Inside AI - June 3rd, 2018 |

Inside AI (Jun 3rd, 2018)

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Welcome to this week's edition of InsideAI.  I'm Rob May, CEO at Talla, and an active angel investor in the AI space.

 If you like the newsletter, I hope you will forward this to a friend so they can subscribe too.  

Or if you really want to support us, go Premium and get a special Wednesday edition each week, plus extra analysis and reports. Thank you to AstroAscent,  Kylie, SwissNex, and Dataquest, for being sponsors. (email if you want to become a sponsor.)

Talla is co-sponsoring a small AI/Blockchain conference on June 28th in NYC.  Check it out if you want to learn about what is happening at the intersection of these two interesting technologies.

-- Changes To InsideAI --

This newsletter started 3 years ago this month as Technically Sentient.  At the time, Talla was just getting started.  Now, 3 years later, we've been rolled up into the family, and are one of the most popular newsletters in the group.  And Talla is taking up more and more of my time, so, we have decided to make some changes.  A few months ago, Deb Kees started helping put together some of the weekly links, and for the past few weeks she has written almost all of the Wednesday updates herself.  So we have decided to move InsideAI to a shorter, daily format M-F.  Deb will write about a handful of links each day, and I will still provide a Big Idea on Monday and some commentary every other Friday.  My off Fridays will be filled in by various AI experts and writers who have applied the past few weeks.

Please give us a couple of weeks to get in the groove with the new flow, and then let us know what feedback you have and what more you would like to see.  Our goal remains to give you a good high level business/applied overview of what is happening in AI.

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--Must Read Links--

Machine Un-Learning: Why Forgetting Might Be the Key to AI. Hackernoon. 

For humans, forgetting is the way that the brain filters out information and makes room to process new information. This neuroscience principle may be helpful in machine learning. 

Microsoft is Creating an Oracle For Catching Biased AI Algorithms.  MIT Tech Review.

Some great ideas out of Microsoft for understanding and detecting bias, which will be necessary as AI algorithms get more widely deployed.

IBM Researchers Explain Machine Learning Models By Exploring What Isn't There.  Forbes.

A really cool approach best summed up by this quote from the article "What this means in practice is that, for example, if a machine learning model is identifying photos of a dog, this method can be used to show not only what the machine model is using to identify a dog (like fur and eyes) but also what things have to be absent for the model to identify a dog (like it doesn’t have wings.)"

--Industry Links--

Facebook VP & Chief AI Scientist LeCun on Advancing AI. (Bloomberg)

Beer-slinging robot predicts whether you’ll give that brew a thumbs up—or down. (Science Mag)

A CIO Hall Of Famer's Approach To Machine Learning. (Forbes)

Machine Learning: Making it work in the real world. (ZDNet)

Machine Learning vs. Machine Reasoning: Know the Difference. (EdgyLabs)

FDA permits marketing of artificial intelligence algorithm for aiding providers in detecting wrist fractures. (FDA)

ARM Details "Project Trillium" Machine Learning Processor Architecture. (Anand Tech)

The Real Scandal of AI: Awful Stock Photos. (Medium)

On the contribution of neural networks and word embeddings in Natural Language Processing. (KD Nuggets)

Four ways AI can make healthcare more efficient and affordable. (Medium)

AI Design Guidelines: A listing of the latest publications on best practices for UX and conversation design using AI. (Medium)


--Research Links--

Context Exploitation Using Hierarchical Bayesian Models.  Link.

Teaching Meaningful Explanations.  Link.

Thanks for reading.  Please send articles and topic ideas via email.  I can't respond to everything but I do read it all.



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