Tencent Says There Are Only 300,000 AI Engineers Worldwide, But Millions Are Needed (theverge.com) 116
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.
To: Surplus Journalists (Score:1)
Learn to code
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"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.+
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The fewer the better... (Score:1)
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Yeah. But one day it could learn to be.
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Most of the work now seems to be building up vision databases of everything from nuts and bolts, medicines and medical instruments. Having an intelligent robot in any field requires being able to recognize various objects.
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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.
It's a huge space (Score:2)
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.
Just wait. (Score:2)
By the time they ramp up another 100,000 AI developers, AI's will have taken their jobs.
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There's none in Oregon.
Re:There are 300K AI scientists and engineers toda (Score:5, Insightful)
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.
That name (Score:4, Funny)
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.
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I don't know, but there is some blathering in the summary about "researchers," even though the field doesn't seem to be researching anything.
It is probably just some idiots at an AI department who didn't know there are also software engineers, who actually do the work.
It is just a regular computer, it is just a set of software techniques and use cases; outside of employees of academic institutions there is no reason to get a narrow research-related degree instead of a mainstream work-related degree.
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More simply, fuzzy logic programmers with the ability to create a false impression of artificial intelligence with great marketing. Keep in mind major corporations are playing the game and playing it for big profits. Just like with data mining, which produces a lot of information, in fact way more than you are capable of processing effectively so heh, heh, AI, to keep the lie going and the billions flowing. You can just data mine, you need to pay extra for AI to process it, we promise it will work this time
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For most business use cases you're better off with an expert system, and all you need are a bunch of regular engineers.
Carrot (Score:3)
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.
Re: Carrot (Score:3)
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.
Seems more likely to be one of the first. I think we are going to succeed in making an AI which can make better AIs long before we build an AI which can actually replace any other complex profession. It doesn't even have too be that good at it initially ... it will get better all on it's own.
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I have conducted an informal survey of humans occupying jobs across the employment spectrum, and the vast majority are of the opinion their job will be one of the last replaced, or never replaced, by robotic workers or Artificial intelligence.
I'm pretty sure it's a coping mechanism.
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Based on the history of AI and the claims made early on when computers were able to pass math tests or predict elections, it's possible that people are vastly underestimating the difficulty of automating many jobs.
Current AI is not very strong. In particular, it lacks what you might call common sense or common knowledge. It's really obvious with translation software that can't understand the context around words and phrases.
A good example would be lawyers. Seems like an easy one to replace, the law is just
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A good example would be lawyers. Seems like an easy one to replace, the law is just a set of rules that are applied, right? Except that much of the work is actually dealing with people, understanding how things work in the real world with timing and banks and people behaving inconsistently or lying.
Appealing to a human judge and jury while representing a human defendant would seem to favor human lawyers, although the job of jury duty might well be one we voluntarily abandon to the machines. Perhaps like migrant workers, robotics and artificial intelligence will gain a foothold by performing those tasks we find the least attractive.
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Do you think it might even learn how to use apostrophes?
Re: Carrot (Score:2)
With you as it's teacher I'm sure its going to do fine.
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First job to be taken over by AI.
Just think about how much sense it makes to work in a job which is by it's nature going to make you first up against the wall.
The first human job(s) replaced by robots, or AI depending on your definition, are already lost. Automotive industry welders and assemblers, stockroom workers at Amazon, soldiers in the field, farm workers, bomb squad technicians, astronauts, and so on...
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Some jobs have already gone and we didn't really notice. Traffic duty cops were replaced by traffic lights. Elevator operators were replaced by electronic systems. Print shops with teams of men loading and unloading copper boilerplate on to metal drums were replaced by laser printers, PostScript, font files and word processors. There was a riot over this - the Wapping Street Dispute. Long distance telephone operators were replaced by automatic exchanges. Snail mail was replaced by instant messaging, Email a
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It's virtually always perspective regarding the replacement of jobs with technological innovation. The owner of the textile manufacturing facility would be in very real jeopardy of losing his business to competitors if he does not employ the labor-saving punch-card looms, yet understandably, the worker who specializes in the trade being rendered obsolete is resentful to the point of outrage over the technology's implementation.
Enough printers were employed – 670 in all – to produce the same number of papers that it took 6,800 men to print at the old shop. The efficiency was obvious and frightened the union into holding out an entire year.
The role of labor unions has diminished, in part, because their function as prot
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Hindi/Urdu, needfuldoing and 6 years' experience in something that hasn't been invented yet.
Same as everything else, really.
Funny that they're not paying C-exec pay? (Score:5, Insightful)
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
Re:Funny that they're not paying C-exec pay? (Score:4, Insightful)
Let's not guss this one up: AI, like regular I (in so far as we can tell), is a state machine. Doesn't matter how many databases you attach to it, or what language you write it in, you're dealing with a state machine.
Call me when Computer Science progresses beyond using state machines.
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If they're talking about random forest type machine learning then there are already well over 300,000 people who can do the work they need. If they're talking about deep neural nets then in 2017 we're playing with magic in hopes of becoming a god.
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we're playing with magic in hopes of becoming a god.
Naw, that's just the echoing sound it makes when people heads get too filled up with buzzwords and arrogance at the same time.
Re: Funny that they're not paying C-exec pay? (Score:1)
We have AIs that can beat us at chess, go, and Jeopardy. They figure out how to play by themselves. Some AIs are driving cars now. In a year you could get an Uber driven by one.
Sure, AIs can't do everything that we can do, but what they can do, they do better than us.
Are the people taking the AI courses being hired? (Score:5, Insightful)
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.
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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.
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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.
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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 s
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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?
be careful (Score:3)
Yeah right (Score:3, Insightful)
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Take marketing classes and learn bullshitting. Then you can talk your way into the latest fad. It doesn't matter if you don't know anything real: the fad will die out or morph into some new BS before they find out.
For example, the fools here got suckered into MS's cloud BS and built something that would make Rube Goldberg jizz. The guy who spearheaded it spouted magic-Lego's plug-and-play reuse, modularity, and instant scalability. Instead, it turned into bruised pasta, not Legos. The power of bullshit
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Have a look at the 64 open positions here: http://hr.tencent.com/position... [tencent.com]
Tencent is a Chinese company, most of their AI research is in China.
Well, duh (Score:2)
Let's just get robots to do it?
The problem is (Score:2)
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.
I heard... (Score:3)
...Google made an "AI" that created an "AI" that's better than itself. Seems like the direction to go?
Not surprised (Score:1)
Needed by who? (Score:4, Informative)
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Automation frees up labor for more interesting work over time. Plus it typically creates a whole work force around it https://xkcd.com/1319/ [xkcd.com] . If you're smart find another thing to do, if you're not just wait around to be forced into something else that you didn't choose. Look at what other Biotech people went to, or find a different thing. Don't be a socialist. Seriously https://fee.org/articles/why-s... [fee.org] .
Teacher shortage (Score:3)
the bottleneck here is education
Indeed it is, and it will remain, since tech giants hired university staff that could teach AI
Regiment-ize AI work, the "lab way" is obsolete (Score:5, Interesting)
Change the way AI is done. [github.com]
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 [office.com] 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.
wouldn't we only need one? (Score:2)
That one makes the AI, then that AI researches more AI?
problem solved! now pay me.
Re: AI is fake, no engineers needed (Score:1)
Every time you post this trash, a fairy dies somewhere. Think of the fairies!