Speaker 1: In a world where technology continues to advance at breakneck speeds,
Speaker 1: education is evolving to meet the needs of the future.
Speaker 1: Years ago, if you were told that the average person
Speaker 1: would have a STEM job, that is, a career in science, technology, engineering,
Speaker 1: or math, a natural assumption would be that the world
Speaker 1: had progressed to most people having advanced degrees. On the contrary,
Speaker 1: it is the technology that progresses and with it our
Speaker 1: ability to keep up with the times. When I was
Speaker 1: growing up, our classroom only had one computer for all
Speaker 1: of us to share. Now my children have their own
Speaker 1: individual iPads and laptops to research, create and learn. It's
Speaker 1: amazing how far we have come with using technology to
Speaker 1: educate our young With their early adoption of technology comes
Speaker 1: to added responsibility of preparing them for how to use
Speaker 1: technology for their future occupations. For many students, those jobs
Speaker 1: will begin sooner than graduating from cos Whether it is
Speaker 1: learning to manage a small team of AI powered self
Speaker 1: service machines at the local grocery store, or learning coding
Speaker 1: skills to oversee a large autonomous robotic warehouse. Education is
Speaker 1: shaping a brighter future, one student at a time. Hey, there,
Speaker 1: I'm grain class and this is technically speaking. An Intel podcast,
Speaker 1: the show is dedicated to highlighting the technology is revolutionizing
Speaker 1: the way we live, work and move. In every episode,
Speaker 1: we'll connect with innovators in areas like artificial intelligence to
Speaker 1: better understand the human centered technology they've developed. We tend
Speaker 1: to see an education and STEM that is science, technology, engineering,
Speaker 1: and maths as something that's highly academic, involving several years
Speaker 1: in high education. Most of the guests on the series
Speaker 1: have graduated from some of the top universities around the world,
Speaker 1: or even developing AI tools before they entered college. While
Speaker 1: it is true that AI and technology are being innovated
Speaker 1: by some of the greatest minds in the world, those
Speaker 1: minds aren't always acquiring their skills the same way because
Speaker 1: it's not always about the degrees that you have, but
Speaker 1: your passion for knowledge and your ability to learn. One
Speaker 1: of the recurring themes for me in recording this series
Speaker 1: is how AI tools have made things more accessible for
Speaker 1: people around the world. However, it is important for education
Speaker 1: around AI and machine learning to be accessible as well.
Speaker 1: In this episode, i'll explore how learning AI is becoming
Speaker 1: more accessible with the help of Intel's AI for Workforce program.
Speaker 1: Before we get into it. Let me introduce our guest
Speaker 1: jotting me now is the lead faculty of Intel's AI
Speaker 1: for Workforce program at Chandler Gilbert Community College. Habib Mattah
Speaker 1: Habib was considered a child prodigy in STEM, beginning his
Speaker 1: collegiate career at the Chandler Gilbert Community College before graduating
Speaker 1: from Arizona State University at age sixteen. Following up his
Speaker 1: bachelor's with the mark in Computer Science, Habib went on
Speaker 1: to become a production lead at Intel, where he oversaw
Speaker 1: the analysis of statistics and led a team of manufacturing engineers. Ultimately,
Speaker 1: it was his love for AI and STEM that inspired
Speaker 1: him to transition into education. He wants to be the
Speaker 1: catalyst and making AI tools a part of the education
Speaker 1: system permanently and ensuring that a new generation of kids
Speaker 1: are fully immersed instead education. Welcome have you, It's good
Speaker 1: to be here.
Speaker 2: Wow. I couldn't have written that. That's one of the
Speaker 2: best introductions I've heard ever, So thank you so much.
Speaker 1: It wasn't from chat GPT either.
Speaker 2: I was about to say that, but well, I get
Speaker 2: it up with those jokes already, being an AI professor.
Speaker 1: That's right, that's right. So I mean, I have a
Speaker 1: son who's twelve and he's just started high school. You
Speaker 1: started college at age twelve, and I can't imagine him
Speaker 1: heading off to universe. So your early achievements are really remarkable.
Speaker 1: What did that experience teach you about learning stem tools
Speaker 1: at an early age and how has it shaped your
Speaker 1: approach to teaching.
Speaker 2: So a small correction there, I was one year older.
Speaker 2: I was thirteen when I started, okay, and I was
Speaker 2: that's just, I know, not a big deal in terms
Speaker 2: of age. So I was going into eighth grade, and
Speaker 2: at the time, I always knew that I was going
Speaker 2: to do some kind of engineering because my dad is
Speaker 2: an electrical engineer, and I wanted to see if it
Speaker 2: was possible to accelerate that process. I had no idea
Speaker 2: what the college space would have been like and how
Speaker 2: I would have came out on the other side of it,
Speaker 2: but I knew that my dad worked there at Chandler
Speaker 2: Gilbert Community College as well as my mom does as well.
Speaker 2: She's an English faculty, and so I knew i'd be
Speaker 2: in a safe place going to the community college, and
Speaker 2: I'd be around family when I'm not in classes. So
Speaker 2: I just ventured out into that big world. I didn't
Speaker 2: really even realize that everyone around me was, you know,
Speaker 2: five or six years older. I was so focused on
Speaker 2: reaching that goal of becoming an engineer like my dad.
Speaker 1: And it was actually quite interesting that you said that
Speaker 1: your father was an electrical engineer. My dad was an
Speaker 1: electronic engineer, and I remember spending quite a bit of
Speaker 1: time in his workshops at a young age. Perhaps tell
Speaker 1: me a little bit more, I mean of his influence
Speaker 1: on yourself going up.
Speaker 2: Well, it's an influence of his and as well as
Speaker 2: the culture. My name's Habib, which is Lebanese. It's actually
Speaker 2: my grandpa's name. And part of the Lebanese culture is
Speaker 2: is that you become either a doctor, a lawyer, or
Speaker 2: an engineer, right, and so I had to choose one
Speaker 2: of those, and I wasn't too good with blood, and
Speaker 2: so engineer definitely was that. On top of that, my
Speaker 2: dad would give me little incentives growing up. So I
Speaker 2: was super video games and he would say, okay, I'll
Speaker 2: give you one dollar for every math sheet that you do.
Speaker 2: So I would do these large multiplication tables just so
Speaker 2: I can get like one dollar and save up for
Speaker 2: that game I wanted.
Speaker 1: Ah, that's cool. I mean, I remember my dad giving
Speaker 1: me sort of logic puzzles and numerical puzzles as well.
Speaker 1: Going out. You didn't give you any money though, that's
Speaker 1: crying shame. So yeah, so I'm quite interested in the
Speaker 1: whole accelerated program that you went through. What sort of
Speaker 1: challenges are there for students to get access to that
Speaker 1: sort of program.
Speaker 2: We had found that if I went through homeschooling and
Speaker 2: tested out of homeschooling, then that could get me admitted
Speaker 2: into the community college. Once I started that process, all
Speaker 2: I did was a placement test, which is very standard
Speaker 2: across all community college goers. To do this placement test,
Speaker 2: I tested into like the hundreds, so not even the
Speaker 2: one hundred classes because again I'm thirteen. But within a
Speaker 2: year I was able to begin my program similarly to
Speaker 2: someone who had just got out of high school. From there,
Speaker 2: my memory of the time was very normal, Like the
Speaker 2: students around me were all pretty mature. I was able
Speaker 2: to talk to the other nerds and play video games
Speaker 2: with them, and so I had found myself in a
Speaker 2: pretty fun community that was quite nice. And actually I
Speaker 2: have people that I've talked to in my life that
Speaker 2: have kids and they've had their own kids go through
Speaker 2: that route as well.
Speaker 1: Despite spending most of his childhood becoming a scholar and STEM,
Speaker 1: his passions lie in teaching and helping others. This education
Speaker 1: is valuable to have even when you're not working in
Speaker 1: a STEM field. In such a role as an engineer,
Speaker 1: just having that sort of background can help others better
Speaker 1: understand the technologies we engage with regularly. If you've ever
Speaker 1: had to help a grandparent use a phone or printer,
Speaker 1: you know the exact challenges of helping others become tech savvy.
Speaker 1: In terms of the role now that you have at
Speaker 1: the college, maybe you could give a little bit of
Speaker 1: a summary. What are the courses, what are the programs
Speaker 1: that you're teaching there?
Speaker 2: Yeah, So when I transitioned from working at Intel into
Speaker 2: Chandler Gilbert, Intel approached us saying, we have a high
Speaker 2: school program that we're using in I believe Singapore for
Speaker 2: teaching AI. Is there any way we could take this
Speaker 2: high school program and make it into like a two
Speaker 2: year vocational program. And so my background was in computer
Speaker 2: science and AI, and I had already been working at
Speaker 2: Intel and I had family at Chandler Gilbert. Right, So
Speaker 2: it's like this perfect marriage between the three. And so
Speaker 2: the program I teach at Chandler Gilbert is in essence
Speaker 2: that it's a two year vocational program for someone to
Speaker 2: learn about artificial intelligence. Now, we started this in twenty nineteen.
Speaker 2: This was before chat GPT and the boom a popularity
Speaker 2: of AI. So what my focus has been since twenty
Speaker 2: nineteen is how can I give my students marketable skills
Speaker 2: while still keeping it accessible Because typically AI is a
Speaker 2: graduate field right now you have to have a master's
Speaker 2: or a PhD to learn about the topic. How can
Speaker 2: I keep this field accessible to learn as well as
Speaker 2: marketable with the skills that they do learn throughout the
Speaker 2: two year program. And so we have six different classes
Speaker 2: that we teach following that goal. Intro to AI is
Speaker 2: one of them, intro to Machine Learning, intro to Natural
Speaker 2: Language Processing, so this is, you know, how does SII
Speaker 2: know what when you say Hey Siri? Or how can
Speaker 2: chat GPT seem to understand the text that you write?
Speaker 2: Then we have computer vision, where it's how do cars
Speaker 2: driving on the road see other cars and pedestrians and
Speaker 2: no one to stop. The last two classes are intro
Speaker 2: to Business Solutions. We actually have an employee from Intel
Speaker 2: teaching that class, giving students important aspects of what work
Speaker 2: looks like in AI, like benchmarking and copyright issues that
Speaker 2: come with data. And then we have a capstone class
Speaker 2: where the students get a whole semester to explore an
Speaker 2: AI project.
Speaker 1: Well that's all in two years. Two years, yes, Well
Speaker 1: that's impressive. And in terms of getting into that sort
Speaker 1: of program, what are the some of the prerequisites that
Speaker 1: students have to have before joining in.
Speaker 2: So we're a community college and we want to keep
Speaker 2: this as accessible as possible. So our first class, Intro
Speaker 2: to AI, also named AIM one hundred. AIM stands for
Speaker 2: AIM machine Learning and it was a funny, you know,
Speaker 2: acronym to put there. But it's no prerequisites to join
Speaker 2: our first course. Now, our next class, AIM one ten,
Speaker 2: which is intro to Machine Learning, has a prerequisite of
Speaker 2: statistics as well as intro to Python, so you'll need
Speaker 2: to know a little bit of Python and statistics.
Speaker 1: Just for everyone's benefit. Python is a popular computing language
Speaker 1: which actually has a lot of free resources for anyone
Speaker 1: to look up and be able to code their own
Speaker 1: AI machine learning programs. So, Habi, do you know if
Speaker 1: this program is trying to be replicated in other community colleges.
Speaker 2: That's actually at the heart of AI for Workforce. So
Speaker 2: I'm the lead faculty at Chandler Gilbert, but I played
Speaker 2: a role in helping advise AI for Workforce and now
Speaker 2: they're their own separate entity. So what we had at
Speaker 2: our campus last week was a summit hosted are at
Speaker 2: Channel Gilbert campus called the AI Teaching and Learning Summit,
Speaker 2: So we had one hundred different folk faculty and administrators
Speaker 2: from across the country and even Canada come to our
Speaker 2: campus and try and learn about building their own AI
Speaker 2: programs within their institutions. Well, one of the leaders of
Speaker 2: AI for Workforce came and talked about I think they've
Speaker 2: reached somewhere between thirty two to forty eight community colleges
Speaker 2: in the country. They've almost hit every single state in
Speaker 2: terms of a community college within the state. So they
Speaker 2: have that many community colleges that have at least taken
Speaker 2: the INTEL training that they have available now, which is
Speaker 2: available for free, to build programs within their own college.
Speaker 2: In terms of who I see that has full fledged programs,
Speaker 2: think there's only like four or five colleges that I'm
Speaker 2: aware of in the country that have an associates or
Speaker 2: a certificate in AI at a community college level.
Speaker 1: We'll be right back after a quick break. Welcome back
Speaker 1: to Technically Speaking, an Intel podcast. I'd like to get
Speaker 1: your thoughts on any data or trends in the job
Speaker 1: market around the significance of learning about AI, and is
Speaker 1: that demand still there and do you see that growing
Speaker 1: and in which areas and which industries do you see
Speaker 1: the best potential for your students going through that program.
Speaker 2: It's a hard marker to pin on right now because
Speaker 2: it's such an emerging field. There's different routes you could
Speaker 2: see AI, this large field of AI going right now.
Speaker 2: So I'll start from the most beginner level. You have
Speaker 2: people who are like prompt engineers who use something like
Speaker 2: chat GPT, these very industry wide models and are able
Speaker 2: to interface with that system such that they get autonomous outputs,
Speaker 2: automatic outputs that increase productivity and reduce the amount of
Speaker 2: work that someone would need to do. Right That prompt
Speaker 2: engineer is a great field for someone who's entry into
Speaker 2: the AI space. Right It doesn't need nearly as much
Speaker 2: math or programming even and there's actually a lot of
Speaker 2: drag and drop interface to perform AI modeling platforms where
Speaker 2: you can kind of input data, drag and drop what
Speaker 2: you need and then get some meaningful output. I can't
Speaker 2: say that I target that too much right now because
Speaker 2: there's not a lot of stability there just yet. Chat
Speaker 2: GPT is still relatively new, no code tools, it's very specified,
Speaker 2: So I focus more on level two. I would say,
Speaker 2: you can hear my video games speak come out. Level
Speaker 2: two is they have some coding. They're like a software developer,
Speaker 2: but more equipped to tackle problems that could evolve automation
Speaker 2: of let's say text and images, have some of the
Speaker 2: data analytics background as well to analyze and process data,
Speaker 2: come up with systems that automatically process that data and
Speaker 2: give meaningful output. So they have to have a little
Speaker 2: bit of math to understand how that data is being
Speaker 2: inputed and what the story is behind the data is
Speaker 2: what I typically say. And then they have to have
Speaker 2: some programming, because if you stick with only no code tools,
Speaker 2: you're very limited to what those no code tools can offer.
Speaker 2: With programming, it opens the doors. So that's level two
Speaker 2: and that's where I try and keep my students. These
Speaker 2: concepts in AI can get very sticky mathematically very quickly,
Speaker 2: and I can't expect a two year student to be
Speaker 2: at that level of foundation. So then level three is
Speaker 2: that they have a very solid mathematical foundation to where
Speaker 2: pretty much any AI algorithm I throw at them they
Speaker 2: can at least orient themselves to quite quickly. Someone with
Speaker 2: a master's background or a bachelor's background can do this, right.
Speaker 2: You come into a new class and it's like, oh,
Speaker 2: that's just the formula I've seen before kind of but
Speaker 2: just in a different way.
Speaker 1: Ye gotcha.
Speaker 2: And then the programming expertise of let's say, Okay, we're
Speaker 2: not going to do this in Python, now we're going
Speaker 2: to do this in R. They know so many programming
Speaker 2: languages at that point that they can kind of easily
Speaker 2: switch between the two for a quick prototype. So I
Speaker 2: see that as level three three, So right now, I
Speaker 2: target that level too.
Speaker 1: Okay, just previously, you talked a little bit about some
Speaker 1: of the student projects that can be quite exciting for
Speaker 1: both the teachers and the students, a like, is there
Speaker 1: just one that is top of your brain right now
Speaker 1: that is quite exciting that you're working on with your students.
Speaker 2: So the one I do is I have them create
Speaker 2: an automatic bubble sheet scanner. So they take a photo
Speaker 2: with their phone and they should be able to grade
Speaker 2: a bubble sheet just based off of a photo. So
Speaker 2: I teach them all about things like how to detect
Speaker 2: the bubbles on a sheet, how to know which position
Speaker 2: is where on the sheet. It doesn't automatically tell you
Speaker 2: where it is, so you have to do that and
Speaker 2: then sort them in a list that the top left
Speaker 2: is zero and then go on from there all the
Speaker 2: way down. Gotcha, And then to know whether or not
Speaker 2: it's filled. So that's about an eight week process, not
Speaker 2: that one project, but what leads up to that project.
Speaker 2: So then let's jump into I guess the capstone projects
Speaker 2: where my students are out in the wild West, right.
Speaker 2: I have students who do stock market prediction brain tumor
Speaker 2: detection based off of MRI or CT scans. One of
Speaker 2: my students is a musician, so he likes to handwrite
Speaker 2: his musical notes and he wants to be able to
Speaker 2: take a picture and have it be electronically printed. I've
Speaker 2: had a student who won actually an Intel competition taking
Speaker 2: brain wave EEG data and trying to detect if there
Speaker 2: is an epileptic seizure occurring within that data. I think
Speaker 2: what I find is is that I'm always amazed that
Speaker 2: I give them these little seedlings of knowledge and then
Speaker 2: that capstone project comes around and they just grow without
Speaker 2: me even being there.
Speaker 1: Yeah, Habib, you mentioned a lot of people need graduate
Speaker 1: level degrees to work in AI. Right now, what path
Speaker 1: have you seen your students go through after these courses?
Speaker 1: Have they said it's opened any doors for them?
Speaker 2: So one of the big challenges we're trying to tackle
Speaker 2: on the community college AI education side is pathways for
Speaker 2: students upon graduation. Right it's pretty bleak in terms of
Speaker 2: having a two year degree and meeting minimum jow brecks.
Speaker 2: Our college actually is beginning to offer or developing a
Speaker 2: bachelor's degree in AI to alleviate that issue. But I'm
Speaker 2: seeing that they're still finding positions because of how marketable
Speaker 2: AI skills are. Right now, it may not be, you know,
Speaker 2: an engineer, but it could be, Hey, here's an entry
Speaker 2: level role at a company, but it's easier for them
Speaker 2: to get through the door because they have these marketable skills.
Speaker 1: And in your view, how do you see the future
Speaker 1: of AI in the workplace And what's your number one
Speaker 1: reason that you tell the younger generation and students why
Speaker 1: AI tools are so important to learn.
Speaker 2: You know, when AI was first emerging, let's say chat
Speaker 2: GPT right into popularity, everyone was like, AI is going
Speaker 2: to replace jobs, and actually there's been a new keynote
Speaker 2: I guess that people have been saying, which is people
Speaker 2: who have AI skills will be better equipped than those without.
Speaker 2: I completely agree on that note, because we work so
Speaker 2: much with technology. If we're better to interface with that technology,
Speaker 2: we're going to be that much more productive. We can
Speaker 2: tackle much more complex problems in a shorter amount of time,
Speaker 2: and so I see the future workforce being able to
Speaker 2: be once again more productive utilizing these tools. I mean
Speaker 2: when you're typing an email and gmails like hey, here's
Speaker 2: the rest of that sentence. Yeah right, it's just so
Speaker 2: convenient and it helps ease the amount of hand to
Speaker 2: paper work we have to do. And we can now
Speaker 2: be more creative with that time and solve more nuanced,
Speaker 2: more complex problems because we have these systems better ready
Speaker 2: to assist us. So someone like me and you can
Speaker 2: do a lot more with this lifespan that we have.
Speaker 2: We can develop, create ID eight more things because we
Speaker 2: have more time to do so.
Speaker 1: The way Habib looks at AI as a tool in
Speaker 1: assisting the workflow reminds me of the invention of the spreadsheet.
Speaker 1: My grandfather worked at the bank for forty years in
Speaker 1: the same desk, the same chair, pouring over bank ledges
Speaker 1: with paper and pencil, ensuring all figures balanced exactly to
Speaker 1: the scent. With the invention of computerized adding machines and
Speaker 1: then later spreadsheets on personal computers, there's laborious efforts that
Speaker 1: my grandfather previously undertook had now become so quick and accurate.
Speaker 1: He retired before the advent of these technologies, but I
Speaker 1: often think how helpful those tools would have been for him.
Speaker 1: AI in the workplace empowers everyone to focus on what
Speaker 1: they do best. Learning these AI tools, like learning how
Speaker 1: to use a spreadsheet, gives employees an added edge in
Speaker 1: how they work as individuals and within their teams. I'd
Speaker 1: just like to get your thoughts about the AI tools
Speaker 1: for the non engineers and non tech people.
Speaker 2: Well, I think I've been giving this rose colored glasses
Speaker 2: look onto AI right where AI is always beneficial and
Speaker 2: always used in the right way. But we know that's
Speaker 2: not the case. I think that it's important to know
Speaker 2: what algorithms and what AI can do because our number
Speaker 2: one interface with AI every day is things like the
Speaker 2: Internet and social media. And so I have students who
Speaker 2: may be dealing with some kind of addictive behavior and
Speaker 2: they don't realize that AI recommendation systems that are used
Speaker 2: in sol social media are constantly feeding them content that
Speaker 2: may make them feel stuck in that frame of mind
Speaker 2: and that addictive cycle. And so I think it's important
Speaker 2: for the general public to know what AI thinked imagery
Speaker 2: looks like, what algorithms are out there, and how they
Speaker 2: use your preferences to feed you more content that you like,
Speaker 2: just for our own mental wellbeing. So I see my
Speaker 2: class AA in one hundred as a place where people
Speaker 2: can come and learn about these technologies so that they're
Speaker 2: better equipped to personally manage their interface with them right
Speaker 2: mentally manage it.
Speaker 1: Yeah, and are there any ethical considerations you try and
Speaker 1: emphasize when teaching your course to your students.
Speaker 2: So I try to give my students a broad overview
Speaker 2: of AI ethics, because again, you could dig into one
Speaker 2: quite a bit and there's still a ton of content
Speaker 2: left there. So I started talking about, like what topics
Speaker 2: there are in AI ethics. There's privacy and surveillance, there's
Speaker 2: manipulation of behavior, there's jobs and autonomy. So those are
Speaker 2: all like separate topics that I go over. Then I
Speaker 2: can take a step further and I talk about frameworks.
Speaker 2: So what frameworks are out there in terms of AI ethics,
Speaker 2: Like the European AI Act came out and they have
Speaker 2: a framework for how they want to regulate this technology.
Speaker 2: Now we're seeing policy on the America side on AI.
Speaker 2: My last little tidbit in the AI ethics realm is
Speaker 2: trying to dispel some of the fear. I am personally
Speaker 2: of the belief that there's not some looming AI monster
Speaker 2: coming to eat us, and if there would be, we
Speaker 2: would see the development of it, Like we've seen the
Speaker 2: development of this technology all along chat GPT wasn't grown
Speaker 2: in a lab and everyone was like, oh, I've never
Speaker 2: seen this before. We had GPT one, GPT two, GPT three. Yes,
Speaker 2: we saw the progress of that technology.
Speaker 1: Yeah, and I generally agree with that that there's going
Speaker 1: to be a net positive to the AI growth that
Speaker 1: we're seeing. But I think it's incumbent upon people like
Speaker 1: you to actually teach and guide students around at least
Speaker 1: understanding some of that, as you said, the ethical frameworks
Speaker 1: around it, because they're the ones that are going to
Speaker 1: be producing these things. Right. So I have three kids,
Speaker 1: two of them are now in high school. What advice
Speaker 1: would you give to parents and educators who are looking
Speaker 1: to introduce AI and STAM related concepts to children at
Speaker 1: an early age.
Speaker 2: Man, that's a great question. I've never been asked that.
Speaker 2: I've done so many interviews that I've never announced that.
Speaker 2: What advice would I give them? You know, I'm a
Speaker 2: family oriented person, right, I'm twenty six. I'm hoping to
Speaker 2: have a family someday, So I kind of think about
Speaker 2: this a lot. One thing I find my classroom is
Speaker 2: is if you make it fun, the students get involved
Speaker 2: and they get interested. Right. It's like if you have
Speaker 2: dessert after your salad. Right, people are just more willing
Speaker 2: to eat the salad so that they can have that
Speaker 2: dessert and feel okay about it. So, getting your kids
Speaker 2: involved in things like Legos Mindstorm, which is a subsect
Speaker 2: like a robotic subsect of Legos, even like video games
Speaker 2: that are less so dopamine addiction for them and more
Speaker 2: so building and creating things using their intelligence in their mind.
Speaker 2: I think making the space more fun for them to access,
Speaker 2: and then on top of that, making it social, having
Speaker 2: them find a friend group where they can relate to
Speaker 2: other people about these kinds of things. I think loneliness
Speaker 2: epidemic is pretty bad in today's world, and there's ways
Speaker 2: you can alleviate that early on in their lives by
Speaker 2: getting them involved in a community of other kids who
Speaker 2: are open to doing those kinds of things.
Speaker 1: Yeah, what do you envision as the future of AI
Speaker 1: and education And what's the number one thing that excites
Speaker 1: you most about the role of AI in shaping the
Speaker 1: learning experiences?
Speaker 2: I think the way we're interfacing what technology is changing
Speaker 2: and being spurred on by AI, that's what we've named this,
Speaker 2: and so I'm really excited for the shift that will
Speaker 2: come in how we interface with technology. On the education side, right,
Speaker 2: we teach people how to use technology, So now we're
Speaker 2: going to teach them how to better their use of
Speaker 2: technology by including AI education. So I'm really excited that
Speaker 2: this new workforce that's coming will be better equipped again
Speaker 2: to tackle more complex problems, and who knows, maybe some
Speaker 2: of the problems that we've been trying to tackle for
Speaker 2: so long will seem simplistic in the next twenty to
Speaker 2: thirty years, and I'm really excited for or this emergence
Speaker 2: of that, and I hope that we use it in
Speaker 2: the right way to better society.
Speaker 1: Awesome. Thanks very much, Havib, Well.
Speaker 2: Thank you. I appreciate your time. It's been fun.
Speaker 1: Thanks to Habib Mata for joining me on this episode
Speaker 1: of Technically Speaking, an Intel podcast. Chatting with Habib was
Speaker 1: really an eye opener. Being a dad of three, I'm
Speaker 1: always on the hunt for ways to help my kids
Speaker 1: flourish in their future careers. What grabs me about the
Speaker 1: course that Intel and Habib created is that it's not
Speaker 1: just your run of the mill four year degree. It's
Speaker 1: like they threw open the doors for people from all
Speaker 1: walks of life, no matter where they are in their career,
Speaker 1: to jump in and really get their hands dirty in
Speaker 1: the emerging fields of AI and STEM. The way Habib
Speaker 1: gets his students fired up is pretty cool. He dives
Speaker 1: into real world applications right from the get go, sparking
Speaker 1: that curiosity bug in his students. This style gets them
Speaker 1: hooked early on, and then they dig deeper into the
Speaker 1: nitty gritty theory behind those AI projects. It's a far
Speaker 1: cry for my old engineering days. It's all about slogging
Speaker 1: through thick theory books before getting onto the hands on
Speaker 1: fun projects. And now, with the solid backing from Intel
Speaker 1: and Habib's relentless effort, this program is rolling out to
Speaker 1: more campuses across the US, and who knows, soon it
Speaker 1: might be a movement that spans the world. That's something
Speaker 1: to be excited about, not just for my kids, but
Speaker 1: for anyone ready to ride the AI and STEM wave.
Speaker 1: Thank you all for listening. Join us again in two
Speaker 1: weeks in December twenty sixth for the season finale of
Speaker 1: Technically Speaking, an Intel podcast. There's been a real journey
Speaker 1: learning about all these new technologies, and our final episode
Speaker 1: will explore the challenges it takes to make them all possible.
Speaker 1: You definitely do not want to miss its. Technically Speaking
Speaker 1: was produced by Ruby Studios from IHET Radio in partnership
Speaker 1: with Intel and hosted by me Graham Class. Our executive
Speaker 1: producer is Molly Sosha, our EP of Post Production is
Speaker 1: James Foster, and our Supervising producer is Nikir Swinton. This
Speaker 1: episode was edited by Sierra Spreen and written and produced
Speaker 1: by Tyree Rush,