Worth Reading 071126


 


A unanimous Supreme Court reversed a $1 billion dollar jury award against a broadband provider in its March 2026 ruling in Cox Communications v. Sony Music.

 


Differential privacy (DP) data synthesizers are increasingly proposed to afford public release of sensitive information, offering theoretical guarantees for privacy (and, in some cases, utility), but limited empirical evidence of utility in practical settings.

 


LLMs are relentless data miners that train on unimaginably large text databases, looking for multi-dimensional statistical relationships among small chunks of text called tokens.

 


Regulatory filings and new business models suggest hyperscalers are shifting from simply building AI capacity to managing the enormous financial risks that come with it.

 


olicymakers are casting more and more problems as issues of cybersecurity. So reframed, wildly different policy issues, from misinformation, to child social media safety laws, to antitrust regulations, to alleged journalist misconduct, to anti-sex trafficking statutes become what this Article calls “cybersecuritized.

Hedge 311: The Dangers of AI

We are often told that if engineers who don’t go “all in” on AI will be left behind. While there are a few voices who argue that AI can be a dangerous tool, impacting not only the quality of our work, but the very quality of our thinking skills. Doug Smith, a critic of using AI for engineering, joins this episode of the Hedge to argue the contrary view of AI.

What are the dangers of relying on AI?

Hedge 310: AI Ops


 
What is AI Ops, and how can it be useful for your network? Akshay Balaganur and Sushanth Mascaren join Tom and Russ to discuss various aspects of AI Ops.

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