Working on math AI at https://xitter.cf/t.co/u95v5xJnFC and telescope software at https://xitter.cf/t.co/Yx0Z8UGvEc. firstflagPOISONed. Formerly: Parse cofounder, Facebook, Google

Piedmont, California
Joined March 2008
Kevin Lacker retweeted
Reading all those recent beautiful essays by Terry Tao, Kevin Buzzard and @wtgowers, I could not resist, but write up my deeply personal perspective on how I perceive and see things: docs.google.com/document/d/e…
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Kevin Lacker retweeted
Starship will expand the aperture of physics research by placing much larger telescopes in orbit and giant ones on the Moon
Starship reached orbit for the first time on Monday. One of my favorite potential use cases is launching the next generation of space telescopes faster and with far fewer constraints. Today, engineers designing the largest space telescopes face extreme mass and volume limits that forces them to make telescopes lighter, foldable, and dependent on incredibly intricate deployment mechanisms, adding years of engineering complexity and increasing the risk of failure. Starship changes that tradeoff. Thanks to its massive payload capacity and volume, telescope builders could "convert risk into mass": build heavier, simpler observatories instead of optimizing every component around launch constraints. That could accelerate the next generation of space telescopes, and astrophysics research, by decades!
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For those saying we wouldn’t be know what to look for to see a Dyson sphere in a far galaxy, how about this? We can see >1 trillion galaxies. This is what one would like a few hundred thousand years into hitting super intelligence and starting to build Dyson spheres. I’m not even joking, I hope Roman finds something like this in the hundred billion new galaxies that it is about to observe.
A trillion trillion galaxies, each one with with a trillion stars and yet no evidence of Dyson spheres 🤔 @FermiExplorer
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Kevin Lacker retweeted
"Between 2018 and 2020... at the bottom of the distribution there was almost nobody. Just 0.14% tested below basic algebra... By 2022-23, more than one-third had severe math deficits, and the single most common score on the exam was zero." -- Zvezda Stankova, Teaching Professor of Mathematics at UC Berkeley
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Kevin Lacker retweeted
Gašper Beguš
@begusgasperAug 4
Since Aristotle, literary theory has studied texts and reception. We propose a new object of literary study: the latent spaces of an AI model trained on a single text. We call the method latent reading and apply it to the first case study: FinneganLM, trained on Joyce’s Finnegans Wake.
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Kevin Lacker retweeted
In the last week, multiple colleagues have expressed concern that generative AI will somehow destroy society's esteem for mathematics and mathematicians. Contrariwise, I conjecture the opposite. I've never seen the level of public fascination with math that we're seeing right now — weekly articles in major outlets; people outside the field teaching themselves arithmetic combinatorics; heck, even the owner of a local café recently asked me to explain the unit distance conjecture. If anything, this seems likely to renew students' excitement, uncover new applications, and open new frontiers — all of which should inure to the benefit of the field and of mathematicians. QED?
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Kevin Lacker retweeted
Prominent mathematicians as recently as the 17th century were proving amazing things, yet were still uncomfortable with negative numbers. Cardano called them “fictitious.” Pascal said that subtracting 4 from 0 is “utter nonsense.” Descartes had mixed feelings but called negative roots “false.” Leibniz said they are just a tools to guide one’s thinking, or an indication that the question with poorly formed.
What historical fact sounds fake but is true?
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Kevin Lacker retweeted
today we have an effortpost about AI and automated theorem proving (and some cool projects!)
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LLMs are teaching me incredibly obvious things about human intelligence that I'd nonetheless never thought much about before. We complain about LLMs forgetting bits of big complicated instructions, but of course, humans would do that too without being able to take careful notes, and in some sense, LLMs had nowhere to take notes until recently and yet seemed to do unexpectedly well. Ever wonder how people got anything done before they were both literate and had cheap paper to write down to-do lists? I would be lost without to-do lists, but they were literally impossible without fairly recent technologies, at least on a historical level. Imagine all the things you probably could not do without being able to write down a plan or a reminder, and then consider that for the bulk of the 200,000 years that there have been anatomically modern humans, no one could have written a simple to-do list for themselves. Even after the invention of writing, it was quite some time before most people were literate and writing media were cheap enough for the masses. It's remarkable how a tiny little technology like the to-do list, which feels incredibly primitive, can transform your abilities. Adding the ability to store just a few kilobytes of to-do items to a normal human suddenly transforms their productivity. And yet, we rarely even think about how much we depend on them, and how much we are forced to compensate for our poor memories using things like this. Sure, reference works and notes and all sorts of other external memories are critical to the way we function day to day, but we even can't reliably remember small things without low technologies like a calendar for appointments, or a grocery list scribbled down on scrap paper, or a list of to-do items. Our own contexts and abilities to do needle-in-a-haystack data searches in our memories are much poorer than we imagine. (And yes, I'm aware that ancient writers complained about the fact that literacy killed people's memories to some extent, but I'm pretty sure the reason people started relying on the crutch as soon as it became available was that only a talented few could reliably remember well enough to begin with. Most people were not Homer and could not recite epic poems from memory, and even the best almost certainly garbled what they were transmitting a bit every time.)
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Kevin Lacker retweeted
mmmmm 🤔 is this the future of theorem proving? i am very intrigued.
I'm happy to announce the launch of Acorn, a new theorem prover that includes an integrated AI. Theorem provers let you write mathematical proofs that are rigorously verified. But they are notoriously difficult to use. Acorn makes it easier, by using AI to fill in the details.
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Kevin Lacker retweeted
New release of the Acorn Prover, with a commonly requested feature: generics! Now you can prove theorems or define functions and structures with placeholder types.
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Kevin Lacker retweeted
#1 under appreciated piece of DeepSeek/R1 story is use of MIT open-source license. Startups, corporate developers, & hosting cos will LEAP at using it, precisely because it is one of the most open, permissive possible. Key difference from Llama. en.wikipedia.org/wiki/MIT_Li…
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Kevin Lacker retweeted
The subway map of the Solar System. In space, distance can be measured in terms of Delta-V, or change in velocity. Because Mars has a weaker gravity, it requires slightly less energy to travel from the Martian surface to Earth's GEO than it does to travel from Earth's surface to Earth’s GEO.
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Kevin Lacker retweeted
A book review of Tomorrow and Tomorrow and Tomorrow by Gabrielle Zevin. This is probably the first book review you will read that has absolutely no spoilers and that you will appreciate equally whether you have read the book or not (at least if you read to the end).
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It is time to build a gargantuan, self-assembling space telescope that will allow us to see distant alien planets in as much detail as we see the Moon. SpaceX-driven decreases in cost to orbit make this possible. Read the new article by @CJHandmer here: palladiummag.com/2024/10/18/…
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Our reputation as a leader in technology & innovation is because we embrace new ideas & serve as a sanctuary for research & development. With the slowest post-COVID economic recovery of any major US city, we shouldn't over regulate an industry so early. nytimes.com/2024/08/14/techn…
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Most interesting thing about the Lex Neuralink podcast is one of the guys describes that when the Neuralink subject moves a cursor on a screen, it actually moves before he expects it to, almost before he tries to move it
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Do you know what is America’s superpower ingredient ? most of these medalists of every nationality will be in America within ten years
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