10.23.16 Recap — Wesley Pennington

Reid Hoffman at Startup School with Sam Altman by Y Combinator
"Anyone inventing products should be able to articulate a...robust theory of human nature." Always enjoy hearing Reid talk, this being no exception. Great insights and interview with Sam.

Historic Achievement: Microsoft researchers reach human parity in conversational speech recognition by Microsoft Research
Major advances in speech recognition by Microsoft Research -- essentially, as accurate as a human. Here is the research paper, worth the read.

And now, a major appearance by POTUS...

Preparing for the Future of Artificial Intelligence by WhiteHouse.gov
As a follow up from the RFI, the White House posted a report on what they perceive to be the future with AI. Plenty to dig into here, but if you are interesting in more of the policy, check out the National AI Research and Development Strategic Plan.

Barack Obama, Neural Nets, Self-Driving cars, and the Future of the World
The president in conversation with MIT's Joi Ito and WIRED's Scott Dadich on how AI will shape the future.

Hey Silicon Valley: President Obama Has a To-Do List for You by Jason Tanz
President Obama outlines imperatives for the Silicon Valley and industry leaders respond.

Awesome to see the President take an interest in tech. Now back to our regularly scheduled programming...

AI research is a ‘moral imperative’ with the power to save lives, experts say by Nat Levy ft. Shivon Zillis and Oren Etzioni
The Partner at Bloomberg Beta and CEO of the Allen Institute of AI share a conversation on the potential impact of AI.

Clay Christensen's New Theory of Innovating has Everything to do with Hiring by Gwen Moran
In his new book -- Competing Against Luck: The Story of Innovation and Customer Choice -- Clay Christensen discusses how the most successful products today aren't bought, they are hired to do a job. Well, yeah. Seems pretty intuitive, especially if you operate in SaaS or run a marketplace. Nevertheless, Christensen offers some good perspective about the tech industry (see, The Innovator's Dilemma) and provides some useful insight -- even if the thinking isn't entirely new.

There is a blind spot in AI research by Kate Crawford and Ryan Calo
With the field moving fast and a focus on technological advances, Crawford and Calo urge researchers to acknowledge and address the shortcomings of the current state of AI systems. In certain contexts, bias and prejudice have been shown to disproportionately affect groups that are already disadvantaged by factors such as race, gender and socio-economic background. This needs to change.

Deep Learning Papers Reading Roadmap by Flood Sung
A curated list of papers on deep learning. If you are looking for more resources or ways to download all of the linked files, check out the Hacker New comments on the matter.

Disney Open Source by Disney
Disney open sourced some tech.

Machine Learning is the New Statistics by Daniel Miessler
FWIW - some are calling ML the new stats.

The Challenge Facing Deep-Learning Powered Startups by Tomasz Tunguz
Not very deep (or technical), but highlights some of the challenges AI faces. Deep learning, in particular, can't always answer 'why.' Sometimes this matters more, and sometimes it doesn't. Nothing new, but true nonetheless and interesting to think about. Ca also appreciate Tomasz's take (and the fact that he always be blogging).

Stephen Hawking opens British artificial intelligence hub

How Network Neuroscience Is Creating a New Era of Mind Control by John Medalgia, et al
Crazy to think about. Also, crazy how productive this group out of Penn is -- Danielle Basset t and colleagues have been on a tear. [Including my boy, Richard F. -- I see you.] Here is a link to this particular research paper if you want to dive deeper.