Princeton Computer Science @PrincetonCS

.@adjiboussodieng on @FRANCE24 today on the importance of AI development and education in Africa. "Africa is a consumer of AI rather than a creator."

Julien Fanciulli @julienfanciulli

13 hours ago

Une colonisation numérique en #Afrique ? "L'Afrique est consommatrice d'#IA plutôt que créatrice" @adjiboussodieng #AutourdumondeF24 #F24 #intelligenceartificelle

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Graves said she was grateful for Princeton’s support in her cross-disciplinary scholarship. “I think it’s really wonderful how Princeton makes it possible for students to find their own path this way,” she said. “You don’t have to just do one thing."

Graves ran 43,470 sentences of Yorùbá text through both a syllable-based statistical model and a sequence-to-sequence LLM, repeating the test several times. The statistical model proved to be more accurate, while the LLM had a higher error and hallucination rate.

Nora Graves graduated from @Princeton in May with a major in computer science and minors in linguistics and German. Fascinated by the puzzle of language, she wrote a thesis that compared automated approaches to adding diacritics to the Yorùbá language. bit.ly/4ewoJr1

Assistant professor of @PrincetonCS @adjiboussodieng has won a CAREER Award from @NSF and will use the grant to build AI methods for discovering new molecules and materials: bit.ly/3QKyBFF

“I made some phenomenal friends in the computer science department,” said Khoretonenko. And each became interested in different areas of computer science. “It’s really wonderful to see everyone finding their own path.”

Khoretonenko learned two very important lessons as an undergrad, he said. The first was to appreciate community: “perhaps even more important than the work you do is the people that you do it with." The second was to build a habit of learning: “curiosity requires practice."

At the end of May, Alexander Khoretonenko graduated from Princeton University with a degree in computer science. Soon, he will begin working in consulting at @OliverWyman in New York City.

📢 NEW essay: the narrative that AI is replacing software engineers seems to be based on AI-washing of layoffs. Among the many lines of evidence: New York State requires firms to disclose which layoffs were due to AI. When there are legal consequences to lying, almost no company blames AI. The best data suggests that software engineer employment in the U.S. is still growing, though slightly more slowly compared to a no-AI counterfactual world. But even this doesn’t account for increased entry into entrepreneurship. Why haven’t AI agents replaced software engineers? Many kinds of knowledge work, including software development, can be seen as a “decide-execute-deliver sandwich”. AI compresses the middle but the other two layers resist automation in a way that will not be overcome by capability improvements alone. In 2026, the middle has already been squeezed and there isn’t much room for further compression, so there isn’t a future capability leap that will cause discontinuous impacts, either. The essay also has a detailed breakdown of the difference between vibe coding and agentic engineering. Conflating the two has unfortunately led to a lot of confusion. We acknowledge that there’s a lot of uncertainty about the future. But we think the unknowns are more about how we will define and carve up roles and who can adapt to the changing needs, and less about whether software engineering skills and judgment will remain in demand (they will). Given that the AI-capabilities-cause-mass-layoffs narrative seems to be false even in a sector with very few regulatory barriers, we think most other professions are likely to be even more cushioned. (The claim isn’t that automation never displaces jobs, but that there are many downstream links in the causal chain, and that we have collective agency to act on those downstream decision points to ensure better outcomes for workers.) This essay by me and @sayashk is the first in a series. Feedback is welcome! We hope that our unique vantage point (leading an AI agent evals research group + fluency with the labor economics literature + the "normal technology" framework for understanding AI impacts + being coders ourselves and well connected to the software engineering community) gives us a way to bring complementary perspectives together for a deep dive into how AI is transforming the profession, in a way that hasn't been done before. Read the essay here for lots of other details: normaltech.ai/p/why-ai-hasnt…

Working in the Princeton Visual AI Lab and advised by @orussakovsky, Beeson was able to combine his interests in squash and computer science, developing methods for reconstructing 3D squash ball trajectories from 2D video of squash matches. This project became his senior thesis.

At Princeton, Beeson was a member of the varsity squash team and was named a Scholar-Athlete by the College Squash Association. One of the most important things he learned at Princeton, Beeson said, was “how to incorporate my passions into my work.”

At the end of May, David Beeson ‘26, graduated from @Princeton with a degree in computer science. In the fall, he will enroll at the @UniofOxford to pursue a master’s degree in computer science with a specialization in artificial intelligence.

📱 Researchers at @PrincetonCITP have created a social media tool that allows users to build their own social media feeds from scratch. bit.ly/4exBLFO

The Initiative for CryptoCurrencies and Contracts (@initc3org) gathered experts from industry and academia to create a survey on the intersections between crypto and AI. CS professor Matt Weinberg and alum Maryam Bahrani both contributed. Check out the survey results👇

IC3 @initc3org

2 weeks ago

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.@adjiboussodieng, an expert in artificial intelligence, has won an @NSF CAREER Award, one of the top honors for early career faculty. Read more from @PrincetonCS: cs.princeton.edu/news/dieng-win…

🚨New preprint!🚨 In a randomized field experiment in a 300-level machine learning course, teaching assistants received AI-assisted feedback drafts after grading student submissions. Did AI help them provide more feedback when feedback was optional? A thread 🧵

Thank you to the United States National Science Foundation (@NSF) for believing in the research we are pioneering @Vertaix_: a new paradigm for #AI centered on discovery. Current AI runs into a problem I'll call 'mode collapse' which prevents it from genuine scientific discovery. My group will continue to work on a new AI paradigm called "Investigative Intelligence" that will enable novel discoveries by mitigating mode collapse. This work is based on the work we've been doing around diversity, which I believe to be the right primitive for discovery. This award would not have been possible without the amazing grad students, postdocs, and collaborators I have had the chance to work with. Thank you all🧡 #VendiScore #AI #II #Discovery #Science

Princeton Computer Science @PrincetonCS

2 weeks ago

.@adjiboussodieng has won a CAREER award from the @NSF, a top honor for early career faculty! Dieng is working to establish a new paradigm for AI, transforming it into an engine for scientific exploration that can uncover revolutionary new materials. bit.ly/4udRPRK

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.@adjiboussodieng has won a CAREER award from the @NSF, a top honor for early career faculty! Dieng is working to establish a new paradigm for AI, transforming it into an engine for scientific exploration that can uncover revolutionary new materials. bit.ly/4udRPRK

Our own @tri_dao!

Brady Long @thisguyknowsai

2 weeks ago

A PhD student at Stanford looked at how every transformer model on Earth was computing attention and realized the entire industry was running into a wall that was not about compute. It was about memory. He sat down with four collaborators in 2022 and wrote an algorithm that fixed

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As an undergrad he also went to Anthropic’s first alignment hackathon with Princeton’s AI Alignment Club. That trip inspired his senior thesis on how to make LLM systems more reliable in unique government environments — a problem he will now be working on full-time.

Zhou said the most important thing the CS department taught him was how to learn. Approaching new, complex ideas is a skill that he uses every day. “Princeton does a great job of giving us the tools to be both deeply technical and broadly versatile,” he said.

Last week, Brian Zhou graduated from @Princeton with a degree in computer science. Soon, he will begin work as an engineer at @cognition, helping to build AI tools for government.