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Speaker 1: In a world where technology continues to advance at breakneck speeds,

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Speaker 1: education is evolving to meet the needs of the future.

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Speaker 1: Years ago, if you were told that the average person

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Speaker 1: would have a STEM job, that is, a career in science, technology, engineering,

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Speaker 1: or math, a natural assumption would be that the world

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Speaker 1: had progressed to most people having advanced degrees. On the contrary,

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Speaker 1: it is the technology that progresses and with it our

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Speaker 1: ability to keep up with the times. When I was

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Speaker 1: growing up, our classroom only had one computer for all

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Speaker 1: of us to share. Now my children have their own

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Speaker 1: individual iPads and laptops to research, create and learn. It's

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Speaker 1: amazing how far we have come with using technology to

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Speaker 1: educate our young With their early adoption of technology comes

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Speaker 1: to added responsibility of preparing them for how to use

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Speaker 1: technology for their future occupations. For many students, those jobs

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Speaker 1: will begin sooner than graduating from cos Whether it is

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Speaker 1: learning to manage a small team of AI powered self

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Speaker 1: service machines at the local grocery store, or learning coding

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Speaker 1: skills to oversee a large autonomous robotic warehouse. Education is

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Speaker 1: shaping a brighter future, one student at a time. Hey, there,

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Speaker 1: I'm grain class and this is technically speaking. An Intel podcast,

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Speaker 1: the show is dedicated to highlighting the technology is revolutionizing

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Speaker 1: the way we live, work and move. In every episode,

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Speaker 1: we'll connect with innovators in areas like artificial intelligence to

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Speaker 1: better understand the human centered technology they've developed. We tend

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Speaker 1: to see an education and STEM that is science, technology, engineering,

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Speaker 1: and maths as something that's highly academic, involving several years

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Speaker 1: in high education. Most of the guests on the series

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Speaker 1: have graduated from some of the top universities around the world,

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Speaker 1: or even developing AI tools before they entered college. While

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Speaker 1: it is true that AI and technology are being innovated

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Speaker 1: by some of the greatest minds in the world, those

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Speaker 1: minds aren't always acquiring their skills the same way because

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Speaker 1: it's not always about the degrees that you have, but

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Speaker 1: your passion for knowledge and your ability to learn. One

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Speaker 1: of the recurring themes for me in recording this series

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Speaker 1: is how AI tools have made things more accessible for

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Speaker 1: people around the world. However, it is important for education

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Speaker 1: around AI and machine learning to be accessible as well.

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Speaker 1: In this episode, i'll explore how learning AI is becoming

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Speaker 1: more accessible with the help of Intel's AI for Workforce program.

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Speaker 1: Before we get into it. Let me introduce our guest

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Speaker 1: jotting me now is the lead faculty of Intel's AI

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Speaker 1: for Workforce program at Chandler Gilbert Community College. Habib Mattah

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Speaker 1: Habib was considered a child prodigy in STEM, beginning his

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Speaker 1: collegiate career at the Chandler Gilbert Community College before graduating

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Speaker 1: from Arizona State University at age sixteen. Following up his

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Speaker 1: bachelor's with the mark in Computer Science, Habib went on

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Speaker 1: to become a production lead at Intel, where he oversaw

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Speaker 1: the analysis of statistics and led a team of manufacturing engineers. Ultimately,

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Speaker 1: it was his love for AI and STEM that inspired

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Speaker 1: him to transition into education. He wants to be the

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Speaker 1: catalyst and making AI tools a part of the education

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Speaker 1: system permanently and ensuring that a new generation of kids

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Speaker 1: are fully immersed instead education. Welcome have you, It's good

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Speaker 1: to be here.

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Speaker 2: Wow. I couldn't have written that. That's one of the

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Speaker 2: best introductions I've heard ever, So thank you so much.

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Speaker 1: It wasn't from chat GPT either.

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Speaker 2: I was about to say that, but well, I get

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Speaker 2: it up with those jokes already, being an AI professor.

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Speaker 1: That's right, that's right. So I mean, I have a

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Speaker 1: son who's twelve and he's just started high school. You

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Speaker 1: started college at age twelve, and I can't imagine him

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Speaker 1: heading off to universe. So your early achievements are really remarkable.

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Speaker 1: What did that experience teach you about learning stem tools

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Speaker 1: at an early age and how has it shaped your

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Speaker 1: approach to teaching.

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Speaker 2: So a small correction there, I was one year older.

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Speaker 2: I was thirteen when I started, okay, and I was

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Speaker 2: that's just, I know, not a big deal in terms

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Speaker 2: of age. So I was going into eighth grade, and

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Speaker 2: at the time, I always knew that I was going

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Speaker 2: to do some kind of engineering because my dad is

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Speaker 2: an electrical engineer, and I wanted to see if it

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Speaker 2: was possible to accelerate that process. I had no idea

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Speaker 2: what the college space would have been like and how

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Speaker 2: I would have came out on the other side of it,

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Speaker 2: but I knew that my dad worked there at Chandler

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Speaker 2: Gilbert Community College as well as my mom does as well.

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Speaker 2: She's an English faculty, and so I knew i'd be

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Speaker 2: in a safe place going to the community college, and

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Speaker 2: I'd be around family when I'm not in classes. So

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Speaker 2: I just ventured out into that big world. I didn't

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Speaker 2: really even realize that everyone around me was, you know,

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Speaker 2: five or six years older. I was so focused on

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Speaker 2: reaching that goal of becoming an engineer like my dad.

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Speaker 1: And it was actually quite interesting that you said that

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Speaker 1: your father was an electrical engineer. My dad was an

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Speaker 1: electronic engineer, and I remember spending quite a bit of

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Speaker 1: time in his workshops at a young age. Perhaps tell

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Speaker 1: me a little bit more, I mean of his influence

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Speaker 1: on yourself going up.

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Speaker 2: Well, it's an influence of his and as well as

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Speaker 2: the culture. My name's Habib, which is Lebanese. It's actually

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Speaker 2: my grandpa's name. And part of the Lebanese culture is

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Speaker 2: is that you become either a doctor, a lawyer, or

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Speaker 2: an engineer, right, and so I had to choose one

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Speaker 2: of those, and I wasn't too good with blood, and

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Speaker 2: so engineer definitely was that. On top of that, my

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Speaker 2: dad would give me little incentives growing up. So I

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Speaker 2: was super video games and he would say, okay, I'll

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Speaker 2: give you one dollar for every math sheet that you do.

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Speaker 2: So I would do these large multiplication tables just so

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Speaker 2: I can get like one dollar and save up for

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Speaker 2: that game I wanted.

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Speaker 1: Ah, that's cool. I mean, I remember my dad giving

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Speaker 1: me sort of logic puzzles and numerical puzzles as well.

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Speaker 1: Going out. You didn't give you any money though, that's

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Speaker 1: crying shame. So yeah, so I'm quite interested in the

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Speaker 1: whole accelerated program that you went through. What sort of

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Speaker 1: challenges are there for students to get access to that

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Speaker 1: sort of program.

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Speaker 2: We had found that if I went through homeschooling and

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Speaker 2: tested out of homeschooling, then that could get me admitted

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Speaker 2: into the community college. Once I started that process, all

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Speaker 2: I did was a placement test, which is very standard

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Speaker 2: across all community college goers. To do this placement test,

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Speaker 2: I tested into like the hundreds, so not even the

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Speaker 2: one hundred classes because again I'm thirteen. But within a

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Speaker 2: year I was able to begin my program similarly to

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Speaker 2: someone who had just got out of high school. From there,

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Speaker 2: my memory of the time was very normal, Like the

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Speaker 2: students around me were all pretty mature. I was able

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Speaker 2: to talk to the other nerds and play video games

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Speaker 2: with them, and so I had found myself in a

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Speaker 2: pretty fun community that was quite nice. And actually I

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Speaker 2: have people that I've talked to in my life that

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Speaker 2: have kids and they've had their own kids go through

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Speaker 2: that route as well.

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Speaker 1: Despite spending most of his childhood becoming a scholar and STEM,

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Speaker 1: his passions lie in teaching and helping others. This education

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Speaker 1: is valuable to have even when you're not working in

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Speaker 1: a STEM field. In such a role as an engineer,

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Speaker 1: just having that sort of background can help others better

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Speaker 1: understand the technologies we engage with regularly. If you've ever

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Speaker 1: had to help a grandparent use a phone or printer,

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Speaker 1: you know the exact challenges of helping others become tech savvy.

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Speaker 1: In terms of the role now that you have at

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Speaker 1: the college, maybe you could give a little bit of

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Speaker 1: a summary. What are the courses, what are the programs

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Speaker 1: that you're teaching there?

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Speaker 2: Yeah, So when I transitioned from working at Intel into

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Speaker 2: Chandler Gilbert, Intel approached us saying, we have a high

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Speaker 2: school program that we're using in I believe Singapore for

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Speaker 2: teaching AI. Is there any way we could take this

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Speaker 2: high school program and make it into like a two

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Speaker 2: year vocational program. And so my background was in computer

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Speaker 2: science and AI, and I had already been working at

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Speaker 2: Intel and I had family at Chandler Gilbert. Right, So

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Speaker 2: it's like this perfect marriage between the three. And so

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Speaker 2: the program I teach at Chandler Gilbert is in essence

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Speaker 2: that it's a two year vocational program for someone to

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Speaker 2: learn about artificial intelligence. Now, we started this in twenty nineteen.

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Speaker 2: This was before chat GPT and the boom a popularity

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Speaker 2: of AI. So what my focus has been since twenty

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Speaker 2: nineteen is how can I give my students marketable skills

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Speaker 2: while still keeping it accessible Because typically AI is a

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Speaker 2: graduate field right now you have to have a master's

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Speaker 2: or a PhD to learn about the topic. How can

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Speaker 2: I keep this field accessible to learn as well as

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Speaker 2: marketable with the skills that they do learn throughout the

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Speaker 2: two year program. And so we have six different classes

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Speaker 2: that we teach following that goal. Intro to AI is

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Speaker 2: one of them, intro to Machine Learning, intro to Natural

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Speaker 2: Language Processing, so this is, you know, how does SII

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Speaker 2: know what when you say Hey Siri? Or how can

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Speaker 2: chat GPT seem to understand the text that you write?

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Speaker 2: Then we have computer vision, where it's how do cars

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Speaker 2: driving on the road see other cars and pedestrians and

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Speaker 2: no one to stop. The last two classes are intro

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Speaker 2: to Business Solutions. We actually have an employee from Intel

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Speaker 2: teaching that class, giving students important aspects of what work

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Speaker 2: looks like in AI, like benchmarking and copyright issues that

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Speaker 2: come with data. And then we have a capstone class

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Speaker 2: where the students get a whole semester to explore an

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Speaker 2: AI project.

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Speaker 1: Well that's all in two years. Two years, yes, Well

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Speaker 1: that's impressive. And in terms of getting into that sort

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Speaker 1: of program, what are the some of the prerequisites that

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Speaker 1: students have to have before joining in.

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Speaker 2: So we're a community college and we want to keep

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Speaker 2: this as accessible as possible. So our first class, Intro

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Speaker 2: to AI, also named AIM one hundred. AIM stands for

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Speaker 2: AIM machine Learning and it was a funny, you know,

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Speaker 2: acronym to put there. But it's no prerequisites to join

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Speaker 2: our first course. Now, our next class, AIM one ten,

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Speaker 2: which is intro to Machine Learning, has a prerequisite of

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Speaker 2: statistics as well as intro to Python, so you'll need

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Speaker 2: to know a little bit of Python and statistics.

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Speaker 1: Just for everyone's benefit. Python is a popular computing language

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Speaker 1: which actually has a lot of free resources for anyone

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Speaker 1: to look up and be able to code their own

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Speaker 1: AI machine learning programs. So, Habi, do you know if

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Speaker 1: this program is trying to be replicated in other community colleges.

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Speaker 2: That's actually at the heart of AI for Workforce. So

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Speaker 2: I'm the lead faculty at Chandler Gilbert, but I played

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Speaker 2: a role in helping advise AI for Workforce and now

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Speaker 2: they're their own separate entity. So what we had at

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Speaker 2: our campus last week was a summit hosted are at

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Speaker 2: Channel Gilbert campus called the AI Teaching and Learning Summit,

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Speaker 2: So we had one hundred different folk faculty and administrators

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Speaker 2: from across the country and even Canada come to our

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Speaker 2: campus and try and learn about building their own AI

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Speaker 2: programs within their institutions. Well, one of the leaders of

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Speaker 2: AI for Workforce came and talked about I think they've

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Speaker 2: reached somewhere between thirty two to forty eight community colleges

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Speaker 2: in the country. They've almost hit every single state in

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Speaker 2: terms of a community college within the state. So they

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Speaker 2: have that many community colleges that have at least taken

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Speaker 2: the INTEL training that they have available now, which is

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Speaker 2: available for free, to build programs within their own college.

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Speaker 2: In terms of who I see that has full fledged programs,

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Speaker 2: think there's only like four or five colleges that I'm

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Speaker 2: aware of in the country that have an associates or

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Speaker 2: a certificate in AI at a community college level.

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Speaker 1: We'll be right back after a quick break. Welcome back

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Speaker 1: to Technically Speaking, an Intel podcast. I'd like to get

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Speaker 1: your thoughts on any data or trends in the job

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Speaker 1: market around the significance of learning about AI, and is

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Speaker 1: that demand still there and do you see that growing

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Speaker 1: and in which areas and which industries do you see

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Speaker 1: the best potential for your students going through that program.

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Speaker 2: It's a hard marker to pin on right now because

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Speaker 2: it's such an emerging field. There's different routes you could

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Speaker 2: see AI, this large field of AI going right now.

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Speaker 2: So I'll start from the most beginner level. You have

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Speaker 2: people who are like prompt engineers who use something like

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Speaker 2: chat GPT, these very industry wide models and are able

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Speaker 2: to interface with that system such that they get autonomous outputs,

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Speaker 2: automatic outputs that increase productivity and reduce the amount of

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Speaker 2: work that someone would need to do. Right That prompt

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Speaker 2: engineer is a great field for someone who's entry into

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Speaker 2: the AI space. Right It doesn't need nearly as much

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Speaker 2: math or programming even and there's actually a lot of

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Speaker 2: drag and drop interface to perform AI modeling platforms where

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Speaker 2: you can kind of input data, drag and drop what

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Speaker 2: you need and then get some meaningful output. I can't

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Speaker 2: say that I target that too much right now because

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Speaker 2: there's not a lot of stability there just yet. Chat

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Speaker 2: GPT is still relatively new, no code tools, it's very specified,

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Speaker 2: So I focus more on level two. I would say,

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Speaker 2: you can hear my video games speak come out. Level

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Speaker 2: two is they have some coding. They're like a software developer,

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Speaker 2: but more equipped to tackle problems that could evolve automation

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Speaker 2: of let's say text and images, have some of the

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Speaker 2: data analytics background as well to analyze and process data,

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Speaker 2: come up with systems that automatically process that data and

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Speaker 2: give meaningful output. So they have to have a little

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Speaker 2: bit of math to understand how that data is being

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Speaker 2: inputed and what the story is behind the data is

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Speaker 2: what I typically say. And then they have to have

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Speaker 2: some programming, because if you stick with only no code tools,

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Speaker 2: you're very limited to what those no code tools can offer.

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Speaker 2: With programming, it opens the doors. So that's level two

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Speaker 2: and that's where I try and keep my students. These

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Speaker 2: concepts in AI can get very sticky mathematically very quickly,

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Speaker 2: and I can't expect a two year student to be

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Speaker 2: at that level of foundation. So then level three is

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Speaker 2: that they have a very solid mathematical foundation to where

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Speaker 2: pretty much any AI algorithm I throw at them they

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Speaker 2: can at least orient themselves to quite quickly. Someone with

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Speaker 2: a master's background or a bachelor's background can do this, right.

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Speaker 2: You come into a new class and it's like, oh,

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Speaker 2: that's just the formula I've seen before kind of but

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Speaker 2: just in a different way.

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Speaker 1: Ye gotcha.

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Speaker 2: And then the programming expertise of let's say, Okay, we're

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Speaker 2: not going to do this in Python, now we're going

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Speaker 2: to do this in R. They know so many programming

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Speaker 2: languages at that point that they can kind of easily

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Speaker 2: switch between the two for a quick prototype. So I

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Speaker 2: see that as level three three, So right now, I

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Speaker 2: target that level too.

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Speaker 1: Okay, just previously, you talked a little bit about some

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Speaker 1: of the student projects that can be quite exciting for

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Speaker 1: both the teachers and the students, a like, is there

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Speaker 1: just one that is top of your brain right now

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Speaker 1: that is quite exciting that you're working on with your students.

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Speaker 2: So the one I do is I have them create

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Speaker 2: an automatic bubble sheet scanner. So they take a photo

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Speaker 2: with their phone and they should be able to grade

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Speaker 2: a bubble sheet just based off of a photo. So

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Speaker 2: I teach them all about things like how to detect

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Speaker 2: the bubbles on a sheet, how to know which position

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Speaker 2: is where on the sheet. It doesn't automatically tell you

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Speaker 2: where it is, so you have to do that and

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Speaker 2: then sort them in a list that the top left

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Speaker 2: is zero and then go on from there all the

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Speaker 2: way down. Gotcha, And then to know whether or not

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Speaker 2: it's filled. So that's about an eight week process, not

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Speaker 2: that one project, but what leads up to that project.

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Speaker 2: So then let's jump into I guess the capstone projects

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Speaker 2: where my students are out in the wild West, right.

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Speaker 2: I have students who do stock market prediction brain tumor

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Speaker 2: detection based off of MRI or CT scans. One of

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Speaker 2: my students is a musician, so he likes to handwrite

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Speaker 2: his musical notes and he wants to be able to

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Speaker 2: take a picture and have it be electronically printed. I've

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Speaker 2: had a student who won actually an Intel competition taking

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Speaker 2: brain wave EEG data and trying to detect if there

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Speaker 2: is an epileptic seizure occurring within that data. I think

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Speaker 2: what I find is is that I'm always amazed that

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Speaker 2: I give them these little seedlings of knowledge and then

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Speaker 2: that capstone project comes around and they just grow without

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Speaker 2: me even being there.

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Speaker 1: Yeah, Habib, you mentioned a lot of people need graduate

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Speaker 1: level degrees to work in AI. Right now, what path

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Speaker 1: have you seen your students go through after these courses?

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Speaker 1: Have they said it's opened any doors for them?

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Speaker 2: So one of the big challenges we're trying to tackle

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Speaker 2: on the community college AI education side is pathways for

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Speaker 2: students upon graduation. Right it's pretty bleak in terms of

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Speaker 2: having a two year degree and meeting minimum jow brecks.

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Speaker 2: Our college actually is beginning to offer or developing a

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Speaker 2: bachelor's degree in AI to alleviate that issue. But I'm

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Speaker 2: seeing that they're still finding positions because of how marketable

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Speaker 2: AI skills are. Right now, it may not be, you know,

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Speaker 2: an engineer, but it could be, Hey, here's an entry

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Speaker 2: level role at a company, but it's easier for them

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Speaker 2: to get through the door because they have these marketable skills.

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Speaker 1: And in your view, how do you see the future

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Speaker 1: of AI in the workplace And what's your number one

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Speaker 1: reason that you tell the younger generation and students why

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Speaker 1: AI tools are so important to learn.

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Speaker 2: You know, when AI was first emerging, let's say chat

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Speaker 2: GPT right into popularity, everyone was like, AI is going

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Speaker 2: to replace jobs, and actually there's been a new keynote

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Speaker 2: I guess that people have been saying, which is people

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Speaker 2: who have AI skills will be better equipped than those without.

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Speaker 2: I completely agree on that note, because we work so

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Speaker 2: much with technology. If we're better to interface with that technology,

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Speaker 2: we're going to be that much more productive. We can

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Speaker 2: tackle much more complex problems in a shorter amount of time,

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Speaker 2: and so I see the future workforce being able to

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Speaker 2: be once again more productive utilizing these tools. I mean

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Speaker 2: when you're typing an email and gmails like hey, here's

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Speaker 2: the rest of that sentence. Yeah right, it's just so

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Speaker 2: convenient and it helps ease the amount of hand to

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Speaker 2: paper work we have to do. And we can now

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Speaker 2: be more creative with that time and solve more nuanced,

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Speaker 2: more complex problems because we have these systems better ready

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Speaker 2: to assist us. So someone like me and you can

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Speaker 2: do a lot more with this lifespan that we have.

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Speaker 2: We can develop, create ID eight more things because we

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Speaker 2: have more time to do so.

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Speaker 1: The way Habib looks at AI as a tool in

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Speaker 1: assisting the workflow reminds me of the invention of the spreadsheet.

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Speaker 1: My grandfather worked at the bank for forty years in

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Speaker 1: the same desk, the same chair, pouring over bank ledges

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Speaker 1: with paper and pencil, ensuring all figures balanced exactly to

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Speaker 1: the scent. With the invention of computerized adding machines and

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Speaker 1: then later spreadsheets on personal computers, there's laborious efforts that

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Speaker 1: my grandfather previously undertook had now become so quick and accurate.

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Speaker 1: He retired before the advent of these technologies, but I

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Speaker 1: often think how helpful those tools would have been for him.

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Speaker 1: AI in the workplace empowers everyone to focus on what

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Speaker 1: they do best. Learning these AI tools, like learning how

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Speaker 1: to use a spreadsheet, gives employees an added edge in

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Speaker 1: how they work as individuals and within their teams. I'd

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Speaker 1: just like to get your thoughts about the AI tools

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Speaker 1: for the non engineers and non tech people.

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Speaker 2: Well, I think I've been giving this rose colored glasses

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Speaker 2: look onto AI right where AI is always beneficial and

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Speaker 2: always used in the right way. But we know that's

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Speaker 2: not the case. I think that it's important to know

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Speaker 2: what algorithms and what AI can do because our number

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Speaker 2: one interface with AI every day is things like the

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Speaker 2: Internet and social media. And so I have students who

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Speaker 2: may be dealing with some kind of addictive behavior and

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Speaker 2: they don't realize that AI recommendation systems that are used

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Speaker 2: in sol social media are constantly feeding them content that

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Speaker 2: may make them feel stuck in that frame of mind

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Speaker 2: and that addictive cycle. And so I think it's important

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Speaker 2: for the general public to know what AI thinked imagery

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Speaker 2: looks like, what algorithms are out there, and how they

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Speaker 2: use your preferences to feed you more content that you like,

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Speaker 2: just for our own mental wellbeing. So I see my

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Speaker 2: class AA in one hundred as a place where people

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Speaker 2: can come and learn about these technologies so that they're

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Speaker 2: better equipped to personally manage their interface with them right

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Speaker 2: mentally manage it.

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Speaker 1: Yeah, and are there any ethical considerations you try and

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Speaker 1: emphasize when teaching your course to your students.

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Speaker 2: So I try to give my students a broad overview

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Speaker 2: of AI ethics, because again, you could dig into one

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Speaker 2: quite a bit and there's still a ton of content

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Speaker 2: left there. So I started talking about, like what topics

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Speaker 2: there are in AI ethics. There's privacy and surveillance, there's

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Speaker 2: manipulation of behavior, there's jobs and autonomy. So those are

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Speaker 2: all like separate topics that I go over. Then I

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Speaker 2: can take a step further and I talk about frameworks.

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Speaker 2: So what frameworks are out there in terms of AI ethics,

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Speaker 2: Like the European AI Act came out and they have

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Speaker 2: a framework for how they want to regulate this technology.

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Speaker 2: Now we're seeing policy on the America side on AI.

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Speaker 2: My last little tidbit in the AI ethics realm is

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Speaker 2: trying to dispel some of the fear. I am personally

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Speaker 2: of the belief that there's not some looming AI monster

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Speaker 2: coming to eat us, and if there would be, we

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Speaker 2: would see the development of it, Like we've seen the

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Speaker 2: development of this technology all along chat GPT wasn't grown

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Speaker 2: in a lab and everyone was like, oh, I've never

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Speaker 2: seen this before. We had GPT one, GPT two, GPT three. Yes,

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Speaker 2: we saw the progress of that technology.

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Speaker 1: Yeah, and I generally agree with that that there's going

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Speaker 1: to be a net positive to the AI growth that

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Speaker 1: we're seeing. But I think it's incumbent upon people like

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Speaker 1: you to actually teach and guide students around at least

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Speaker 1: understanding some of that, as you said, the ethical frameworks

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Speaker 1: around it, because they're the ones that are going to

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Speaker 1: be producing these things. Right. So I have three kids,

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Speaker 1: two of them are now in high school. What advice

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Speaker 1: would you give to parents and educators who are looking

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Speaker 1: to introduce AI and STAM related concepts to children at

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Speaker 1: an early age.

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Speaker 2: Man, that's a great question. I've never been asked that.

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Speaker 2: I've done so many interviews that I've never announced that.

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Speaker 2: What advice would I give them? You know, I'm a

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Speaker 2: family oriented person, right, I'm twenty six. I'm hoping to

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Speaker 2: have a family someday, So I kind of think about

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Speaker 2: this a lot. One thing I find my classroom is

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Speaker 2: is if you make it fun, the students get involved

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Speaker 2: and they get interested. Right. It's like if you have

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Speaker 2: dessert after your salad. Right, people are just more willing

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Speaker 2: to eat the salad so that they can have that

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Speaker 2: dessert and feel okay about it. So, getting your kids

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Speaker 2: involved in things like Legos Mindstorm, which is a subsect

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Speaker 2: like a robotic subsect of Legos, even like video games

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Speaker 2: that are less so dopamine addiction for them and more

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Speaker 2: so building and creating things using their intelligence in their mind.

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Speaker 2: I think making the space more fun for them to access,

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Speaker 2: and then on top of that, making it social, having

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Speaker 2: them find a friend group where they can relate to

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Speaker 2: other people about these kinds of things. I think loneliness

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Speaker 2: epidemic is pretty bad in today's world, and there's ways

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Speaker 2: you can alleviate that early on in their lives by

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Speaker 2: getting them involved in a community of other kids who

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Speaker 2: are open to doing those kinds of things.

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Speaker 1: Yeah, what do you envision as the future of AI

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Speaker 1: and education And what's the number one thing that excites

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Speaker 1: you most about the role of AI in shaping the

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Speaker 1: learning experiences?

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Speaker 2: I think the way we're interfacing what technology is changing

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Speaker 2: and being spurred on by AI, that's what we've named this,

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Speaker 2: and so I'm really excited for the shift that will

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Speaker 2: come in how we interface with technology. On the education side, right,

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Speaker 2: we teach people how to use technology, So now we're

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Speaker 2: going to teach them how to better their use of

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Speaker 2: technology by including AI education. So I'm really excited that

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Speaker 2: this new workforce that's coming will be better equipped again

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Speaker 2: to tackle more complex problems, and who knows, maybe some

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Speaker 2: of the problems that we've been trying to tackle for

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Speaker 2: so long will seem simplistic in the next twenty to

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Speaker 2: thirty years, and I'm really excited for or this emergence

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Speaker 2: of that, and I hope that we use it in

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Speaker 2: the right way to better society.

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Speaker 1: Awesome. Thanks very much, Havib, Well.

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Speaker 2: Thank you. I appreciate your time. It's been fun.

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Speaker 1: Thanks to Habib Mata for joining me on this episode

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Speaker 1: of Technically Speaking, an Intel podcast. Chatting with Habib was

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Speaker 1: really an eye opener. Being a dad of three, I'm

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Speaker 1: always on the hunt for ways to help my kids

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Speaker 1: flourish in their future careers. What grabs me about the

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Speaker 1: course that Intel and Habib created is that it's not

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Speaker 1: just your run of the mill four year degree. It's

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Speaker 1: like they threw open the doors for people from all

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00:28:42,080 --> 00:28:44,960
Speaker 1: walks of life, no matter where they are in their career,

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Speaker 1: to jump in and really get their hands dirty in

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Speaker 1: the emerging fields of AI and STEM. The way Habib

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Speaker 1: gets his students fired up is pretty cool. He dives

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Speaker 1: into real world applications right from the get go, sparking

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Speaker 1: that curiosity bug in his students. This style gets them

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Speaker 1: hooked early on, and then they dig deeper into the

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Speaker 1: nitty gritty theory behind those AI projects. It's a far

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Speaker 1: cry for my old engineering days. It's all about slogging

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00:29:11,200 --> 00:29:13,680
Speaker 1: through thick theory books before getting onto the hands on

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Speaker 1: fun projects. And now, with the solid backing from Intel

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00:29:17,520 --> 00:29:20,760
Speaker 1: and Habib's relentless effort, this program is rolling out to

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Speaker 1: more campuses across the US, and who knows, soon it

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Speaker 1: might be a movement that spans the world. That's something

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Speaker 1: to be excited about, not just for my kids, but

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Speaker 1: for anyone ready to ride the AI and STEM wave.

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Speaker 1: Thank you all for listening. Join us again in two

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Speaker 1: weeks in December twenty sixth for the season finale of

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Speaker 1: Technically Speaking, an Intel podcast. There's been a real journey

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00:29:45,400 --> 00:29:48,600
Speaker 1: learning about all these new technologies, and our final episode

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00:29:48,680 --> 00:29:51,720
Speaker 1: will explore the challenges it takes to make them all possible.

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Speaker 1: You definitely do not want to miss its. Technically Speaking

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Speaker 1: was produced by Ruby Studios from IHET Radio in partnership

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Speaker 1: with Intel and hosted by me Graham Class. Our executive

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Speaker 1: producer is Molly Sosha, our EP of Post Production is

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Speaker 1: James Foster, and our Supervising producer is Nikir Swinton. This

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Speaker 1: episode was edited by Sierra Spreen and written and produced

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Speaker 1: by Tyree Rush,