computer science

Welcome aboard this episode of the Tech Roundup, where we're taking a flight into the future of artificial intelligence.

Today we'll dive into OpenAI's recent groundbreaking discoveries in mathematics, computer science, and physics.

Buckle up as we navigate through these exciting developments.

OpenAI has just released jaw-dropping discoveries that are sending ripples through the worlds of mathematics, computer science, and physics.

Just a few weeks after unveiling over 700 pages of solutions for 372 major math problems, the company announced they've engaged an external group of experts to help explain their findings.

It's like having a co-pilot who's an ace mathematician, computer scientist and physicist all rolled into one.

So sticking with just the basic four from a practical point of view, if you want to go into the lab and do experiments, is definitely the advantage.

There's another advantage that I think is the primary reason I like sticking with just the four is it's sort of like, well, you know, back in the nineties to two thousands, there was a, uh, big fight in the computer industry between risk architectures and CISC architectures, the reduced instruction set versus the complex instruction set, you know, which way are you going to do things to make the computers faster and cheaper? And, um, I've always found the risk architectures on the computer science side much more elegant.

You have a small number of building blocks.

You figure out the tricks that you can play the game in a uniform way rather than lots of idiosyncratic things.

But you're really thinking, you're sort of abstracting away to the input-output relationship in some way.

Yeah.

I would even say input-output is a particular kind of behavior, and computer science doesn't steady just input-output functions.

That's a building block for computations.

I mean, Waymo, the first eight years, it was hard to do, easy to do, and then the last 20 years, it took a decade.

Distributed systems being one of the areas in which computer science, where it's very hard for the models to get it right.

How do you expect your own version to look different in two years from

now? So I think AI timelines are moving extremely fast in ways where it's very hard to predict something one year from now.

Let's take that after the class.

Okay.

I think the computer science profession is not going anywhere.

And if you are able to reason for fundamentals, that is very

I did pursue formal education and trying to decide what.

It was a cross between computer science at the time, so this would have been the late 70s, linguistics, because I was very interested in languages.

and also voice because I used to do a lot of more classical singing at the time.

And I chose the one that I thought would be the future and revenue generating so that I didn't have to wash dishes and I never had to, you know, just at home.

You chose computing pragmatically.

as a continuation of your mother's path, I would say, inspired.

And even though mathematics was not necessarily effortless for you, you made perseverance an early strength, which then sort of segues into later with your EMBA where you may have these challenges and again the resilience adaptability persistence perseverance hard work and you have to maintain some kind of optimism to say you know i can find i can do anything right and then You end up then earning a B, a Bachelor of Science in Computer Science from the University of Alberta, which is a very good school.

You went to Ottawa to Quasar Systems, later Cognizant and IBM.

I remember growing up and seeing, you know, I grew up in the 80s as well, unemployment, you know, could be like 6% or more, right? So, you know, we're dealing with historically low unemployment levels as compared to probably what we saw back in the day.

But this is not the full story, right? If you look at underemployment, for example, 42% of recent graduates are underemployed, working at jobs that don't typically require the degree that they worked for, right? And so, Computer engineering grads are at 7.8% unemployment and CS grads are at 7%.

So again, this is higher than nearly every other major right now.

I'm just going to have some stats here.