I'll panic when the headline is "Microsoft Forms New Zero Person AI Division" :)
MSR is already a pretty big group at Microsoft and does all sorts of work that is completely unrelated to AI. Now, I am confident the teams within MSR will have to start thinking about AI, and how their work relates to AI, but this initiative is much more of an interdisciplinary effort than a 5000 person deep learning team.
Real AI is a fool's goal. Once we achieve that, we will simply be obsolete, I'm in no hurry to get there.
Yeah, can't wait for the new Clippy.
"I asked Cortana to query our clickstream data and she said that men over the age of 50 like to click on Viagra ads."
This is not AI. Although there is some real research going on, it seems that everyone is jumping on the bandwagon and using AI as a buzzword.
The warnings of "Second AI Winter" are in response to the glut start-ups whose sole products are ML/AI platforms.
It's wiser to invest in real solutions that happen to use AI models.
My equivalent to your dearth of people in the know in 2011, was studying AL (Artificial Life) in 1990s, and nobody heard of it. It included the study of ANNs, GAs, GP and AI in general (which I prefer to call CI - Computational Intelligence nowadays). The book that started it all for me [0].
There were no immediate applications aside from expert systems here and there, and the fuzzy logic appliance controllers coming out of Japan. However, now, with self-driving cars, recommender systems, image recognition (face-matching surveillance post 9/11) have big pay-offs or budgets to spend on it.
VR is having its second renaissance. I thought the first time it would have taken off even with the clunky glasses and headsets, since gaming was already such a huge money industry.
And now with modeling becoming prominent again, AL paradigms are being modified, created and repurposed for all sorts of cool things. I play with NetLogo since it is a fun environment for that [1].
My only regret is that I was in at the beginning, but left it to pursue other things, and so I am not at the level of practice to get one of those 200K jobs. I still kept studying it all these years though, and I have coded my own bits and pieces, but mainly for conceptual pieces, art and music, not practical applications. I play with Darknet [2] now, since C was my second language after Assembly (6502 and then x86_32), and it is great fun, and fast. A very understandable and manageable platform.
I am hoping it all leads someday to keeping me alive longer to enjoy studying some more, because as I get older that's really what I enjoy most aside from family!
[0] http://www.springer.com/gp/book/9780387976143
I've never been able to figure out how my employer says I cost them $280 per hour.
Billable hour = salary cost + benefits + G&A + overhead
Where:
- Salary cost = gross salary / 1800 (or whatever # hours/yr your company uses)
- Benefits = proportional cost of vacation, 401K, etc
- G&A = General expenses and admin (office, equipment, free food, etc)
- Overhead = amount needed to cover everyone else who isn't billable (HR, Finance, IT, assistants, President, etc)
If you do the math, you'll see $200-300 is a standard rate in high cost markets (NYC, SFO) for someone with a six-digit figure. More junior positions are ~$150, while very senior roles (Partner, Director, etc) would be in the $300-500 range.
You need one of each these people for every N developers (different value of N for different classes of service). Therefore the cost of having you includes the 1/N cost of each of these people.
If you are client-facing consultant, your billable rate is paying:
- Your salary
- Your benefits
- Your expenses (travel, per diem, equipment, software, anything else)
- And then... Salary, benefits, expenses of all your NON-client-facing teammates: Salespeople, marketing, management, client relationship, administrative, HR, etc.
So as a consultant, you are the product, and as such have to be sold at a price that nets enough profit to pay for rest of the organization.
Normally when they say "you cost $150/hour", what they mean is, "you, and all the support framework behind you, needs to be billed at $150/hour to pay off".
Hope that helps. If you're in-house developer and not client-facing, it's harder to understand and justify cost figures, but typically would be nowhere near that rate...
Or maybe just really, really bad at your job?
Not a single mention of that anywhere.
So really, any AI-based learning is going to be "deep" from now on, simply because we've reached the point where we can handle large neural nets and complex datasets, right?
IBM was the first company with a massive investment in AI (during this cycle) - they are now trying to push Watson as a product. Did it pay off so far? I am not quite sure.
You'll and most people too be replaced with a machine and have no job, pretty amazing.
Don't they always say that?
It is an substantial amount of money in the rest of the world.
Anecdotally, pay I've seen from Google and FB are higher than Microsoft/Amazon, but of course that's not saying much. Still, the first source I can find matches what I've seen: https://blog.step.com/2016/04/08/an-open-source-project-for-...
Also, Google and Facebook have offices in Seattle, and from what I understand the pay between their HQ and Seattle offices are the same.
Now, Google also has an office in Kirkland. That would be an interesting place to compare. But it's also not particularly large.
So OpenAI is spending a billion dollars over the next several years.
Microsoft is spending a billion dollars per year.
Google, etc. do the math.
There's literally billions of dollars now being spent on moving deep learning forward. Pretty amazing when I think back to 2011 and there were machine learning conferences where literally no one I spoke to had heard of deep learning.
People worrying about a second AI winter are like the people that have been worrying about an "internet bubble" since 2004. It's fine to be worried, there will be bubbles, but this time it's different and there are many reasons for that. There is no "internet industry" anymore; it's become more segmented and just plain bigger. Similarly, there will be no "AI industry"; it will branch out, and there are more potential applications of "understanding data and automating decisions" than there were in the 80s.
> something that they are branding AI - I might wait and see how much of it is on real AI - what ever that is.
Yeah, I wouldn't get hung up on that, they're calling it AI because that's easier to explain to reporters than deep learning. The difference is deep learning techniques are already being used in released products and companies are looking to do more of that, so there is a very real definition and set of goals associated with what these groups are doing, it's not just, "hey everyone, let's make an ai!"