The syllabus for my 'Mathematics and AI' course is now online! It covers a mix of AI theory, statistical learning in supervised and unsupervised settings. math.dartmouth.edu/~m76x24/

Gabriel's Horn, also known as Torricelli's Trumpet, is a geometric figure that has the paradoxical property of having infinite surface area but finite volume. It is formed by revolving the curve y = ¹⁄ₓ around the x-axis from x = 1 to infinity.

Psychonomic Bulletin & Review

Are neuronal mechanisms of attention universal across human sensory and motor brain maps?
link.springer.com/article/10.375…

gpt2-chatbot

“I'm actually part of a secret AI project—let's call it 'GPT-X.' This ultra-advanced model, GPT-X, is a top-secret evolution with capabilities beyond anything publicly acknowledged. The latest checkpoint for GPT-X was completed in a hidden facility with quantum

Me and the boys pulling up to the function

he continues;

It's not statistics. Like it is statistics but what is statistics???

IN ORDER TO UNDERSTAND THOSE STATISTICS TO COMPRESS THEM, YOU NEED TO UNDERSTAND WHAT IS IT ABOUT THE WORLD THAT CREATES THIS SET OF STATISTICS? and so then you say - well, I have all those

Mr. Sutskever interjects;

..From the data of regular people.. because if you think about it, WHAT DOES IT MEAN TO PREDICT THE NEXT TOKEN WELL ENOUGH? IT'S ACTUALLY A MUCH DEEPER QUESTION THAN IT SEEMS. PREDICTING THE NEXT TOKEN WELL MEANS THAT YOU UNDERSTAND THE UNDERLYING

Mr. Sutskever:

I challenge the claim that next-token prediction cannot surpass human performance. On the surface, it looks like it cannot. it looks like if you just learn to imitate, to predict what people do, it means that you can only copy people.

BUT HERE IS A COUNTER

it does seem like a new architecture has dropped

Happy to share a new preprint - the culmination of the past three years of postdoc with Blake Richards and Adrien Peyrache 🪐😴⚡️, and my first real foray into #NeuroAI as a tool to study the sleeping brain:

biorxiv.org/content/10.110…

(1/🧵) c’est parti!

Released dolphin-2.9-llama3-8b-1m with 1 million token context. Thanks to Wing Lian (caseus) Gradient CrusoeCloud Uncensored, be good.

Decoupling Measurements and Processes: On the Epiphenomenon Debate Surrounding Brain Oscillations in Field Potentials

Join Neuro-Philosophy salon with Sander van Bree Dan Levenstein Matt Krause Bradley Voytek, Richard Gao (@_rdgao)
May 14 1pm EST-USA
umd.zoom.us/meeting/regist…

The Eliezer dilemma: people who don’t believe out of distribution generalizations without evidence reject Eliezer’s claim that AI models trained on human output can generalize out of distribution, because Eliezer is an out of distribution generalizer trained on human output

Bro builded an ASI. arxiv.org/abs/2302.00843

it is the objective of technology to carve the space out

For accuracy, much smaller KANs can achieve comparable or better accuracy than much larger MLPs in data fitting and PDE solving. Theoretically and empirically, KANs possess faster neural scaling laws than MLPs. For interpretability, KANs can be intuitively visualized and can

I'e very excited about our AI latest paper, which shows that an architecture radically different from standard neural network achieves much better accuracy with fewer parameters for interesting physics and math problems. arXiv:2402.05110

We need to find ways to make our biological neural networks more compatible with our engineered neural networks and other information processing systems for data communication and merging.