@PeterDiamandis I just can't wait to tell my grandkids "we used to print directions from MapQuest."
Right after their electric car kick-flips over a semi. ⚡
Everyone's watching how smart AI gets. This paper says watch how well AIs work together.
Past a coordination tipping point, every new agent makes the team better, not slower.
We're not there yet. But when we are… oh boy ⚡
https://t.co/0QYaTv0STk
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
@Torerone@ericzakariasson@bot@poteto Great point. My idea is a verified-number lock, so it can only ever call or text me about my own workflows. Not a cold caller. Just a teammate who rings when something matters.
@SawyerMerritt I saw one of these pull into my hotel in Vegas last week. Breathtaking, but I was like “Hey, little buddy.. are you lost? I thought you were supposed to stay in Texas..?” 🤔😂
@PeterDiamandis This is the problem I can’t seem to picture a solution to. Really, I would love to dedicate my time to solving this with like-minded people.
@DaveBlundin Ohio checking in. Lots of land, lots of power lines, and a few neighbors protesting the data center on Facebook.
Which, technically, runs on a data center. 😄
Ohio man shakes his fist at the local data center.
Decides to make a change.
Writes a 600-word post about how evil data centers are.
Hits post.
That same data center serves it to all his followers.
Life is weird.
@DaveBlundin The answer to bad actors with powerful tools is good actors with better ones. @alexwg calls it defensive co-scaling, and I'd put it right in your alignment bucket. Millions of good engineers can solve this. Halting progress over a few bad actors won't.
@PeterDiamandis@VanJones68 Working in addiction recovery taught me that hope is the first step, not the reward at the end. People can't build a future they can't picture. That's why showing them one matters so much. Thank you for all that you do, Peter.