My 2023 snapshot:
* I went from zero AI experience to writing my first research paper thanks to @PetarV_93 ๐, presenting it @neur_reps (๐ธ @heyu0208).
* Iโve visited some wonderful places ๐บ๐ธ #NeurIPS2023 & ๐ญ๐ท.
I also wanted to shoutout @gordic_aleksa and his community members!
we really have reached peak mech interp when I am going to give a seminar at my old uni and there's a seminar in the same building the hour before that would have plausibly shared ~1/4 of the content
Announcing new ARENA material: 8 new exercise sets on alignment science, interpretability & AI safety - each containing 1-2 days of structured, hands-on content replicating key papers in the field.
All open source on a public GitHub, and available for study. Here's what's in it:
@WilliamsF1@AnthropicAI@claudeai I donโt think we need the AI benchmarks no more. F1 should be the new AI race. We got @GeminiApp in the papaya car, whoโs sponsoring the other teams? ๐๏ธ
started teaching geometric deep learning at cambridge for the fifth year running!
no pics were taken this time, but kind messages from our students are even better ๐
Another year of 'Machine Learning with Graphs' at the School of Computer Science and AI at @TelAvivUni has come to an end, and hereโs a short summary video of me explaining Graph Neural Networks with my hands ๐
This year I had around 80 students from across Computer Science, Math, and Electrical Engineering who came to explore the magic of Graph Learning.
We wrapped up with nearly 30 final research projects, and it was truly inspiring to see students come up with novel, creative ideas, combining graph methods in diverse domains and leveraging their own unique expertise.
Itโs always fascinating to see how graph modeling can enhance performance or solve challenges in almost every field. While some ideas didnโt fully work out (as research often goes!), many did, and I genuinely hope to see some of them published soon. Well done to all the students!!!
Once again, I have to say that TAU students are simply brilliant, curious, and incredibly hard-working.
Next year, Iโll continue lecturing as a Teaching Fellow at CS@TAU and Iโm already excited about the many updates I plan for the course (Graph Foundation Models are coming ๐).
affiliated lectureship @Cambridge_Uni extended for a fifth consecutive year!!
perhaps @pl219_Cambridge and i can do sth special for this year's geometric dl course... ๐งโ๐ซ
The above truly changed my life and overall career direction!
Soon, I will be sharing some exciting news and my next steps into AI research! ๐๐ฃ
(3/3)
Did okay at Undergrad; then SWE in industry for 4 years. Did some soul searching and decided I wanted to do something _impactful_!
Fell in love with education again, and start self-learning AI/ML.
Cold-emailed @PetarV_93, and he kick started my research journey. โค๏ธ
(1/3)
Exciting, mechanistic interpretability has a dedicated lecture in the syllabus of a Cambridge CS masters course! The field has come so far in the past few years โค๏ธ
Check out this blogpost from @ffabffrasca and the GLOW reading group on the future of graph learning!
Iโve also contributed and my main take is - its actually working and its an exciting moment to work on applications!
@jxmnop > - im working up the courage to say hi to yann lecun
just do it! i sent a cold email to yoshua bengio and it was literally career-changing.
whether you're just starting out or a turing award winner, we're all people :)