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This article examines how open source software defies classical economic principles such as the free rider problem, price signaling, and the tragedy of the commons, yet thrives through non-monetary incentives and community contributions.
This paper presents a knowledge-based theory of capital, examining the value of both natural and artificial intelligence from an economic perspective.
An analysis of the economics and performance impact of AI reasoning models, showing that enabling reasoning can improve accuracy by 10-20% but costs 5-10x more tokens, and discussing different reasoning types and their applications.
Charity Majors discusses how AI flipped the economics of code production, making code generation cheap and instant, transforming code from a treasured asset into a disposable, regenerable resource.
a16z podcast invites former partner Benedict Evans to explore the analogy between AI and the internet in 1997, pointing out that current AI infrastructure investment is massive but ROI is unclear. Historical experience suggests value will shift upward, and models themselves will find it difficult to achieve differentiated profits.
Jeff Bezos is betting $12 billion on his new company Prometheus, which builds AI tools to accelerate the design and manufacturing of physical products, aiming to lower costs so that one paycheck can support a family again.
This essay argues that AI will not replace software engineers because the 'decide' and 'deliver' layers of knowledge work resist automation, and evidence from recent layoffs at Block and Snap shows that CEOs often overestimate AI's capabilities.
This 1989 paper draws a historical analogy between the dynamo and the computer to explain the modern productivity paradox, comparing the slow productivity gains from electrification with those from computing.
An interview with economists Alex Imas and Phil Trammell discussing the economic implications of AGI, including what will remain scarce, how to tax and redistribute AI-generated wealth, and potential inequality scenarios.
A team reflects on six common structural failure points in AI builds: context, identity, decision memory, attention, write-back, governance, and economics, and offers a diagnostic tool based on their experiences.
New Harvard paper proposes a decentralized multi-agent system where agents coordinate in a market-like environment using auctions and payments.
This paper introduces an economic framework for multi-agent AI systems, where agents interact through economic mechanisms to produce emergent collective intelligence, drawing from Harvard and MIT researchers.
A tweet discussing the decline of illustrators' earnings since the 1970s and questioning whether AI has fully ended their lucrative era, with a link to a Substack article exploring the topic.
Cheaper AI technology is increasing demand and creating more jobs, with no evidence of widespread AI-related job losses, according to an Apollo report.
Chris Manning reflects on the uncertainty around AI's impact on jobs, citing Dan Shipper's observation that AI agents have not reduced human work but increased demand, leading to more hiring.
A reflection on whether intelligence is an unprecedented commodity with infinite or recursively expanding demand, unlike any other in human history, potentially requiring new economic models.
A news article discussing whether AI technologies and companies are becoming profitable.
Discusses how AI automating high-skill work could reduce the competitive advantage of elite firms like Citadel, as individuals with AI tools could replicate work previously requiring large teams.
A call for economics professors to seek funding to work on major AI questions, emphasizing the need for economists to engage with AI problems.
A tweet criticizes Mark Cuban's proposal for a small federal tax on AI tokens, arguing it reflects flawed economic thinking.