Comment by roymurdock | Hacker News Reader

Comment by roymurdock | Hacker News Reader

DeepMind sounds more and more like IBM Watson by the day. Both created AI engines for games (Jeopardy, Go) and are now focusing on the medical market. The two examples of actual AI applications cited in the article focus on DeepMind's healthcare efforts:

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.

AFAIK the health stuff at DeepMind is just one part, the research division is the main bit. Not like IBM Watson consultancy-pretending-to-be-AI-research.

> 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/

Those are 2 very different things as much as we'd like to believe they're one since they're within the same company.

I wouldn't be surprised if google sunsets the company and absorbs the employees in its more profitable products.

No way I could see that happening. I mean, they might conceivably decide to fold the group into Google Research rather than keep the DeepMind name, but I doubt they'd do even that due to the name recognition that DeepMind has garnered even among the general public.

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.

On the contrary, DeepMind is a subsidiary in the new alphabet structure and is looking at a stick wielding CFO with a profitability question on her face.

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 :)

Deepmind isn't completely separate from Google. They have a team that helps apply their research to google products. I find it highly unlikely the team would be dissolved considering how successful and prestigious they are becomeing.

I wasn't implying that DeepMind (or its research team) are going to be dissolved. My point was: I wouldn't be surprised if that happens if they don't find compelling products to make money off of given Alphabet's revenue focus. Also it can go the consultancy type route it currently seems to be headed for and consultancies can make a lot of money (look at IBM), so they could be a great business. But that might leave the researchers unsatisfied with their impact.

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.

> 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.

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.

Lets keep in mind that DeepMind is a subsidiary of Alphabet that has to justify its existence (not tomorrow, but over time) with revenue. Interval research corporation is a good example of a very high profile research entity that couldn't produce revenue and shut down. https://en.wikipedia.org/wiki/Interval_Research_Corporation

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.

>I'm just not sure what else separates them from any other "AI" (read machine learning/algorithm-building/efficiency consultancy) out there.

Probably mostly the CEO https://backchannel.com/the-deep-mind-of-demis-hassabis-1561...

Google's translation technology and much of the stuff in Google Now was built by the DeepMind (and Google Brain) groups.

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