Worth Reading 051826


 


We’ve all been in that meeting where someone pulls up a chart and says, “Our AI product boosted conversion by 15%.” Everyone nods. Nobody dares to ask: “What if conversions had risen anyway?”

 


The proposed repair is Running-Code Primacy: the number-resource layer should be interpreted only by reference to the minimum technical function running networks require—uniqueness, interoperability, proof of control, routing-adjacent security, and locally verifiable state.

 


You already know IPv6 is overdue. You’ve known for years. You’ve probably sat in a meeting where you laid out the case — address exhaustion, rising costs, growth constraints — and watched leadership nod politely before approving the budget for another batch of leased IPv4 addresses.

 


A key question was whether this reflected a breakthrough specific to one model, or part of a broader trend. Results from an early checkpoint of GPT-5.5 suggest the latter: a second model, from a different developer, now reaches a similar level of performance on our cyber evaluations.

 


The most mature U.S. small modular nuclear reactor vendor — NuScale Power — and a politically connected firm planning to build perhaps the largest reactor project in the U.S. to power an enormous Texas data center — Fermi America — have both suffered recent, major, possibly existential blows.

Worth Reading 051526


 


Given the trend of using generative AI tools like ChatGPT, Gemini, Copilot, and Claude for software development, many companies have decided that developers must use GenAI to succeed. I strongly disagree.

 


Here, through a series of randomized controlled trials on human-AI interactions (N = 1,222), we provide causal evidence for two key consequences of AI assistance: reduced persistence and impairment of unassisted performance. Across a variety of tasks, including mathematical reasoning and reading comprehension, we find that although AI assistance improves performance in the short-term, people perform significantly worse without AI and are more likely to give up.

 


Last month, market research company, Gartner, said that AI companies need close to “$2 trillion per year in revenue by 2029”, token consumption of between 50,000 and 100,000 times its current rate by 2030, and “a 10% profit margin per token.” With huge losses and small revenues, it is not likely that AI companies will achieve these goals on time.

 


He said that about 20% of all network traffic today, about 80 exabytes, comes from machine-to-machine traffic, and that alone is big news. Nokia is betting its future growth will come from meeting this growing demand.

 


For centuries, political power has repeatedly attempted to territorialize systems whose operational logic depended upon openness, circulation, and coordination beyond borders.

Hedge 305: From Security to Networking


 
We don’t often hear the stories of those who move from some other IT career field into network engineering. Ayush Mishra, a student at University of Colorado Boulder, joins Tom and Russ to discuss why he moved from security to network engineering.

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