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TensorFlow Lite for Android (Coding TensorFlow)

In this episode of Coding TensorFlow, Laurence Moroney, Developer Advocate for TensorFlow at Google, talks us through how TensorFlow Lite works on Android. You’ll see how to deploy a trained model to an Android App, and how you can run inference with it in Java. “Building TensorFlow on Android” article → https://goo.gl/B8SV2d TensorFlow Lite Demo […]
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What is a quantum computer? (QuantumCasts)

In this video, Marissa Giustina addresses some basic questions about quantum computing. You’ll learn about what makes a quantum computer “quantum”, and what differentiates it from a regular computer. In addition, you’ll get to see what Google’s current quantum processors look like, and see the stack of hardware infrastructure needed to run the full system. […]
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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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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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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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#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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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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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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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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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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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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CoRL 2020, Spotlight Talk 171: Safe Policy Learning for Continuous Control
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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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Multi-modal Deep Learning for Complex Document Understanding with Doug Burdick – #541

Today we’re joined by Doug Burdick, a principal research staff member at IBM Research. In a recent interview, Doug’s colleague Yunyao Li joined us to talk through some of the broader enterprise NLP problems she’s working on. One of those problems is making documents machine consumable, especially with the traditionally archival file type, the PDF. […]
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[ML News] DeepMind builds Gopher | Google builds GLaM | Suicide capsule uses AI to check access

#mlnews #gopher #glam Your updates on everything going on in the Machine Learning world. Sponsor: Weights & Biases https://wandb.me/yannic OUTLINE: 0:00 – Intro & Overview 0:20 – Sponsor: Weights & Biases 3:05 – DeepMind releases 3 papers on large language models 11:45 – Hugging Face Blog: Training CodeParrot from scratch 14:25 – Paper: Pre-Training vision […]
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Trends in Machine Learning & Deep Learning with Zachary Lipton – #556

Today we continue our AI Rewind 2021 series joined by a friend of the show, assistant professor at Carnegie Mellon University, and AI Rewind veteran, Zack Lipton! In our conversation with Zack, we touch on recurring themes like “NLP Eating AI” and the recent slowdown in innovation in the field, the redistribution of resources across […]
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MIT's Mini Cheetah robot runs faster than ever

A new method allows MIT’s Mini Cheetah to learn how to run fast and adapt to walking on challenging terrain. This learning-based method outperforms previous human-designed methods and allowed the Mini Cheetah to set a record for speed. More info: https://news.mit.edu/2022/3-questions-how-mit-mini-cheetah-learns-run-fast-0317 Visit the project page at https://sites.google.com/view/model-free-speed/ The work was supported by DARPA Machine Common […]
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Adding Machine Learning to your developer toolbox

Machine learning can be a challenging field, as there are a lot of new concepts to learn from the perspectives of mobile, web, and back-end developers. Find out how easy it is to start using machine learning in your app with TensorFlow tools. Resource: TensorFlow website → https://goo.gle/3KejoUZ Speaker: Gus Martins Watch more: All Google […]
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Data-Centric AI: Why This Trend Is Here To Stay (Panel)

To scale AI solutions across nearly every industry, data quality becomes increasingly important. With a data-centric approach, industries that aren’t typically synonymous with AI-driven applications can use AI to drive innovation because of excellent data collection, labeling, and transformation. In this discussion, we explore how data scientists and ML/AI practitioners can use data-centric AI to […]
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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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