Arvind Narayanan

@random_walker

Princeton CS prof and Director @PrincetonCITP. Coauthor of "AI Snake Oil" and "AI as Normal Technology". normaltech.ai Views mine.

Princeton, NJ

cs.princeton.edu/~arvindn/

Joined December 2007

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Arvind Narayanan
@random_walker
Jul 14
1) If you haven't read AI as Normal Technology, these annotated slides are probably the easiest way to get a high-level overview. cs.princeton.edu/~arvindn/talks… 2) If you're already familiar with the core ideas, Part 1 of the talk is largely a summary of what I and @sayashk have
Arvind Narayanan
@random_walker
Jul 13
I had the honor of giving a keynote at the International Conference on Machine Learning in Seoul last week titled “What will be left for us to work on?” I addressed the widespread anxiety about how we should adapt as AI capabilities increase. I was thrilled by the talk’s
Arvind Narayanan
@random_walker
Aug 14
In this short editorial for Science, @akashkapur and I talk about how India should approach AI sovereignty given the trend of models commoditizing and competition moving up the stack
science.org
How should India approach AI?
In an unstable geopolitical environment, countries are looking to secure access to artificial intelligence (AI) capabilities, which are seen as essential to economic growth, scientific research, and...
Arvind Narayanan
@random_walker
Aug 13
Prediction: we will soon enter an era where the latency of agentic work is bottlenecked not by LLM inference speed but by tool use. Shell commands, build pipelines, computer use, web data extraction, and everything else that happens in the background is way slower than it needs
OpenAI
@OpenAI
Aug 13
Previewing Ultrafast mode: GPT-5.6 Sol at up to 14x the speed. Launching first in the OpenAI API to a select group of customers with expanded access to more businesses as capacity grows.
00:00
Arvind Narayanan
@random_walker
Aug 12
Two contrasting patterns of working with agents are emerging: delegation and collaboration. Delegation makes sense when it's a long-horizon task that you want the agent to tackle asynchronously, your intent and specifications are clear to the agent, and it's easy to verify the
Arvind Narayanan
@random_walker
Aug 6
Recursive Self Improvement is a possibility worth taking seriously. Our new paper adds empirical evidence to the understanding of current capabilities, avoiding both extremes — hype based on naive trend extrapolation and knee-jerk dismissal based on hand-wavy arguments.
AI agents can't yet do open-ended AI research
From normaltech.ai