Does Aggregation Theory survive in a world of constrained compute? Yes, insomuch as controlling demand will give power over supply.
Aggregation Theory
About | Articles | Updates | Speaking | Consulting What is Aggregation Theory? Aggregation Theory is a completely new way to understand business in the Internet age. Business schools suggest that w…
Can we billionaire-proof inference? - Graze Newsletter
A small, federated compute co-op called co/core — and the wider experiment it's a part of.
EAAMO Conference 2026
ACM conference on Equity and Access in Algorithms, Mechanisms, and Optimization
Gajesh on Twitter / X
TL;DRapple has turn on this switch for everyone to participate in decentralized inferenceppl can rent out their unused compute space and anyone can use this with privacy guarantees https://t.co/LTP4zyjsdt pic.twitter.com/8Dvo7XK8jJ— Gajesh (@gajesh) February 18, 2026
Call for Participation
ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization
Open Science Needs Open Compute
Why independent science will depend on compute, not just funding, and why providing it is the best bet we can currently make.
Alex Komoroske on Twitter / X
Infinite software won't counter the hyper-aggregation problem if the software is distributed within the same origin paradigm. pic.twitter.com/yZfdqanvPF— Alex Komoroske (@komorama) June 6, 2025
Malleable Systems Collective
The Malleable Systems Collective catalogs and experiments with malleable software and systems that reset the balance of power in computing
Capacities
Capacities turns your ideas into connected objects. Think naturally, find everything instantly.
LLMs Can Design Near-Optimal OR Algorithms
We ask whether large language models (LLMs) can design effective algorithms for well-specified operations research (OR) problems. We study inventory control, queueing network control, and assortment optimization. We evaluate two levels of LLM use: at level 1, the model receives one problem instance and returns a solution for that instance; at level 2, it receives only the problem class description and broad parameter ranges, and returns an algorithm that maps instance parameters to solutions. Human input is minimal: we give one untuned prompt that describes the problem, and the model has access to a Python sandbox tool with a fixed compute budget. The strongest model we test, gpt-5.6-sol, matches or outperforms the best existing method on almost all evaluated instances. This holds even at level 2, where the returned algorithm is fixed before seeing the evaluation instances. Performance also improves sharply across models released less than eight months apart, suggesting that this capability is moving quickly. Thus, for the well-specified operations problems we study, a single untuned LLM query can already produce algorithms competitive with specialized methods. These results suggest that frontier LLMs can be a serious empirical baseline for algorithm design in well-specified OR problems.
SF Compute: Commoditizing Compute to solve the GPU Bubble forever
Selling GPUs to avoid bankruptcy, empowering researchers with short term clusters, and why CoreWeave is maybe a real estate business
Agents Over Bubbles
Agents are fundamentally changing the shape of demand for compute, both in terms of how they work and in terms of who will use them. They’re so compelling that I no longer believe we’re…
Groq On-demand Pricing for Tokens-as-a-Service
Groq powers leading openly-available AI models. View the pricing of our core models including GPT-OSS, Kimi K2, Qwen3 32B, and more.
A big lesson of my China visit: compute shortages are holding back Chinese AI
One estimate suggests that OpenAI has about as much compute as the entire Chinese AI industry.
Liberatory Computing
We live under a capitalist mode of computing. The tools, languages, techniques, and assumptions of digital systems are structured by economic forces that shape not just what we can do, but what we can imagine doing. By separating production from use, producing inflexible software, and slicing up computing into siloed apps, your agency is held back by a tech industry that profits from a population rendered computationally passive.
