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10:47

Recitation 0i | What to do if you're struggling

Carnegie Mellon University 11785 Introduction to Deep Learning | Spring 22 Slides link: https://drive.google.com/file/d/17o40LacH2ktTq8MtXGvMO-GSgRrj4Rql/view?usp=sharing Struggling with lectures/quizzes: 0:45 Struggling with HWs: 3:20 Overwhelmed in general: 7:39 YouTube Source for this AI Video

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01:08:02

Tech Special Docker for Data Science @ TWiML Online Meetup EMEA 4 March 2019 1080p

**SUBSCRIBE AND TURN ON NOTIFICATIONS** **twimlai.com** This video is a recap of our March 2019 EMEA TWiML Online Meetup. In this month’s community segment, we discuss the upcoming EMEA Meetup in April, the progress of the v3 Deep Learning Part 1 study group, the preparation for the v3 Deep Learning Part 2 course and study […]

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02:03:37

SingularityNET: Ambassador Town Hall meeting #5 | June 7 2022

Miro board with notes: https://miro.com/app/board/uXjVO0WVUBA=/ Slides: https://docs.google.com/presentation/d/1Bqx1xtDD-Cw59lP4H_32eXpUYqejDMBDR8ASb2MRLYo/edit?usp=sharing Dework: app.dework.xyz/singularitynet-ambas The next Town Hall meeting will be June 14th, 18UTC. Special thanks to those who joined live! —- SingularityNET is a decentralized marketplace for artificial intelligence. We aim to create the world’s global brain with a full-stack AI solution powered by a decentralized protocol. We gathered […]

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11:47

Tensorflow.js Explained

Tensorflow.js is Google’s new Javascript verison of its popular Machine Learning library Tensorflow. This allows developers, hobbyists, and researchers to build & train AI models in the browser! It allows for both training and inference to happen entirely client-side, which means we can utilize our users GPUs (all types). This is really exciting, it opens […]

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14:14

Tom Scott Articulately Debunks the Robot Apocalypse

Check Out Tom! ► http://bit.ly/TomScottYoutube Watch Other Episodes! ► https://www.youtube.com/watch?v=XR0JMN6diG8&list=PLIGnUoWRzxxuij19Sre873goi7taYeNEF&index=3& Subscribe! ► http://bit.ly/corridor_cast_subscribe Watch Our Studio Vlog ► https://www.youtube.com/watch?v=ic0nHede8qc& Wren sits down with Youtube Educator and all around good guy Tom Scott where they talk about the possibly banal future of Artificial Intelligence. FOLLOW US ON ► Google Podcasts: http://bit.ly/Corridor_Cast_On_GooglePodcasts iTunes: http://bit.ly/Corridor_Cast_on_iTunes Spotify: http://bit.ly/corridor_cast_on_spotify Corridor […]

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11:57

ML News: Anthropic raises $124M • ML execs clueless • Collusion rings • ELIZA source discovered & more

#mlnews #anthropic #eliza Anthropic raises $124M for steerable AI, peer review is threatened by collusion rings, and the original ELIZA source code was discovered. OUTLINE: 0:00 – Intro 0:40 – Anthropic raises $124M 3:25 – 65% of execs can’t explain AI predictions 4:25 – DeepMind releases AndroidEnv 6:10 – Collusion rings in ML Conferences 7:30 […]

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39:30

Get started with TensorFlow's High-Level APIs (Google I/O '18)

High-level APIs like tf.keras enable developers to train models easily and effectively. This session will introduce these APIs, and notebooks you can run live in the browser to get started using Colab. We’ll walk you through writing your first neural network in TensorFlow using just 10 lines of code with tf.keras, and then we’ll introduce […]

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08:54

SimCLR implementation- NT-Xnet Loss

This is video no. 6 in a series walking through simCLR research paper, going over the NT-Xnet loss implementation. William Falcon, PyTorch Lightning founder, and Ananya Harsh Ja, Lightning research engineer, deep dive into simCLR (“A Simple Framework for Contrastive Learning of Visual Representations”), self-supervised representation learning on images. Start here for simCLR overview: https://www.youtube.com/watch?v=pDJx8i3jenA&list=PLaMu-SDt_RB4k8VXiB3hOdsn0Y3GoXo1k […]

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01:04:04

Recitation 1 | Setting Up AWS Deep Learning AMI and Google Colab

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2019 Notebook: http://deeplearning.cs.cmu.edu/document/recitation/recitation1.tar.gz For more information, please visit: http://deeplearning.cs.cmu.edu/ Contents: • AWS EC2 • Jupyter Notebook Setup • Google Colab • Mounting Drives YouTube Source for this AI Video

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34:03

LIVE FROM TWIMLcon! Overcoming the Barriers to Deep Learning in Production with Andrew Ng – #304

Earlier today, Andrew Ng joined us onstage at TWIMLcon to share some of his immense knowledge. As the Founder and CEO of Landing AI, Co-Chairman and Co-Founder of Coursera, and founding lead of Google Brain, Andrew is no stranger to knowing what it takes for AI and machine learning to be successful. In this episode, […]

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07:51

Jeff Dean, Head of AI at Google discusses the impact of ML (TensorFlow Meets)

In this episode of TensorFlow Meets, Laurence Moroney sits down with Jeff Dean, a Google Senior Fellow working in the area of Machine Intelligence Engineering. Laurence taps into Jeff’s insights about machine learning (ML) and how it’s impacting many different engineering domains and scientific domains in general. Jeff Dean and his team have conducted research […]

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43:32

Disentangled Representations & Google Research Football with Olivier Bachem – TWIML Talk #293

Today we’re joined by Olivier Bachem, a research scientist at Google AI on the Brain team. Initially, Olivier joined us to discuss his work on Google’s research football project, their foray into building a novel reinforcement learning environment, but we spent a fair amount of time exploring his research in disentangled representations. Olivier and Sam […]

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15:55

Training NVIDIA StyleGAN2 ADA under Colab Free and Colab Pro Tricks

Google Colab and Colab Pro can be used to train GANs, but with some restrictions. In this video I demonstrate how to use Colab to train images for StyleGAN2 ADA. 1:20 Jupyter Notebook for GAN Training in CoLab 1:38 Setting up GDRIVE 3:33 Output from StyleGAN 5:16 Colab GPUs and Limitations 5:35 Google Colab Throttling […]

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08:36

Content-based filtering & collaborative filtering (Building recommendation systems with TensorFlow)

In this video we will be walking you through the concepts of content-based filtering and collaborative filtering, which are traditional algorithms for recommendation systems but are useful to help us better understand modern recommenders. Recommendation systems on Google Developers website → https://goo.gle/3yx9XK9 Building a recommendation model using Stochastic Gradient Descent → https://goo.gle/2SNAm70 Neural Collaborative Filtering […]

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01:30:51

#TWIMLfest: Office Hours – Reinforcement Learning

In the Office Hours series, we invite experts and practitioners in various topic areas for AMA (ask-me-anything) style sessions to answer community member questions. The intent is to answer technical questions and/or help participants advance their specific projects and interests. This week’s topic will be centered on Reinforcement Learning! Resources: Show notebooks in Drive – […]

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06:35

Recitation 0b | Fundamentals of Numpy – Intro (1/8)

Python Notebook: https://colab.research.google.com/drive/1KaKkHCzccwa5Q4Zyj4UlJ5QH7fuIqV-N For more information, please visit: http://deeplearning.cs.cmu.edu/ YouTube Source for this AI Video

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48:52

TWiML x CS224n Study Group – Introduction

This video is a recap of our first CS224n: Natural Language Processing with Deep Learning Online Study Group. In this session, we went over the Introduction. It’s not too late to join the study group. Just follow these simple steps: 1. Head over to twimlai.com/meetup, and sign up for the programs you’re interested in, including […]

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55:49

Delivering Neural Speech Services at Scale with Li Jiang – #522

Today we’re joined by Li Jiang, a distinguished engineer at Microsoft working on Azure Speech. In our conversation with Li, we discuss his journey across 27 years at Microsoft, where he’s worked on, among other things, audio and speech recognition technologies. We explore his thoughts on the advancements in speech recognition over the past few […]

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TWiML x Fast ai v3 Deep Learning Part 2 Study Group – Lesson 12 – Spring 2019 1080p

**SUBSCRIBE AND TURN ON NOTIFICATIONS** **twimlai.com** This video is a recap of our TWiML Online Fast.ai Deep Learning Part 2 Study Group. In this session, we had a mini presentation on Deep Representation Learning for Trigger Monitoring and a review Lesson 12 of the Fast.ai v3 Deep Learning Part 2 course. It’s not too late […]

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11:07

The Only Artificial Intelligence that can Learn – Deepmind Meta-Learning

Artificial Intelligence’s biggest Problems is their inability to keep on learning after they’ve completed their training. But now, Google’s Deepmind has created a Meta-Learning AI which keeps on learning and improving indefinitely without any Human supervision. Deepmind created the AI Game: Alchemy, which is a chemistry-based game for AI Agents to play and improve in. […]

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06:03

This Neural Network Turns Videos Into 60 FPS!

❤️ Check out Weights & Biases here and sign up for a free demo here: https://www.wandb.com/papers Their blog post on hyperparameter optimization is available here: https://www.wandb.com/articles/find-the-most-important-hyperparameters-in-seconds 📝 The paper “Depth-Aware Video Frame Interpolation” and its source code are available here: https://sites.google.com/view/wenbobao/dain The promised playlist with a TON of interpolated videos: 🙏 We would like to […]

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08:49

Reading Memories from the Human Brain – SECRET Brain Project

For the first time ever, Scientists working for the United States Government and Google have managed to read and understand a portion of a brain in real time. This is going to enable abilities such as reading minds and memories from humans in the future. The question is how long it will take until the […]

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This AI Helps Testing The Games Of The Future! 🤖

❤️ Check out Weights & Biases and sign up for a free demo here: https://wandb.com/papers ❤️ Their mentioned post is available here: https://colab.research.google.com/drive/1gKixa6hNUB8qrn1CfHirOfTEQm0qLCSS 📝 The paper “Improving Playtesting Coverage via Curiosity Driven Reinforcement Learning Agents” is available here: https://www.ea.com/seed/news/cog2021-curiosity-driven-rl-agents 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: […]

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05:20

CoRL 2020, Spotlight Talk 171: Safe Policy Learning for Continuous Control

“**Safe Policy Learning for Continuous Control** Yinlam Chow (Google AI)*; Ofir Nachum (Google); Aleksandra Faust (Google Brain); Edgar Dueñez-Guzman (DeepMind); Mohammad Ghavamzadeh (Google Research) Publication: http://corlconf.github.io/paper_171/ **Abstract** We study continuous action reinforcement learning problems in which it is crucial that the agent interacts with the environment only through near-safe policies, i.e.,~policies that keep the agent […]

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