Ben Brubaker

New York

Staff writer @QuantaMagazine covering computer science. Former freelance physics writer, ex-physicist. Same handle at bluesky and mastodon.

Articles

For Algorithms, a Little Memory Outweighs a Lot of Time

2 weeks ago | quantamagazine.org | Ben Brubaker

One of the most important classes goes by the humble name “P.” Roughly speaking, it encompasses all problems that can be solved in a reasonable amount of time. An analogous complexity class for space is dubbed “PSPACE.”The relationship between these two classes is one of the central questions of complexity theory. Every problem in P is also in PSPACE, because fast algorithms just don’t have enough time to fill up much space in a computer’s memory.
For Algorithms, a Little Memory Outweighs a Lot of Time

2 weeks ago | flipboard.com | Ben Brubaker

2 hours agoThe smart ring will also more accurately measure calories burned during exercise by factoring in your heart rate. Following the debut of the Oura Ring 4 last October, which featured improved accuracy for blood oxygen tracking and heart rate readings, the company has announced it’s introducing …
Por que modelos de linguagem, como os que turbinam o ChatGPT, intrigam tanto os cientistas?

1 month ago | estadao.com.br | Ben Brubaker

Normalmente, não se constrói uma máquina sem entender como ela funciona. Mas para os pesquisadores de inteligência artificial (IA) que criam grandes modelos de linguagem (LLMs), a compreensão é a única coisa que eles ainda não conseguiram. De fato, às vezes, o trabalho deles parece mais com jardinagem do que com engenharia. “Coloque uma semente de tomate no solo e você terá um tomateiro”, disse Martin Wattenberg, pesquisador de modelos de linguagem da Universidade de Harvard.
Why Pigeons at Rest Are at the Center of Complexity Theory

1 month ago | technewstube.com | Ben Brubaker

Tech News Tube is a real time news feed of the latest technology news headlines.Follow all of the top tech sites in one place, on the web or your mobile device.
Why Pigeons at Rest Are at the Center of Complexity Theory

1 month ago | wired.com | Ben Brubaker

The original version of this story appeared in Quanta Magazine. They say a bird in the hand is worth two in the bush, but for computer scientists, two birds in a hole are better still. That’s because those cohabiting birds are the protagonists of a deceptively simple mathematical theorem called the pigeonhole principle. It’s easy to sum up in one short sentence: If six pigeons nestle into five pigeonholes, at least two of them must share a hole. That’s it—that’s the whole thing.
Why Pigeons at Rest Are at the Center of Complexity Theory

1 month ago | flipboard.com | Ben Brubaker

Physicist Says He's Identified a Clue That We're Living in a Computer Simulation"The universe might work like a giant computer." What if gravity were informed by the way matter was arranged in the universe — and a sign that we …
Why Language Models Are So Hard To Understand

1 month ago | quantamagazine.org | Ben Brubaker

You don’t typically build a machine without understanding how it works. But for artificial intelligence researchers building large language models, understanding is about the one thing they haven’t achieved. In fact, sometimes their work feels more like gardening than engineering. “Put a tomato seed into the ground and you get a tomato plant,” said Martin Wattenberg, a language model researcher at Harvard University.
How Can AI ID a Cat? An Illustrated Guide.

1 month ago | quantamagazine.org | Ben Brubaker

Look at a picture of a cat, and you’ll instantly recognize it as a cat. But try to program a computer to recognize cat photos, and you’ll quickly realize that it’s far from straightforward. You’d need to write code to pinpoint the quintessential quality shared by countless cats in photos with distinctive backgrounds and taken from different camera angles. Where would you even begin?
To Make Language Models Work Better, Researchers Sidestep Language

1 month ago | quantamagazine.org | Anil Ananthaswamy |Ben Brubaker |Webb Wright |Janna Levin

Language isn’t always necessary. While it certainly helps in getting across certain ideas, some neuroscientists have argued that many forms of human thought and reasoning don’t require the medium of words and grammar. Sometimes, the argument goes, having to turn ideas into language actually slows down the thought process. Now there’s intriguing evidence that certain artificial intelligence systems could also benefit from “thinking” independently of language.
How a Problem About Pigeons Powers Complexity Theory

2 months ago | quantamagazine.org | Ben Brubaker

By January 2020, Papadimitriou had been thinking about the pigeonhole principle for 30 years. So he was surprised when a playful conversation with a frequent collaborator led them to a simple twist on the principle that they’d never considered: What if there are fewer pigeons than holes? In that case, any arrangement of pigeons must leave some empty holes. Again, it seems obvious. But does inverting the pigeonhole principle have any interesting mathematical consequences?

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Ben Brubaker @benbenbrubaker

12 Feb 25

RT @SimonsInstitute: In this episode of Polylogues, @benbenbrubaker and @boazbaraktcs discuss Boaz’s path TCS, theory and practice in crypt…

Ben Brubaker @benbenbrubaker

13 Jan 25

Can neural networks learn languages that are impossible for humans? My latest story for @QuantaMagazine explores how making language models worse at learning might make them better tools for linguists: https://t.co/VjvJO9ZQ5A

Ben Brubaker @benbenbrubaker

3 Jan 25

My latest in @QuantaMagazine: why theoretical computer scientists like to pose questions to imaginary black boxes: https://t.co/meZInYAbUg

Ben Brubaker

Articles

For Algorithms, a Little Memory Outweighs a Lot of Time

For Algorithms, a Little Memory Outweighs a Lot of Time

Por que modelos de linguagem, como os que turbinam o ChatGPT, intrigam tanto os cientistas?

Why Pigeons at Rest Are at the Center of Complexity Theory

Why Pigeons at Rest Are at the Center of Complexity Theory

Why Pigeons at Rest Are at the Center of Complexity Theory

Why Language Models Are So Hard To Understand

How Can AI ID a Cat? An Illustrated Guide.

To Make Language Models Work Better, Researchers Sidestep Language

How a Problem About Pigeons Powers Complexity Theory

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Emails

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X (formerly Twitter)