chewxy

BigQuery has that and I've been loving using it since they introduced it

> Limited training data, as compared to kanguages like Python or javascript.

I use my own APL to build neural networks. This is probably the correct answer, and inline with my experience as well.

I changed the semantics and definition of a bunch of functions and none of the coding LLMs out there can even approach writing semidecent APL.

Maybe read the paper first?

> This study asked whether Large Language Models (LLMs) understand sentences in the minimal sense of representing “who did what to whom”. In Experiment 1, we found that the overall geometry of LLM distributed activity patterns failed to capture this information: similaritiesbetween sentences reflected whether they shared syntax more than whether they shared thematic role assignments. Human judgments, in contrast, were strongly driven by this aspect of meaning.

> In Experiment 2, we found limited evidence that thematic role information was available even in a subset of hidden units. Whereas activity patterns in subsets of hidden units often allowed for significant classification of whether sentence pairs had shared vs. opposite thematic role assignments, the effect sizes were small; even the best-performing case appeared to lag behind humans, and its representation of thematic roles did not seem robust across syntactic structures.

> However, thematic role information was reliably available in a large number of attention heads, demonstrating LLMs have the capacity to extract thematic role information. In some cases, information present in attention heads descriptively exceeded human performance.

Barry Jay's got an upcoming paper at PEPM regarding typed tree calculus. Good read too.

Thanks :)

At this point I'm writing mostly for myself. GTM strategies for novels... that's an interesting way to think about things. I've not thought about it just yet. Happy to hear if you have any ideas tho.

I'm working on my scifi novel. I had started writing it when LLMs started taking off - I had been doing AI for two decades and I was well-placed to be in a good position to profit with the rise of LLMs, but I ended up gaining nothing much and I was depressed about it - so I started writing instead. Been picking at it for about a year before befriending an editor who encouraged me to keep writing. He's helped me developmentally edit it to a point I am now ready to work on my second draft.

It's a hard scifi novel with mild existential horror tones that is borne mostly of maths jokes. At one point the main character tries to escape the matrix (reality). But the matrix is defective, so the best way out was to orthogonalize the subspace and reduce the matrix to its eigenbasis instead. Most of the scenes are based on similar maths jokes.

Tentative name is Diagonalization of the Meta (I had previously called it The Metaverse).

Not really, this is actually pretty readable

I told a variant of the original Little Mermaid story as part of a school outreach program. The kids came to the conclusion that God wasn't a fair being because he didn't give mermaids souls. I walked away satisfied that my little counterprogramming against catholic school indoctrination might have worked. I wasn't invited back (at least for school year 2024).

there's also a good paper - Can a neuroscientist understand a microprocessor - by Kording's lab which is also an excellent read.

Dana Angluin's group were studying chat systems way back in 1992. There even was a conference around conversational AI back then.