> I'm just not sure what else separates them from any other "AI" (read machine learning/algorithm-building/efficiency consultancy) out there.
probably the amount of pure research they produce: https://deepmind.com/research/publications/
I wouldn't be surprised if google sunsets the company and absorbs the employees in its more profitable products.
The idea that they'd take the people and put them to work making Blogger better or something? Not a chance. AI research is pretty much Google's core function. They'd no more break up that functional area than Apple would take Jonny Ive's team and put them answering support calls.
If they don't figure out compelling products in reasonable time, the researchers will become part of google research (maybe retaining the deepmind name as part of a group within google research) and the engineers will become absorbed or find new jobs. Also, DeepMind is not such a big name outside our little geek community. Try it with someone :)
My point was that ideally we like to believe that research supports products, but generally speaking, most of Google research or Microsoft research papers are rarely applicable to their products. And good researchers like being independent (that's how you woo them - with the promise of independence) so you can't usually dictate what they work on.
I have no inside information here, but my hunch is that that's overly pessimistic. From the outside, we hear about DeepMind finding cats in YouTube videos or learning to play Atari games or Go, and it's tempting to say, "Google doesn't sell Go programs, so what was the point."
However, Google does do incredibly good image labeling in Google Photos. Their autonomous vehicles might eventually be a profit maker, potentially using deep reinforcement learning methods developed to play Atari games. Certainly, Google Translate and Inbox use ideas developed from their machine learning groups.
You're right that there's often a pressure to make internal research groups more profit-driven and more connected to the revenue stream that runs a company. Microsoft Research saw this happen to some degree 10 or so years ago. But Google's core competitive advantage is their ability to collect and analyze data. Data is the revenue stream that runs the company.
Also, I think the "independence" aspect of research is overblown to some extent. Almost no one is truly independent. If nothing else, you're subject to the needs of funding agencies. Typically, researchers just want the ability to work on problems that interest them using ideas they have some control over developing. You can do that inside a company, provided that company is interested in the same types of problems you're interested in. That's been the success of corporate AI/ML labs -- many of the best researchers want to go there because it's a steady stream of interesting work free from the need to do the constant dance for grant money.
Retaining researchers who write papers is highly correlated with providing a de facto academic environment for them to work in. Microsoft research has become almost the most interesting place for researchers to go to in the last 10 years because they have developed the place to feel like a university department. Look at their research papers (public). Any overlap with commercial products looks providential more than intentional.
I'm obviously not talking of people like Jeff Dean, whose intent is to build, not publish papers. The big table paper was not the intent - building Big Table was the intent and when they were done, they ended up writing a paper about it.
If Google uses some of the DeepMind research itself, that's really good. DeepMind can make revenue from Google that way (if they have that arrangement). If they can't, it's hard to justify their existence as an independent financial entity - they're better off just being part of Google.
Probably mostly the CEO https://backchannel.com/the-deep-mind-of-demis-hassabis-1561...
The company is working with the National Health Service (NHS) in the UK on a project around the early detection of acute kidney injuries. Critics, however, argue that the collaboration with DeepMind is wider than the company and the NHS previously disclosed. In addition, it’s also working with the Moorfields Eye Hospital on looking at how it can use the hospital’s eye scans to diagnose eye conditions better and faster. The NHS, however, mostly used its own algorithm in its project, with DeepMind focussing on the front-facing app. Suleyman argued that this is due to the fact that it’s still early days for this collaboration, which only started 12 months ago.
So in the health space they're currently doing anomaly detection and building applications for their clients. Sounds very Watson/consulting. Lots of money in healthcare due to the amount of data generated and the complexity of building regulation-compliant.
Judging from their website, they've also built an algorithm for reducing cooling energy usage in Google's data centers.
There are a ton of IoT platforms that are currently competing to connect a bunch of industrial/medical/automotive/aerospace and defense devices and servers, analyze that data with machine learning and statistical techniques, make it easy for users to build their own cloud/edge applications, and eke out every last drop of efficiency they can for their customers.
DeepMind is fortunate to have Google's brand, infrastructure, and reach. I'm just not sure what else separates them from any other "AI" (read machine learning/algorithm-building/efficiency consultancy) out there.