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Using AI to accelerate scientific discovery – Demis Hassabis (Crick Insight Lecture Series)

Using AI to accelerate scientific discovery Demis Hassabis, co-founder and CEO, DeepMind At The Francis Crick Institute in King’s Cross, London Abstract: The past decade has seen incredible advances in the field of Artificial Intelligence (AI). DeepMind has been in the vanguard of many of these big breakthroughs, pioneering the development of self-learning systems like […]
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Two Minute Papers: What is Optimization? + Learning Gradient Descent | Two Minute Papers #82

Let’s talk about what mathematical optimization is, how gradient descent can solve simpler optimization problems, and Google DeepMind’s proposed algorithm that automatically learn optimization algorithms. The paper “Learning to learn by gradient descent by gradient descent” is available here: http://arxiv.org/pdf/1606.04474v1.pdf Source code: https://github.com/deepmind/learning-to-learn ______________________________ Recommended for you: Gradients, Poisson’s Equation and Light Transport – https://www.youtube.com/watch?v=sSnDTPjfBYU […]
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Two Minute Papers: AI Builds 3D Models From Images With a Twist | Two Minute Papers #129

The paper “IM2CAD” is available here: http://homes.cs.washington.edu/~izadinia/im2cad.html LSUN Challenge datasets: http://lsun.cs.princeton.edu/2016/ More related papers are available here: http://www.cs.toronto.edu/~fidler/projects/rent3D.html http://web.engr.illinois.edu/~slazebni/publications/iccv15_informative.pdf http://ieeexplore.ieee.org/document/6619238/?reload=true WE WOULD LIKE TO THANK OUR GENEROUS PATREON SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Sunil Kim, Daniel John Benton, Dave Rushton-Smith. https://www.patreon.com/TwoMinutePapers Subscribe if you would like to see more of these! – http://www.youtube.com/subscription_center?add_user=keeroyz […]
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Two Minute Papers: Deep Reinforcement Terrain Learning | Two Minute Papers #67

In this piece of work, a combination of deep learning and reinforcement learning is presented which has proven to be useful in solving many extremely difficult tasks. Google DeepMind built a system that can play Atari games at a superhuman level using this technique that is also referred to as Deep Q-Learning. This time, it […]
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Two Minute Papers: Game AI Development With OpenAI Universe | Two Minute Papers #125

OpenAI Universe + blog post: https://openai.com/blog/universe/ https://universe.openai.com/ Also, make sure to check out Google DeepMind’s lab: https://github.com/deepmind/lab https://deepmind.com/blog/open-sourcing-deepmind-lab/ For the record: no, I am not an Edge user. 🙂 Terrain learning footage credit: http://www.cs.ubc.ca/~van/papers/2016-TOG-deepRL/ WE WOULD LIKE TO THANK OUR GENEROUS PATREON SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Sunil Kim, Daniel John Benton, Dave […]
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05:04

CoRL 2020, Spotlight Talk 45: Positive-Unlabeled Reward Learning

“**Positive-Unlabeled Reward Learning** Danfei Xu (Stanford University)*; Misha Denil (DeepMind) Publication: http://corlconf.github.io/paper_45/ **Abstract** Learning reward functions from data is a promising path towards achieving scalable Reinforcement Learning (RL) for robotics. However, a major challenge in training agents from learned reward models is that the agent can learn to exploit errors in the reward model to […]
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Two Minute Papers: 10 Even Cooler Deep Learning Applications | Two Minute Papers #59

For the third time, we present another round of incredible deep learning applications! ___________________ 1. Geolocation – http://arxiv.org/abs/1602.05314 2. Super-resolution – http://arxiv.org/pdf/1511.04491v1.pdf 3. Neural Network visualizer – http://experiments.mostafa.io/public/ffbpann/ 4. Recurrent neural network for sentence completion: http://www.cs.toronto.edu/~ilya/fourth.cgi 5. Human-in-the-loop and Doctor-in-the-loop: http://link.springer.com/article/10.1007/s40708-016-0036-4 6. Emoji suggestions for images – https://emojini.curalate.com/ 7. MNIST handwritten numbers in HD – […]
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Enhance! Super Resolution From Google | Two Minute Papers #124

The paper “RAISR: Rapid and Accurate Image Super Resolution” is available here: https://arxiv.org/abs/1606.01299 Additional supplementary materials: https://drive.google.com/file/d/0BzCe024Ewz8ab2RKUFVFZGJ4OWc/view Blog posts: https://research.googleblog.com/2016/11/enhance-raisr-sharp-images-with-machine.html https://www.blog.google/products/google-plus/saving-you-bandwidth-through-machine-learning/ WE WOULD LIKE TO THANK OUR GENEROUS PATREON SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Sunil Kim, Daniel John Benton, Dave Rushton-Smith, Benjamin Kang. https://www.patreon.com/TwoMinutePapers Subscribe if you would like to see more of […]
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What is an Autoencoder? | Two Minute Papers #86

Autoencoders are neural networks that are capable of creating sparse representations of the input data and can therefore be used for image compression. There are denoising autoencoders that after learning these sparse representations, can be presented with noisy images. What is even better is a variant that is called the variational autoencoder that not only […]
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01:11:04

Directions in ML: “Neural architecture search: Coming of age”

Neural Architecture Search (NAS) is a very promising but still young field. I will start this talk by discussing various works aiming to build a scientific community around NAS, including benchmarks, best practices, and open source frameworks. Then, I will discuss several exciting directions for the field: (1) a broad range of possible speedup techniques […]
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01:25

AI Impact on Insurance Panel | CogX17 Highlights | CogX

Join the CogX Global Leadership Summit and Festival of AI and Breakthroughs Technology – June 8th to 10th 2020 – https://cogx.co/ Subscribe to our epic newsletters for free https://cognitionx.com/newsletter-subscribe/ Being a heavily data driven business, insurance is ripe for AI disruption. Insurance tech startups received over $1.6 billion in funding in 2016 across 173 separate […]
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Scaling AI at H&M Group with Errol Koolmeister – #503

Today we’re joined by Errol Koolmeister, the head of AI foundation at H&M Group. In our conversation with Errol, we explore H&M’s AI journey, including its wide adoption across the company in 2016, and the various use cases in which it’s deployed like fashion forecasting and pricing algorithms. We discuss Errol’s first steps in taking […]
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Facebook F8 Event Highlights, Amazon Shareholder Letters and Sleep with William Bourke

Listen on Anchor: https://anchor.fm/mrdbourke Or Apple Podcasts: http://bit.ly/bourkebrothers1 Connect with William – https://www.linkedin.com/in/williambourke/ LINKS FROM THE SHOW: Will’s shirt is from the MIT AGI course available FREE on YouTube – https://agi.mit.edu/ Amazon 2016 shareholder letter – https://bit.ly/amazon2016letter Amazon 2017 shareholder letter – https://bit.ly/amazon2017letter AWS Sagemaker – https://amzn.to/amazonsagemaker Facebooks 2018 F8 event – https://www.f8.com/ Facebook’s Open […]
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TEACHING BOTS TO PLAY GAMES | 100 Days of Code 9

Over the past few days, I learned how Google’s Deep Mind created AI bots that were able to learn how to play Atari games at a superhuman level. I even trained my own agent (another word for bot) to play a simple game called cart-pole. Links mentioned in the video: Medium 100 days of code […]
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Learning with Limited Labeled Data with Shioulin Sam – TWiML Talk #255

Today, in the first episode of our Strata Data conference series, we’re joined by Shioulin Sam, Research Engineer with Cloudera Fast Forward Labs. Shioulin and I caught up to discuss the newest report to come out of CFFL, “Learning with Limited Label Data,” which explores active learning as a means to build applications requiring only […]
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52:44

Organizing for Successful Data Science at Stitch Fix with Eric Colson – TWiML Talk #257

For the final episode of our Strata Data series, we’re joined by Eric Colson, Chief Algorithms Officer at StitchFix, whose presentation at the conference explored “How to make fewer bad decisions.” Our discussion focuses in on the three key organizational principles for data science teams that he’s developed at StitchFix. Along the way, we also […]
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Language Modeling and Protein Generation at Salesforce with Richard Socher – #372

Today we’re joined Richard Socher, Chief Scientist and Executive VP at Salesforce. Richard, who has been at the forefront of Salesforce’s AI Research since they acquired his startup Metamind in 2016, and his team have been publishing a ton of great projects as of late, including CTRL: A Conditional Transformer Language Model for Controllable Generation, […]
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06:23

Streams – a platform for a digital NHS

In this excerpt from his speech at the NHS Expo in September 2016, DeepMind co-founder and Head of Applied AI Mustafa Suleyman discusses the needs of a digital NHS and how Streams aims to solve address them. YouTube Source for this AI Video
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Applied AI at The Coca-Cola Company (TensorFlow Dev Summit 2018)

In 2016, Coca-Cola updated its core loyalty marketing program to a mobile-first web platform. The program requires consumers to input 14-character proof-of-purchase codes for entry into promotions. Consumer engagement would have been badly impacted if users had been required to thumb-enter these codes into web forms on their mobile devices. To solve this problem, Coca-Cola […]
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03:07

DeepMind Health – What Patients Want From Tech: Patient Engagement Events 2017

DeepMind Health was established in 2016 to put the UK’s most advanced technology at the service of patients, nurses and doctors. We believe that outcomes are better when patients and clinicians make decisions together. As part of that, we spend a lot of time listening to and working with patients, clinicians and others interested in […]