Hacker News: andrewgleave

New comment by andrewgleave in "The zipper is getting its first major upgrade in 100 years"

andrewgleave — Sun, 19 Oct 2025 18:12:16 +0000

My Lindy alarm has gone off!

New comment by andrewgleave in "NVIDIA DGX Spark In-Depth Review: A New Standard for Local AI Inference"

andrewgleave — Tue, 14 Oct 2025 08:22:44 +0000

Looks like MLX is not a supported backend in Ollama so the numbers for the Mac could be significantly higher in some cases.

It would be interesting to swap out Ollama for LM Studio and use their built-in MLX support and see the difference.

New comment by andrewgleave in "Legends of the games industry: Roger Dean"

andrewgleave — Mon, 13 Oct 2025 19:15:33 +0000

For any stamp collectors here, the Isle of Man Post Office [1] has just issued an official set of 6 Roger Dean and Rick Wakeman stamps [2]:

[1] https://iomstamps.com/collections/wakeman [2] https://www.bbc.co.uk/news/articles/clyqe679gqno

New comment by andrewgleave in "Vibe engineering"

andrewgleave — Wed, 08 Oct 2025 09:13:02 +0000

Theory building is the secret sauce, and all variants of "this is how to use AI effectively" I've seen are inferior to the epistemologically sound theory Naur outlines in his paper.

New comment by andrewgleave in "AI tools I wish existed"

andrewgleave — Tue, 30 Sep 2025 06:53:27 +0000

Feynman said, "The first principle is that you must not fool yourself - and you are the easiest person to fool" when talking about science, but it also applies to the properties of LLM output.

New comment by andrewgleave in "Cosmic simulations that once needed supercomputers now run on a laptop"

andrewgleave — Fri, 26 Sep 2025 11:15:47 +0000

Not cosmological but yesterday Apple released an interesting protein folding model with 3B param transformer-based arch which runs on M-series hardware and is competitive with state-of-the art models. [1] Code [2]

[1] https://arxiv.org/pdf/2509.18480 [2] https://github.com/apple/ml-simplefold

New comment by andrewgleave in "AI was supposed to help juniors shine. Why does it mostly make seniors stronger?"

andrewgleave — Sun, 21 Sep 2025 17:08:05 +0000

Yes. Juniors have a lack of knowledge about how to build coherent mental models of problems whose solution will ultimately be implemented in code, whereas seasoned engineers do.

Seniors can make this explicit to models and use them to automate "the code they would have written," whereas a junior doesn’t know what they would have written nor how they would have solved it absent a LLM.

Same applies to all fields: LLMs can be either huge leverage on top of existing knowledge or a crutch for a lack of understanding.

New comment by andrewgleave in "EU court rules nuclear energy is clean energy"

andrewgleave — Sat, 13 Sep 2025 08:46:26 +0000

For anyone interested in the history of Sellafield and its role in reprocessing, "Britain's Nuclear Secrets: Inside Sellafield" on BBC 4 at the moment is worth a watch. Presented by Jim Al-Khalili.

https://www.bbc.co.uk/programmes/b065x080

New comment by andrewgleave in "AR Fluid Simulation Demo"

andrewgleave — Thu, 04 Sep 2025 10:16:00 +0000

Reminds me of Brett Victor's demo of projected AR turbulence around a toy car at Dynamicland. Only a short clip, but you get the idea: https://youtu.be/5Q9r-AEzRMA?t=47

New comment by andrewgleave in "Anthropic raises $13B Series F"

andrewgleave — Tue, 02 Sep 2025 21:45:04 +0000

> “There's kind of like two different ways you could describe what's happening in the model business right now. So, let's say in 2023, you train a model that costs 100 million dollars. > > And then you deploy it in 2024, and it makes $200 million of revenue. Meanwhile, because of the scaling laws, in 2024, you also train a model that costs a billion dollars. And then in 2025, you get $2 billion of revenue from that $1 billion, and you spend $10 billion to train the model. > > So, if you look in a conventional way at the profit and loss of the company, you've lost $100 million the first year, you've lost $800 million the second year, and you've lost $8 billion in the third year. So, it looks like it's getting worse and worse. If you consider each model to be a company, the model that was trained in 2023 was profitable.” > ... > > “So, if every model was a company, the model is actually, in this example, is actually profitable. What's going on is that at the same time as you're reaping the benefits from one company, you're founding another company that's like much more expensive and requires much more upfront R&D investment. And so, the way that it's going to shake out is this will keep going up until the numbers go very large, the models can't get larger, and then it will be a large, very profitable business, or at some point, the models will stop getting better. > > The march to AGI will be halted for some reason, and then perhaps it will be some overhang, so there will be a one-time, oh man, we spent a lot of money and we didn't get anything for it, and then the business returns to whatever scale it was at.” > ... > > “The only relevant questions are, at how large a scale do we reach equilibrium, and is there ever an overshoot?”

From Dario’s interview on Cheeky Pint: https://podcasts.apple.com/gb/podcast/cheeky-pint/id18210553...

New comment by andrewgleave in "Getting good results from Claude Code"

andrewgleave — Fri, 08 Aug 2025 21:10:05 +0000

Yeah. Read “Programming as Theory Building” by Naur [1] to understand why you need to still need to develop a theory of the problem and how to model it yourself lest the LLM concoct (an incorrect) one for you.

[1] https://gwern.net/doc/cs/algorithm/1985-naur.pdf

New comment by andrewgleave in "Ask HN: What are you working on? (March 2025)"

andrewgleave — Mon, 31 Mar 2025 08:34:31 +0000

I recently built a quick SwiftUI app to pin quotes and posts from X to my home screen.

I found I was liking/bookmarking insightful content on X I rarely saw again and wanted a way to resurface them somewhere I would see multiple times per day.

Can import from X via share sheet or manually enter them. It's minimal, but I've found having:

"i hate how well asking myself "if i had 10x the agency i have what would i do" works"

there every time I unlock my phone, was worth the development effort.

https://apps.apple.com/gb/app/lumatta/id6740705796

New comment by andrewgleave in "Bayesian Epistemology (2022)"

andrewgleave — Mon, 03 Feb 2025 10:38:47 +0000

Going to leave this here: https://plato.stanford.edu/entries/popper/#GrowHumaKnow

New comment by andrewgleave in "Ask HN: What's the most creative 'useless' program you've ever written?"

andrewgleave — Wed, 23 Oct 2024 08:35:48 +0000

This is very similar to when I used OpenCV to read the angle of a cardboard knob I pinned on the wall in my office to change the volume on Spotify!

New comment by andrewgleave in "Richard Feynman and the Connection Machine (1989)"

andrewgleave — Sat, 07 Sep 2024 20:51:09 +0000

"""But what Richard hated, or at least pretended to hate, was being asked to give advice. So why were people always asking him for it? Because even when Richard didn't understand, he always seemed to understand better than the rest of us. And whatever he understood, he could make others understand as well. Richard made people feel like a child does, when a grown-up first treats him as an adult. He was never afraid of telling the truth, and however foolish your question was, he never made you feel like a fool."""

This is why he is spoken of with such reverence and why his insights have profoundly impacted both scientists and non-scientists alike. Few Nobel laureates have achieved such popular influence.

New comment by andrewgleave in "ChatGPT consumes 25 times more energy than Google"

andrewgleave — Tue, 14 May 2024 16:38:33 +0000

Unsurprisingly, this pessimistic and shortsighted take emanates from a newspaper in heart of the EU...

New comment by andrewgleave in "On the Double-Slit Experiment and Quantum Interference in the Wolfram Model (2020)"

andrewgleave — Thu, 07 Mar 2024 12:25:19 +0000

And by the third slit simulation they seem to have refuted their own hypothesis.

New comment by andrewgleave in "How Gödel's proof works (2020)"

andrewgleave — Thu, 23 Nov 2023 22:47:07 +0000

You may find Constructor Theory interesting. An attempt to express physical laws solely in terms of possible and impossible transformations.

“These include providing a theory of information underlying classical and quantum information; generalising the theory of computation to include all physical transformations; unifying formal statements of conservation laws with the stronger operational ones (such as the ruling-out of perpetual motion machines); expressing the principles of testability and of the computability of nature (currently deemed methodological and metaphysical respectively) as laws of physics; allowing exact statements of emergent laws (such as the second law of thermodynamics); and expressing certain apparently anthropocentric attributes such as knowledge in physical terms.”

https://arxiv.org/abs/1210.7439

New comment by andrewgleave in "The Ends of Knowledge"

andrewgleave — Thu, 05 Oct 2023 14:47:31 +0000

Perversely, this "settled knowledge" nonsense actively inhibits the growth of knowledge and just leads to the "justified true belief" swamp...

All we have is our current best explanations/understanding. We use them to make progress until we find a problem with it – something it fails to account for, something it makes an incorrect prediction for etc.

Then, we attempt to conjecture new explanations which solves the new problem while still accounting for all the useful aspects of the old theory.

That is knowledge creation, and also progress.

[Edit]

New comment by andrewgleave in "The Ends of Knowledge"

andrewgleave — Thu, 05 Oct 2023 13:59:22 +0000

It's just blind prophecy and therefore a fiction.

There is no way to predict the growth of future knowledge. If there was it would be equivalent to already having said knowledge.

Whether people do or don't create some specific piece of knowledge is solely down to what problems they have, and whether we choose (individually or as a species) to attempt solve them or not.

Our fallible knowledge is the byproduct of us solving problems.