Best Machine learning & deep learning Videos
「Machine learning & deep learning」下面有131部被不同的人、在不同月份推荐过的视频。挑的时候先看对象:入门25部,适合还没学过的人;进阶51部,适合已经懂术语的人;普通向38部,按兴趣就能看;更硬的17部,留给想看推导或细节的人。这一类数量最多的是演讲,所以它们的共同点是一位讲者把一个判断讲完,例子是为了撑住这个判断。常出现的频道包括Andrej Karpathy、3Blue1Brown、Google TechTalks。目录给这个主题划的范围是:Machine learning: neural networks, deep learning, backpropagation, training, optimization, reinforcement learning, AlphaGo, ML research lectures, Karpathy, Hinton, LeCun, Stanford CS231n.如果只看三部,就从《The spelled-out intro to neural networks and backpropagation: building micrograd》开始,它负责把问题讲出画面;然后看《But what is a neural network? | Deep learning chapter 1》,换一种讲法或例子;最后看《AlphaGo - The Movie | Full award-winning documentary》,留给已经有基础的人。页面按每页24部切开,顺序看的是被推荐跨越了多少个月,不是播放量。每条标题下面那一句是这部片子自己的内容说明,用来区分它在讲定义、过程、演示还是观点。点进去能看到推荐原话、原文链接和适合谁看。看的时候把强烈推荐当成有人明确叫你去看,把引用当成只是拿来举例,把批评留下来对照,不要把每条评论都当成同一力度。

Deep Visualization Toolbox
A short demo of the Deep Visualization Toolbox, which shows the activations inside a convolutional neural network as it processes live camera input.

Speech Recognition Breakthrough for the Spoken, Translated Word
Microsoft Research's Rick Rashid demonstrates a speech recognition and translation system, built on deep neural networks, that turns his spoken English into Chinese speech in 2012.

Visualizing Data Using t-SNE
A Google Tech Talk by Laurens van der Maaten, co-creator of t-SNE, on visualizing high-dimensional data by mapping it to two dimensions.

Journey on the Deep Dream
A six-minute journey through the layers of a neural network using Deep Dream, with each frame fed back into the network starting from random noise and the targeted layer changing every four seconds.

VACNET Anti-cheat
3kliksphilip summarizes Valve's GDC talk on VACNet, a deep-learning system that flags CS:GO cheaters and feeds the Overwatch review queue.

Clojure is Not Afraid of the GPU - Dragan Djuric
Dragan Djuric presents Clojure libraries for GPU and numerical computing, including ClojureCL, ClojureCUDA and Neanderthal.

Neural Network Learns The Physics of Fluids and Smoke | Two Minute Papers #118
Two Minute Papers covers a paper on speeding up fluid and smoke simulation with convolutional networks.

But how do AI images and videos actually work? | Guest video by Welch Labs
A guest video by Welch Labs on 3Blue1Brown explaining how text-to-image and video models work.

Multi-Agent Hide and Seek
OpenAI's short demo of agents playing hide-and-seek in a simulated environment.

CVPR 2018: Learning to See in the Dark
A short video accompanying the CVPR 2018 paper Learning to See in the Dark.

Human AI is Decades Away, But We Need to Start the Debate Now | Demis Hassabis | Google Zeitgeist
Demis Hassabis of DeepMind speaks at Google Zeitgeist, saying human-level AI is decades away but the debate should start now.

Swift for TensorFlow: The Next-Generation Machine Learning Framework (TF Dev Summit '19)
Chris Lattner and Brennan Saeta present Swift for TensorFlow at the TensorFlow Dev Summit 2019, covering language-integrated automatic differentiation and tooling for machine learning in Swift.

Ken Stanley: Discovery Without Objectives
A 92-minute RMIT University seminar in which Ken Stanley argues that setting an objective can block achieving it.

Experiences Building Edge TPU with Chisel
A Google talk from the Chisel community in which engineers recount designing the Edge TPU with the Chisel hardware construction language.

Building the Software 2 0 Stack (Andrej Karpathy)
Andrej Karpathy's Databricks talk on Software 2.0, the shift from human-written code to code produced by neural network training.

We Were Right! Real Inner Misalignment
Robert Miles covers a paper where researchers ran real versions of his earlier mesa-optimizer thought experiments.

Richard Sutton – Father of RL thinks LLMs are a dead end
Dwarkesh Patel interviews Richard Sutton, reinforcement learning pioneer, Turing Award winner and author of The Bitter Lesson.

Geoff Hinton: On Radiology
A one-minute clip from a 2016 Toronto conference in which Geoff Hinton comments on deep learning and radiology.

An Observation on Generalization
Ilya Sutskever gives a Simons Institute talk on why neural networks generalize, framing learning as finding short descriptions, like compression.

Ray Summit 2022 - Day 1 Keynote - Fireside Chat
A Ray Summit 2022 keynote fireside chat between OpenAI's Greg Brockman and Anyscale's Robert Nishihara.

Unitree Introducing | Unitree G1 Humanoid Agent | AI Avatar | Price from $16K
A short Unitree promo for its G1 humanoid robot, priced from $16K, showing agile motion, dexterous hands and imitation and reinforcement learning.

Building AI Silicon
Jim Keller, CTO of Tenstorrent, talks at Samsung Foundry's SAFE 2021 about building AI silicon through modular, provable design.

George Hotz | Programming | can tinygrad whisper? | AMD Rant | Giving up on AMD | Speech to Text
A long George Hotz live-stream from June 2023 in which he works on tinygrad and rants about AMD's drivers, ultimately declaring he is giving up on AMD.

Evolved Virtual Creatures (1994)
A restored 1994 video of Karl Sims' research on evolved virtual creatures, where simulated block creatures are bred through artificial evolution to swim, walk, follow and compete.