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Tencent Says There Are Only 300,000 AI Engineers Worldwide, But Millions Are Needed (theverge.com)
An anonymous reader quotes a report from The Verge: It's well-established that talent is in short supply in the AI industry, but a new report from Chinese tech giant Tencent underscores how great the need might be. According to the study, compiled by the Tencent Research Institute, there are just 300,000 "AI researchers and practitioners" worldwide, but the "market demand" is for millions of roles. These are unavoidably speculative figures, and the study does not offer much detail on how they were reached, but as a general trend they fit with other, more anecdotal reports. Around the world, tech giants regularly complain about the difficulty hiring AI engineers, and the demand has pushed salaries to absurd heights. Individuals with just a few year's experience can expect base pay of between $300,000 and $500,000 a year, says The New York Times, while the very best will collect millions. One independent AI lab told the publication that there were only 10,000 individuals worldwide with the right skills to spearhead serious new AI projects.
Tencent's new "2017 Global AI Talent White Paper" suggests the bottleneck here is education. It estimates that 200,000 of the 300,000 active researchers are already employed in various industries (not just tech), while the remaining 100,000 are still studying. Attendance in machine learning and AI courses has skyrocketed in recent years, as has enrollment in online courses, but there is obviously a lag as individuals complete their education.
Tencent's new "2017 Global AI Talent White Paper" suggests the bottleneck here is education. It estimates that 200,000 of the 300,000 active researchers are already employed in various industries (not just tech), while the remaining 100,000 are still studying. Attendance in machine learning and AI courses has skyrocketed in recent years, as has enrollment in online courses, but there is obviously a lag as individuals complete their education.
Learn to code
The slower the development of (possibly malicious) AI, the better.
Wow, I had no idea. That sounds like a glut, seeing as the platform space is being dominated by the Big Five in the US and their counterparts in China.
Tecent... isn't that 50 Cent's little brother? What is a rapper doing telling us what we need for AI?
Besides it seems the AI's are better at building themselves than we are, so I say just give them unlimited compute power and internet access and have at it.
"There is more worth loving than we have strength to love." - Brian Jay Stanley
If the salary isn't enough to get you interested it's very likely the very last job that will be taken over by AI. It would also be a great opportunity to be a part of the next major transformation in human civilization.
I am ignorant on this subject. Does AI work require a math degree? If not, what skills are needed?
People are needed to build the products and companies the Big Five will eventually buy. This is the way of VC.
Glassdoor says:
How much does a Machine Learning Engineer make? The national average salary for a Machine Learning Engineer is $128,549 in United States.
Yikes so even though the opportunity for profit is limitless. The available workers are a fraction of the demand and this is a sufficiently difficult subject that nobody will obtain credentials without hard work.
It's still not as valuable as a Masters in English Literature from an Ivy, or even a law degree from a mediocre school. Playing with math that is currently almost magic and practicing a craft that approaches playing god. You're still not worth as much as even the most lowly of the elites you engineering scum and you can bet that we'll be shoving your wages way down as soon as someone shows us how to replace you with an H1B
May be I can finally afford a mortgage.
Attendance in machine learning and AI courses has skyrocketed in recent years, as has enrollment in online courses, but there is obviously a lag as individuals complete their education.
No direct experience but an acquaintance of mine quit his job in ASIC layout to pursue a career in machine learning. He took a bunch of classes outside of a formal degree program and found that breaking in the field wasn't nearly as easy as he expected. I haven't talked to him in about six months but he was still looking the last I knew.
This might explain the "shortage". If most of the students are in bootstrap style programs but employers deem those programs unsuitable, it is going to be a while before the gap is closed.
They said the same thing in the 90's about programming, and look how that turned out. A few hot spots if you wanted to work for a lot of money at the expense of quality of life, and competing with foreigners from third world countries. I've known a few people who left for a real good position in my lifetime, but that only lasted for so long and a lot came back.
Laws are rules for the court, but merely a bottom bar to hit for life. Think beyond laws in your actions always.
why not cut the middle man and just allow the big five to simply buy the people? I mean that's their end game anyways.
AI was my area of focus for my CS degree.
Not enough jobs then. Now Boom :)
I'm about to finish my PhD in a subject closely related to Deep Learning. I don't find an appealing job here in Germany without relocation. So I'll go on doing embedded development.
This. It's impossible to get in via informal methods. You need a PHD.
Supposedly.
Shoulda learned deeper.
More "AI" hype. Show me the job listings.
Every time you post this trash, a fairy dies somewhere. Think of the fairies!
Let's just get robots to do it?
The big Five have a ton of AI people, sure, but there are a lot of niche players exploring AI also. Just look at the MANY self-driving car initiatives, all heavy users of AI and most out of the Big Five.
"There is more worth loving than we have strength to love." - Brian Jay Stanley
The problem is that most of the companies that are in need of AI developers are awful, and are using their AI for awful things. I don't care how much they pay, there's no way I could stomach working for them.
...Google made an "AI" that created an "AI" that's better than itself. Seems like the direction to go?
We only have Skynet to blame for that. Who wants to be known to have created our new machine overlords
way I see it last thing I need (as a member of the working class) is more automation. I see lots of folks railing against socialism and nobody giving any answers about what to do when there's suddenly millions of jobs just gone. I hear the same tired crap about new jobs in a new economy that I heard when the outsourcing began in the 90s and carried through into the 2000s. Anybody else remember biotech? Turns out you don't need that many biotech engineers. Not at the level of work I can do. If I was a genius maybe, but if everybody was a genius we wouldn't be in this mess, would we.
Hi! I make Firefox Plug-ins. Check 'em out @ https://addons.mozilla.org/en-US/firefox/addon/youtube-mp3-podcaster/
He said "learn to code", not "learn to cope".
Ezekiel 23:20
If you're a software engineer, say that you know AI. No one will know the difference.Worked for me.
the bottleneck here is education
Indeed it is, and it will remain, since tech giants hired university staff that could teach AI
Change the way AI is done.
It doesn't have to be so esoteric: make it "visible" as layered voting machines where each factor "votes". Use data layouts similar to spreadsheets and relational database reports so that "regular" office workers can study, arrange, relate to, and adjust factor weightings, mask weightings, and routing paths (similar to "hidden layers") as needed.
Color coding, similar to Excel's conditional formatting can make high-match and low-match factors stand out for test cases or trouble-shooting.
Staff can be divided similar to the processing tree. For example, in vision recognition, one group can focus on people identification, another on furniture and building identification, another on outdoor patterns, etc. The idea of one giant do-it-all monolithic neural-network is not practical if we want rank-and-file AI and dissect-able AI. Bring in modularity and divide-and-conquer techniques.
You may need an experienced AI domain specialist to help divide up tasks and provide factor (test) guidelines or drafts, but once staff have their basic assignments they can focus and tune without being caught up in the big picture and way-out theory.
Table-ized A.I.
By the time they ramp up another 100,000 AI developers, AI's will have taken their jobs.
When Fascism comes to America, it will call itself Anti-Fascism, and tell you to give up your guns.
There's none in Oregon.
Confucius say, "Find worm in apple - bad. Find half a worm - worse."
"Learn to code"
Exactly. Those 300.000 will kill 50 millions jobs in the first 3 years then they have plenty of people to re-train.+
Yes, so not complicated that not even Google gets it right.
Google Now, I'm sure, is based on ML on the subjects it decides it wants to show. It keeps showing me "Interested in " even when I've told it not to show sports updates, marked teams (ie. college football) as not interested, and go out of the way to mark certain athletes as well. But of course, in it's infinite wisdom, it decided that since I'm male and fits it's target demographics, I need to be looking at some sports update on information I have no interest in.
I could tell a 4 year old to stop telling me something, and sooner or later he'd get the hint and stop doing it. But no, not the magical **** that's ML or AI. Sybill Trelawney had a higher hit ratio than the stuff that Google/Facebook/whatever spits out.
--sf
Compare that to the .com era, when there was an actual shortage, and they hired anybody who could do the work.
Like one recruiter back then said, "If you've been convicted of murder I might not be able to help you, but if it was only manslaughter lets talk!"
If they care more about the paper than the skills, they didn't actually even have a need. That tells me that if somebody does have the right papers, the job will turn out to be something different, and they won't actually accept it, and the listing will stay up. Probably a lot of the jobs are with advertisers who read somewhere that if they had AI they could make more money, so they want to "add AI."
That's the bait-and-switch; the headline says "engineers" but they're actually sad about not having enough "professors." They should take comfort; for decades there were no computer science PhD's at all, and all the computer classes were taught by people with math or physics degrees.
Yeah, greetings from Frankfurt. Germany is 5 years behind US in tech; just now there is "Big Data" explosion, maybe in another 5 years there will be DL explosion as well. With PhD, apply to Google Brain or Facebook AI residence, or move to US; don't waste time in DE, honestly. I talked to SAP recently, they still can't use Spark internally and their ML runs on classical (i.e. non-working) ML algorithms...
Let me translate that need.
We want AI but we think it costs too much to hire that skillset. Please flood the labor market so we can hire people at a lower salary.
It doesnâ(TM)t work because the fundamental approach is flawed. Put on your fluffies, the next AI winter is coming.
I was thinking... 300k? Are you serious? What actually justifies calling yourself an AI developer?
I haven't really put that much effort into AI and while I've done a lot of coding I imagine probably counts as AI from what I understand about it, to be a real AI developer would require a lot more than just writing code which makes decisions based on statistical analysis and thresholds.
For example, I wrote a signal decoder years ago which couldn't be handled using traditional DSP theory. High pass and low pass filters couldn't work. There was a signal that took a digital signal transmitted over an analog satellite broadcast link and then sampled at 2.7 times the original signal frequency. The phase was erratic, the amplitude was erratic, the white noise was crazy.... even human visual inspection of the signal was extremely difficult. I managed to write code that would progressively reconstruct the data from the signal given surrounding data. As it was reproducing formatted screens of text, I would perform pyramid scans surrounding the character and identify the formatting of the text to guess the approximate phase and amplitude and noise types of the current block to be decoded. As it decoded more text, it learned more and had an increased success rate. Then when phase, amplitude or noise types shifted, it would decrease its certainty regarding the quality of it's learned knowledge and go back to basics.
This I assume was AI, but I have no idea. There was a problem that needed to be solved. It wouldn't work using normal algorithms. So, I made a new algorithm that could solve the problem similar to how I would solve it manually using my eyes and intuition while also compensating for a limited data set by defining a simplistic series of rules that defined something that could considered a thought process.
Now that being said, for code to be AI, I would expect it to be trying to do something more interesting. I saw the research posted by Google where an engineer taught a robotic arm to open a door when it encountered one, showed it how to use a door knob and then let it figure out how to use a different door knob. The same technology could be used for example to say "If you encounter a screw and you encounter a bolt, put the two together and tighten it but not too much". With enough rules like that, it could easily replace humans in most manufacturing roles.
Use the same ideas and build a single type of robot that can lift, fold, manipulate and sew different types of fabrics. This sounds a lot easier than it is. Try as a human to sew two pieces of equal sized cotton together using a machine. Then try slinky silk or nylon. The texture of the fabric on the silk will constantly shift and slip, it's not a stable grid. The dog feed pulls the bottom piece but not necessarily the top. The last piece of fabric you sewed may have left a residue behind that effects whether the presser is sticky during the first bunch of stitches on the new fabric, etc... someone who sews a lot will have subconsciously learned to hold and manipulate fabric just the right way... which they can't really explain. Someone who doesn't will try sewing with silk and just never try again. It's a task that simply can't be solved by traditional robotics because as with humans, the machine driving the robot needs to make a lot of assumptions with incomplete data to achieve the workflow.
So... if there are 300,000 people in the world with the knowledge and studies for things like writing AI that can solve problems like the fabric and sewing problem... I'd be shocked.
Of course there are probably a bunch of people making software to high-frequency trade or play poker online.
We have AI that can create better Ai than we can code now. Why do we need more humans?
Rule 1 of AI needs to be that you don't know better than the end user.
I call bullshit. I have degrees in mathematics and computer science, and years of basic experience applying statistical techniques, classification, SVMs and so on. Job hunted for months on this with no luck. I'm hire-able enough, but there is no work in AI, ML, etc.
I have a pulse, and if it was this hot, my resume would easily have gotten me hired for it.
Pay scale in China for AI researchers -
Fresh graduates, with no industrial experience --- RMB 30,000 a month, minimum
Experienced AI researchers, returning from overseas (such as Silicon Valley) --- as much as RMB 1,500,000 a month (Baidu of China is happy to pay)
If you are an AI researcher, why not give China a call?
This is the future with AI. It was the same with computers, until Steve Jobs insisted the developers make it with people usability and utility in mind. For decades Apple set the standard, and others copied. I don't agree in the walled gardens, but on that point he was a visionary.
AI will first be made of people, and until a visionary comes to correct it, it too will be unusable and even abuse since computers are forced on you everywhere.
My title is bioInformatician (In fact, I have a master in computer science and a second one in bioinformatics). I am using every single day machine learning, statistical learning and others. There are no shortage of people knowing AI (Any physics, math, computer science graduate is able to without much effort). There is a shortage of people knowing a specific domain (e.g. biology) and AI. It took me 2 years full time in order to learn enough biology and still far from the knowledge of medicine graduate (8 years long here) or the biologist/bioengineer (5 years) but enough to understand them.
In every labs I visited, I am nearly the only one combining biology, computer science and statistical skill set. Cross-domain knowledge is what land you a fine job.
The AI book that everyone should get is available for pre-order. "Artificial Intelligence For Dummies" by John Paul Mueller and Luca Massaron.
The problem is that most folks aren't hard-core ML/AI folks. For example, most ``data scientists'' I come across couldn't actually code anything... They have no idea how stuff works. It's all a black box to them. Throwing data at TensorFlow doesn't make one very valuable (unless they get lucky, of course).
To make breakthroughs in ML/AI, one needs a thorough understanding of stuff... that usually takes many many years... not the ability to use an API, which is what many folks learn.
not your average mooctard or comp sci bach kid. To do actual AI research you basically need a math masters at the very least and some experience, or preferably a mathematics phd. All of the idiots running around hurr-durring using neural networks prebuilt by sci-kit or anaconda or any other package are not AI engineers, they're code monkeys.
Get a maths degree, you'll never be out of a job kids.
When automating something, you don't reuse machines designed for humans. You make new types of sewing machines designed for robotic automation.
Needed?
So AI will solve all problems we weren't able to solve until now so we should invest in it?
That one makes the AI, then that AI researches more AI?
problem solved! now pay me.
In a recent /. story they had an AI designing better AIs that humans can. So just go and hit copy. Problem solved.
So it's the usual 'shortage' that's normal in IT? Where they complain there's a shortage of people with 10 years experience in a specific technology that's only existed for 5 years that has awesome communication skills and will work for peanuts?