economics
PulseAugur coverage of economics — every cluster mentioning economics across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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Understanding P-Values: A Guide to Statistical Significance
This article explains the concept of p-values, which are crucial for understanding statistical significance in research. It uses a courtroom analogy where the null hypothesis represents innocence and the alternative hyp…
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New paper axiomatizes Boltzmann rationality in reinforcement learning
A new paper introduces an axiomatic characterization for Boltzmann rationality, a common model of stochastic choice in reinforcement learning. The research distinguishes between randomness in choice and environmental ch…
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Economists develop theoretical framework for pre-trained embeddings
Researchers have developed a theoretical framework for using pre-trained deep learning embeddings in econometrics, addressing challenges where models are trained on different datasets or tasks. The paper provides condit…
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X (Twitter) User Guide: Curated Lists and Blocking AI Slop
The author provides an updated guide on how to effectively use X (formerly Twitter) in 2026, emphasizing the continued importance of curated lists for managing the feed. Due to X's increasingly hostile interface for chr…
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Foundation models coordinate in multi-agent system for enhanced reasoning · arXiv research
Researchers have developed a multi-agent framework to enhance the reasoning capabilities of foundation models by coordinating diverse models. This system involves solver models generating initial drafts, critic agents r…
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New benchmark BehaviorBench assesses AI for behavioral science tasks
Researchers have introduced BehaviorBench, a new benchmark designed to evaluate how well foundation models perform on tasks relevant to behavioral science, such as psychology and sociology. The benchmark assesses models…
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AI's economic model criticized for exacerbating inequality
The article "AI's Brokenomics" critiques the economic model behind artificial intelligence, arguing that its current structure benefits a select few while exacerbating existing societal inequalities. It suggests that th…
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Companies Shedding Workers Due to Economics, Not AI, Say Analysts · 2 sources tracked
Companies are shedding workers not due to artificial intelligence, but rather for economic and business reasons. This perspective challenges the common narrative that AI is the primary driver of job displacement. The fo…
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AI economics explained via McSweeney's article and YouTube videos · 10 sources tracked
Multiple users on Mastodon are sharing resources that explain the economics of artificial intelligence. The most frequently shared item is an article from McSweeney's Internet Tendency titled "AI Economics for Dummies,"…
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LLM evaluator reveals research publication hinges on merit and networks
A new study published on arXiv investigates the factors influencing research paper publication in prestigious journals, using economics as a case study. Researchers developed an LLM-based evaluator to assess paper quali…
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AI could solve capitalism's resource inequality, user claims
A Mastodon user suggests that capitalism and economics inherently lead to resource concentration, and a hyper-intelligent AGI could potentially distribute resources equally without money. The user criticizes "Broligarch…
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AI can now write financial research papers indistinguishable from human work
A new study suggests that AI can generate financial research papers that are indistinguishable from those written by humans. This capability raises concerns about the integrity of economic research, potentially enabling…
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Author links fluid dynamics, spacetime, and economics
Brandon Bedard's Substack series explores the intersection of fluid dynamics and spacetime, drawing parallels between astrophysical phenomena and economic principles. The author posits that understanding these fluidic p…
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Gaussian Processes tutorial explores preference learning for personalized applications
This paper presents a comprehensive framework for preference learning using Gaussian Processes (GPs). It integrates principles from economics and decision theory into the machine learning process. The framework allows f…