Su Park

81 posts

Su Park

Su Park

@sunotsue_

terminal bench · post-training & evals against global banality prev @ltiatcmu @columbia

San Francisco, CA Katılım Ocak 2024
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Su Park
Su Park@sunotsue_·
meanwhile at the warehouse / sf finally stopped being lame as of 2026
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Deedy@deedydas

The vibes in SF feel pretty frenetic right now. The divide in outcomes is the worst I've ever seen. Over the last 5yrs, a group of ~10k people - employees at Anthropic, OpenAI, xAI, Nvidia, Meta TBD, founders - have hit retirement wealth of well above $20M (back of the envelope AI estimation). Everyone outside that group feels like they can work their well-paying (but <$500k) job for their whole life and never get there. Worse yet, layoffs are in full swing. Many software engineers feel like their life's skill is no longer useful. The day to day role of most jobs has changed overnight with AI. As a result, 1. The corporate ladder looks like the wrong building to climb. Everyone's trying to align with a new set of career "paths": should I be a founder? Is it too late to join Anthropic / OpenAI? should I get into AI? what company stock will 10x next? People are demanding higher salaries and switching jobs more and more. 2. There’s a deep malaise about work (and its future). Why even work at all for “peanuts”? Will my job even exist in a few years? Many feel helpless. You hear the “permanent underclass” conversation a lot, esp from young people. It's hard to focus on doing good work when you think "man, if I joined Anthropic 2yrs ago, I could retire" 3. The mid to late middle managers feel paralyzed. Many have families and don't feel like they have the energy or network to just "start a company". They don't particularly have any AI skills. They see the writing on the wall: middle management is being hollowed out in many companies. 4. The rich aren’t particularly happy either. No one is shedding tears for them (and rightfully so). But those who have "made it" experience a profound lack of purpose too. Some have gone from <$150k to >$50M in a few years with no ramp. It flips your life plans upside down. For some, comparison is the thief of joy. For some, they escape to NYC to "live life". For others still, they start companies "just cuz", often to win status points. They never imagined that by age 30, they'd be set. I once asked a post-economic founder friend why they didn't just sell the co and they said "and do what? right now, everyone wants to talk to me. if i sell, I will only have money." I understand that many reading this scoff at the champagne problems of the valley. Society is warped in this tech bubble. What is often well-off anywhere else in the world is bang average here. Unlike many other places, tenure, intelligence and hard work can be loosely correlated with outcomes in the Bay. Living through a societally transformative gold rush in that environment can be paralyzing. "Am I in the right place? Should I move? Is there time still left? Am I gonna make it?" It psychologically torments many who have moved here in search of "success". Ironically, a frequent side effect of this torment is to spin up the very products making everyone rich in hopes that you too can vibecode your path to economic enlightenment.

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Su Park
Su Park@sunotsue_·
@andyfang v tempted to build a Terminal Bench task around this — multi-objective optimization over daily meal credits, delivery windows, dietary constraints, coupons, dynamic inventory, etc
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Andy Fang
Andy Fang@andyfang·
Today we're opening up the DoorDash CLI in limited beta. `dd-cli` lets you order DoorDash directly from your agent: search stores, find the best deals, check out, and more. Early access for US/Canadian macOS developers by waitlist. Excited to see what folks build!
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Hyeri Jo
Hyeri Jo@hyerijo_·
Claude is now calling me UNNIE...🙄
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lily zhang
lily zhang@lily_gpupoor·
this is a $100B market for AI training data including RL env. my take: it's not more data. it's the right data. what is the right data? deep integration with the product, model, service. and the verification that gains can actually land with the customer. today this deep integration only happens for the coding domain, but the world is your oyster. we need the same force on unsexy domains, like telecom-at&t, reltail-walmart, manufacturing, supply chain ...
Deedy@deedydas

Every single startup selling AI Training Data (July 2026) >50 cos sell data and RL environments to big AI labs and drive AI progress behind the scenes. They total ~$8.5B in rev and ~$100B in valuation, >75% of which are just 4 players: Scale, Surge, Mercor and Handshake.

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Su Park
Su Park@sunotsue_·
ily seoul 🩷 my cutie home city that never stops reinventing itself. i grew up spending weekends at coex, and coming back for #icml last week felt both strange and familiar. now back to soulless sf 🥀 늘 조금 낯설고 제법 따뜻하고 꽤 정갈한 내 도시!
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Markus Wulfmeier
Markus Wulfmeier@m_wulfmeier·
Honestly not sure how long all those 'data for robotics' startups will make it... Pitch me why your data will make our model better for the things that we care about!
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Spencer Mateega
Spencer Mateega@spencermateega·
AfterQuery is quickly closing the gap on the “giants.” We’ve already grown multiples past the $100M revenue run rate cited here. If you’re a post-training researcher or lab that needs long-horizon tasks, professional / knowledge work data, high-fidelity RL environments, code generation data, or internal evals done right, my DMs are open or reach out to us at research [at] afterquery [dot] com.
Deedy@deedydas

Every single startup selling AI Training Data (July 2026) >50 cos sell data and RL environments to big AI labs and drive AI progress behind the scenes. They total ~$8.5B in rev and ~$100B in valuation, >75% of which are just 4 players: Scale, Surge, Mercor and Handshake.

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Su Park
Su Park@sunotsue_·
before flying back to sf, do find time to check out korean modern art! art seems to be the one thing sf struggles to cultivate despite all its pursuit of science and progress. my personal favorite seoul art museums, in order: 1. amorepacific museum of art (the current lee bul & nam june paik exhibition is worth it) 2. mmca (right by the palace, in the heart of samcheong-dong) 3. leeum (run by samsung in hannam)
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Su Park
Su Park@sunotsue_·
back home in seoul city for #ICML 🇰🇷 I’m Su, based in SF, making TerminalBench tasks by day. let’s grab coffee if you’ve been thinking deeply about data efficiency, data attribution, or simulation lately - I’ll take you to the cutest ones (I grew up here!) here till monday!
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Su Park
Su Park@sunotsue_·
I think this conflates data efficiency with information efficiency? better attribution, curricula, synthetic data, and feedback signals can dramatically change what the model learns, even in low-resource settings. the objective isn’t just fewer tokens, it’s higher information density
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Charlie O'Neill
Charlie O'Neill@oneill_c·
We now have a finetuning product called loops that uses similar abstractions to tinker! It makes it very easy to deploy your model after training. For example, it’s often difficult to export a model to serve because you have to quantise it to get good performance in production. As such we are very opinionated on how quantisation should be handled during training, so there’s zero mismatch between your trained model and your deployed model. There’s many other things to consider too of course, and thinking machines has built a great product, but the future is training much more tightly coupled with inference. Some of our biggest customers are using loops, dm me if you want beta access
Vaibhav Tulsyan@xennygrimmato_

Post-training for domain-specific tasks is commoditised. @thinkymachines provides really good Claude Code / Codex skills for anyone out there to finetune open-source models. For inference, use @baseten or @FireworksAI_HQ as per your choice.

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Su Park
Su Park@sunotsue_·
@m1nj12 someone needs to make a nangmyeon map in english
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Minji Lee
Minji Lee@m1nj12·
my ICML recs for foodies - At COEX: cheese room, katsu8 (but in average COEX foods r good) - Walkable: butai ilmak, brooklyn the burger joint, sushi U (if u wanna splurge) - Uber, but still near: Garam noodles, Jinmi Pyeongyang nangmyeon (controversial tho)
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himanshu
himanshu@himanshustwts·
Cool META drop on a random monday
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AI at Meta@AIatMeta

We’re sharing the next major milestone in our non-invasive brain-to-text decoder research: Brain2Qwerty v2. Building on v1, which was published today in @Nature, Brain2Qwerty v2 is the highest-performing end-to-end pipeline capable of real-time sentence decoding from raw brain signals. It advances beyond character-level performance to decoding words and semantics, enabling accuracy for overall communication. We believe this research has the potential to make a real difference for the millions of people who suffer from brain lesions or disorders that prevent them from communicating. 🧵👇

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empowa
empowa@imempowa·
hi <3 im ash i run an art gallery in SF • i’ve had striped hair since 2023 • i can figure skate pretty well too lol • i love media art / have worked in “creative technology” for almost a decade • i’ve hosted 250+ public art/tech events since opening @tiatplace 8 months ago feel free to email me if u want to be friends, lovers, or enemies
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Su Park retweetledi
Hamish Ivison
Hamish Ivison@hamishivi·
Trained some terminal agents with friends! Introducing Tmax, open RL terminal agent models. Under default settings and shorter length (65k) token budgets, tmax outperforms prior open work on terminal use. We are releasing all data+weights+rollouts publically!
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