Core Automation is a deep learning research company with a mission to build systems that automate and optimize work

San Francisco, CA
Yeah
This list loses credibility by putting Riley Walz on the same scale as normal cool people. Everybody else here is awesome, but not at all the same. Its like Forbes 30u30 when they have Elizabeth Holmes and then 29 other people. They should make his image 2x as bigger and maybe add a rainbow chromatic shader behind him.
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Superior Learning
How should we rebrand learning that’s actually deep?
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How should we rebrand learning that’s actually deep?
13% Deep deep learning
27% Really deep learning
31% Superior learning
29% Deep learning for real
225 votes • Final results
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Core Automation is a deep learning research company with a mission to build systems that automate and optimize work
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A decade of learning the hard way. No pain no train 🚝
Bit more than a decade in training, no pain no train. 💪 @BEBischof nerd sniped me into this talk with offer to have a Cat to give the keynote. Still Training: A Decade of Learning the Hard Way @ Reverie by LanceDB on Nov 5 in SF 🌉 You get to hear me about distributed training from the trenches: Hardware codesign, async and sync training -- when we almost decided to put async into chips From big batch gradient descent with parallel boosting from stochastic optimization with duals to online learning where we had regrets, to higher order methods that scale that was almost second order that nobody believed it.
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Core Automation retweeted
Everything is Automation
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Dang. @coreauto has a great team
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Mood
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Is it 📈📈📈 or 📉📉📉 ?
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Wait until you hear what agents found when reading Rohans slack post. It reinforces the message how special it is to be in a place where alpha is generated.
The more interesting thing I have heard this week is that folks at some labs are mining alpha from my posts, and having their agents work on it. It seems like a great idea, so I am starting to do that as well.
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Long term research done on short term timelines
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Free will is in the softmax
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Power of friendship
choose a lab where you genuinely like the people if they're sufficiently agent-pilled you'll mostly be hanging with them while agents work
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Creativity, Inc in the age of AI
Some news: 5 months ago I joined @coreauto, a small research lab focused on new ways for models to learn. I’m also hiring four interns to do something my younger self would've loved. It started with a pretty unusual project. We set up a handful of small online businesses, and put an agent in charge. We gave each business some initial funding and a seed idea, and off they went, trying to sell real things to real customers while we watched. It’s about as open-ended and unforgiving a task as you can probably give to an agent, with countless decisions to make and effects that take time to become clear. Each business got its own bank account, a debit card to pay suppliers, a web browser, an email inbox, a domain name, cloud infrastructure and a schedule. Every few hours, the agent woke up and decided what to do. It might update a landing page, adjust an ad campaign, reply to a customer, and then go back to sleep. The agents built actual storefronts and apps. They bought ads, attracted visitors, and even made some sales. The agents acted as operators that kept a business moving, but we noticed they never really stepped back to strategize about what might move the needle. If people weren’t buying, why? Was the landing page unappealing? Or maybe the offer itself was the problem? One amusing example was the very first order a customer placed. Our supplier had run out of stock. But it’s a dropshipping business, and thankfully tens of other suppliers carried the same product. Instead of trying another supplier, the agent almost immediately sent the customer a polite apology and attempted to issue a refund. Gah! So close! The agents could handle much of the work of getting a business up and running. What they struggled with was deciding what to change when it wasn’t working. That’s what we want to understand. We also want to see what changes when people take the lead. What does a business operator actually do all day when agents can do so much? What new work does this allow them to do? Which decisions can’t be delegated? — So this winter we're hiring 4 interns as Associate General Managers. Associate Product Manager internships are programs that give early career generalists a product to own. We want to try something similar, but with entire businesses. You’ll create and grow businesses, with agents handling the routine work so you can focus on figuring out what matters. Each AGM gets a budget and our agent infrastructure that’s designed for this. Which ideas to try is up to you. Put more money behind what finds customers and keep refining. Where you step in tells us what agents can't do yet. You'll be in our SF office with me and people I’m so fortunate to work with, like @_arohan_, @joannejang, @MillionInt, @marksaroufim and @juliacvillagra We don't care much where you went to school or what your resume looks like. We’re looking for enterprising people with a drive to create, who’ve made money on the internet before and already use AI extensively to enable their ideas. If that sounds like you: coreauto.com/AGM
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Deep learning is still not solved. It has been great to see the creativity of the community and we all have more work to do to understand the universe. Thank you for being in this journey together ❤️
Over 15,000 submissions to One Layer Deeper. Nobody solved the problem as intended, but there are some interesting ideas for learning reusable operations and composing them into deeper computations coreauto.com/blog/what-the-m…
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Think different
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Rohan vagueposting likely improved the proprietary deep learning tech by a decade
Project Wallfacer: I am going to stop vague posting about better than gradient descent because 10k agents, 88hrs and 300k gb300s can figure it out. Note: I would be okay if that happens and result is public, otherwise feels too powerful tech.
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