeted
Life is Short — How to Add a Sense of Urgency
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Ayush Ranjan retweeted
Binance crypto hacked. AI bubble popped. Gold being created in a lab. Everybody loses. Thanks for playing.
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Ayush Ranjan retweeted
Energy first, then compute. @ChaseLochmiller, co-founder and CEO of @CrusoeAI is building a lot of the data centers that power the age of intelligence. They just closed a round at a $31B valuation, about 8 years into a company that started as two guys burning flared gas in the Bakken oil field to mine Bitcoin. That wasn’t a pivot, btw. Chase was AI-pilled early. The bet was: if data and compute are the bottleneck, compute becomes an energy problem. So instead of bringing stranded energy to a market, bring the market to the energy. Bitcoin was the easiest way to turn electrons into money while he waited for AI demand to show up. It showed up on November 30th, 2022. He’s a learning machine. On track to be a professor, then a quant, then Everest, now running a 2,000+ person vertically integrated business with welders and AI researchers in the same company. A few things we get into: •Why Crusoe is an AI supermajor: upstream (power), midstream (data centers), downstream (AI cloud). Exxon famously doesn’t hedge oil because the stack hedges itself. Margins move around the stack; own the whole thing.

 •“Most startups die from suicide, not homicide.” We said the exact same thing at HubSpot. If someone else is chasing your opportunity, that’s a compliment.

 •Coopetition. He’ll partner with companies he competes with elsewhere.  Useful when you’re building infrastructure the entire industry needs.

 •The CEO journey isn’t linear. “As soon as I’m sick of hearing myself say something, we’re just scratching the surface.”

 •How he scales himself: a domain expert owns each vertical. Energy, data centers, manufacturing, AI cloud. He goes deep enough to get aligned on direction and understand how it connects to the rest of the business. Then he holds them accountable to execute. Alignment first, then trust with accountability.

 •Should every CEO hire a coach? Yes. His coach was as much therapist as coach, and it was critical for him and the company. We get into that more. •People scale linearly, companies scale exponentially (h/t First Round). When you start thinking about letting someone go, that was probably the right time.

 •Actively hunt bad news. Good news is nice, but the CEO’s job is to “run into the burning buildings,” find what’s broken, and fix it.

 •Selling the Bitcoin business to NYDIG while it was making money. One word: focus. •The data center backlash. “The industry has a marketing problem. The truth is on our side.”
 Timestamps: 0:00 – Cold open 1:10 – Intro 1:35 – Professor, quant, Everest, energy, data centers: is there a throughline? 2:43 – What people get wrong about the CEO journey 3:53 – Live on the infinite growth loop 4:44 – “My biz is becoming dizzyingly complex beneath me” 6:44 – Scaling yourself with domain experts 7:36 – Trust, DRIs, and not being hands off 8:33 – Cross-org execution and the weekly staff meeting 10:11 – “As soon as I’m sick of hearing myself say it” 11:37 – Keeping urgency at 2,000 employees; the Elon tension 13:12 – Books, mentors, and a coach 15:12 – Most startups die from suicide, not homicide 16:50 – Paranoia and coopetition 17:26 – The AI supermajor: upstream, midstream, downstream 19:47 – Propeller, Blue Energy, and energy first 23:24 – Flared gas, Bitcoin, and bringing the market to the energy 24:45 – Wait But Why, Andrew Ng, and compute as an energy problem 28:52 – November 30, 2022 30:19 – Selling the Bitcoin business: focus 32:43 – Polish is learned: public speaking and Shane Metcalfe 34:31 – Should every CEO hire a coach? Yes. 37:54 – Hire slow, fire fast, and reading the mosaic 41:09 – Ali Ghodsi vs. Dev Ittycheria on exec turnover 42:51 – AI researchers and welders: the collective genius 44:15 – The data center backlash and the marketing problem 48:53 – Thick skin and speaking truth to power 51:09 – Everest: the 2014 avalanche and the Khumbu Icefall 55:12 – The Balcony and the summit 57:36 – My takeaways
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Today, we're shipping real-time graphics. Using Sol 6.1 Ultrafast we can generate custom overlays, diagrams, and even interactive 3D scenes right on a user's screen, no chat. It's a new visual interface for AI. Here's me learning about LLMs + hardware. Demo:
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Ayush Ranjan retweeted
phunk is live 🫡 find your old frens on @farcaster_xyz, meet new folks since Farcaster changed hands on Oct 15, people are spreading across clients. phunk makes sure you don’t lose the ones you vibe with follow + like right in the feed, casting soon try it: phunk.social
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Ayush Ranjan retweeted
Neurotech is Humanity’s Next Frontier! I’ve been investing in neurotech since 2021 and working with teams building BCIs, NeuroAI, and connectomics. It now feels like AI did in ~2019. We are entering an extraordinary era: neurotech already restores functions, it can enhance our capabilities, and will evolve what it means to be human. PLC Neurotech is the fund backing the extraordinary founders and defining companies of this booming industry.
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negative thinking destroys your brain being a silly goose and delusionally optimistic is the ultimate longevity hack
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Ayush Ranjan retweeted
CONGRATS Anthropic on their S-1 filing! Unsurprising, but first observations: inflection in operating profit, strong emphasis on novel discovery/bio, mismatch b/w consumption based revenue and long term compute obligations, limited shareholder influence. a lot of case studies!
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Ayush Ranjan retweeted
Neoclouds that are able to lock in forward compute prices in derivatives markets will be able to get financing as long as they have a credible track record of execution.
Replying to @chamath
Pretty much. As of the past few weeks, debt markets have almost entirely shut off access to money for any company that doesn’t have substantial revenue independent of AI data centers. SpaceX closed $40B of debt for GPUs, but we’re investment grade and have Starlink & launch revenue. That means the 200+ neoclouds are going to see guppy-level death and consolidation. Some will make it through, but not many.
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Ayush Ranjan retweeted
There is an absolute barrage of inference providers popping up that get to $1M/mo extremely quickly. This is the rough economics of inference providers: Even if you rent on-demand B300s at $8/GPU-hr, many open source models (GLM 5.3, Kimi K3, DeepSeek 4.1 Flash / Pro) can get you >$10-20/GPU-hr at reasonable throughputs (100tok/s). DeepInfer from DeepSeek directly shows they can get $38/GPU-hr on off-peak hours. Every chip / model has a different throughput / interactivity curve, but there is a lot of arbitrage between even high rental spot prices and token prices. New chips (Vera Rubins) also change this meaningfully. Your ability to be making gross margin relies on your utilization and how good your stack is. Gateways like OpenRouter, Vercel and more help solve that problem by aggregating demand to you. May inference providers discount their tokens to get longer term commits too. I've even heard stories of selling back Chinese model tokens to Chinese labs! One thorn in the economics of these players is that many Chinese open source model labs are now asking for rev share if you're at a certain scale, espp for pre-release access to their models for day 1 support. That further pushes the threshold to be in the money. The barrier to entry seems low and falling. There are even stories of smaller ones who can "vibe code" a way to stand up OSS models on a cluster they rent. And as a result, we're seeing 10s of such companies pop up almost every week and immediately skyrocketing revenue at low-ish gross margin and raising rounds on the back of that. Unsurprisingly, because the actual service provided seems commodity, this eventually drives up compute prices and drives down token prices. In theory, it would seem like neoclouds who have the lowest cost of compute and themselves have started inference businesses would win the race to the bottom (Crusoe Coreweave Nebius and GMI all have inference businesses), with larger players (Modal Fireworks Baseten) being second because they are well capitalized to make bigger compute commits cheaply and have demand (high utilization), but the reality is the pie is growing so quickly that even upstarts are absolutely crushing it and growing aggressively (inference dot net, DeepInfra, Wafer, Relace, Morph). Strategies vary across the board: neoclouds want to serve inference, inference players want to be neoclouds and do higher margin reserved instances / post training, and some want to go heterogeneous hardware or creatively flexible compute constructs. The risks are: do open source models continue to be competitive? Will their creators rent seek more? Will their shape change compute needs? How do different chips change economics? Who gets compute in a supply crunch? Below is a aggressive sketch of how gross margin scales with utilization for various models / chip sets. For now, there are many inference providers and they’re all ripping!
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Ayush Ranjan retweeted
When is the ChatGPT moment for robotics? Some say it's happened, some say it's coming. How capable are Physical AI models today? What does the adoption curve for robotics look like? We've talked to most of the major players and make sense of it here robostrategy.co/news/the-cha…
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Ayush Ranjan retweeted
Lifting weights is a long term investment in your mental health.
Lifting heavy things will do wonders for your mental health.
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Ayush Ranjan retweeted
Goldman buy thesis on $CRWV
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Ayush Ranjan retweeted
Big personal news today: I have decided to leave @a16z, move to SF, and start a company. It's time to build :) It has been almost 10 years since I joined the firm. I met @cdixon, @bhorowitz, and @pmarca in 2017. At the time, I was an engineer at Google Brain working on robotics. I had a deep interest in open source. I knew nothing about investing. Chris meanwhile had already planted the @a16z flag at the frontier that was early crypto with investments in companies like Coinbase. But the crypto team at the firm consisted of only him, and he had the ambition to expand. His pitch to me was simple: "You should leave Google and come help me build the crypto vertical at the firm." The work we've done together since then to build out our team and support our founders has been the most meaningful work of my life. I am grateful to have spent a decade working with everyone here, supporting our founders, learning from Chris, Ben, and Marc, and living the firm's culture. It is a culture that values integrity, life-long working relationships, and the belief that we humans have the power to build our own future. Marc and Ben have built a16z into an incredible force for good in the world. Before I joined the firm, I always thought that my inevitable path was to become a founder. The truth is that I wasn't ready for it then. Somehow, this year I've gotten the overwhelming feeling that this has changed. As for what I want to build: It is early, but I care most about building infrastructure that enables open software ecosystems. I am starting with two core observations: 1. AI today is largely a single-player technology. Most uses involve one human talking with one agent in isolation from the rest of the world. That will soon change. Most uses of AI will soon be many-to-many: many humans and many agents working together. There will be at least one massive open network on top of which those uses will be built. 2. Software is now free. It can now be written just-in-time, on the spot for a single individual's hyper-targeted use case, and it can even be thrown out after a single use. This means that our entire software stack will have to change. In the limit, it will lead to a whole new kind of AI-mediated operating systems, which in turn will create an ecosystem of AI-native developers who build applications that actively rebuild themselves on the fly. If you are working on related ideas, and especially if you are in the Bay Area, hit me up. Let's chat! @bhorowitz , @pmarca, @cdixon, @eddylazzarin, @guywuolletjr, @jasonrosenthal , and our whole team — I want to thank you. Working with you has been the time of a lifetime. I am forever an a16z superfan and your ally. Onward 🫡
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Last month, we demonstrated high-rate alchemy: turning mercury into real, stable gold, beating CERN’s record by a factor of 10. Last week, we enriched isotopes in the world’s most powerful plasma centrifuge, beating the Soviet record that stood for 40 years. Now, we’re building a fusion reactor in San Francisco to achieve record power density.
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Ayush Ranjan retweeted
if you're wondering how dire robotics manufacturing in the US is: in the last 2 months there have been 3 robotics startups launch that just wrap a Unitree G1
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Ayush Ranjan retweeted
Elon Musk says blaming difficulty of bringing massive AI compute online on a "lack of electricity" is an oversimplification because power, memory, networking, cooling and construction all need to come together. Real advantage is shifting toward companies that can actually deliver working compute rather than just announce more data centers.
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