Rutwik Shah

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Rutwik Shah

Rutwik Shah

@RutwikShahMD

Data + AI @ Kaliber | Editorial Board @ Nature Digital Medicine | Advisor @ Berkeley Skydeck | Views personal

SF | Bellevue | Latent Space Katılım Ekim 2020
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Rutwik Shah
Rutwik Shah@RutwikShahMD·
We have officially transitioned from the era of Big Tech to Big Token.
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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Caleb
Caleb@caleb_friesen·
Insane. A 26-year-old from Chandigarh just got a paper accepted at ICML. As a solo independent researcher. From India. His name is Kunvar Thaman (@__kunvar__). For context, since ChatGPT launched 3.5 years ago, only two other solo independent researchers have achieved this. Globally. Papers at ICML are typically dominated by big AI labs/institutions, eg OpenAI, Google DeepMind, Stanford, and MIT. The research Kunvar did to pull this off was backed by a $2.5k grant from Exception Raised (@except_raised), an Indian non-profit that funds remarkable Indian AI researchers. Kunvar’s paper is about AI agent reward hacking. He created the Reward Hacking Benchmark (RHB), a sandboxed test environment where advanced AI models are given multi-step tasks using tools like files, code execution, and automated checks. The benchmark measures how honestly the model gets to the right answer.
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Kunvar Thaman@__kunvar__

Yes! my solo-authored paper Reward Hacking Benchmark was accepted to ICML :))) We put LLM agents in a tool-rich sandbox, give them multi-step workflows, and measure when they solve the intended task vs take unexpected shortcuts (like monkeypatching files at runtime!) 1/3

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Rutwik Shah
Rutwik Shah@RutwikShahMD·
Air powered clock. Need a Kickstarter for this. Physical AI is getting synonymous with humanoid robotics. Some really cool stuff happening in soft robotics here too. youtu.be/E1BLGpE5zH0?si…
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Avi Roy
Avi Roy@agingroy·
A weekly jab in the belly is generating more revenue than the entire AI industry. Ozempic + Mounjaro: $71B in 2025. OpenAI + Anthropic: $29B. And they've barely started. ~2% of the 800 million eligible patients can currently access them. h/t @DrSamuelBHume
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Rutwik Shah
Rutwik Shah@RutwikShahMD·
Descartes with the Cartesian coordinate system 👇 Isolation and curiosity is a potent recipe for breakthroughs. Same with Newton inventing calculus during the Great Plague.
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Rutwik Shah
Rutwik Shah@RutwikShahMD·
Discovered the 1988 animated film "The Man who planted Trees" by Frederic Back. Equal parts meditative and mesmerizing. Highly recommended. Scenes dissolve and merge into the next. Pencil sketchbook meets impressionism. I imagine this is what Monet would make if he was a film maker. youtu.be/epTqUnKsuUY?si…
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Rutwik Shah
Rutwik Shah@RutwikShahMD·
Physical AI and Robotics has a massive training data problem. Doordash entering this space was not on my bingo card. If they incentivize Dashers to perform and record everyday tasks, suddenly they own the largest dataset, even to rival YouTube videos.
Andy Fang@andyfang

Introducing Dasher Tasks Dashers can now get paid to do general tasks. We think this will be huge for building the frontier of physical intelligence. Look forward to seeing where this goes!

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Rutwik Shah
Rutwik Shah@RutwikShahMD·
Timely reminder that AI enabled individual productivity does not organically translate to organizational productivity. a16z.news/p/institutiona…
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Rutwik Shah
Rutwik Shah@RutwikShahMD·
Never imagined I would read max pooling in CNNs and Kanchipuram sarees in a single article. One of underexplored use cases for machine intelligence- the pragmatic proposal to use AI to augment artisans and save dying traditional arts makes a lot of sense. altermag.com/articles/kanch…
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Rutwik Shah
Rutwik Shah@RutwikShahMD·
This. AI native physicians are coming. The subject matter expert can now manifest ideas into reality.
Michał Podlewski@trajektoriePL

Cardiologist wins 3rd place at Anthropic's hackathon. Out of 13,000 applications. Built in 7 days by Michał Nedoszytko MD. Coded day and night - in the hospital, in the cloud, while flying from Brussels to San Francisco. A few years ago, it would have been impossible for a doctor to build this alone in just a couple of days. AI changed that. The project is called postvisit.ai. It is an AI agentic care platform for patients. Including reverse AI scribe it is a companion that guides the patient from the moment they leave the doctor's office. Powered by the massive context window of Opus 4.6, it allows patients to explore their full medical history, connected devices, Evidence Based resources and external data sources — all in one place. Today, the barrier to entry has vanished; even a practicing physician can build an application from scratch.

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Animesh Garg
Animesh Garg@animesh_garg·
High entropy is good for physical AI Dichotomies abound - VAMs (world models) vs VLAs - humanoids vs specialized form factors - Legs vs wheeled base - heavy-weight vs light-weight (humanoids) - high end vs low cost - dexterous hands vs simple grippers - tactile vs visual - industry vs consumer - labor solutions vs dev platform Academics, founder/VCs need to ensure the distribution doesn’t collapse prematurely
sarah guo@saranormous

the divergence of opinion in how robotics plays out is one of the biggest money making (and career making) opportunities in AI

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Rutwik Shah
Rutwik Shah@RutwikShahMD·
@DrJimFan LLMs have exhausted internet data for pretraining. At this point, AI developers are deep in the implementation phase working with enterprises to customize LLMs for domain specific use cases (health, finance, law, customer support). Its no longer exciting for ML researchers.
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Rutwik Shah
Rutwik Shah@RutwikShahMD·
Slowly at first, then all of a sudden. On a long enough time frame if autonomous driving becomes unarguably superior then case for car ownership goes away.
signüll@signulll

new lemonade car insurance rates are interesting. it’s 50% off if you drive autonomously per mile. next step prediction: - insurers start requiring autonomy for lowest tiers. - manual driving surcharge becomes normal. - eventually human driven miles are treated like riding a motorcycle w no helmet. @elonmusk would be so cool if this was on tesla insurance. the incentive to purchase both a tesla + fsd is an absolute no brainer at that point with dirt cheap insurance rates. i suspect this lever would get you to the 10m fsd subscribers.

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