Our thoughts on symbols in mental representation, given today's advanced neural nets, w/ Griffiths Computational Cognitive Science Lab Tom McCoy Brown NLP Taylor Webb Major open Q: Can neural nets learn symbol-related abilities *without* training on massive, unrealistic data generated from symbolic systems?

Our new preprint explores how advances in AI change how we think about the role of symbols in human cognition. As neural networks show capabilities once used to argue for symbolic processes, we need to revisit how we can identify the level of analysis at which symbols are useful.

People ask me what my take on AI is these days, so here's a thread on a new idea I dont think anyone who's working in AI is really thinking about. 1/12

"Hello world!" sounds like a word followed by a crossword clue for that word: "Hell: Low world"

Good time to read Embers of Autoregression! pnas.org/doi/10.1073/pn…

The legend lives on from Vaswani on down Of the model trained by grad descension The model, it is said, rekindled what it read In the Embers of Autoregression!

Our new lab for Human & Machine Intelligence is officially open at Princeton University! Consider applying for a PhD or Postdoc position, either through the depts. of Computer Science or Psychology. You can register interest on our new website lake-lab.github.io (1/2)

Highly recommend working with Brenden if you're interested in the CogSci/AI intersection!