Ethan Mollick

Ethan Mollick

276,345 Twitter followers

Follow

Professor @Wharton studying AI, innovation & startups. Democratizing education using tech Book: https://t.co/CSmipbJ2jV Substack: https://t.co/UIBhxu4bgq

Posts

Surprisingly rapid & high Ai adoption by doctors: 67% use it daily, 84% says it makes them better doctors, 42% says it makes them want to stay in medicine more (10% said less). A lot of the use cases appear to be administrative and research assistance. 2025-physicians-ai-report.offc...

Summarizing 2025 in AI in a tweet 1) No sign of a slowdown in exponential pace of gains 2) Jaggedness remains the main issue of AI 3) Early days for deployment, but many companies reporting positive ROI 4) GenAI became an industry, with industry-level impacts 5) AI is still weird

Interesting post & agree AI has missing capabilities, but I also think this perspective (common in AI) undervalues the complexity of organizations. Many things that make firms work are implicit, unwritten & inaccessible to new employees (or AI systems). Diffusion is actually hard twitter.com/emollick/status/19...

A focus on AGI (whatever it is) obscures the fact that we have increasing evidence from early results like GDPval that today's AI models are good enough to create major transformations over 5-10 years as companies figure out how to deploy them and integrate them into processes.

Reasoning models (apparently without tool use) scored #1 (OpenAI) & tied for #2 (Google) in the International Collegiate Programming Contest Its been one year since reasoners were first announced, it is genuinely surprising how good they have gotten at hard problems, so quickly

Interesting example of how open weights models provide opportunities for innovation. Salesforce builds a strong deep research agent from OpenAI’s small open source model. Though open models development is dependent on the good will of OpenAI, Mistral & a few Chinese firms. twitter.com/emollick/status/19...

The Pile, which was the initial training corpus for many LLMs, famously included Books3, a set of texts that included copyrighted works. Anthropic just settled for $1.5B for using Books3 in training. I wonder if the labs using Books3 gained more value from it than they will pay.

This is a fascinating paper that suggests that AI agents can indeed be used for social science experiments, but that just using a chatbot isn't good enough, instead prompts developed based on social science & game theory makes AI agent actions predictive of real human outcomes. twitter.com/emollick/status/19...

This is disappointing. Purposefully underselling what models can do is a really bad idea. It is possible to point out that AI is flawed without saying it can't do math or count - it just isn't true. People need to be realistic about capabilities of models to make good decisions. twitter.com/emollick/status/19...

Loading..