My Book Is Out! Why I Wrote It and How You Can Help Bridging the Gap Between Deep Learning and Causal Inference—A Code-First Approach

newsletter.altdeep.ai/p/my-book-is... The connection between genAI and causality is obvious but could nevery find any good learning material that made the connection.

So I wrote a book

Glad to hear this! Was hoping the 2nd chapter primer would hit but wasn't sure.

Would love to meet if you have the time.

My team at
@MSFTResearch
is seeking an intern interesting in task-specific distillation of #largelanguagemodels. Join us! Apply now: jobs.careers.microsoft.com/global/en/jo... #AIInternship

My team at MSR is hiring an intern to explore the intersection of structured probabilistic reasoning and LLMs, and generative AI in general. Touches on causal reasoning, Bayesian modeling, and probabilistic ML. Join us! jobs.careers.microsoft.com/global/en/jo... #AIResearch #Internship

Modeling rapid language learning by distilling Bayesian priors... Humans can learn languages from remarkably little experience. Developing computational models that explain this ability has been a major challenge in cognitive science. Bayesian models that build...

I forget if I've already shared this but I'm so obsessed with this paper from the Toms (McCoy & Griffiths):

arxiv.org/abs/2305.14701

nvm. I realized your original post was not about a Bayesian statistic.

Anyone know of any work that evaluates the relationship between LLM prompting strategies and generalizability? Eg, if one applies a bunch of prompting hacks to ramp up accuracy on a benchmark, you might be sacrificing the ability for that prompt to generalize to new settings?

Ever heard of Bayesian statistics Loo or Waic?

I got #COVID19. I have one toddler. We're a two-parent household with external help, so I can self-quarantine and just wait to stop feeling shitty while my wife does heavy lifting.

My heart weeps for parents who had to do this alone, especially during the pandemic.

✋