An ML scientist writes about the extreme strain of working in an AI industry collectively shaken up by ChatGPT, as he oscillates between motivation and burnout
Fear, FOMO, and the scientific exodus driven by ChatGPT — Every single person I know working in AI these days … LinkedIn: Veysel Kocaman and Ahmad Anis Mastodon: @gowthami@sigmoid.social and @carnage4life@mas.to Tweets: @natolambert , @emeka_okafor , @marie_haynes , @mariofilhoml , @gowthami_s , @mpshanahan , @voxbec , @mmitchell_ai , @omgroth , @thecat , @ericjang11 , @bg_learning , @rsbutner , and @anderssandberg LinkedIn: Veysel Kocaman : Some quotes: — “Every single person I know working in AI these days (in both the academy and industry) has been sparked by the ChatGPT moment. … Ahmad Anis : Be a goldfish. When things are moving so fast, it's good to remember that sometimes you'll waste a lot of effort or get scooped. … Mastodon: @gowthami@sigmoid.social : This is exactly how I've been feeling for the last few months. It is becoming almost impossible to keep up with the current pace of research. — #phdlife #machinelearning — RT @natolambert … Dare Obasanjo / @carnage4life@mas.to : Interesting post on what it's like to work in AI since ChatGPT and generative AI burst on the scene. Teams are in a rush to be first, best or most open. — Roadmaps are being tossed to chase after buzzworthy projects. … Tweets: Nathan Lambert / @natolambert : Almost everyone I know working in AI these days feels one step away from total burnout. I took the time to take you behind the curtain and know what people on the state-of-the-art AI are struggling with: https://robotic.substack.com/ ... @emeka_okafor : AI, an industry experiencing upheaval... https://twitter.com/... Dr. Marie Haynes / @marie_haynes : How about the SEO community? How are you doing in trying to keep up with all the change lately? https://twitter.com/... Mario Filho / @mariofilhoml : ML friends, please remember to take care of your mental health Your 🧠 is a great asset and, if you hurt it, fixing it is VERY hard Slow down, take a breath 😉 https://twitter.com/... @gowthami_s : This is exactly how I've been feeling for the last few months. It is becoming almost impossible to keep up with the current pace of research. #phdlife #machinelearning https://twitter.com/... https://twitter.com/... Murray Shanahan / @mpshanahan : “Almost everyone I know working in AI these days feels one step away from total burnout” https://twitter.com/... Bec Johnson / @voxbec : Great read: what it feels like to work in the LLM space now. As a final year PhD working on the ethics of LLMs for several years, I've found it overwhelming of late how much extra activity there is now: papers, tweets, media, models, & oomplah from the bandwagon. 🙌 @natolambert https://twitter.com/... @mmitchell_ai : SUPER timely piece from colleague @natolambert. Captures a lot of the discussions in my research circles rn. “Clickyness is the driving trend in the last few months, which has such a sour flavor.” Curious abt what AI researchers are thinking/feeling right now? Check it out. https://twitter.com/... Oliver Groth / @omgroth : A very thoughtful piece by @natolambert on the state of affairs in A(G)I right now. Well worth a read if you also sometimes feel overwhelmed by the current pace of developments. My TLDR: Acknowledge the change, but look past the low-hanging fruits and keep asking tough questions. https://twitter.com/... Jeremy Lu / @thecat : There is no “working in AI”, a few thousand people are doing real AI at most, the rest of us are calling an API. 嘻 居.有人如 此..說出實 話.是坦..好 討喜~🤗 https://robotic.substack.com/ ... Eric Jang / @ericjang11 : Great read by @natolambert on the simultaneous feeling of excitement and anxiety that is AI research & startups right now https://open.substack.com/... Bijay Gurung / @bg_learning : A thoughtful, reflective piece; reading it felt like taking a brief pause (lol) from the feeling of being both inundated/overwhelmed and awe-struck by the progress, or rather more generally the movement in the field... https://twitter.com/... Ryan Butner / @rsbutner : The burnout I feel stems from seeing the coming fight over AI: its already a culture war hot potato, and the discourse gets super dumb as the moment regulation is brought up. It will be a fight that doesn't produce a catharsis or conclusion, just another forever war here. https://twitter.com/... Anders Sandberg / @anderssandberg : This feels like what I have seen from the near sidelines. https://twitter.com/...
Context & Ripple Effects
Nathan Lambert's account lands two months into the post-ChatGPT scramble, and it names what most coverage of that period skips: the people inside the field are not just racing, they are fraying. He writes that every researcher he knows, in academia and industry alike, was 'sparked' by the ChatGPT moment — and that the same event is producing fear, FOMO, and an exodus out of research roles.
That tension has a visible counterpart in the skepticism camp: the earlier profile of Emily M. Bender captured the linguists arguing LLMs were being oversold even as industry momentum made their position feel untenable. Read together, the corpus shows a field where belief and burnout are both responses to the same shock.
First-order effects
- Individual ML researchers like Lambert face immediate career pressure: stay productive through a hype cycle that rewards speed over reflection, or exit toward less exposed roles — the exodus his piece documents among people he knows in both academy and industry.
- Academic AI researchers lose ground right now to industrial labs that can absorb the pace and compute demands of the post-ChatGPT cycle, accelerating the talent drain Lambert describes.
Second-order effects
- Labs competing in this climate convert FOMO into a retention problem: the emotional toll Lambert describes becomes a recruiting lever, with stability itself pitched against the churn of startup-era urgency.
- The human strain sits atop a hidden labor layer — the subject-matter-expert 'taskers' hired by firms like Scale AI — meaning the same generative-AI surge stressing researchers is also expanding an invisible annotation workforce whose conditions get far less scrutiny.
Third-order effects
- If the pattern holds, AI research consolidates structurally around well-resourced industrial labs while universities become training grounds rather than research competitors — a step toward the institutionalization of frontier work rather than open scientific inquiry.
- The burnout-versus-belief split also hardens public discourse: between Bender-style skepticism on one side and the argument from the later Platformer piece that skeptics underestimate how real AI's dangers are, the field's internal stress shapes whether society gets sober assessment or polarized noise.
The trend: AI research is shifting from steady scientific work to a crisis-paced industrial race, with researcher burnout, talent migration to labs, and hidden annotation labor as the human costs of the post-ChatGPT acceleration.