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• AI-assisted development is here to stay, and Tabnine is expanding its capabilities beyond code completion |
• Importance of curating and training data for AI models, and the challenges that come with it |
• Tending to one's "garden of code" to prepare for AI-assisted development |
• Future of AI-assisted development and its potential impact on the development lifecycle |
**Jerod Santo:** So, Eran, you are CTO and co-founder of Tabnine. You're also a professor of CS at Israel's Technion University. Welcome to The Changelog. |
**Eran Yahav:** Thanks, guys, for having me. It's great to be here. |
**Jerod Santo:** It's great to have you. |
**Adam Stacoviak:** Wow, professor. |
**Jerod Santo:** Yes. |
**Adam Stacoviak:** That's very cool. |
**Eran Yahav:** Yeah, let's say it is cool, yeah... \[laughter\] |
**Adam Stacoviak:** I'm not a professor, so I think it's super cool. |
**Jerod Santo:** I also read that prior to this you also worked at IBM on the Watson project. Is that right, working on Watson? |
**Eran Yahav:** No, I did not work on the Watson project. I worked in the T.J. Watson Lab. The Watson project was actually just a few rooms down the corridor from me, so I heard all the sessions where they were doing the jeopardy training and all that; it was super-exciting. But I was not involved with that at all. |
**Jerod Santo:** Oh, bummer. |
**Eran Yahav:** But I got to witness a few of the first runs; that was literally in the same corridor, so that was cool. |
**Jerod Santo:** Yeah. I connected those dots, because you're doing ML stuff and I figured, "Well, he's doing AI. He was at IBM. He's got to be working on Watson." |
**Eran Yahav:** No. So I worked on very cool things that were not Watson, that were program synthesis, which are related to what we're doing also in Tabnine. And at the time, we worked on program synthesis for synthesizing low-level concurrent programs. So the idea that you would write some sequential code and hit a bu... |
**Jerod Santo:** Yeah. So from there to here, now you have Tabnine, which is your company, trying to do AI-assisted development workflows... Tell us how you got from that play to this place. |
**Eran Yahav:** \[04:01\] So I've always been fascinated with programs that run on programs. That has been my kind of long-standing fascination. I've worked on compilers for a long time, in the early days, then worked on program synthesis, which is programs that generate other programs. And generally speaking, I also w... |
And so working on these synthesis ideas in early days, I guess a decade ago, we started hitting stuff that seems to have actual practical value, as opposed to just academic papers and fascinating ideas. And at the time, Dror, who is the CEO of Tabnine - he's a long-time friend, so I just met him for coffee and I said, ... |
Initially, it was just now the two of us building some technology, pretty much in coffee shops, as these things go... At the time, it was called Codota, by the way. Then we started rolling with that, and things started to work. It was very, very exciting. So that's the early days of Codota at the time. |
**Adam Stacoviak:** So the chasm between research and real-world, so to speak - is that quite distant then? Because I guess with the researchers sort of thinking what's so far in the future...? |
**Eran Yahav:** They're just trying to mix different target functions, in a sense; like, when you're doing research, you're trying to do innovative stuff, and stuff that has interesting core ideas, even if the ability to realize them lies like 10 years, 20 years down the road, or never ever; you just want this core ide... |
**Adam Stacoviak:** Yeah. What about program synthesis in terms of application? Is this a trend in parallel with the possibilities of AI and machine learning and training models and deploying things? Or is it a whole different animal? |
**Eran Yahav:** No. So program synthesis - it is a different animal, but it has been using techniques from AI and language models to make synthesis more practical and maybe expand it to additional domains. |
\[08:03\] So the idea of program synthesis is super-old. The original papers are like from the '50s, the idea of being able to synthesize something. But with the technology that came from ML and language models and things like that, you could do much more practical stuff in program synthesis. But program synthesis is a... |
**Adam Stacoviak:** Yeah, for sure. |
**Jerod Santo:** So I'm trying to see if I'm following you... So program synthesis is an idea or a concept of which deep learning models can be used in order to accomplish it. It's like they are parts of a larger concept. Is that what you're saying? |
**Eran Yahav:** Yeah, that's correct. The problem of program synthesis, which is I give you some sort of specification or intent and you generate the program for me, guaranteed that it does what I asked it to do - this is an ages-old problem. The ability to solve it for realistic payloads is a thing of recent years, an... |
**Adam Stacoviak:** This is like high-performance computing power, or is that the kind of machine to run this kind of stuff on? |
**Eran Yahav:** It's just like, today it's clusters of GPUs or PPUs that you can get on Amazon, GCP, Azure. It's a commodity these days. |
**Adam Stacoviak:** Gotcha. I saw somebody recently ask their employees on Twitter, they said, "Hey, here's another Christmas present. Do you want a beefy Linux laptop, or would you rather like a phenomenal cloud dev environment?" They're like, "I want a phenomenal dev environment on the cloud" kind of thing. "I want s... |
**Eran Yahav:** Yeah. I like both. |
**Jerod Santo:** Yeah. Why not..? |
**Adam Stacoviak:** "Yeah, can I have both, please?" |
**Jerod Santo:** "Yeah. I'll take both, please." |
**Adam Stacoviak:** Wasn't either-or. Would you say that art that is artificially generated - I don't know how to describe that, but art in the AI space, like how you see that AI-generated art... Is that a version of program synthesis? Because you say "Here's an intent", and you've got some models, and then here's this... |
**Jerod Santo:** Art synthesis. |
**Adam Stacoviak:** Yeah. |
**Eran Yahav:** It is a synthesis. It's art synthesis, as you said. It's not program synthesis. It's interesting, because it involves the same act of curation that you get with a lot of program synthesis that the machine generates something for you, and now you have to look at the code that has been generated and say, ... |
**Adam Stacoviak:** Very subjective. |
**Eran Yahav:** It's much easier to do than to get 100 lines of code generated for you and say, "Oh, yeah, I'm sure that this actually connects to Kafka, gets a record, puts them in Mongo, and then sends the email through Twilio", or whatever, which is, I think, my much harder to do. |
**Jerod Santo:** It all seems very hard. I agree, I think program synthesis sounds a lot harder. And we're getting to a point now where we have-- you can talk about where Tabnine is today, and maybe where it's headed, but there's so many avenues we can go down with this conversation. I guess where we should start is, w... |
**Eran Yahav:** \[12:19\] Yeah. So I'll start by saying what Tabnine does, just so we have context. So what Tabnine does is it's an AI assistant that connects to your IDE and generates code from you based on the context in which you're operating. So a massive part or challenge in instances, in generating code is figuri... |
So in a sense, if you're familiar with Google Smart Compose, Gmail Smart Compose, it's like Smart Compose for code; it generates the next thing for you, you just have to tab through and accept them. That's kind of what Tabnine does. I can talk, again, forever on the challenges of what that is, and I think we can go dow... |
**Jerod Santo:** Yeah. Is that what you showed him? |
**Eran Yahav:** Absolutely not. Not even close. \[laughter\] I think it's totally unrecognizable. Some of the core technology is still there, but it is utilized in completely different ways. So what I showed him back in the day was being able to take a huge codebase, train on the codebase and generate a model that if y... |
It's funny how these things evolve, because a lot of challenges-- the bottleneck for a lot of these processes is actually the human, which is surprising, right? So you have this very tight loop of human and machine who are writing a program together. This is what's going on in Tabnine and in other synthesis systems. An... |
**Jerod Santo:** Right. Well, if you think about the end-game of program synthesis, you kind of remove what now is what a developer is, is a person who takes human intent and turns it into something that the machine can execute. There's a lot to that as well. But if you think of the end game, perhaps -- this is what I ... |
**Eran Yahav:** \[16:23\] I don't think so, because a lot of programming is actually discovering the spec. I would say that programming is actually mostly discovering the spec. |
**Jerod Santo:** Yeah, because you don't actually know what you want, right? |
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