Deep learning will lead next tech investing wave

An historic technological evolution is underway with powerful themes that are transforming business and society while offering unique opportunity for investors, believes New York’s ARK Invest.

“We look at where technology is going, not where it is,” says James Wang, an internet analyst with the firm. “Our job is to find the companies we believe are going to be trillion-dollar companies tomorrow.”

ARK recently published its annual list of Big Ideas that fit this bill and there is no shortage of radical change among the 11 it identifies. They include aerial drones, 3D printing,  driverless cars, advances in DNA and genome sequencing, and the rise of Bitcoin.

It believes the biggest idea is deep learning, a term which refers to software that learns as it goes without human help. The software can see, hear, and understand natural language at near human level of accuracy. This includes software that serves up ads when we go to a Web site, robots that help doctors create surgical plans based on thousands of similar operations, or Google Home, which gets better at answering questions.

ARK manages five active ETFs as a sub-advisor for Emerge Canada Inc. Emerge launched the five ARK funds on the NEO exchange in Toronto last year.

Mr. Wang, who has a degree in computer engineering, explored the implications in an interview.

Why is deep learning having such an impact?

Deep learning is the most important foundational technology since the invention of the internet. It is a completely new way of thinking about software.

Traditional software is written by programmers. It can’t do things like see what’s in a picture, understand what’s said by a voice, comprehend a sentence, that kind of stuff.

Deep learning isn’t created by programmers. It’s software that learns from the data it collects. This makes it able to learn human-like functions such as vision, caring, understanding language,  strategy, and so on.

Can you give me an example?

Sure. Our most powerful cognitive function is probably vision. We can see the world and  understand 3D relationships. We know where we can walk and where we can’t walk. We know what’s a cat, what’s a dog and the different breeds.

Until 2012, we could not write software that could differentiate between a cat and a dog with any level of accuracy. It wasn’t possible. You were using math to write equations to describe these differences.

In 2012, deep learning emerged. Now you can show a computer thousands of pictures of cats and dogs and the software has achieved human-level accuracy for telling which is which. It’s used across billions of devices, in everything from your iPhone camera to surveillance videos to tagging friends on Facebook.

So what’s next? 

A conversational computer, which is a computer without a screen. You talk to it rather than look at it and click. This wasn’t possible five years ago, because the computer wouldn’t have been able to understand you.

What else is coming?

Self-driving cars. Google (NDQ: GOOGL) and Tesla (NDQ:TSLA) have been working on this for years. Previous efforts couldn’t work because the sensors couldn’t understand the world with enough accuracy.

Now the sensors can use video to understand what’s happening from a 360-degree point of view. Humans are not able to do this. Without deep learning, self-driving cars wouldn’t be possible.

How far off are driverless cars?

We expect they will be on the road as of next year, in 2021. Waymo vehicles have already travelled over 20 million miles autonomously. (Waymo is owned by Alphabet, Google’s parent.)

What are the advantages?

One, they are going to eliminate the need for many people to own a car. That is great for economic and environmental reasons. They also free up a huge amount of human labour and productivity.

Washing machines freed people from the menial task of having to wash clothes. That time is now spent doing other things. A self-driving car is going to free up hours per person.

Where are the investable opportunities?

Tesla is 100 per cent focussed on self-driving. Waymo is also doing great work. Other companies are  DiDi Chuxing Technology Co., a private  Chinese company and Nvidia. Nvidia (NDQ:NVDA) supplies the most powerful and widely used chips for deep learning.

Are these investments risky?

Most of the stocks with exposure to self-driving do not have huge expectations built in. Alphabet is valued pretty much on its internet business. Nvidia is valued on its data centre and gaming business. So, you kind of get this theme for free.

You say mobile apps are a third way deep learning will affect things

Yes. We all use Facebook and Instagram. The fastest-growing social media app in history is a Chinese app called TikTok. The secret sauce is the way it generates the content.

It just plays videos and there are two things you can do. You can keep watching, or you can swipe to go to the next one. Based on that, it’s able to learn what you like.

It’s already larger than Pinterest and Snapchat and will probably end up being bigger than both of them put together.

Why do you think electric vehicles are at a tipping point?

We believe EVs will be cheaper than gas-powered cars within four years, because the biggest cost of an EV,  is a lithium-ion battery. They are being produced at ever-increasing scale. As production increases, costs decline which is driving price declines in the cars.

We believe that this year the price of an EV will fall to about US $33,000, which is the price of a mid high-end sedan.

By 2022, we think there’s a crossover when an EV costs just a little less than a comparable gas-powered car. There is going to be a seismic shift when that happens. It’s going to change the notion that EVs are a toy for rich Silicon Valley folks to one where they are cheaper than owning a gas-powered car.

They will be more fun to drive. They will be better for the environment. And it will create a lot of opportunities for investors because it’s going to make the auto industry a growth industry again, which it hasn’t been for 50 years.

What horizon should investors have?

It takes time for these technologies to mature, so five years or more. The best way is a portfolio-based approach. Our portfolios have 40 to 50 companies and while we think each of them could do well, in the end a few will do spectacularly well.

Any concluding comments?

In 15 years the smart phone has gone from a business toy to something every teenager has in their pocket. We’ve gone from buying food at a grocery store and clothes from a department store to ordering from Amazon. Wouldn’t it have been great if we had been able to understand these massive changes 15 years ago and had invested in them?

(This is a longer version of an interview that appeared in the Globe Advisor section of the Globe & Mail’s Report on Business on Feb. 19, 2020.