The Deep Learning Framework Backed By Facebook Is Getting Industry's Attention
PyTorch is an open source project from Facebook which is used extensively within the company. For a long time, Facebook developers used another homegrown framework called Caffe2, which was adopted by academia and researchers. Last year, Facebook announced that it is merging the efforts of developing Caffe2 and PyTorch to focus on creating a unified framework that is accessible to the community.
Uber releases Ludwig, an open source AI ‘toolbox’ built on top of TensorFlow
Uber today debuted Ludwig, an open source “toolbox” built on top of Google’s TensorFlow framework that allows users to train and test AI models without having to write code. Feb 12,2019
Understand TensorFlow by mimicking its API from scratch
Feb 11,2019
Scientists Translate Brain Waves Into Speech
A group of scientists have developed a way to translate brain waves directly into human speech, potentially giving patients who are unable to use their voices another way to communicate. While the science is still a long way from being used as an interpreter for people who otherwise can’t talk, it’s a promising first step toward that goal.
Oh great, AI will apparently match humans in creativity and emotional intelligence soon
An Australian AI expert, Toby Walsh, said during the Festival of Dangerous Ideas in Sydney recently that he thinks AI will learn and possibly match human traits like creativity, emotional intelligence and adaptability in less than 50 years. And Walsh — a Scientia Professor of Artificial Intelligence at UNSW Sydney — predicts robots will be as smart as humans by the year 2062. Nov 9, 2018
AI Detects Patterns of Gut Microbes for Cholera Risk
Researchers from Duke University, Massachusetts General Hospital and the International Centre for Diarrheal Disease Research in Dhaka, Bangladesh have used machine learning algorithms to spot patterns within communities of bacteria living in the human gut that no human would ever be able to pick out. These patterns could indicate who among the approximately one billion people around the globe at risk of cholera infection will get sick with the diarrheal disease.
Machines See the Future for Patients Diagnosed With Brain Tumors
For patients diagnosed with glioma, a deadly form of brain tumor, the future can be very uncertain. While gliomas are often fatal within two years of diagnosis, some patients can survive for 10 years or more. Predicting the course of a patient's disease at diagnosis is critical in selecting the right therapy and in helping patients and their families to plan their lives.
Researchers at Emory and Northwestern Universities recently developed artificial intelligence (AI) software that can predict the survival of patients diagnosed with glioma by examining data from tissue biopsies. The approach, described in Proceedings of the National Academy of Sciences, is more accurate than the predictions of doctors who undergo years of highly-specialized training for the same purpose.
Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning
Stefan Kojouharov has collected several cheat sheets including Tensorflow, Keras Numpy, Python Data Science Scikit-Learn, Pandas and Scipy.
Learning from mistakes with Hindsight Experience Replay
Dealing with sparse rewards in Reinforcement Learning. Hindsight Experience Replay is a paper submitted by OpenAI to NIPS2017.
Techniques in artificial intelligence and machine learning are dramatically altering the landscape of biological research, but Engelhardt doesn’t think those “black box” approaches are enough to provide the insights necessary for understanding, diagnosing and treating disease. Instead, she’s been developing new statistical tools that search for expected biological patterns to map out the genome’s real but elusive “ground truth.”
WuXi NextCODE, Google Cloud Launch Genomics Partnership
WuXi NextCODE said today it will partner with Google Cloudwith the goal of delivering comprehensive genomics capabilities to partners and customers worldwide, through a collaboration whose value was not disclosed. Google Cloud plans to host WuXi NextCODE’s core suite of capabilities and make them available through the Google Cloud Launcher marketplace. Among those are the Genomically Ordered Relational database (GORdb) designed for large quantities of genomic data; WuXi NextCODE secondary analysis, the Sequence Miner case-control research application, and the Clinical Sequence Analyzer clinical interpretation system. WuXi NextCODE said its platform will integrate and co-deploy key Google genomics and research tools—including the BigQuery serverless enterprise data warehouse; the DeepVariant secondary analysis pipeline; and other open-source analysis pipelines and tools available through Google Cloud Platform.
Machine Learning in Health and Biomedicine: A PLOS cross-journal Call for Papers
PLOS Medicine, PLOS Computational Biology and PLOS ONE are excited to announce a cross-journal Call for Papers for high-quality research that applies or develops machine learning methods for improvement of human health. The team of Guest Editors for this Collection seeks research with direct clinical and health policy implications, studies that elucidate biological processes underlying health and disease, innovations in machine learning methodology and data provision, and other advances in the field.
O'Reilly Artificial Intelligence Newsletter
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. Use cases for enterprise AI
2. Intro to LSTMs with TensorFlow
3. Another interesting, but terrifying, use of AI
4. Robocrop
5. Stop reading. Start doing AI.
6. Square off: Machine learning libraries
7. The Google Brain team looks back on 2017
8. 7 types of neural networks for NLP
9. Beyond the rhetoric of algorithmic solutionism
10. How to name a guinea pig

O'Reilly Artificial Intelligence Newsletter
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. Building self-doubt into AI
2. Physical adversarial examples against deep neural networks
3. Could AI offer an X-ray of the immune system?
4. 30 amazing machine learning projects
5. Managing identities online
6. Bringing AI into the enterprise
7. Are old algorithms more racist?
8. What won't happen with AI
9. AI proves major time savings for federal employees
10. What'd I miss?

O'Reilly Artificial Intelligence Newsletter
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. A new AI computing stack
2. Bringing AI into the enterprise
3. The last grand challenge you've never heard of
4. Accelerate your data management systems
5. Cognitive analytics takes flight
6. What you need to know about GANs
7. Google's voice-generating AI is now indistinguishable from humans
8. Raising salaries
9. AI pioneers: Peter Norvig, Google
10. 22 experts

The AI that can read your mind
Chilling Black Mirror-style machine recreates the image you're thinking about by decoding your brain signals
Experts used a neural network to predict images based on brain signals in scans
This let them build up pictures of everything from swans and ducks to postboxes
Geometric shapes and other objects imagined by volunteers were also recreated
The technique could one day be used to create video footage of daydreams

O'Reilly Artificial Intelligence Newsletter
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. Augmenting human intelligence
2. Practical applications of reinforcement learning in industry
3. The case for learned index structures
4. AI 100: The AI startups redefining industries
5. Sound classification with TensorFlow
6. Elon Musk admits Tesla is working on custom AI chips
7. GPU-accelerated TensorFlow on Kubernetes
8. Neural networks in JavaScript with deeplearn.js
9. Facebook launches an AI residency
10. What did that dolphin just say?

NVIDIA CUDA 9.1 now available
NVIDIA CUDA 9.1 now available
O'Reilly Artificial Intelligence Newsletter
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. Progress in AI isn't as impressive as you might think
2. Visualize training results with TensorFlow summary and TensorBoard
3. When two trends fuse: PyTorch and recommender systems
4. The most exciting AI applications in media
5. A bag of words meets popcorn
6. Sentiment and emotion-aware natural language processing
7. Deep image prior
8. Restoring movement in paralyzed man's hand
9. Solving the Facebook QA bAbI Tasks Challenge
10. The impossibility of intelligence explosion

Hvass Labs TensorFlow Tutorial #03-C Keras API
Hvass has a new video. How to use the Keras API to greatly simplify the implementation of a Convolutional Neural Network in TensorFlow. This is used for recognizing handwritten digits from the MNIST data-set.
O'Reilly Artificial Intelligence Newsletter
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. The top 15 employers hiring AI talent
2. Infrastructure 3.0
3. Associative memory AI fights financial crime
4. 10 powerful DL methods for AI engineers
5. A NLP detective story
6. If you're happy and you know it...StarGAN can change it
7. 51 AI predictions for 2018
8. AI in health care
9. Confusion mapping
10. Can analog AI help you hear?

51 Artificial Intelligence (AI) Predictions for 2018
From Forbes Nov 28, 2017
O'Reilly Artificial Intelligence Newsletter
O'Reilly Artificial Intelligence Newsletter Nov. 27
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. 10 ways to seem like an AI expert
2. Deep learning is eating software
3. The tools that make TensorFlow productive
4. Capsule networks and how to use them
5. Why decentralized AI will change the industry
6. How Facebook's oracular algorithm determines the fates of startups
7. EY, Deloitte, and PwC embrace AI
8. 4 AI productivity tools
9. Not Hotdog vs. mission-critical AI applications for the enterprise
10. Scamming scammers

MIT Conference Videos
AI and the Future of Work videos are now available

Feature Visualization — Appendix
After reading "Feature Visualization" (article below) you may be curious what other channels of GoogLeNet look like.
Feature Visualization How neural networks build up their understanding of images
This article focuses on feature visualization. While feature visualization is a powerful tool, actually getting it to work involves a number of details. In this article, we examine the major issues and explore common approaches to solving them. We find that remarkably simple methods can produce high-quality visualizations. Along the way we introduce a few tricks for exploring variation in what neurons react to, how they interact, and how to improve the optimization process.
O'Reilly Artificial Intelligence Newsletter
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. What is backpropagation (and what's it doing)?
2. The titans of AI are getting their work double-checked by students
3. Feature visualization
4. How to build an NLP library for Spark
5. Baselines need more love
6. AI spots suicidal tendencies in brain scans
7. Machine learning at Condé Nast
8. Despite all our fancy AI, solving intelligence remains the greatest problem in science
9. Recipes for material fabrication
10. Crash catcher

O'Reilly Artificial Intelligence Newsletter
O'Reilly Artificial Intelligence Newsletter (note: the above link to the ongoing week's edition and doesn't change week to week)
1. A new twist on neural networks
2. Why AI should be more Canadian
3. Google's Colaboratory
4. Do you have 100,000 examples?
5. Fake news just got easier to create
6. A guide to neural networks with TensorFlow
7. One pixel attack for fooling deep neural networks
8. TensorFlow Mask R-CNN code
9. How to use ML to build recommender systems
10. Who's got a lasionycteris noctivagans?
11. How we built an AI to play Street Fighter II: can you beat it?

Late last week, Hinton released two research papers that he says prove out an idea he’s been mulling for almost 40 years. “It’s made a lot of intuitive sense to me for a very long time, it just hasn’t worked well,” Hinton says. “We’ve finally got something that works well.”
Capsule Networks: An Improvement to Convolutional Networks
Siraj Raval has a new video
Geoffrey Hinton (who popularized backpropagation in the 80s) recently published his long-awaited paper on "Capsule Networks" - which provide state of the art classification accuracy on the MNIST dataset.
O'Reilly Artificial Intelligence Newsletter
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. I just coded my first AI algorithm, and oh boy, it felt good
2. Huge salaries for scarce AI talent
3. Will vanishing gradients ever vanish from deep learning?
4. Object detection with TensorFlow
5. Key considerations for building an AI platform
6. Does your AI know how humans cook, hug, and fight?
7. Comcast as smart home platform
8. AI in the boardroom
9. Curated list of GAN applications
10. End black box algorithms in government

Tech Giants Are Paying Huge Salaries for Scarce A.I. Talent
Nearly all big tech companies have an artificial intelligence project, and they are willing to pay experts millions of dollars to help get it done.
From : Silicon Valley Is Gobbling Up A.I. Experts
Venture capital funding in AI has risen to more than $9.5 billion in the first five months of 2017 from $3.2 billion in all of 2014. It’s been called the biggest investment trend of the year, but it may also be the biggest hiring trend.
Deep Learning without Backpropagation Tutorial: DeepMind's Synthetic Gradients
Andrew Trask's blogpost:
We're going to prototype (from scratch) and learn the intuitions behind DeepMind's recently proposed Decoupled Neural Interfaces Using Synthetic Gradients paper.
Understanding Synthetic Gradients and Decoupled Neural Interfaces
When training neural networks, the use of Synthetic Gradients (SG) allows layers or modules to be trained without update locking – without waiting for a true error gradient to be backpropagated – resulting in Decoupled Neural Interfaces (DNIs).
O'Reilly Artificial Intelligence Newsletter
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. Algorithms have already gone rogue
2. How AI will change strategy
3. AI and advances in data warehousing
4. Enterprises are the natural environment for AI deployments
5. The seven deadly sins of AI predictions
6. What the CIA wants from AI
7. Tensorflow sucks
8. DeepMind launches new team to investigate AI ethics
9. Phone-powered AI spots sick plants
10. Maximum entropy deep reinforcement learning

Virtual Reality is the Next Training Ground for Artificial Intelligence
Recent advancements point to a potentially disruptive combination of virtual reality and artificial intelligence.... Oct 11,2017
O'Reilly Artificial Intelligence Newsletter 9/25/17
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. China is using America's plan to dominate AI
2. Why AI companies can't be lean startups
3. Visualizing convolutional neural networks
4. What's the future of AI (and humanity)?
5. The Chick-fil-A clerk will know your name.
6. Andrew Ng's advice for learning AI
7. 15 mind-blowing stats about AI
8. How Coca-Cola uses AI
9. Reusing code
10. Nature-inspired AI

How Artificial Intelligence Can Help Us Solve the 33-Year-Old “Two-Sigma Problem”
AI allows educators to deliver the kind of learning experiences that researchers have long understood to be most impactful – namely, “mastery learning” environments supported by one-to-one tutoring – but that in the past were just not scalable. Sept 20,2017
O'Reilly Artificial Intelligence Newsletter
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. Awesome AI security
2. How to escape saddle points efficiently
3. AI gaydar?
4. How to find meaning in GANs
5. Letting Siri's "personality shine"
6. "One of the most lucrative partnerships ever"
7. Facebook and Microsoft introduce new open ecosystem for interchangeable AI frameworks
8. The Quartz guide to artificial intelligence
9. Voice assistant hack: Ultrasound
10. Taryn Southern's AI-composed aIbum

O'Reilly Artificial Intelligence Newsletter
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. From infinity to eight
2. How to use Watson to analyze the tone of social media posts
3. An inside look at Alphabet's most ambitious AI project
4. The gap between ambition and execution
5. Moving from academic ml to industrial AI
6. Generate images with PixelRNNs and TensorFlow
7. The new rules of build versus buy in an AI-first world
8. Can AI feed the world?
9. 4 deep learning trends
10. AI on the Daily Show

O'Reilly Artificial Intelligence Newsletter
(note: the above link to the ongoing week's edition and doesn't change week to week)
1. How businesses succeed with AI
2. Eh, what?
3. Exploring the world without an objective
4. Kaldi now offers TensorFlow integration
5. How fast is AI actually progressing?
6. 10 signs you're ready for AI
7. Predicting dementia
8. How to train a basic audio recognition network
9. Machine learning in production
10. 11 tech leaders talk about AI

Microsoft’s Project Brainwave accelerates deep learning in Azure
Using FPGAs deployed throughout the Azure cloud, Microsoft’s new system for accelerating deep learning poses a challenge to Google’s TPUs
Microsoft’s Project Brainwave accelerates deep learning in Azure
Using FPGAs deployed throughout the Azure cloud, Microsoft’s new system for accelerating deep learning poses a challenge to Google’s TPUs
O'Reilly Artificial Intelligence Newsletter
(note: the above links to the ongoing week's edition and doesn't change week to week)
1. 6 guidelines for implementing conversational AI
2. Bringing gaming to life with AI and deep learning
3. I trained a chatbot to talk like me
4. 12 times AI startled the world
5. Contouring learning rate to optimize neural nets
6. Superresolution with semantic guide
7. A brief survey of deep reinforcement learning
8. PyTorch or TensorFlow?
9. She giggles; he gallops
10. Create your own Mini-Me

O'Reilly Artificial Intelligence Newsletter
(note: the above links to the ongoing week's edition and doesn't change week to week)
1. The fatal flaw of AI implementation
2. Lots of AI cheat sheets
3. How Shutterstock uses deep learning
4. AI learns from pro gamers—then crushes them
5. Fixing video streaming stutters
6. We need new algorithms for new AI chips
7. LinkedIn loses right to protect data from AI scraping
8. Teach machines to 10. Space: The final frontier
9. 7 HR experts on AI in recruiting
10. Space: The final frontier

(Udacity) This Week in Machine Learning, 31 July 2017
Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. That’s why we created This Week in Machine Learning! Each week we publish a curated list of Machine Learning stories as a resource to help you keep pace with all these exciting developments.
Machine Learning Top 10 Articles For the Past Month (v.August 2017)
Mybridge AI ranks articles based on the quality of content measured by our machine and a variety of human factors including engagement and popularity. This is a competitive list and you’ll find the experience and techniques shared by the experienced Data Scientists particularly useful.
Facebook authors Dhruv Batra with Denis Yarats respond to viral coverage of AI to AI 'language'
I have just returned from CVPR to find my FB/Twitter feed blown up with articles describing apocalyptic doomsday scenarios, with Facebook researchers unplugging AI agents that invented their own language. I do not want to link to specific articles or provide specific responses for fear of continuing this cycle of quotes taken out of context, but I find such coverage clickbaity and irresponsible.
O'Reilly Artificial Intelligence Newsletter
(note: the above links to the ongoing week's edition and doesn't change week to week)
1. AI is stuck.
2. Best practices: Deep learning for NLP
3. AI is inventing languages humans can't understand. Should we stop it?
4. Million-dollar babies
5. Intro to computer vision with neural networks
6. From prototype to product with hybrid neural networks
7. Reinforcement learning for complex goals
8. Robust physical-world attacks on ML models
9. How advanced NLG is evolving application design
10. Musk versus Zuckerberg

AMD Targets Machine Learning With New Radeon Vega Frontier & Optimized Software
Advanced Micro Devices AMD +NaN% (AMD) has shared more details about its upcoming Vega family of GPUs, as well as information regarding the progress the company has made with its open-source ROCm software stack for HPC and Machine Learning (ML). These new Vega GPUs look like they have sufficient performance to be in the same ballpark as NVIDIA NVDA +3.1%’s highly acclaimed family of PASCAL GPUs.
O'Reilly Artificial Intelligence Newsletter
(note: the above links to the ongoing week's edition and doesn't change week to week)
1. The business of AI
2. Demis Hassabis says AI needs neuroscience
3. The limitations of deep learning
4. How big data and AI will reshape the auto industry
5. Non-tech companies investing in AI
6. Kaggle announces adversarial attack competition
7. AI in the Enterprise: Ford Motor Company
8. Is "AI washing" rampant?
9. The key to AI and poker? Counterfactual regret minimization
10. A USB stick to make AI plug and play

Deal or no deal? Training AI bots to negotiate
From the moment we wake up, our days are filled with a constant flow of negotiations. These scenarios range from discussing what TV channel to watch to convincing your kids to eat their vegetables or trying to get a better price on something. What these all have in common is that they require complex communication and reasoning skills, which are attributes not inherently found in computers. June 14,2017
Ethereum miners are renting Boeing 747s to ship graphics cards and AMD shares are soaring
Advanced Micro Devices’ (AMD) share price jumped after it beat revenue estimates thanks to cryptocurrency miners snapping up the firm’s graphics cards. July 27,2017
Want To Get Into Machine Learning Without Any Prior Tech Experience?
Answer by Ian Goodfellow, AI Research Scientist at Google Brain, on Quora:
If you have almost no technical knowledge but want to get started with machine learning, it’s important to master some of the basics, like linear algebra, probability, and python programming. July 26,2017
Google's DeepMind creates an AI with 'imagination'
Google's DeepMind is developing an AI capable of 'imagination', enabling machines to see the consequences of their actions before they make them. July 26,2017
How to make a racist AI without really trying
Perhaps you heard about Tay, Microsoft’s experimental Twitter chat-bot, and how within a day it became so offensive that Microsoft had to shut it down and never speak of it again. And you assumed that you would never make such a thing, because you’re not doing anything weird like letting random jerks on Twitter re-train your AI on the fly. This tutorial is to show that you can follow an extremely typical NLP pipeline, using popular data and popular techniques, and end up with a racist classifier that should never be deployed. July 13, 2017
AI is changing how we do science. Get a glimpse
AI’s early proving ground: the hunt for new particles Particle physicists began fiddling with artificial intelligence (AI) in the late 1980s, just as the term “neural network” captured the public’s imagination. July 23,2017
A new breed of scientist, with brains of silicon
You don’t even notice the robots until you hear them: They sound like crickets singing to each other amid the low roar of fans. July 23,2017
New O'Reilly Artificial Intelligence Newsletter July 18,2017
1. How GE is building their AI workforce
2. Weird, wonderful, and often extremely funny
3. What is neuroevolution?
4. A look at eBay's focus on AI
5. Google wants to solve artificial stupidity
6. Detect heart arrhythmias (better than a cardiologist)
7. Intel protects lead, pivots to AI
8. Cars, teach yourselves.
9. Seeing AI
10. 8 more things you didn't know AI could do

Projecting a visual image directly into the brain, bypassing the eyes
Imagine replacing a damaged eye with a window directly into the brain — one that communicates with the visual part of the cerebral cortex by reading from a million individual neurons and simultaneously stimulating 1,000 of them with single-cell accuracy, allowing someone to see again.
That’s the goal of a $21.6 million DARPA award to the University of California, Berkeley (UC Berkeley), one of six organizations funded by DARPA’s Neural Engineering System Design program announced this week to develop implantable, biocompatible neural interfaces that can compensate for visual or hearing deficits. July 16,2017
New O'Reilly Artificial Intelligence Newsletter July 11,2017
1. Winning strategies for applied AI companies
2. AI in the software engineering workflow
3. A reality check for IBM's AI ambitions
4. Do we think like machines, or do they think like us?
5. Bad news for the corrupt
6. 25 AI terms you need to know
7. Mind reading with machine learning and fMRI
8. No investors for AI startups?
9. Cars that coordinate with people
10. 7 myths about AI that hold your business back

DeepMind expands to Canada with new research office in Edmonton, Alberta
Today we’re thrilled to announce our next phase: the opening of DeepMind’s first ever international AI research office in Edmonton, Canada, in close collaboration with the University of Alberta (UAlberta). July 5,2017
Google could soon get access to hundreds of thousands of patients' genetic data
Google's DeepMind has already worked with the NHS in monitoring technology A new study suggests Google could soon work with Genomic England This would give the firm access to hundreds of thousands of patient data In an article for The Conversation, a researcher explains the risks of letting a private company gain access to genetic data
Data in, intelligence out: Machine learning pipelines demystified
Info World (requires registration)
Data plus algorithms equals machine learning, but how does that all unfold? Let’s lift the lid on the way those pieces fit together, beginning to end May 31,2017
The 11 industries most under threat from artificial intelligence
UK chip designer ARM released a report on Tuesday highlighting which industries consumers expect to be disrupted the most by AI machines. June 27, 2017
New O'Reilly Artificial Intelligence Newsletter
1. Vertical AI startups
2. How GE adopted AI in the enterprise
3. How AI can deliver real value to companies
4. When AI can transcribe everything
5. The art of the deal
6. US weighs restricting Chinese investment in AI
7. Inside Microsoft's AI comeback
8. Agitated? Your bot knows and wants to help.
9. Fighting extremism with AI
10. Guide to working in AI policy and strategy June 26,2017
Accelerating Deep Learning Research with the Tensor2Tensor Library
Google has released Tensor2Tensor (T2T), an open-source system for training deep learning models in TensorFlow. T2T facilitates the creation of state-of-the art models for a wide variety of ML applications, such as translation, parsing, image captioning and more, enabling the exploration of various ideas much faster than previously possible. June 19, 2017
This conference should be attended by IT and policy decision makers throughout the public sector who want to understand more about the challenges and opportunities AI will bring, both in terms of technical deployment and political/societal governance. Date: Wednesday 20 September 2017 Venue: One Great George Street, Westminster, London SW1P 3AA
A New O’Reilly Artificial Intelligence Newsletter
AI news, insights from industry insiders
1. A (computational) linguistic farce in three acts
2. Teaching machines to draw
3. If you're not good at analytics, you're not ready for AI
4. What Amazon teaches us about AI
5. Apple's struggle to become an AI powerhouse
6. AI jobs for the next generation
7. Airborne AI
8. Can you help gather open speech data?
9. When AI makes us less human
10. We may trust robots. But they don't trust us.

A New O’Reilly Artificial Intelligence Newsletter
1. What's a machine learning engineer?
2. A year in Google Brain's residency
3. Hashing eliminates more than 95% of computations
4. 8 ways ML improves companies' work processes
5. 86% of healthcare companies are using AI
GANs for beginners
6. Reverse-engineering the human brain
7. Sweet 16 and ready to rock the world of AI
8. What wins AI competitions?
9. How to conquer 3 types of ML debt
10. AI will beat us at everything
Jun 12,2017
A New O’Reilly Artificial Intelligence Newsletter
1. Google's new AI investment arm
2. Is China outsmarting America in AI?
3. The machine learning paradox
4. When will AI outperform humans?
5. The 10 most cited AI papers
6. Banks are eager for AI but slow to adopt
7. Constraints of communication
8. AlphaGo: How it works
9. Whose malpractice is it?
10. How machine learning infects our tastes
June 4,2017
Artificial Intelligence Course with Sebastian Thrun and Peter Norvig: Udacity Course. June 03, 2017
Stanford professors Peter Norvig and Sebastian Thrun is offering their ever popular Introduction to AI for free on the internet. Norvig and Thrun, leaders in artificial intelligence, are using automated systems to help them at every level of the massive endeavor, from deciding which questions to answer to grading final exams.
Cera is building an AI for social care decision support
The startup has today taken the tiniest baby steps to launch an AI chatbot that it hopes will, at an unspecified point in future, be able to assist carers with recommendations for home care of people with conditions such as dementia. May 23,2017
"AI First" Microsoft Goes All In on Artificial Intelligence, Microsoft Build 2017 in 12 Minutes
May 15,2017
How to Tell a Person’s “Brain Age”
Cole and his colleagues recently devised their own technique of predicting the biological age of people’s brains using a combination of machine learning and magnetic resonance imaging (MRI) scans.
New O'reily Artificial Intelligence Newsletter
Current issue of the newsletter is available at link. It is intended to be a subscription. By subscribing you might be able to see archived issues.
Geena Davis Inclusion Quotient
The Geena Davis Inclusion Quotient (GD-IQ) is a ground breaking software tool developed by the Geena Davis Institute on Gender in Media at Mount Saint Mary’s University to analyze audio and video media content.
Salesforce created an algorithm that automatically summarizes text using machine learning
This year, people are expected to spend more than half their day reading e-mail, articles, or posts on social media, and it’s only going to get worse. To help solve this problem, researchers at Salesforce have developed an algorithm that uses machine learning to produce “surprisingly coherent and accurate” summaries according toMIT Technology Review. May 15,2017
Machine Learning: An In-Depth Guide - Data Selection, Preparation, and Modeling
In this article, we will briefly introduce model performance concepts, and then focus on the following parts of the machine learning process: data selection, preprocessing, feature selection, model selection, and model tradeoff considerations. 02/08/2016
National Geographic’s New Six-Part Series YEAR MILLION Paints a Stunning Picture of Life in the Deep Future
Narrated by Laurence Fishburne, YEAR MILLION Unites the Brightest Scientific Minds, Including Ray Kurzweil, Michio Kaku, Peter Diamandis and Brian Greene With Sci-Fi/Pop-Culture Figures, Including Graphic Novelist Brian Michael Bendis, Nerdist Co-Host Matt Mira and Musician David Byrne
The Future is Coming Faster Than We Think: YEAR MILLION Premieres Monday, May 15, at 9/8c
How Artificial Intelligence Can Break a Business in Two Minutes
Reacting to false information or misinterpreting information could be catastrophic, especially if it (AI) doesn’t realise the information is a mistake. May 4, 2017
Robo-Pharmacist: This AI is Designing Structures for Futuristic Wonder Drugs
A team of MIT researchers led by Alán Aspuru-Guzik developed an artificial intelligence (AI) program that could change the way pharmaceutical research is conducted. Usually, drug development research relies on simulations that attempt to identify or predict useful molecular structures based on rules written by chemists for pools of candidate molecules. This approach is often limited by human involvement, the accuracy of available simulations, and required processing power.
How to Prepare for an Automated Future -- The New York Times
We don’t know how quickly machines will displace people’s jobs, or how many they’ll take, but we know it’s happening — not just to factory workers but also to money managers, dermatologists and retail workers. The logical response seems to be to educate people differently, so they’re prepared to work alongside the robots or do the jobs that machines can’t. But how to do that, and whether training can outpace automation, are open questions. May 5,2017
UC Berkeley Machine Learning Crash Course: Part 1
Machine learning (ML) has received a lot of attention recently, and not without good reason. It has already revolutionized fields from image recognition to healthcare to transportation. May 02, 2017
Here’s why more students should focus on artificial intelligence
Young people who are going to be leaving school and starting their tertiary education studies soon might be wondering what career paths they should focus on. And for anyone who is in touch with what is happening in the world and future technology trends, the answer should be obvious. Artificial intelligence. Literally changing the way our world operates, we’re all dealing with aspects of this tech daily and likely don’t even know it.
"Brain age" found to be a predictor of death
.... IC London researchers believe they have found yet another way to determine how well we're aging by combining MRI scans of the brain with machine-learning algorithms. April 27,2017
Lyrebird - an API for generating human voice
Lyrebird will offer an API to copy the voice of anyone. It will need as little as one minute of audio recording of a speaker to compute a unique key defining her/his voice. This key will then allow to generate anything from its corresponding voice. April 26,2017
Caffe2 A New Lightweight, Modular, and Scalable Deep Learning Framework
Caffe2 aims to provide an easy and straightforward way for you to experiment with deep learning and leverage community contributions of new models and algorithms. April 20,2017
Caffe2 Deep Learning Framework
Caffe2 is a deep learning framework enabling simple and flexible deep learning. Built on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind, allowing for a more flexible way to organize computation. April 20,2017
The Skills You Need to Become a Data Scientist
Specializing in statistics, programming, business, and design sounds like a daunting task. But getting background in all these skills is incredibly rewarding because you can tackle the business questions that are racking the brains of your company’s senior leaders. March 1, 2017
Artificial intelligence: How to avoid racist algorithms
From BBC News April 16, 2017

"...many of the algorithms that make decisions about our lives - from what we see on the internet to how likely we are to become victims or instigators of crime - are trained on data sets that do not include a diverse range of people."

Suresh Venkatasubramanian states, "...bias, or skew, in decision-making will shift from things we recognise as human prejudice to things we no longer recognise and therefore cannot detect - because we will take the decision-making for granted."

Suresh Venkatasubramanian offers a number solutions:
*better and more diverse data sets with which to train the algorithm
*sharing best practice among software vendor
*building algorithms which explain their decision making

The Algorithmic Justice League (AJL) was launched by Joy Buolamwini, a postgraduate student at the Massachusetts Institute of Technology, to work to end algorithmic bias.
April 16,2017

O'Reilly Artificial Intelligence Newsletter New O'Reilly Artificial Intelligence Newsletter
O'Reilly Artificial Intelligence Newsletter is available
Article titles:
1. How does IBM Watson search TED Talks?
2. Build a talking, face-recognizing doorbell for $100
3. What's Baidu up to?
4. AI won't replace lawyers. (Yet.)
5. Adapting ideas from neuroscience for AI
6. Petrificus Totalus!
7. "This kind of breakthrough could cause our species to go berserk."
8. Applications in AI
9. Naked Tensor
10. Intel creates AI products group
11. Simon says...
March 27,2017
DeepMind Finds Way to Overcome AI’s Forgetfulness Problem
DeepMind, claims it overcame a key limitation affecting one of the most promising machine learning technologies: the software’s inability to remember. March 16,2017
There's a raging talent war for AI experts and its costing automakers millions
"The growth of demand is much faster than the rate of which we can produce people with PhDs or even master’s in this area," Yoshua Bengio, head of the Montreal Institute for Learning Algorithms, told Business Insider. "There’s just an explosion of interest from the industry... and it’s like a fire growing on the prairie." March 12, 2017
Conversational AI and the road ahead
Despite great strides in natural language processing (NLP) by data-driven approaches, natural language understanding remains elusive. The Winograd Schema Challenge is a recently proposed improvement on the Turing Test for assessing whether a machine can be judged “intelligent.” February 25, 2017 by Katherine Bailey (@katherinebailey)
We Are The Robots: Is the future of music artificial?
February 19, 2017
New NVIDIA® Jetson™ TX2
From Nvidia: The new NVIDIA® Jetson™ TX2 is a high-performance, low-power supercomputer on a module that provides extremely quick, accurate AI inferencing in everything from robots and drones to enterprise collaboration devices and intelligent cameras.
New O’Reilly Artificial Intelligence Newsletter
There is a new O’Reilly Artificial Intelligence Newsletter out. March 6,2017
Deep learning meets genome biology
Brendan Frey, a co-founder of Deep Genomics, talks about his work using machine learning to understand the genome and to realize new possibilities in genomic medicine. April 27,2016
The Rise of AI Makes Emotional Intelligence More Important
The booming growth of machine learning and artificial intelligence (AI), like most transformational technologies, is both exciting and scary. As machine learning continues to grow, we all need to develop new skills in order to differentiate ourselves. But which ones? FEBRUARY 15, 2017
Nvidia Shows Artificial Intelligence Revolution Is Biggest Trend Of Our Time
AI is increasingly being used in everything and everywhere, most notably data centers for machine learning, where Nvidia's GPUs have a tremendous lead over the competition......

Whatever happened to the DeepMind AI ethics board Google promised?
When the search giant bought the artificial intelligence company, part of the deal was setting up an ethics board. Three years on, where is it? Thursday 26 January 2017

'Partnership on AI' formed by Google, Facebook, Amazon, IBM and Microsoft
Two big Silicon Valley names are missing from the alliance, which aims to set societal and ethical best practice for artificial intelligence research Sept 28,2016

From the BBC Could robots be marking your homework? 14 December 2016

February 11,2017