Some more

- Cambridge Centre for Computing History - https://www.computinghistory.org.uk/

- London Museum for Science - Babbage's Difference Engine https://www.sciencemuseum.org.uk/objects-and-stories/charles...

- National Museum of Computing (near Bletchley Park Museum) https://www.tnmoc.org/

- Bletchley Park Museum https://www.bletchleypark.org.uk/

- Manchester Museum (Manchester Baby) https://www.scienceandindustrymuseum.org.uk/whats-on/meet-ba...

I visited these all last year in a single trip to the UK and it was incredible. I can recommend it to anyone who has spent some time thinking about the history of computing.

Bletchley is great! I need to go again

Second the Cambridge Centre for Computing History

I'd like to call out the work from Nada Amin in this area:

Dafny and verification-aware programming, including proof by induction to verify properties of programs (for example, that an optimizer preserves semantics). Dafny Sketcher (https://github.com/namin/dafny-sketcher)

Multi-stage programming, a principled approach to writing programs that write programs, and its incarnation in multi-stage relational programming for faster synthesis of programs with holes—with the theoretical insight that a staged interpreter is a compiler, and a staged relational interpreter for a functional language can turn functions into relations running backwards for synthesis. multi-stage miniKanren (https://github.com/namin/staged-miniKanren)

Monte Carlo Tree Search, specifically the VerMCTS variant, and when this exploration-exploitation sweet spot is a good match for synthesis problems. VerMCTS (https://github.com/namin/llm-verified-with-monte-carlo-tree-...), and Holey (https://github.com/namin/holey).

Nada is the best! Don't forget the mind bending https://dl.acm.org/doi/10.1145/3158140 (not quite on topic, but in the multi-stage rabbit hole)

Very Interesting; thanks for the pointer.

Nada Amin website - https://namin.seas.harvard.edu/

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Thanks for your article. The references section was interesting.

I'll add to the discussion a 2018 Nature letter: "Vector-based navigation using grid-like representations in artificial agents" https://www.nature.com/articles/s41586-018-0102-6

and a 2024 Nature article "Modeling hippocampal spatial cells in rodents navigating in 3D environments" https://www.nature.com/articles/s41598-024-66755-x

And a simulation in Github from 2018 https://github.com/google-deepmind/grid-cells

People have been looking at spacial awareness in neurology for quite a while. (In terms of the timeframe of recent developments in LLMs).

> Anything more complex than a few lines, you can just copy it from lib\ folder of the CD-ROM. There's a component for everything. You want to left-pad a string?

This got me.

I checked and there's also lib\str\basic\pad\right - they really thought of everything!

They started with a different, more brilliant idea, of using human brains as a giant neural net, then backed away from that: https://news.ycombinator.com/item?id=12508832

oh wow that's cool. I do understand why they moved away from it. Battery is waaaayyyyy easier to understand for the layman and lay-kid (me).

“Zero success” seems a bit strong. People have been able to get 96% accuracy on MINST digits on their local machine. https://norse.github.io/notebooks/mnist_classifiers.html I think it may be more accurate to say “1970s level neural net performance”. The evidence suggests it is a nascent field of research.

Quibble: Both Clojure and Scala have a Software Transactional Memory implementation, and the original Clojure Ant demo showed this.

I did the tour of Bletchley Park today and my Tour Guide said he'd met Betty Webb, that he mourned her loss, and that when he had met her at a reunion, she had remained tight-lipped about what her work had been on.

> These “limitations” inhibit truly intelligent behavior in machines, LeCun says. This is down to four key reasons: a lack of understanding of the physical world; a lack of persistent memory; a lack of reasoning; and a lack of complex planning capabilities.

aligns with (or is based on) Demis Hassabis' assessment from yesterday on missing cognitive capabilities for AGI: long-term memory, reasoning, hierarchical planning. He then goes on to suggest scientific creativity may be essential.

https://www.youtube.com/watch?v=yr0GiSgUvPU https://news.ycombinator.com/item?id=42817089