James Swingos

I spent 8 years scaling Discord and got burnt out cause modern work is broken. We’re overwhelmed with too much info across apps, teams, and agents. AI made it worse. We’re building the solve. I've joined @tryhighlight as CEO and we raised a $40M Series A led by @KhoslaVentures.

There is a tremendous amount of progress happening in World Models. Multiple labs have raised more than $1B. WMs were the star of GTC. They are a real path to embodied AI. So @PimDeWitte & I wrote a comprehensive 19k word overview of World Models. notboring.co/p/world-models

"We invented text as this way of compressing the world around us. Now, we  model systems that represent interactions of how the real world works." - Our CEO @PimDeWitte in discussion with @johnhanke of @NianticSpatial moderated by @mbaierlentz - at @SlushHQ 2025. Perfect Thanksgiving content digest 🦃

Launching @kyutai_labs x @Gen_intuition - research collab at the frontier World models and agents capable of spatiotemporal reasoning are the next frontier. As builders of this technology, we have a responsibility to educate. This is impossible without both unique data and world-leading talent. Through our research collaboration, both labs will share data and talent seamlessly. - The necessary data lives inside only a few companies, and isn’t available on the internet. @gen_intuition owns the largest, most diverse, ground truth action labelled dataset. @Kyutai_labs utilizes the data for open research, resuming their culture of publishing on the frontier - Talent moves between the two labs, switching freely between open-ended research and application Join us in NYC and Europe - open roles below jobs.ashbyhq.com/medal & kyutai.homerun.co/technical-staf…

With enough data, robots and AI can learn “world models” that let them predict the results of their actions. These models are a way to learn how embodied AI agents can perform a wide variety of useful tasks — but they require a huge amount of data. The team at General Intuition @gen_intuition has a solution: use data from video games! Games teach movement, problem solving, and complex spatial reasoning, and they come in a staggering diversity of forms, covering a wide variety of problems. What’s more, the captured data is high-quality, without the noise or annotation error that can come from We sat down with @PimDeWitte and @AdamJelley2 from the General Intuition team to learn more about their history, their plans, and their philosophy.

With enough data, robots and AI can learn “world models” that let them predict the results of their actions. These models are a way to learn how embodied AI agents can perform a wide variety of useful tasks — but they require a huge amount of data. The team at General Intuition @gen_intuition has a solution: use data from video games! Games teach movement, problem solving, and complex spatial reasoning, and they come in a staggering diversity of forms, covering a wide variety of problems. What’s more, the captured data is high-quality, without the noise or annotation error that can come from We sat down with @PimDeWitte and @AdamJelley2 from the General Intuition team to learn more about their history, their plans, and their philosophy.

Full episode dropping soon! Geeking out with @PimDeWitte @AdamJelley2 , cofounders of @gen_intuition leveraging large-scale game recordings to build agents with deep spatial/temporal reasonings. Built upon the work by Adam, @EloiAlonso1 @micheli_vincent (all cofounders at General Intuition) : DIAMOND - Diffusion for World Modeling: Visual Details Matter in Atari diamond-wm.github.io Co-hosted by @micoolcho @chris_j_paxton