Happy Sunday and welcome to the latest edition of Inside AI (Formerly Technically Sentient)! For those of you who are new, I'm Rob May, CEO of Talla and active investor in the A.I. space.
This week's issue is awesome. If you agree, I hope you will forward this to a friend so they can subscribe too.
Inside AI (Jun 11th, 2017)
-- BIG IDEA --
The most interesting thing I read this week was Tim O'Reilly's post "Do More. What Amazon Teaches Us About A.I. And the Jobless Future." Tim's core argument is that good applications of technology don't take jobs, they allow us to do more. He points out the growth in employees at Amazon even while they use more robots and A.I. Tim makes some great points, and I share his optimism over the next decade about the impact of A.I. on the economy. But, I think there are also plenty of counterexamples to Tim's post. And logically, when robots do every single thing better than humans someday, it seems likely that there won't be much reason for us to work, if we don't want to. Nonetheless, I'm not particularly worried about that outcome. It is a ways off and much will change before we get there so, I don't see the need to fret today. But Tim's article is a great contribution to this discussion.
-- MUST READ LINKS --
The Indestructible Idea of the Basic Income. Reason.
Much of the focus of A.I. writing is on what happens in a post-work world, if we reach it. This article is a fantastic comprehensive analysis of the history of Universal Basic Income, where it has been tried, what worked, what failed, and where it may go.
Dawn of the Ultimate Unfair Competitive Advantage. Medium.
A great post by Philipp Stauffer examining why A.I. companies may be the ultimate defensible business models.
Why Apple Is Struggling To Become An Artificial Intelligence Powerhouse. Washington Post.
The culture that made Apple great for the last decade is now working against the company as we shift to an A.I.-first world.
An Adversarial Review of An Adversarial Review of Natural Language Generation. Medium.
Yoav Goldberg, a natural language processing researcher, takes aim at the tone and what he considers extreme over-selling of some recent papers claiming NLP/NLU success. Also see Yann LeCunn's response to this.
The Yellow Brick Roadmap of Human Intelligence. Medium.
Last week we looked at Jeff Hawkins' argument that we need to look to the human brain to build intelligence. This piece argues the opposite - that we have other (often better) examples of intelligence from non-human sources.
-- INDUSTRY LINKS --
A Neural Approach To Relational Reasoning. Deep Mind Blog.
Adapt or Die. How A.I. Will Redefine Creativity in Marketing. Medium.
The Octogenarians Who Love Amazon Alexa. MIT Tech Review.
How Machine Learning Is Impacting The Way We Test Software. TechZone360.
The Machine Intelligence Behind Gboard. Google Brain Blog.
If Your Company Isn't Good At Analytics, It Isn't Ready For A.I. Harvard Business Review.
Rise of the Machines: AI and ML in Infosec. CSO.
Darpa Fund a New Type of Processor. EETimes.
Banned From the U.S.? There's A Robot For That. Wired.
DeepMind Shows That A.I. Has Trouble Identifying Homer Simpson's Actions. IEEE Spectrum.
Softbank Buys Robotics Company Boston Dynamics From Alphabet. Techcrunch.
Apple Launches CoreML - Machine Learning for Mobile AI. The Verge.
The Deep Learning Age Of Computing. Medium.
A New Technology From MIT Improves Robot Grip Dexterity and Sensitivity. MIT News.
A.I. Ethics Is Missing As Machine Learning Advances. Voice of America Blog.
$300 Yoga Pants Powered by Machine Learning. CNN.
Cortana Can Now Do Comparison Shopping For You. TechCrunch.
-- Commentary --
I recently finished Robin Hanson's book The Age of Em: Work, Love, and Life When Robots Rule the Earth. While the book is a bit technical, it's one of the first that approaches the future from a purely economic perspective. Hanson assumes that A.I. doesn't actually make enough progress to take over the world but, instead, we humans figure out how to scan our brains to make functional copies of ourselves. He calls these "emulations" or "ems" for short, and using basic calculations for hardware and electricity, estimates what it would cost to run an "em."
Hanson then proceeds to analyze, like an economist, what incentives would arise and how Ems would likely respond. He also spends a fair amount of the book cautioning the reader that these incentives could lead to a very strange world that we may not fully agree with. For example:
As the em world is a very competitive world where sex is not needed for reproduction, and as sex can be time and attention-consuming, ems may try to suppress sexuality, via mind tweaks that produce effects analogous to castration. Such effects might be temporary, perhaps with a consciously controllable on-off switch…it is possible that em brain tweaks could be found to greatly reduce natural human desires for sex and related romantic and intimate pair bonding without reducing em productivity. It is also possible that many of the most productive ems would accept such tweaks
The most interesting part to me, is the discussion about how Ems can easily spawn copies of themselves, then shut them down. Think of it as being able to parallelize your brain. You can spin up a copy to do one task and then shut it down when it is no longer needed. This has implications for law and society and much much more.
I'm not convinced in Hanson's argument that emulations are the future, but, what I like about this book is that much of the analysis can apply to disembodied minds in general, so it is just as relevant to A.I.s as it is to Emulations. If you want to learn more, you can watch Hanson's Ted Talk. If you are looking for a thought provoking summer read, this is a book worth checking out.
That's all for this week. Thanks again for reading. Please send me any articles you find that you think should be included in future newsletters. I can't respond to everything, but I do read it all and I appreciate the feedback.
@robmay
-- ABOUT ME --
For new readers, I'm the co-founder and CEO of Talla, I'm also an active angel investor in A.I. I live in Boston, but spend significant time in the Bay Area, and New York.
