10.16.16 Recap

Annnd, we're back. Continuing to map various readings, notes, and musings over the weeks.

Differentiable neural computers by Google DeepMind
Blog post on DeepMind's recent work on adding memory to neural networks (see below for paper).

Hybrid computing using a neural network with dynamic external memory by Google DeepMind
The associated paper in Nature from DeepMind mentioned above ☝️.

Graph Powered Machine Learning at Google by Sujith Ravi
Highlights Google's work with graph-based, semi-supervised learning. Pretty awesome work where they are taking multi-graph representations of data and are pairing them with nodes of concepts and edges connected by similarities.

Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation by Sujith Ravi and Qiming Diao
A paper from the Sujith Ravi (author of the Google post above ☝️) that covers some of this work.

The Hive is the New Network by Arjun Sethi
Networks are so 2015, or so they say. Arjun Sethi from Social Capital outlines the notion of a 'hive' and its implications for products and companies.

We don't sell saddles here by Stuart Butterfield
Found this old memo from Stuart to the team as they built Slack. Great principles for early stage companies to embrace and hits on core topics from building great product, to selling, to driving change, to execution. TL;DR - Build something people want. Market from both ends. Sell the innovation, not the product (to which he noted, we're not selling "a group chat system...what we're selling is organizational transformation). Who do we want our customers to become? How do we do it? ("We do it really fucking good.") Why? ("Because why the fuck else would you even want to be alive but to do things as well as you can? Now: let’s do this.")

Neural correlate of the construction of sentence meaning 
Interesting work on how brains extract and hold meaning from words.

Some good AI/ML courses that I've come across recently:
- MIT Artificial Intelligence 6.034 by Patrick Henry Winston
- MIT Human Intelligence Enterprise 6.803 by Patrick Henry Winston (via kennethfriedman on HackerNews) 
- CMU Machine Learning 10-601 by Tom Mitchell and Maria-Florina Balcan

Go to Market Bootcamp by by Jaimie Buss, Tom Butta, Mark Cranney, and Mahesh Iyer
Came across this from a16z and thought it had some good info for developing go-to-market strategies and building out sales teams.

If SaaS Products Sell Themselves, Why Do We Need Sales? by Mark Cranney
Speaking of a16z and sales teams, Mark Cranney dives into the importance of sales and what it's like to sell to the enterprise.

The AI Revolution: Why Deep Learning is Suddenly Changing Your Life by Roger Parloff
General overview on some of the ins and outs of AI, what it is, and why it matters in Fortune. Always interesting to see what people think about the matter, even if the subject itself is a bit old news.

How to Keep Building Great Organizations by Willy Braun 
Applies the Red Queen Effect to organizations and corporate development.

The idea maze for AI startups by Chris Dixon
Older post, but familiar maze. Highlights some of the challenges facing AI startups.

ICYMI - Data isn't a business model, it's much more important by Tomasz Tunguz
Tomasz preaching the importance of data for both product and businesses alike.

Airbnb is offering free housing to people displaced by Hurricane Matthew
Saw this and thought it was awesome -- much love for Airbnb 🙌