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5 things you need to know about the future of AI

A candid podcast discussion with EVP Matt Grob.

In an exclusive Gigaom podcast interview, Qualcomm Technologies Executive Vice President Matt Grob delved deeply into the future of AI and provided the rare insight that comes from many years of driving bleeding-edge R&D and contemplating their possibilities. This candid interview expands upon Matt’s previous blog post about Qualcomm’s role in making on-device AI ubiquitous, discussing topics ranging from AI capabilities and their impact on jobs to 5G and science fiction. Here are five nuggets that stood out (edited for clarity).

1. We’re still in the early days of AI and the ability to mimic a human brain.

Many of the machines that we have today, the agents that run our phones and in the cloud…are not really yet akin to a living brain. They are very, very useful. They are getting more and more capable…Many metrics are improving but they still fall short. There’s an open question as to just how far you can take that type of architecture, how close can you get. It may get to the point where, in some constrained ways, it could pass a Turing test and if you only had limited input and output you couldn’t tell the difference [between] a machine and a person on the other end of the line.

But we’re still a long way away and there are some pretty respected folks who believe that you won’t be able to get to creativity and the imagination and those things by simply assembling large numbers of AND gates and processing elements — that you really need to go to a more fundamental description that involves quantum gravity and other effects. And most of the machines we have today don’t do that. So, while we have a rich roadmap ahead of us, a lot of incredible applications, it’s still going to be a while before we create a real brain.

2. The AI capabilities that are available today are revolutionizing computing.

What is right around the corner is a lot of greatly improved capabilities as these AI techniques fundamentally replace traditional signal processing for many fields. We’re using it for image and sound, of course. But now we are starting to use it in cameras and modems and controllers and complex management of complex systems — all kinds of functions. So, it’s really exciting what’s going on.

3. AI is improving at exponential rates, creating tremendous opportunity.

AI advances are coming very rapidly because there’s an exponential nature. You’ve got machines that have processing power which is increasing in an exponential manner. Whether it continues to do so is another question but right now it is. You’ve got memory which is increasing in an exponential manner. And then you’ve also got scale which is the number of these devices that exist and your ability to connect to them…

So, you’ve got all of those combined with algorithmic improvements and especially right now, there’s such a tremendous interest in the industry to work on these things so lots of very talented graduates are pouring into the field. And the product of all those effects is causing very, very rapid improvement.

What is right around the corner is a lot of greatly improved capabilities as these AI techniques fundamentally replace traditional signal processing for many fields.

Matt Grob

4. On-device AI is essential, but cloud AI and ubiquitous connectivity also have a complementary and crucial role to play.

When you make [AI capabilities] available in a mobile environment, ubiquitously, at reasonable cost, then you are going to have incredible things. “Autonomous vehicles” is an example because that’s a mobile “thing” that needs a lot of processing power. And it needs processing power local to it — "on the device.” But also needs to access tremendous capability in the network and it needs to do so in a high reliability and low latency [environment]…

And again, you want, in many cases, a very powerful capability in the cloud or in the network but also at the device. There are many cases where you’d want to be able to do some processing right there on the device. That can make the device more powerful or more economical. And that’s a mobile use case. There can be applications in education, entertainment, games, management of resources like power and electricity and heating and cooling...

So, it’s really a wide swath, but the combination of connectivity with this [on-device AI] capability together is really going to do it.

5. AI will increase productivity and have a net positive effect on humanity.

It’s definitely true that increases in unemployment did not keep pace with increases in productivity. Productivity went up, you know, orders of magnitude. Unemployment did not go up in orders of magnitude….

We are at a place now where machines — even with their processing that they use today, based on neural networks and SVMs [Support Vector Machines] and things like that — are able to replace a lot of the existing manual or repetitive-type tasks. So, I think society as a whole is going to benefit tremendously, and there are going to be some groups that we have to take some care about…

So, there will be a migration. Not necessarily a wholesale replacement. But I do feel, fundamentally, that the overall effect of all of this is going to be net positive. We are going to make more efficient use of our resources. We are going to provide services and capabilities that have never been possible before that everyone can have… There’s going to continue to be a skill shortage more than a job shortage.

Be sure to listen to the entire Gigaom podcast to learn about Qualcomm’s role in 5G and some of Matt’s more personal interests, such as his passion for sci-fi and Star Trek he takes pleasure in knowing that his last name spelled backward is “borg.”


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