very weird thing happening rn
technical people are sad, they think their skills are now useless
non-technical people are desperately wishing they were more technical so they could use agents better
We're open-sourcing Autopilot.
A self-improving agent that plays your game and finds bugs. Unity, Godot and Unreal.
→ 43% more accurate
→ Almost 2X faster
→ Beats Claude Code at playtesting
It’s Computer Use for games – closing the agentic loop and solving the most tedious part of game dev.
Stop being your agent’s tester. Free trial + GitHub below.
Today we’re launching the first AI modeling agency 💅 right inside Glif.
Cast hundreds of real AI models, drop your product, idea or brief and let Glif create super compelling content for you end to end.
If you still think AI models aren’t ready for real work, watch this 👇
You can now generate, preview, and edit documents, PDFs, presentations, spreadsheets, and more directly in Gemini.
Easily turn your handwritten notes into a PDF study guide, manually tweak content, highlight sections for Gemini to edit text or visuals, and even ask follow-ups.
I joined @GoogleDeepMind to develop a research program on the economics of AGI. Today, together with Andrew Koh (@andrewjkoh) and Shane Legg (@ShaneLegg), we are incredibly excited to release The Economics of Intelligence, the first in a series of projects from our group on how AGI will change the economy.
How do capability improvements transform the economy, and when? In this project, we define thresholds of economic capabilities, e.g., minimal AGI, based on how they transform the economy. We then track how the economy–market structure, employment, and wages–changes during the transition across capability regimes.
We have seen exponential increases in what AI agents can do but the broader economy seems almost remarkably unchanged. Part of the reason is that the solo AI agent is the wrong economic object; economic transformation is an equilibrium outcome where organizations compete. Looking at how intelligence functions within organizations, transformation will depend on when two key capability thresholds are crossed: competence (gains on individual skills, e.g., coding, math) and coordination (gains on ability of agents to cooperate and work together).
We show that what economic transformation looks like depends on whether AI becomes supercompetent, supercooperative, or both—the regime of artificial superintelligence (ASI). Tracking this transition shows why the real visible transformation may come from improvements in coordination—a capability most benchmarks don’t yet track. Past a certain threshold, AI capabilities can break the Coasian ceiling on firm size and lead to an economy that looks drastically different than the one we see today.
Two main takeaways:
1. To understand the path of transformation, we should be tracking agentic coordination more closely.
2. The impact of AI will likely show up in wages before market structure or employment.
We are really excited about this paper. Excited to hear people’s thoughts.
Link: https://t.co/9DTGSeKoSA