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Simons Foundation
Приєднався 8 чер 2009
The Simons Foundation’s mission is to advance the frontiers of research in mathematics and the basic sciences.
Co-founded in New York City by Jim and Marilyn Simons, the foundation exists to support basic - or discovery-driven - scientific research undertaken in the pursuit of understanding the phenomena of our world.
The Simons Foundation’s support of science takes two forms: We support research by making grants to individual investigators and their projects through academic institutions, and, with the launch of the Flatiron Institute in 2016, we now conduct scientific research in-house, supporting teams of top computational scientists.
Co-founded in New York City by Jim and Marilyn Simons, the foundation exists to support basic - or discovery-driven - scientific research undertaken in the pursuit of understanding the phenomena of our world.
The Simons Foundation’s support of science takes two forms: We support research by making grants to individual investigators and their projects through academic institutions, and, with the launch of the Flatiron Institute in 2016, we now conduct scientific research in-house, supporting teams of top computational scientists.
Nick Scoville - Cosmic Evolution of Galaxies (May 17, 2024)
More details: www.simonsfoundation.org/event/109499-2024-05-17/
Переглядів: 232
Відео
Megan Bedell - The Search for Other Earths (April 26, 2024)
Переглядів 164День тому
More details: www.simonsfoundation.org/event/109499-2024-03-01/2024-04-26/
Mitchell Luskin - Physics and Math at the Moiré Scale (May 9, 2024)
Переглядів 26414 днів тому
The incommensurate stacking of multilayered two-dimensional materials has become an active experimental method to investigate physical properties and a challenging problem from a theoretical perspective. The configuration space is a natural description of such incommensurate layered materials and gives an exact formulation of electronic properties such as the density of states and Kubo optical ...
Sara Haravifard - Exploring New Candidates for Dirac Quantum Spin Liquids (May 14, 2024)
Переглядів 11614 днів тому
Frustrated quantum magnets offer a promising arena for exploring exotic states of matter. The talk will focus on the newly designed quantum magnets which are predicted to host a Quantum Spin Liquid (QSL) state. QSL is a novel state of matter in which spins do not order even at low temperatures, exhibiting exotic properties like tractionalized excitations and topological order. This presentation...
Feng Wang - Electron solids in two-dimensional semiconductor heterostructures (April 23, 2024)
Переглядів 10514 днів тому
Atomically thin two-dimensional (2D) semiconductors and heterostructures offer an exciting platform for the study of tunable correlated electronic phenomena. The interaction between electrons in 2D semiconductors can be adjusted by manipulating the electron density and confinement potential, leading to the formation of various electron solid phases. When electrons are confined within a moire su...
Xiaodong Xu - Observation of Fractional Quantum Anomalous Hall Effect (March 19, 2024)
Переглядів 19214 днів тому
The interplay between spontaneous symmetry breaking and topology can result in exotic quantum states of matter. A celebrated example is the quantum anomalous Hall (QAH) effect, which exhibits an integer quantum Hall effect at zero magnetic field due to topologically nontrivial bands and intrinsic magnetism. In the presence of strong electron-electron interactions, fractional-QAH (FQAH) effect a...
Michael Long - Neural Mechanisms of Interactive Communication (May 8, 2024)
Переглядів 537Місяць тому
Vocal communication is central to our everyday lives, facilitating social exchange. Despite significant recent discoveries, the neural mechanisms underlying coordinated vocal exchanges remain poorly understood. In this Presidential Lecture, Michael Long will examine the brain processes involved in interactive vocal behaviors with a focus on forebrain circuitry in the human brain as well as a ra...
DMFT-QE Symposium - Laura Fanfarillo (April 15, 2024)
Переглядів 196Місяць тому
Iron-based superconductors represent an intriguing playground to study the role of electronic correlation in the realization of quantum orders. On the one hand a wealth of evidence shows that the phenomenology of the normal state can be fully accounted in terms of Hund’s metal physics, on the other hand the emergence of quantum orders at low-temperature can be explained as the results of Fermi ...
DMFT-QE Symposium - Luca de’ Medici (April 15, 2024)
Переглядів 129Місяць тому
Hund metals are paramagnetic phases in which high-spin local configurations dominate. This paradigm is now a useful guidance to interpret the physics of many transition-metal compounds, like Ruthenates and Iron-based superconductors. I will show how this physics is extremized by moving towards a half-filled Mott insulator, and that it gives rise to charge instabilities and heavy fermionic behav...
Lenka Zdeborová - Statistical Physics of Machine Learning (May 1, 2024)
Переглядів 13 тис.Місяць тому
Machine learning provides an invaluable toolbox for the natural sciences, but it also comes with many open questions that the theoretical branches of the natural sciences can investigate. In this Presidential Lecture, Lenka Zdeborová will describe recent trends and progress in exploring questions surrounding machine learning. She will discuss how diffusion or flow-based generative models sample...
Naomi Ehrich Leonard - Fast and Flexible Group Decision-Making (April 24, 2024)
Переглядів 458Місяць тому
A wide range of animals live and move in groups. Many animals do better in groups than alone when, for example, foraging for food, migrating and avoiding predators. A key to group success is social interaction. Less well understood is how a group with no centralized control is capable of the fast and flexible decision-making required to carry out its tasks in an environment with uncertainty, va...
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - Alex Cayco Gajic (March 4, 2024)
Переглядів 265Місяць тому
More details: www.simonsfoundation.org/event/cosyne-2024-workshop-i-cant-believe-its-not-better/
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - Chethan Pandarinath (March 4, 2024)
Переглядів 165Місяць тому
More details: www.simonsfoundation.org/event/cosyne-2024-workshop-i-cant-believe-its-not-better/
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - Cina Aghamohammadi (March 4, 2024)
Переглядів 127Місяць тому
More details: www.simonsfoundation.org/event/cosyne-2024-workshop-i-cant-believe-its-not-better/
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - Cole Hurwitz (March 4, 2024)
Переглядів 89Місяць тому
More details: www.simonsfoundation.org/event/cosyne-2024-workshop-i-cant-believe-its-not-better/
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - Cristina Savin (March 4, 2024)
Переглядів 91Місяць тому
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - Cristina Savin (March 4, 2024)
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - John Pearson (March 4, 2024)
Переглядів 190Місяць тому
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - John Pearson (March 4, 2024)
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - Nathan Cloos (March 4, 2024)
Переглядів 65Місяць тому
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - Nathan Cloos (March 4, 2024)
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - Siyan Zhou (March 4, 2024)
Переглядів 55Місяць тому
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - Siyan Zhou (March 4, 2024)
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - Tahereh Toosi (March 4, 2024)
Переглядів 152Місяць тому
COSYNE 2024 Workshop: I Can’t Believe It’s Not Better! - Tahereh Toosi (March 4, 2024)
Maya Fishbach - Astrophysical Lessons from LIGO-Virgo-KAGRA's Black Holes (March 29, 2024)
Переглядів 154Місяць тому
Maya Fishbach - Astrophysical Lessons from LIGO-Virgo-KAGRA's Black Holes (March 29, 2024)
Meridith Joyce - Stellar Evolution in Real Time (April 12, 2024)
Переглядів 221Місяць тому
Meridith Joyce - Stellar Evolution in Real Time (April 12, 2024)
Zhaohuan Zhu - Magnetospheric Accretion and Companion-Disk Interaction (April 5, 2024)
Переглядів 93Місяць тому
Zhaohuan Zhu - Magnetospheric Accretion and Companion-Disk Interaction (April 5, 2024)
John Dabiri - Bioinspired Ocean Exploration (April 17, 2024)
Переглядів 2802 місяці тому
John Dabiri - Bioinspired Ocean Exploration (April 17, 2024)
Vanessa Ruta - Themes and Variations in Social Brain Circuits (April 10, 2024)
Переглядів 5602 місяці тому
Vanessa Ruta - Themes and Variations in Social Brain Circuits (April 10, 2024)
Miles Cranmer - The Next Great Scientific Theory is Hiding Inside a Neural Network (April 3, 2024)
Переглядів 178 тис.2 місяці тому
Miles Cranmer - The Next Great Scientific Theory is Hiding Inside a Neural Network (April 3, 2024)
DMFT-QE Symposium - Gautam Rai (March 11, 2024)
Переглядів 1402 місяці тому
DMFT-QE Symposium - Gautam Rai (March 11, 2024)
DMFT-QE Symposium - María José Calderón (March 11, 2024)
Переглядів 652 місяці тому
DMFT-QE Symposium - María José Calderón (March 11, 2024)
Emma Beasor - The evolution of red supergiants to supernova (March 22, 2024)
Переглядів 2542 місяці тому
Emma Beasor - The evolution of red supergiants to supernova (March 22, 2024)
Massimo Vergassola - The Story of the First Two Hours of a Fly’s Life (March 27, 2024)
Переглядів 6852 місяці тому
Massimo Vergassola - The Story of the First Two Hours of a Fly’s Life (March 27, 2024)
I loved it!
Eventually, we need to ask why we need to understand. AI will eventually solve problems without us needing to, or sometimes being able to, understand.
It is probably dumb or anyone else have trouble understanding folding analogy at 12:15? Is he suggesting that the planes are superimposed with one top of other? Or is he suggesting that sum of figure a and figure b lead to figure c? Can anyone help me in understanding it?
Thank you for your talk. I found it extremly interesting. I have some comment on your statement that simplicity is implied by utility : Differential Equations are very useful in describing our world, however they are at least in my mind not simple and to most people also not familiar. I would love to discuss about it !
Define these letters already
Which A.I. came up with that Theory? They usually hide inside Brains.
Best 25 minutes of my life.. Physician telling me a language model is just a chatbot refined.. I can do that. Let's go!
I really want to contribute to physics like Prof. Elliot😅, dude is phenomenal.
one of the best suggestions of the algorithm. there is a phrase widely used in education circles nowadays: 'Learning how to learn' and it is often criticised as human babies are already born with the ability to learn. But in the case of machines I suspect that is the way to go. They lack the genetic encoding we embedded in our biological systems for so long. Maybe we should treat these early machine learning models as their DNA?
The mental features discoursed of as the analytical are in themselves but little susceptible of analysis. --- Edgar Allan Poe To put it simply, it’s hard to understand why prodigies are the way they are
Great talk!!
Why does he have a giant stick, is he blind?
Yea it’s great if ur trying to use a system In a system to garner traction
Can change ringing be done with electric motors instead of bellringers?
i find it interesting special relativity wasn't an example of needing to fit the data. oh wait, i'm not, because there was no underlying data
Along with being so intelligent, he is such a likable guy. In the 4 minutes I've heard him talk, I already like the guy
I was pretty surprised to see this not actually purpose much of anything other than using tools to analyse patterns, three same tools that have been in use for decades. Is this a venture pitch? Throwing more processing at it helps, but doesn't "solve" anything on its own.
Your cat doesn't teleport?
Most likely a biological neural network
yooo, i'm so glad i came across this! i've been thinking about how neural networks can teach us about our own thinking and pattern finding; i'm glad there is discussion about it
okay it's not about what i initially thought, but whoa. this polymath approach sounds excellent. i feel it's similar to how people who study many different fields can be quicker to grasp a novel problem
33:16 Mark my words. There won't be any foundational-level model can achieve 5-digit of accuracy like the finite difference does for PDE, which was popularized three hundred years ago by Euler. Using the model alone (without the help of non-blackbox outer algorithms or second-order optimizer), no matter you have 1000 billion params, or what, never. 1000 years later our AI overlords will still use finite difference (maybe the BDF table will be learned by blackbox).
What happens if it’s trained on Schrödinger’s cat videos?
What makes him great? I don't found any of good quality between him!
Well more fun than AI churning out what are the most lethal substances. Modern nerve agent analog were in the outputs.
Very nice and interesting
Folding is an analogue to reducing dimensional complexity.
So wisdom is better than raw intellect. Got it. The more we know, the more it enhances anything else we do and think about. Not really a mystery, but nice to see the theory and it being proven. ML has always felt wrong to me because of the "toddler" he describes. Now that ai can know everything that the entire human race knows, of course it will start solving problems we can't think to solve alone with our own minds and data within. Who built our ai?
Damn wholesome mathematician.
Wow this is incredible and sort of confirms some thoughts I’ve had about neural networks and the compression of knowledge.
Go f yourself and learn to explain things in an orderly manner . You are a disgrace to humanity ...
Why is everyone recommended this video?
Mostly because of the folding analogy around 12:00 that helps build a good intuition about how chaining the layers of the neural network from perspective of a single neuron does produce a complex function that can learn to approximate complex relationships. The main topic of the presentation is fine, but more like an early sketch of an idea how we might extract new simplified scientific models from LLM - but the prompt method doesn’t seem to be scalable enough for practical application. The core insight seems to valid, though.
Interesting topic and well put presentation, however the speaker should practice a bit more its communication skills (not saying "I mean" or "like" every 2s) and stop reading the damn PowerPoint - I bet most viewers can read-. Again, it is a great topic and a good presentation. I will read his previous research after watching this.
Planets are older and dead stars.
Here's an April fools episode idea. Tales from the dark side episode where you discuss the extremely creative solutions you had to come up with while trying to do chase films on some UFO test object. Deliver it in a straight face with digressions on how it would be cool if / or how you are waiting to see the technology make it's way into the civilian market ect . For the photos have blurry images of birds or maybe say that the reason pictures are blurry is because UFOs are just blurry. Even when in the hangar
Quote (16:40): State of the art for symbolic regression... 25 days later a paper was released where so called KAN's where used to do symbolic regression, and I am pretty sure that this will be the state of the art. I know it was used only on small datasets and has some other flaws, but this is not worth talking about since we will make it work. They also refrence Miles Cranmer.
KANs does not scale well
The AI field is hallucinating.
Biological or silicon network?
Wow; what a bridge from physics to number groups😊
Great presentation! My main takeaway is that we need a more unified approach to neural network models. Interoperability is important and can substitute for or even supercede the quality increase of pre-training.
even at 720p the quality is too poor to make out important details from his figures. Makes this difficult to follow.
She only got this award because Ukraine got invaded. If nothing happens to Ukraine, the award would go to an even more outstanding mathematician
Loved this video. Now I know a little more about you, Barry, and who my son, William Stein, was talking about. You and Gretchen are amazing people.
Grate path to walk on .. wish luck to the lecturer and hiss fellow researches
I'll bet my Bitcoin it won't.
Eric Lerner has spoken to H Alfven Wave and Plasma instabilities-stabilities along Magnetic field lines of the sun and stars in general for decades. It’s not an association that some will dare to make yet I think he deserves recognition for his huge contributions since VNadi and others.
They could put the questions!
Is the part in 12.40 just convolution or am I just dreaming?
this was very interresting
unknowingly to him, this man was one my teachers in maths. God bless him.
This guy has obviously not spent enough time with LLMs or transformers, the ways in which they are 'dumb' and _don't_ make very obvious connections is far more astounding than the ones they do.... I wouldn't trust that NNs in the way we've formulated have any hope of making any type of interesting connection that one of 8 billion humans has not thought of already.
He's doesn't seem to be extolling those achievements. More like how a shitty NN can do water wiggles better than the special effects team making water for movies. (Just the most fundamental part of water, but if it does that with far less gas, that's an achievement. It's actually what the champion info compressor does [black holes]
@@seanmcdonough8815 He does initially, but I watched the rest. You are right. He has a point about simple-curve-fitting-NNs. I approve of ignoring Navier Stokes nonsense, rock on you self-water-wiggling algos, rock on...