Deep Learning—A Powerful Tool, with a Name that Means Nothing

Tesla isn’t the only car brand in the world producing or aiming to produce self-driving cars. Every single car brand is working on developing self-driving cars. But what does this mean for our future? We talk about this and other interesting deep learning projects and history with Ran Levi, science and technology observer and podcaster, who explains in thought-provoking ways what we have to look forward to.

Below is a partial transcript. For the full interview, listen to the podcast episode by selecting the Play button above or by selecting this linkor you can also listen to the podcast through Apple PodcastsGoogle PlayStitcher, and Overcast.

Ran Levi: “I actually had the pleasure of being invited to Google’s Mountain View headquarters, and they took me for a drive in one of their autonomous vehicles, and it was, to tell you about that drive because it was boring—boring in a good way. Nothing happened! We were just driving around. The car was driving itself all around Mountain View. And it worked.

“The first time I entered such a car, I didn’t know what to expect. I mean, I didn’t know how reliable are those kinds of cars. So I had the idea that maybe I should sit somewhere where I can maybe jump and grab the wheel if necessary. You know, I was a bit dumb. They don’t need me, really. And probably if I touch the steering wheel, I would probably make some mistake and ruin the car. It drives better without me.”

Ginette: “I’m Ginette.”

Curtis: “And I’m Curtis.”

Ginette: “And you are listening to Data Crunch.”

Curtis: “A podcast about how data and prediction shape our world.”

Ginette: “A Vault Analytics production.”

Ginette: “We have a great live show planned that we hope to give at SXSW 2018. It’s a really awesome show about the power of niche artificial intelligence, and we’re going to share details from our research into what amazing things AI is doing right now on the fringe and in mainstream AI projects. We’re really excited to share it, so if you’re going to SXSW, or you just want to be good hearted and help us out, please vote on our dual panel by going to panelpicker.sxsw.com, signing in, and liking our topic, which you can find by searching for ‘The Power of Niche AI: From Cucumbers to Cancer.’

“Today we get to talk to Ran Levi, who’s been researching and reporting on science and technology for the past 10 years. He’s a hugely successful science and tech podcaster in Israel, producing a Hebrew-language show called Making History, and he’s also producing two English podcasts right now for an international audience, so since he’s steeped in the subject, he has a lot of very interesting insights for us.”

Ran: “I’m actually an electronics engineer by trade. I was an engineer for 15 years. I was both a hardware and software developer for several companies in Israel. And during my day job as an engineer, I wrote some books about the history of science and technology, which was always a big hobby of mine. And actually, I started a podcast about this very subject about 10 years ago, and it became quite a hit in Israel I’m happy to say. So about four years ago, I quit my day job, and I actually started my own podcasting company, and now we are podcasting both in Israel and in the U.S. for international audience and actually launched my brand new podcast last week. It’s called Malicious Life about the history of malware and cybersecurity, which is a fun topic. Actually, the day I launched the podcast, there was a big ransom attack in Europe mostly. So it was . . . I didn’t plan it. You’ve got no proof against me.”

Ginette: “This is a topic well worth learning more about because cyber attacks can affect anything from your access to electricity to your bank account, so check out his new podcast on the website Malicious.life. But today, we’re talking about a different topic—deep learning. This is something Ran knows quite a bit about, technically and historically.”

Ran: “The name ‘deep learning,’ when you are stopping to think about it, it’s not a very good name—it doesn’t connect with artificial intelligence in any way except maybe ‘learning.’ But what is ‘deep?’ It doesn’t mean really anything. And that’s not by chance, that’s by design. The guys who came up with the name ‘deep learning’ did so because they wanted to distance themselves from artificial neural networks, which was a kind of outcast idea in the academy back then. And they said, ‘OK. Let’s invent a name which would be vague enough so that it will not remind people of the failed concept of neural networks, and they came up with the name ‘deep learning,’ which means nothing in a sense, and only in the late 2008, 2009, did the big companies, such as Google and Microsoft and Facebook, start to get interested in the ideas. They had the hardware to do that. They had enough examples to teach computers how to learn by example, and then we see it, from that point on, we see deep learning really taking off, and now it’s everywhere. Almost every startup . . . you can throw a stone in silicone valley. It will probably hit a startup who is using deep learning for something.

“So deep learning is the technological basis behind today’s major leaps forward with artificial intelligence. When people were trying to teach computers how to do new things, how to, to for example, analyze pictures or to understand human speech. These were traditionally difficult tasks, but then deep learning came on the scene, which is a very different way to solve complicated problems. Deep learning is not explaining to the computers how to solve a problem but giving the computer many, many examples of solved problems, and if you give enough examples to the computer, we’re talking about millions of examples usually, after a time, deep learning enables the computer to figure out a way to solve the problem on its own. Deep learning in a sense is an algorithm that enables the computer to learn from its previous mistakes and improve itself, and if you give the computer enough examples of how to improve itself, it does so, and it does so remarkably well.”

Curtis: “We talked to Ran about what he sees impacting the world the most, and what he sees is really interesting. As you heard in the intro, Ran was invited to Google’s headquarters to ride in a self-driving car. This is what he’s most excited about, and he sees it completely changing our life experiences.”

Above is a partial transcript. For the full interview, listen to the podcast episode by selecting the Play button above or by selecting this linkor you can also listen to the podcast through Apple PodcastsGoogle PlayStitcher, and Overcast.

Sources

Music

http://freesound.org/people/frankum/sounds/157330/#
https://creativecommons.org/licenses/by/3.0/

Links

https://malicious.life/ 
http://aan.org/aan/journalism-ran-levi-breaks-big-ideas-curious-minds/
http://fortune.com/2017/07/25/mark-zuckerberg-elon-musk-artificial-intelligence/