AI software market to hit $78B by 2025, here are the top applications for the technology

Apparently the global market for AI was $2.65 billion, mainly focused on a few core suppliers. The US is the biggest single spender at over 35%, and although text processing was the most common used application in 2017, this is clearly expected to move towards video and other media over the coming years.
The market for AI software is exploding, with IBM and Google leading global suppliers, according to QY Research.

Survey: Whole Foods customers have liked changes since Amazon takeover

As if to back up concerns that grocery retailers should be scared of Amazon's entry to the segment, Whole Foods customers are reporting mainly positive improvements since the purchase by Amazon last year, including higher quality merchandise, and of course, the promised lower costs.
According to a new survey released by market research firm Morgan Stanley, Whole Foods customers indicated they have had a better overall experience at the grocer since Amazon took over last fall.

Strategic Competition in an Era of Artificial Intelligence

A further useful insight from the CNAS report is the list of properties of successful AI adoption which should guide both private as well as state interests:
– possessing large volumes of the right data
– training, enabling and sustaining people with the right (AI) skills
– identify the correct incentives for adoption – including recognition of AI as a general purpose tool
– ensure strong collaboration between public and private actors, including development of appropriate regulatory frameworks (e.g. balance of privacy vs. public interest, or whether distribution of AI-specialised hardware should be controlled like weapons are today)
Developing strong, pragmatic and principled national security and defense policies.

Strategic Competition in an Era of Artificial Intelligence

In choosing to frame previous industrial revolutions in terms of warfare and the balance of power between state actors (instead of, say, improvements to the lives of individuals, redistribution of wealth to reduce global inequality, or the generation of new forms of capital and "worthwhile" work), the authors are able to articulate a clear set of actions for the US (or any) government who wants to build and cement a technological advantage in to a global projection of power.
Developing strong, pragmatic and principled national security and defense policies.

Walmart wants us to believe it’s turning into a tech company

I'm not sure I'd call facebook (media), Amazon (retail, logistics), uber (cabs) etc. technology companies now either. Yes, they are heavily technology-leveraged, but ultimately the machine under the covers matters less than what it achieves. Walmart, like many large companies, is identifying that significant new business opportunities can be released by better leveraging technology. Does that make it a "tech company"?
Its latest partnerships and new services show the retailer’s continued evolution toward becoming a tech-focused business.

Hinge uses AI to suggest a ‘most compatible’ date every day

I'm not sure what to make of this report. I remember reading about the history of "online dating" and how it is all basically smoke and mirrors (if people believe "the computer" paired them for a reason their dates are more likely to be successful, so does AI really help?
It’s betting that machine learning can find a mutual match.It’s betting that machine learning can find a mutual match.

Facebook improves AI by sending ‘tourist bots’ to a virtual NYC

A recent experiment by Facebook pitted humans against AI to see which was better at helping another robot to navigate a (virtual) walk around an area of Hells Kitchen in New York. The bot had to describe its location using natural language ("I can see the bank on the corner"). Although the AI only scored 50% in this mode, when using "symbols" instead, it was able to beat humans 87.08% to 76.74%. The two AI were able to communicate far more efficiently than humans could. But as a test for their new "MASC (Masked Attention for Spatial Convolution)" model, it was a success.
Virtual guides help a ‘lost’ AI find its way.

Stanford AI can predict negative side effects of millions of drug combinations

Often when prescribing multiple drugs, doctors have very little information to judge side effects or drug interactions, and it can take years for drug side effects to be identified, as their discovery is usually purely by chance. Stanford University researchers trained their system on over 19,000 proteins and their drug interactions, which was able to successfully predict drug interactions based solely on the prescribing combinations.
When a doctor prescribes a patient more than one drug they have no way to predict whether that combination will have an adverse side effect. A new system from Stanford University presents a novel…

Building the Google Photos Web UI – Google Design – Medium

There's a nice breakdown of the usability and scaling challenges the Google Photos team went through with the redesign of their app. Creating a "scrubbable" infinite scrolling page, maximising screen real estate, while maintaining photo aspect ratio, with instant loading and rendering, with libraries of 250,000 photos or more. The compromises and engineering challenges they encountered are laid out with clear explanations. An interesting read.
A peek under the hood