GEOMETRIC DEEP LEARNING BLUEPRINT

Heard rumors about this MLST - and missed it when it came out. Looking forward to the talk!

Geometric learning, life ? 🤣🤣

Excellent content again. Damn another book to read !

Y

hey Street Talk crew. Watching out for the next one ✌️

Waiting for your new videos.

During my study of Statistics, ML and DL I never understood the connection between different NN architectures - they simply pop up without any history or proofs. Shut up, learn and memorize. Therefore my professors in ML do not earn my respects, because they do not real understand what they are teaching.

I like thank you for bringing of the fundamental understanding of the zoo of DNN models. I lost the intuition for long time about DNN models. Again thank you for the clarity.

As a lot of this is quite over my head. BUT, I'm using OpenAI's playground to have the concepts I don't understand explained to me. And it works extremely well. Ideas like gage symmetry and such now make sense to me. On a very broad level of course, but still. An AI explaining tome the concepts that went into it's own creation! Truly amazing!

it would be extremely helpful for phd students who are very busy if you can make a highlight video of this that contains only the most eseential academical discussions done in this video.

This episode is beyond good... Finally, some visionaries turning ML from its alchemy stage into proper science!

I am enjoying it thoroughly. Its fascinating to see different perspectives from all GDL experts!

Symmetry is all you need

It's my 1st time here. Your show already brings me wow!!! Thank you!!

Where do I find the learning courses that you mentioned? :)

Thanks for podcasts. It helps me with other stuff i found to be in touch with ML, Ai, and neuroscience. Before this new hype around ML and transformers i didnt know that i will found that i will be in love with neuroscience

Absolutely amazing episode! When you eavesdrop on a topical conversation of such detail you are almost bound to pick up some wisdom and sync in with the speakers at least for some time (prerequisite you have some background)

Remarkable channel. Inspiring, challenging, eye opening... I have been following it for months and I love it. Thank you

Teaching a computer to recognize natural laws as it computes and extrapolate relevance.

A grande unified theory is needed.

Cellular automata. Stephen wolfram ,I think , is working on that.

Now getting close to the end off your video , I realize that the" architecture" is the grande unified theory. Got excited , jumped the gun...

I still think that coming from an understanding of a thing ,it is much easier to determine the way to think about it. BIOS
Which are rules...I'm getting interested in computer science.

That was really interesting.

I really enjoyed this one the second time around. One thing, the transformer is mostly a pyramidal graph network -- just FYI.It's a fully-connected Feed Forward NN A pyramidal graph is a type of graph that has a hierarchical structure where nodes are organized into layers. The nodes in each layer are connected to all nodes in the layer above it. Pyramidal graphs have been used in various applications such as object detection1, EEG classification2, and spatial significance exploration3

Love the armchair :) What is it!

Honestly, this channel has such a great format. It's the perfect mix between a podcast and a documentary. It reminds me a lot of Sixty Symbols or Numberphile but for ML instead of physics and maths

Fantastic, thank you. (Minor improvement suggestion - might just be me, but I would prefer if the music was not constantly playing.)

old edited

The content was great! The editing was a bit disjointed. I love long form videos like this, but a touch more planning may have made for a smoother experience.

the only deep question about AI is one never raised, which is whether the Galilean metaphor that the universe is a book written in mathematics is still relevant, I think it is not, the metaphor is dead. Then the question is whether AI has the potential to mutate beyond the Galilean metaphor, like the scholasticism that preceded it the worldview embedded in the metaphor has exhausted itself. Nothing in AI supports the metaphor, if anything it negates it. Which is why AI's potential to inaugurate a new era is really the only interesting philosophical question to ponder.

wumao

Hey can you educate me on why this is being ridiculed so much by the comment section😂im new to both religions and it would be helpful for me in my studies

I enjoyed watching it very much!!!. Thanks.🙂

I am so happy!!!!!!!!!!! thank tou so much

One year after, still one of my favorite episode, with the Chomski one

Wow

Okay Tim... I have a question worthy of your intellect and imagination.

Granting arguendo the proposition that we operate within a carefully designed simulation, is it conceivable that the manifold hypothesis illustrates an intentionally implemented efficiency in our computational regime?

Otherwise put, is the low dimensionality of crucial correlations and symmetries in source data an artificially induced property of our technical methodology in some sense?

If proper pedagogy compels the sim architects to deploy logic that is never compromised by later learning--but the sim requires some mechanism for invisibly adjusting the computational reach of our algorithms--then would it not be logical to establish that control inside the dimensionality of our data?

please find better sound fx.

Still trying to figure out how this guy stays so buff despite being five magnitudes more nerd than me

Tim, your channel is the best of its kind. Kudos man, much love 🤘🏻

I'd love to talk to alpha fold n other A.I's

If u need efficiency y not use quantum computer

While the focus is on approximation error, I think understanding will be limited. The most interesting behaviour is when useful novel outputs occur for new inputs, based on assimilation of abstract patterns.