JB Rubinovitz
8.8K posts
@rubinovitz
Something new Prev: ML/AI @medialab, @eightsleep, @columbia, Crypto #bailbloc
MPAIC: massively parallel AI coding AI can now code anything for you, from an app to a game, the rate limiter is that most people are doing this single threaded in a local IDE. But what if you had the scaffolding to scale your ideation to execution by 100x?
I don't know if this is a skill issue or something... But I've been playing with OpenClaw a ton for the past 4ish months. I feel like lately I'm spending more time troubleshooting issues with it and telling it what it's doing wrong than I am actually getting valuable use from it.
So much use of LLMs by patients and physicians in the US
It’s getting lonely in the “AI will indeed take ~all the jobs” X “and that’s good” quadrant
Optimistic take: US healthcare is actually set up very well for the AI era. GP shortage. Best therapies and proceduralists in the world for actual interventions. And a ton of admin bloat / bad incentives that create surface area to arbitrage.
Most people I know in AI think the median person is screwed, and they have no idea what to do about it. I spent the last 3 months talking to dozens of researchers, economists, and policy experts about AI's impact on work; including reps from every frontier lab and several Congressional offices. Unfortunately, I was not reassured. The AI industry is raising the alarm, but can't change course. These companies' core business model relies on the disruption they are warning about: their faith in full automation only makes them go faster. Policymakers are waking up, but still paralyzed by data and debates. Econ wonks disagree on plenty, but even the limited scenario looks like a "painful transition" that will disempower millions of workers. But an "underclass" is not inevitable, but rather a societal choice — and one we can and should stop. Instead of waiting for impact, we should start planning now to support workers through AI disruption. Whether policymakers can assuage concerns about economic security may determine if we get to reap AI's gains at all. New from me for @NYTOpinion. I put a ton into researching what I think may be the biggest topic of the year, so hope you read it (gift link here!) nytimes.com/2026/04/30/opi…
Personal AI Cooperative Networks Individuals organize into AI-coordinated micro-coops for buying power, services, and income generation. These systems negotiate on behalf of groups, allocate work, and distribute value transparently. The shift is from gig platforms (extractive, centralized) to coordinated collectives (aligned, bottom-up). Humans have always formed groups for leverage; AI removes coordination friction.
We don’t talk enough about how any state or group which is harvesting encrypted packets right now will be able to read those contents once quantum computers arrive. There’s a huge espionage and transparency overhang on any information that is currently “secret” and hasn’t been encrypted using post-quantum cryptography.
Can LLMs simply tell us about unwanted behaviors they’ve picked up in training? We train a single Introspection Adapter (IA) that makes fine-tuned models describe their behaviors. It generalizes to detecting hidden misalignment, backdoors and safeguard removal.
If you skip some or all of college to start a startup, it's on you to develop your mind the way college would have. And that's not something that happens by default in most startups.
counterintuitively, the steepest gains from AI in medicine will land in the specialties we describe today as "more art than science." the data-rich fields only look like the frontier because they are easiest to see.
