AI project strategy overview

0:05 So, what I want to do today is um continue our discussion on AI project strategy. So, if you're building a deep learning system for some task, and today um for the first part of today I'm going to use the speech recognition uh voice-activated device example, and then for the second half I'm going to use the kind of AI deep researcher example. But, what I want to do is um walk you through a couple concrete examples of, you know, projects you might work on.

0:30 Um um And let you understand what it feels like to be in the thick of building AI system, making day-to-day decisions on what to do next. Uh I find that I I think it's important Let me say before, understanding the algorithms is important. So, in this class you learn a lot here from the online videos about the uh deep learning algorithms, how to build pipelines. But, even beyond understanding how the algorithms work, what really drives performance is a team's ability to have an efficient development process.

0:52 How do you tune hyperparameters? How do you collect data? When you try something and it doesn't work the first time, which it often doesn't, what do you do next? This skill in making those decisions is what often makes a massive, literally 10x difference in productivity. And as I was reflecting as preparing for, you know, what to say to you today, I was reflecting on quite a few projects where um that 10x difference in productivity is is is is really not an exaggeration, right?

1:16 Maybe more than 10x, but I've literally seen many teams in many, you know, well-known companies with good brands um spend a year work on a project that I will see a more skilled team execute in like a month, right? So, these differences in skill are real. And one of the challenges um for many people learning this is if you work for some company, maybe you work on a different project every year or two, right? But, so it takes you like you know, 2 years of every 2 years or a year of your life to gain experience on one more project.

2:02 And then after, I don't know, 10 years you finally seen 10 projects and pretty experienced. Uh but, what I want to do is in today's class walk you through a few concrete examples of projects that similar to the ones kind of simplified versions of stuff that I've seen myself to try to accelerate your hands-on experience looking at these projects and thinking through if you are the one in the hot seat building a system and it works or it doesn't work or there's a problem or whatever, making those decisions for what you would do.

2:25 So, try to get you through that um today with a couple examples rather than you having to spend years and years of your life to finally see a small number of examples of how these projects can be driven.