This newsletter sometimes contains affiliate links for places that I think are amazing.

Here’s my weekly round up of Automation and AI news:

9th August 2019



Everyone is using data science for sport

ESPN were able to produce a ranking of teams based on their use of analytics. As it turns out one of the most successful football teams in the world doesn’t have an analytics team.




The Future of Work: Preparing for Disruption

There’s a cool MOOC on the future of work by the World Bank starting on 19th August.

The Future of Work: Preparing for Disruption is about automation, lifelong learning, reentering the workforce, social inclusion etc. 

A Great Tweet by Francois Chollet

“I am pretty critical of deep learning in general. Simultaneously, I invest tons of work into deep learning. I don't intend to dwell on its limitations and leave it at that. I want to overcome them.

I *am* a deep learning fan.”

Why traders and finance professionals should move away from Excel and use Python

Some really great arguments about why you need to be scripting in Python for repeatable and less error prone data analysis. Even some major firms are teaching their traders to code.



How to ship your first Python package

If you ever thought of contributing a package this is the video for you. There are also things you can take away to develop your own Python packages to share with your team.

Tensorflow Extended: How to Deploy your Tensorflow Models

Have a look at this video series, this is the latest video. The difference between your tensorflow model running on your laptop and running on the Cloud.

Using Visual Studio for debugging

Many data scientists don’t use Visual Studio for their development, I think it is a pretty sweet tool if you are writing code to deploy data products. Here is a run down of the debugging features.




There seems to be a bit happening with various Government departments in Australia moving from paper and Excel to automation and AI, so really exciting. Some really great people have reached out to me last week. 


Some of the short term 3-6 month contracts look really interesting to me. That’s the sweet spot for me (ideally work from home, but that is tough in Australia). So yeah pretty keen to check out of here for 3-6 months to avoid the hottest part of Summer where even I melt.


I’m hanging around here in Bundaberg for a week before heading to Brisbane for a few days to see a client. A really great company in the mining industry based in Brisbane.


Next month I will have a few presentations, one for Data Science Melbourne:


and the other for TedX. So I’ll have to get cracking on those later this month:

Apologies for the hiatus on the newsletter, I thought I would try a new format and also let you guys see a bit more about what I am learning and what I am up to.


5th August 2019


Here’s a throwback to the 1990s. Dial up internet sounds, MSN Messenger and all that other good stuff we have all been missing for the last 20+ years, 


Andrew Yang raises concerns about automation and job loss.

It is extraordinary to me that concerns about automation and job loss have entered political debates. In my mind AI and automation will create more jobs that it destroys but there will be some short term pain for long term gain and opportunity.

ArchiGAN generates floorplans for apartments using Tensorflow

This thing blew my mind, just give it a shape and it will generate some really impressive floor plans for an apartment.

Microsoft invests $1b in OpenAI

I keep thinking we are pretty far away from AGI (Artificial General Intelligence) but maybe not as far as I thought. You see, currently the AI we develop has a very narrow scope and applicability, a system may detect credit card fraud and nothing else for instance. However opening the door to AI that could be applied to many domains is truly exciting.

The final course for the TensorFlow in Practice Specialisation on Coursera has just dropped


PowerApps AI Builder

I freaking love PowerApps. It takes the headache out of building a mobile app to capture data. Think of technicians out in the field, or people capturing credit decisions. What’s amazingly cool is that it now has AI capabilities. This is amazing.

Deploying R Models on Azure

There’s a great series of slides on deploying R models using Azure Pipelines and Azure ML. The YAML and R files are also available in this repo. There is also links to some great resources.

Microsoft Flow Online Conference

9 hours of free tutorials on how to automate business processes using Microsoft Flow on September 10th 2019 from 9AM EST.

Microsoft Code Samples

This is pretty cool, a library of 1124 code samples to get you up and running with Microsoft dev stack.


Developing Business Applications with Microsoft PowerApps, CDS, and Flow

Learning path for Azure Data Engineer

I was pretty excited to discover this, I had picked up bits and pieces of Azure, but never seen anything comprehensive like this.

Here’s the path:


Here’s the certification at a high level:




I have been overseas for the last month (New Zealand and the UK), so the thing now is to re-engage with the local data science and business community. 


I am pretty much swinging my consulting around to targeting larger companies looking at getting into automation and AI using the Microsoft tech stack. I think the Microsoft tools for automation and AI, as well as the Team Data Science Process and Azure DevOps etc just knock the competition out of the park.   


There have been a few meetings with some organisations in Regional Queensland which is encouraging, at the same time there are a few interesting looking short term (3-6 month) contracts emerging from the capital cities namely Brisbane and Sydney. Sydney would involve moving the dogs and kids there for 3-6 months, but that would just be another cool adventure for everyone, something I am quite interested in. Also my folks are around there and it is close to where I grew up. 


I’ve also had a few really great conversations with some of my friends in the data science community around Australia, always great to hear from these guys! By the look of things this month will involve another few trips to Brisbane, which is a great city!


Next month I will have a few presentations, one for Data Science Melbourne and the other for TedX. So I’ll have to get cracking on those later this month.

13th June 2019.


Have a top week everyone!




Top Common Errors with #Python + How to Fix Them

A useful summary in a graphic of how things can go janky with python and what those cryptic warnings actually mean.


10 Frequently Asked ML Interview Questions

You may not be asked these exact questions in an interview, but it is worth digging around for these sorts of questions before heading to an interview.

A Coursera Specialization for App Developers Deploying Applications on Google Cloud Platform

“In this specialization, application developers learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem.”



TF.Text released

The aim of the library is to make it easier to work with text in Tensorflow models.

LOLs by Hadley

A great quote by Hadley "It’s true. I’ve tried to make some plots in Python and it was not pretty." To be honest with you all, I feel the same way. Some things Python is amazing at, but to me ggplot is a winner. Interview here aimed at data journalists.

TensorFlow can be used to standardize interfacing with many public research datasets

New Tensorflow Datasets standardizes interface to public datasets. It makes it easier to grab public data and play around. So, it is easier for you to feed into a ML pipeline.



Robert Downey Jr.'s "Avengers" character Tony Stark is a genius bent on using technology to save the world.

Now with life imitating art he wants to do the same thing in real life.

Tableau Acquired by Salesforce

For just a silly amount of money, but it is interesting.

Do Your Data Scientists Know the ‘Why’ Behind Their Work?

More than this the article talks about why data science projects fail and what you can do about it.



Kaizer Chiefs would like to sponsor 20 women to take up a four-month Data Science course.

It’s the Microsoft Professional Program through Pink Codrs Africa. The sign up form is here:

And there is more information here:


Applications for our Applied AI growth programme are now open

A “scaleup growth programme for ambitious UK companies that place artificial intelligence at their core. The programme, part of the UK Government AI and Data Sector Deal, is designed to give a cohort of some of the UK’s most exciting tech companies exposure to later-stage founders with first-hand experience of key scaling challenges, and a peer network of like-minded founders structured under values of honesty, intimacy and trust.”

Laptops for developers

A great program to donate money for laptops and online courses to aspiring developers in Africa. Really there should be more of this.

6th June 2019

Have a top week everyone!


A really gentle approach to linear algebra

If you want to know Linear Algebra in detail I would recommend Gilbert Strang, if you want a quick overview of important concepts have a flick through this. Remember machine learning is really just playing around with matrices.

A look at some of the Google Udacity Deep Learning Course Assignments

These CNN exercises look like pretty fun challenges, to be honest I don’t know much about the Udacity Deep Learning course. If anyone has done it I’d be curious to know.


Data Science Cheat Sheet

Some of these can be pretty ordinary, this one is more about high level concepts than code.

Microsoft AI for Earth

I can’t believe I am just hearing about this, and that this video has had only 65 views. Microsoft has $50m in grants for people using AI for sustainability.

It is incredible, and I have never heard of this, it’s completely awesome!



An AI-driven robot hand spent a hundred years teaching itself to rotate a cube

This seems like a bit of a lame exercise, but the idea of the robot getting better and better through reinforcement learning is pretty cool. Much better way of implementing this kind of dexterity as opposed to a bunch of “if” statements. You can see the motion of the cube in the hand looks a bit how we’d play around with a cube in our hands. Super cool!

Watch a GAN forget a face

I am constantly amazed at how as we move down the road of AI we learn more and more about ourselves. By switching off neurons gradually we can see how the neural network effectively forgets a face. It’s cool and creepy at the same time.

AI doesn’t run on magic pixie dust

“Artificial intelligence doesn’t run on magic pixie dust. It runs on invisible laborers who train algorithms relentlessly until they’ve automated their own jobs away.”

Whether that is hand labelling data or testing algorithms there are plenty of people (often smart people) still doing this grunt work required to get algorithms to work with good data.

30th May 2019


Have a top week everyone!




How to explain neural nets to a 5 year old

A laugh out loud, but undeniably brilliant explanation using the idea of little league baseball kids screaming their preference for lunch at you. Each kid screams their preference (based on their past experiences eating out) and you go with the loudest thing you hear. Just brilliant!


Keras: Feature extraction on large datasets with Deep Learning

A great tutorial by Adrian Rosebrock. Part 2 of a 3 Part series on transfer learning. This tutorial walks through how you can do feature extraction on large image datasets when the dataset won’t fit in your computer’s memory. Hot tip: use incremental learning (also known as online learning)!

Data from freaking Mars!

Maybe you are a bit sick of doing a data analysis using the Iris or Titanic data? Well here is data from Mars!  There is going to be more and more of this data released to the public. The new release was on May 24, 2019. It includes raw data from November 26, 2018 - February 28, 2019.




Python 2 will reach end of life on 1/1/2020

So that’s another potential Y2K issue waiting right there for the procrastinators. So if you have projects using Python 2 make sure you switch them over to Python 3!

How to train and evaluate a deep learning model for very imbalanced classification.

This one is from Francois Chollet, detecting credit card fraud is a very, very difficult problem with very few known true frauds in the data. This example uses the Kaggle credit card fraud dataset. It’s an interesting notebook and well worth stepping through. The hardest thing about these problems of course is what about the frauds we haven’t correctly flagged in the training data? Still a great solution to a very tricky problem.


Swift for Machine Learning, it’s going to be big!

I’d encourage you to jump in and have a play around. Chris Lattner the inventor of Swift talks about using Swift for Machine Learning. At a high level using Swift for ML allows you to customise your tensorflow code at a level you just can’t get at easily with Python. I mean you can get so far and then the library drops down to C++ and you are kind of screwed, you have to switch debuggers and it is just pain. are already doing a lot of work with Swift and Tensorflow.

Get started with Swift for TensorFlow →

A Swift Tour in Colab →

Swift on →



Watch Mona Lisa smile in a deep fake video!

Deep fakes are getting amazingly good and creepy at the same time. Here researchers used a Deep Fake algorithm to make Mona Lisa smile. However, it isn’t great if this technology was ever weaponised, I mean imagine making it seem like any world leader said anything at all?

If Your Data Is Bad, Your Machine Learning Tools Are Useless

It’s what people in the industry know to be true. Charles Babbage had a good idea when he invented his “computational machine”. Here’s what he says on the subject:


On two occasions I have been asked, — "Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?" In one case a member of the Upper, and in the other a member of the Lower House put this question. I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question."

AI will tell you who to cast and predict how much money you’ll make

There are a few companies out there with software aimed at film makers helping them predict how much money they will make from films with different permutations of themes and key talent. This is interesting reading, also interesting to think of the public datasets that are available which could be leveraged for building AI SAS solutions.


There’s a beautiful quote I’m going to pull out (I see this everywhere):

“On a film set now, it’s robots, it’s drones, it’s super high-tech, but the business side hasn’t evolved in 20 years,” he says. “People use Excel and Word, fairly simplistic business methods. The data is very siloed, and there’s hardly any analytics.”

23rd May 2019.

Have a top week everyone!


How to ace data science interviews

Microsoft Free AI with Azure Learning Path

A set of free videos highlighting features of the Microsoft AI stack.

Very, very simple Machine Learning introduction

I mean you could send this to your 96 year old great-uncle

Matrix Methods in Data Analysis, Signal Processing, and Machine Learning

Free course from probably the best linear algebra lecturer on the planet


The Deep Learning Humble Bundle

A stack of cheap deep learning books supporting charity.

Tensorboard introduction

Data Science Learning Path For Complete Beginners


Canada slashes funding for AI research

$20 million from the Vector Institute for Artificial Intelligence and $4 million

annually from the Canadian Institute for Advanced Research (CIFAR).

A.I. Took a Test to Detect Lung Cancer. It Got an A.

Computers were as good or better than doctors at detecting tiny lung cancers

on CT scans, in a study by researchers from Google and several medical centers.

Top Data Science and Machine Learning Methods

This has been my experience too, everyone is talking AI big game but the reality

is regression and decision trees are still getting used everywhere.

Why many machine learning projects fail to deliver results and how product management is adapting to AI

A really great “in the trenches” account of how ML projects can go janky.

16th May 2019


Have a top week everyone!


The best public datasets for Machine Learning and Data Science

80 Best Data Science Books That Are Worthy Reading

Using Python for Research

Harvard course on edx. Introduces python syntax, tools and scikit-learn.

CS50's Web Programming with Python and JavaScript

Your ML model will probably need to sit on a website, this course takes you through Flask and Django as well as everything else you need for a web app in Python.


TensorFlow Model Optimization Toolkit — Pruning API

Weight pruning for Tensorflow models.

Free ebook “Foundations of Data Science” available to download

All the main types of neural networks in one chart

InterpretML: a library to enable intelligibility in machine learning


Microsoft to Release Version of Word That Makes Your Grammar ‘Politically Correct’

New features will screen out ‘offensive’ language.

Robot valets may soon park your car at this London airport

Geoffrey Hinton Explains the Evolution of Neural Networks

10th May 2019

Have a top week everyone!


Deep Learning Specialization Coursera

A series of courses for breaking into AI.

Microsoft Introduction to Data Science Course edx

First step to becoming a Data Scientist.


TensorFlow Federated: Machine Learning on Decentralized Data

TensorFlow Federated (TFF) is an open-source framework for machine learning and other computations on decentralized data.

Smarter training of neural networks

MIT team shows that neural networks can work just as well even if they're 10x smaller.

The Artificial Overmind Challenge

You can enter a competition to build an AI that can play StarCraft 2.

R drops out of top 20 programming languages

Even though there are stacks of data jobs at the moment, it is looking like Python is winning.


Machine Learning Can Make Jordan Peterson Rap Like Eminem

Using AI, someone made a very haunted video of Jordan Peterson rapping "Lose Yourself."

AI Helps Generate Speech From Brain Recordings

Brilliant news, one day it may be possible for people who can’t communicate to generate speech with their thoughts.

Why Python is more popular than Kim Kardashian

Google searches for the open-source project outstripped those for the reality star in the last 12 months, according to The Economist.

Crossing the Big Data / Data Science Analytics Chasm

A great article on the evolution of analytics in an enterprise and how to push your business further along the path.

2nd May 2019

Have a top week everyone!


MIT 6.S191 Introduction to Deep Learning has been open sourced

I mean this happened in February, but you should definitely check it out.

AI for Everyone

If the above course is a bit heavy feel free to check out this introductory course.


Data Analysis and Interpretation Specialization - using SAS or Python

Plenty of places like banks and insurance companies do their analysis in SAS. Until recently I was unaware that there were SAS courses on coursera. For everyone else though who don't have access to SAS this specialization uses Python which is open source.

Blockchain: Understanding Its Uses and Implications

Understand exactly what a blockchain is, its impact and potential for change around the world, and analyze use cases in technology, business, and enterprise products and institutions.


A Recipe for Training Neural Networks

Andrej Karpathy’s tips and a process for training neural networks. This blog post is simply awesome!

The Humble Book Bundle: Python by O'Reilly

Really cheap python book bundles supporting charity, it’s a really nice thing!

Python at Netflix

A discussion of how Python is used at Netflix.

Free Python Data Science coding Book series

Data Science Central is launching a free book series “AI / ML coding in a weekend”


Sep 2008 - Nov 2018: How Python became the dominant language thanks to ML

A visualization of the most popular programming languages on stack overflow.

Facebook Says First-Person Christchurch Video Foiled AI System

Terror footage from a first-person perspective "was a type of video we had not seen before,”. Because a video like this was not in the training data sadly Facebook’s artificial intelligence failed to flag the video.

Computer scientists design way to close 'backdoors' in AI-based security systems

Interesting short article about how people could trick AI systems and how some researchers are looking at ways to stop such attacks.

Fuelling change in the vehicle architecture with big data

I was blown away to discover that autonomous vehicles are the largest producers of data in the world. In one tenth of a second they collect 15,000 pieces of data!

How Technology Could Revolutionize Refugee Resettlement

A software program called “Annie” uses machine learning to place refugees in cities where they are most likely to be welcomed and find success.

26th April 2019

Have a top week everyone!


Convolutional Neural Networks in TensorFlow.

Course 2 of the TensorFlow Specialization is now available on Coursera. Check it out!


Astrobiology: Exploring Other Worlds

After seeing an image of a black hole I have become interested in space and data together. There’s a new MOOC out “Astrobiology: Exploring Other Worlds”. My hot tip is the person who discovers evidence of alien life is going to be a data scientist!


Links on Mathematics for Machine Learning from Towards Data Science

However, notably missing from the article was a Coursera Specialization called “Mathematics for Machine Learning


Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data

New Data Science Cheat Sheet, by Maverick Lin

A beginner’s guide to AI: Neural networks

Intro to neural networks, GANs, CNNs, CNNs.

Control Flow in TensorFlow

An internal training video from the TensorFlow team

ML.NET 101 Tutorial

Machine Learning for .NET apps

Swift for TensorFlow (TensorFlow Meets)

Jeremy Howard talking about a new course he is creating for Swift and about Swift for numerical computing.

Automated Machine Learning: how do teams work together on an AutoML project?


AI Startup Zebra Medical Vision Enlists Deep Learning To Save Lives

Former NASA astronaut Mark Kelly hopes to bring some science to the Senate

‘Science and data is at the root of most of the issues that we have to deal with’

The only way to rein in big tech is to treat them as a public service

“The drive for profit is behind many of the ills of Google, Facebook et al. Unions and public ownership are the only way to solve this”

Debunking The Myths And Reality Of Artificial Intelligence

An article about the current state of play in AI including a sobering view of the “smoke and mirrors” elements. A fantastic read!

Machine Learning vs Traditional Programming

Revisiting the Jobs Artificial Intelligence Will Create

A discussion with a couple of guys who put together an 2017 article called “The Jobs AI Will Create”. Fantastically interesting stuff!

Machine teaching – How people’s expertise makes AI even more powerful

Bringing domain experts and data scientists together in the same room!

19th April 2019

Happy Easter everyone!


Sebastian Thrun discusses the new Udacity Intro to TensorFlow for Deep Learning course and how TF 2.0 makes it easy to get started with Deep Learning

Specialization: Machine Learning
 from Coursera


MRNet dataset of 1000+ annotated knee MRIs

A new knee dataset of MRI images released and there is also a competition to classify knee injuries from the dataset

Transformer model for language understanding

Tutorial from Tensorflow showing how to write model to translate Portuguese to English. (Warning: this is pretty heavy).

Good News For Data Scientists, Google Launches AI Platform To Democratize ML

This is again me prattling on about how Google Cloud and Tensorflow will be a winning combo, the AI Platform from Google simplifies the process of ingesting data, model development and deployment.

The best machine learning and deep learning libraries

The article requires you to sign up, you don’t have to but follow the links in the “at a glance” section to read more about the libraries.

Tensorflow Extended (TFX) Developer Tutorial

A simple introduction to the steps required to build and deploy a Tensorflow model. Links for more advanced tutorials in the article.

Top 5 Machine Learning Projects for Beginners

Starting is often the hardest part, but here are a few approachable projects for building your portfolio.


AI Robot paints its own moonscapes in traditional Chinese style

I really can’t make this stuff up!

Stackoverflow survey says Python is the fastest growing language

My hot tip is because data science is “so hot right now”! :)

Sophia the humanoid robot to speak at Transform Africa 2019 summit

Sophia will be speaking about artificial intelligence at the 5th Transform Africa Summit to be held in Kigali, from the 14th to the 17th of May 2019.

'Disastrous' lack of diversity in AI industry perpetuates bias, study finds

It makes sense, if a lot of people doing AI are white and male there is probably going to be bias there.

How Millennials Should View the World of Data Science

A recipe for how to think like a data scientist and how to work well with data scientists.

11th April 2019


Have a top week everyone!




Machine Learning with TensorFlow on Google Cloud Platform Specialization

I keep saying Tensorflow with Google Cloud is a killer combo for building and deploying ML.

Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization

^read above… I keep saying it! :)

Kaggle CareerCon is a totally free, totally digital three-day event that's all about helping new data scientists land their first data science jobs. This year the event will be held from April 16 - 18th.

Coursera Announces Two MOOC-Based Degrees from the University of Colorado Boulder.

I can see the writing on the wall for brick and mortar higher education places that don’t have offerings online. Last week Imperial College London announced a Master of Science in Machine Learning on Coursera.

Star Trek: Inspiring Culture and Technology: a new MOOC course from edx

Strictly speaking this isn’t data science or AI, but I thought it was pretty cool!

Programming 101: An Introduction to Python for Educators
This one is a free intro to Python programming.



Which Machine Learning Algorithm To Choose For My Problem?

Really great intuitive article of advantages and disadvantages of each algorithm and a walkthrough of the process of fitting models to data.

Inferring the function performed by a recurrent neural network

Short article, it has a bit of math. Using reinforcement learning to understand what a recurrent neural network is doing.

Expanding Google Cloud AI to make it easier for developers to build and deploy AI

Man, did you see what I was saying above about Google Cloud? Well, here it is again. AI platform and AutoML updates from Google. Making running models and managing and deploying AI solutions easier for teams.

Unlocking the power of AI with solutions designed for every enterprise

Google is going hard with its enterprise play for business. Document Understanding AI for digital documents, Contact Centre AI for customer conversations - this was the compelling hair salon booking demo!  

Uber AI Labs Open Sources Pyro, a Deep Probabilistic Programming Language

A probabilistic programming language unifying deep learning and bayesian modeling.


Top 10 Artificial Intelligence Trends in 2019

Look, some of these lists can be kind of dumb. This one however resonates with what I am seeing and reading.

How Swisscom’s Custom-Built TensorFlow Model Improved Business Operations by Classifying Text

TensorFlow business cases from a Telco.

Supercharge Your Social Media Marketing With Artificial Intelligence

AI social media use cases: chatbots and virtual assistants.

A Biologically Plausible Learning Algorithm for Neural Networks

Backpropogation is not how the brain actually works.. These researchers thought of a biologically plausible way that neural networks could learn using an unsupervised learning approach.

Foundations Built for a General Theory of Neural Networks

Some researchers are working on a theory of neural networks, how they work, how to structure and optimise them.

Top 10 Big Data Challenges – A Serious Look at 10 Big Data V’s

Volume, Variety, Velocity, Veracity, Validity, Value, Variability, Venue, Vocabulary, Vagueness.

The Age of Robot Farmers

AI based farming will be taking over a lot of the repetitive, labor-intensive farming work.

The AI Roles Some Companies Forget to Fill

AI is a team sport and requires math and stats as well as engineering, business and leadership skills to work.

April 5th 2019


Collection of DataScience and Machine Learning Cheat Sheets for Data Scientists

Pretty self-explanatory really!

What machine learning tools do the people who win Kaggle competitions use?

A graph of the top 5 tools. A tweet by Francois Chollet.

22 Great Articles About Neural Networks

Call for speakers at the TensorFlow World Conference

Which Deep Learning Framework is Growing Fastest?

Tensorflow vs PyTorch.


Imperial College is launching an online Coursera Masters degree in Machine Learning

You can check it out here, really is amazing to see machine learning education available like this!

Andrew Ng Interviews with Yann LeCun and Geoffrey Hinton

New online course from AWS and Coursera - AWS Fundamentals: Building Serverless Applications

Starting programming with Python

Free course on Tensorflow: Intro to Tensorflow for Deep Learning




The College Fix

Duke University to pay $112.5 million for faking scientific research data.

But, they did it to get research grants that they probably wouldn’t have got… so you know...

LeCun, Hinton and Bengio win the Turing Award for their work on neural networks.

I mean these dudes were into neural networks before they were cool, I mean when they were powerfully uncool!

How Machine Learning is being used in Medicine.

Machine Learning is being used to grow extra delicious tasting basil plants.

Models are being trained on taste outcome to determine the ideal growing conditions.

IBM artificial intelligence can predict with 95% accuracy which workers are about to quit their jobs.

Researchers are building an artificial intelligence system that can mimic human clinical decision making.


Done right, machine learning could transform treatment and diagnosis for patients worldwide