The Upside: POV: Emerging Technologies in Action

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Subtitles are AI-Generated.

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Hello everyone, and welcome to The Upside.

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I'm Kyle Cheropita. The world of emerging technologies is vast

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and exciting. Emerging tech is characterized by rapid change,

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significant disruption, and unlimited potential.

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Self-driving vehicles, artificial intelligence with decision-making abilities,

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and smart homes that learn your habits and predict your needs, are just a few

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recent examples. We've also seen significant advancements in medical

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technologies. But for every good news story there are also considerations

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around privacy, regulation, and the brisk speed of tech advancements.

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Joining me today to share what he is seeing first-hand is John Bradley,

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Director of Emerging Technologies here at Fidelity.

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John spends his time staying a step ahead of what's next, attends many

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conferences, and brings those insights back.

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I'm very happy to have John in the studio with me today.

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Welcome, John.

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Thanks for having me.

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Really happy to you here. We're talking emerging tech today but to be clear to

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everyone out there, you're not an AI generation, we're not in the metaverse,

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if that's even still a thing, and you're not a hologram.

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You're here with me live in real life.

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Absolutely.

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I appreciate it. As I mentioned in the intro, you are travelling a lot and you

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started the year going to the Consumer Electronics Show in Vegas.

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You escaped the cold and snow that we're stuck with here again.

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Perhaps you can tell me a little bit about what is CES and

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what were some of the key themes you saw there?

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Just at a very high level the Consumer Electronics Show is one of the biggest

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technology conferences in the world.

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I think this year there was around 140,000 participants which is

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three times more than my lovely hometown of Chatham, Ontario.

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Shout out to Chatham.

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At CES, that's where a lot of the major tech vendors release their product

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lineup for the year so there's a lot of big announcements from household

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names like Google, Sony, Panasonic.

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Just about everybody is there.

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I'd love to dive a little bit deeper into some of the key themes that you saw

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there but first, you travel there, a recent trip to Africa as

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well, you travel a lot. It must get pretty tiring having to book all these

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trips and plan. Do it all yourself?

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No, I actually had some help from AI so...

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Of course you did, tell me about that.

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Part of the emerging tech team, what we did is we put together a multi-agentic

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system so we used AI agents to help plan all these conference

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visits and attendance.

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We have an AI agent that specializes in coordinating things like

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flights, hotels, restaurants, cool things to see,

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piles that all back together into an itinerary,

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an agenda, and then based on that we kind of plan the rest of our schedule.

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We had some help from AI but there was also some human overlay on that as well.

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That's really interesting. Now, do you like, I don't know, to tell the

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agent, I'm heading there on this day, tell me what to do?

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What's the process like there?

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It's actually much more straightforward than that and simple.

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Essentially, what we do is we put in the conference that we want to go to and

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we put it where we're leaving from and then the AI agents take care of

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everything else.

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It's that simple.

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It's that simple. The full itinerary is kind of then given

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to us and then we will make adjustments. At that point it's more minor

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adjustments so it takes care of all the heavy lifting.

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When we get it we're just making fine kind of

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tuning to the overall plan to whatever suits our

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travel schedule.

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That's very interesting. I'm curious if others are using this as well

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and then what would happen when, say, 500 people show up at that best

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steakhouse in Vegas because that's what their agents look for all of them.

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I'm sure people are using AI to some degree to help manage their travel.

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It's one of those things that it's super helpful for.

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I don't know if they have a multi-agentic system like we do at Fidelity but

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it's possible. To your point about everybody showing up at the same spot,

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there's always that risk because AI will go out and

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search the internet and these popular websites that have information

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about hotels and restaurants so there's a chance that he different

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AI versions of this travel planner are all referencing the same site so

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everybody's going to show up to the same spot.

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You can adjust for that but it's a possibility.

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That's really interesting.

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Now, I'm curious, you mentioned this before we started recording here,

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that now you're also getting the agents who start to talk to each other.

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Is the next step of this that your conference planning agent will then

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even connect with the steakhouse and the restaurant's agent and complete the

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reservation?

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That's what they're talking about kind of future potential of these AI agents.

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They have an ability to kind of work together in a team like you would at

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wherever your job or you would work together with your friends to plan a

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trip. That's the next iteration.

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Right now it's kind of doing the planning but it stops short of actually

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booking the flight or booking the reservation.

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You can easily see that being the next step, just to remove that level of

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friction between, say, a restaurant or a hotel and the

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people that are trying to book their services.

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Let's expand on that a bit, take it away from just the conferences.

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What are some other examples in the world right now of where multiple agents

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might be talking to each other to accomplish something?

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You could see something like creating various types of content.

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There could be agents specific to going out and doing the preliminary

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research and then creating a draft of something and then having a different

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agent review that to make sure it's compliant with whatever the message or

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the organization is trying to convey.

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There could be another agent that's doing the legal or regulatory review.

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You could kind of piece these agents together much like you would have an

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internal team. If you think about the various teams across different

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organizations you could have agents set up to replicate some

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of those workflows and those different interactions.

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The possibilities are almost endless.

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Continuing on that topic of sort of the chat bots and the agents, a term

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that is being passed around a lot more lately is vibe coding.

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Hoping you could define that for our audience and explain a bit about what that

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is.

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At a very kind of high level what vibe coding really is is leveraging

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AI to do a lot of the heavy lifting for you when you're doing some type of

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development or coding task.

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Previously somebody would have to write all of these things, write all of the

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code themselves. Now this vibe coding, what you can do is much like you

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interact with, say, Chat GPT or Microsoft Copilot you can tell these tools,

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hey, this is what I'm looking to create and it'll go off and do the majority of

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the work for you. It's more you get into this kind of groove or you get into a

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vibe where you're interacting with this AI development tool and that AI

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development tool then creates the app or the process or the product that you're

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looking for. It's not a perfect solution.

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You definitely want to have people check that over.

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Your development team should check that just to make sure everything is safe

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and compliant but that's essentially what vibe coding is at a high level.

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Interesting. Now, I don't have much experience with the coding side of things

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but using those chat bots to do research and other other things.

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I know historically the problem of hallucinations have been big.

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Is that something that's still happening with the coding side of it as well?

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It definitely is. That isn't going to go anywhere regardless of what kind of

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generative AI tool that you're using.

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Because it's AI there is a possibility that there's going to be errors or

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incorrect information provided.

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You always want to check the output, whether you're using Chat GPT, Copilot,

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or one of these kind of new vibe coding tools.

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That's always going to be present.

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There are certain things that you can do to mitigate that kind of error rate

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but it doesn't fully go away.

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What have you seen? This has been new, relatively new,

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but it's been around for a few years now.

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What improvements have you seen over the past few years?

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What I'm kind of drawing from this question is I've heard some of our PMs and

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analysts say the current version of AI that you're using is the worst version

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that it will ever be because it's always improving.

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Anything to say on that?

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There's going to be a few things that will help improve the quality of the

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output. The more data that these tools have access to

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the better the responses are going to be, the higher the quality, the more

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accurate they're likely to be.

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The previous tools that we would have been using a couple of years ago,

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they had a smaller data set.

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Some of them would have frozen from a particular time period and looking

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backwards. Now these new tools are generally looking

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at kind of more current events, they're able to search the internet to get

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up-to-date information so there's higher likelihood that the information is

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going to be more accurate.

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In addition to that, when we're building out these multi-agent systems what we

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can actually do is we can set up an agent to fact check the

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kind of initial output. Like I was saying, in content generation, for an

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example, if there's an agent that's going to go search the internet to put

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together an article we might be looking to publish we then have an agent to

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make sure that information is correct.

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Again, you have AI checking AI.

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There's still probability that some of that information could be incorrect

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but the more checks and balances that you incorporate into that overall

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pipeline the higher the likelihood that you're going to get an accurate

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and complete answer.

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The point there about the frozen in time is interesting because I've found

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... maybe it's because I'm seeing some free versions of this but I'll always

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start by asking what date is it today?

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I've had it in the past where it is frozen in a prior part of time

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and it'll tell me the current prime minister is Trudeau or the current

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president is Biden.

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Then it's a clear indication like, okay, it's not pulling relevant current

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data.

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Absolutely. That was historically when Chat GPT first hit the scene it

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was current up to I think 2020 or something around that time period

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even though we were sitting in 2023, 2024.

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If you're asking in a historical example about who won the World Series in 1920

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it was going to give you that answer correctly 99% of the time.

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But if you're asking about a current event that happened last week there's a

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high likelihood it was going to be incorrect.

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Now these new tools are searching the internet, incorporating new data all the

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time so there's still, again, an opportunity that they're going to be

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incorrect but that kind of margin of error is going down.

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With the different agents who are talking to each other, fact-checking each

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other. Also something that's been rising lately is that stitching.

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It's not just an agent finding a piece of data from one place and presenting it

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to you but pulling that data from numerous spots, customizing

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it and then presenting.

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Exactly. That's something where we're talking about those multiple agents

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again, behind the scenes there's a potential that these

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kind of major enterprise-wide

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tools or public facing tools that actually have

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multi-agent systems. They have an agent, say, dedicated to Reddit, they have an

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agent dedicated to LinkedIn, just as an example.

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They're specialized in these various data sources and then they all bring their

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information back and then there's, say, a project manager agent that

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synthesizes it all together and delivers it in a format that is going to

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be relevant to you. A lot of that is happening behind the scenes.

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Very cool. A lot of new stuff happening. With that stitching example I'll just

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pull this ... this is for our audience as well ...

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Louis Têtu, who is the Executive Chairman of Coveo, joined our Fidelity

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Connects program  last month. He did both an English and a French interview,

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they were fantastic. Check them out on YouTube.

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He was talking a lot about the advancements with the AI agents and the

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stitching.

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It's really cool. Absolutely.

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We talked a lot about the AI agents, let's pivot back to CES a little bit.

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Wearables was a big takeaway from that conference.

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Love to get your thoughts on wearables.

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Wearables is something really interesting because it seems to have.

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been a big thing.

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They had Google glasses and those kind of went away.

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Now it seems like the whole wearables in smart glasses has come back with

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full force. You have Meta that's really promoting their kind of new Meta

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glasses and you have other competitors in the space.

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That was a big topic that was talked about at CES.

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If you were to listen to those companies they're suggesting that these wearable

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glasses might be the next iteration of smartphones.

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Whereas a lot of us are walking around today looking down at our phones and

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bumping into things, the kind of promise of these smart glasses is

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that you can have all of this information surface to you while you're walking

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around, while you're talking to people, so you don't necessarily lose that

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connection with your environment and what's going on around you.

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It's a more integrated technology experience.

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That was a big discussion at CES.

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Wow. Is that strictly at this point talking about glasses or does it get into,

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say, watches and, I don't know, VR headsets?

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Is that all still connected?

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Glasses seem to be the big push right now just because that's how you can

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surface information but you could easily envision a world where all of

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these things are integrated into kind of a seamless ecosystem where you have

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your smart glasses on that are surfacing your texts and news and other things

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but they're also surfacing alerts from your smart watch that's monitoring

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your heart rate maybe in a stressful situation, or while you're exercising, say

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you're going for a jog and it's telling you to go left and here's how

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the next portion of your run, all these other things.

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You could easily envision a world where they're all tied together.

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Very interesting. There's a medical angle. Anything more to say on sort of

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those advancements and the link back to the medical field with wearables?

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There seems to be a big promise just because the cost of these different types

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of medical sensors is going down so they seem to be integrated into more and

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more things, consumer products.

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For example, you buy a smart watch now and it can tell you everything

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about your heart rate, how you're walking, how your sleep score is.

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I would imagine that as the technology advances

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those types of sensors are going to being included in more things and then that

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could potentially have predictive power for identifying if

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you're maybe at an early stage for various types of medical

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conditions or if you need to kind of be proactive about certain things related

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to your health.

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There's definitely opportunity there.

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I'm thinking with wearables though, there's this overarching theme with tech

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that the tech advancements are happening faster than regulation can keep up.

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From a privacy perspective, I don't know, what's it going to be like in a few

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years if everybody's walking around with little mini computers on their face.

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It's an interesting question. If you think about even from a work perspective

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I'm sure most of our employers aren't going to want us walking around looking

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at sensitive documents or having conversations with clients and all of it being

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recorded. It represents an interesting problem that I think both has to be

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addressed from the regulators from a privacy perspective, you know, walking

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around, what are our rights in terms of this new technology?

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Do we have the right to say I don't want you to record or I don't want this in

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certain sensitive areas?

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From an employer's perspective how are you going to take advantage of this

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technology effectively while not putting ourselves in potential

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risk situations. I think it's an evolving landscape.

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Technology generally moves much faster than regulators but there is some

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nuance there and there's going to have to be some consideration from companies

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about how much further out

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in front do they want to be than the regulators. Do they want to be at the

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bleeding edge and adopt this technology immediately or do they want to kind of

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wait around to see how the regulatory landscape kind of

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shapes up before they start to adopt this type of technology?

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Interesting. It's always a balance and I guess the company is deciding

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how much they want to play by the rules or not.

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And how much risk they want to expose themselves to in terms of,

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you know, there's advantage to being a first mover but there's also the

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uncertainty that comes with that. It's a delicate balance and individuals

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and corporations have to make that judgement call for themselves.

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Maybe to make things a little bit positive as we ramp up towards the end of our

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chat here, at CES, I was also reading one of the big key themes of the

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conference was green products and sustainable products.

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What did you see there?

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There's a lot of interesting things.

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The sustainable products ranged all the way from new

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types of screens and laptops and TVs that are much more energy efficient

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so that helps reduce the load on

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our various kind of power plants and other things which can be a positive, all

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the way to the opposite end of the spectrum where using

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AI to kind of manage the energy

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load within your house, being able to understand kind of

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what the general patterns are when you use your stove, when you're using your

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laundry, and routing the power appropriately to those

16:34.193 --> 16:38.130
major appliances in order to kind of both

16:38.130 --> 16:39.965
save energy and save money.

16:39.965 --> 16:43.002
This smart home was something that was talked about a lot in the opportunities

16:43.002 --> 16:47.106
for kind of sustainable tech. That was a big component there as

16:47.106 --> 16:47.606
well.

16:47.606 --> 16:51.377
I mentioned the smart homes off the top as well.

16:51.377 --> 16:54.813
I still think it's pretty cool that I can tell Alexa to turn on a lamp.

16:54.813 --> 16:59.451
We call him Cornelius because he lives in the corner, but

16:59.451 --> 17:01.320
it's so much more than that these days.

17:01.320 --> 17:03.155
What else are you seeing in smart homes?

17:03.155 --> 17:07.493
I have a Google Nest at my house, actually, it's able to

17:07.493 --> 17:10.796
understand our patterns. We like to turn the heat down when we go to bed but

17:10.796 --> 17:14.466
turn it on when we wake up. It's been able to recognize those patterns

17:14.466 --> 17:17.569
throughout the four different seasons that we have.

17:17.569 --> 17:21.140
It'll make recommendations. It's like, hey, do you want to save an extra $10 a

17:21.140 --> 17:25.244
month on your heating and cooling bill, we suggest doing this.

17:25.244 --> 17:28.547
It'll establish those patterns. That's something that's really cool.

17:28.547 --> 17:32.785
Again, certain types of appliances have intelligence to them that they'll only

17:32.785 --> 17:37.389
turn on at certain times of day or certain scenarios

17:37.389 --> 17:40.159
just to reduce the overall kind of energy consumption from the house.

17:40.159 --> 17:41.860
So that's, I think, pretty neat.

17:41.860 --> 17:45.064
Now, are we at the point where all the routines get linked, where you leave to

17:45.064 --> 17:49.201
go to work and the car has already started and then the temperature

17:49.201 --> 17:52.671
of the house is already going down because it knows your pattern so well.

17:52.671 --> 17:56.708
Absolutely. Right now, for example, my car had the ability to kind

17:56.708 --> 17:59.478
of set those patterns. The house would also set those patterns.

17:59.478 --> 18:02.881
When it detected that I had walked far enough away from the house it would go

18:02.881 --> 18:06.018
into away mode and when I got close enough it would turn back on.

18:06.018 --> 18:10.055
Now, right now those things are kind of happening independently but

18:10.055 --> 18:12.324
you can easily see a world where everything talks to each other.

18:12.324 --> 18:14.893
That's kind of the Internet of things that people talk about.

18:14.893 --> 18:19.031
That's really a game changer if we're talking about efficiency and

18:19.031 --> 18:23.302
sustainability, if all of your appliances and the major things that you

18:23.302 --> 18:26.772
interact with on a daily basis can talk to each other then you can get real

18:26.772 --> 18:31.343
efficiencies in terms of energy consumption and just helping

18:31.343 --> 18:32.544
you manage your day.

18:32.544 --> 18:35.714
Wow. Well, we'll have to have you back again to learn more about this.

18:35.714 --> 18:36.715
Yeah, I'd love to be back.

18:36.715 --> 18:40.252
When is the next trip, or where is the next trip to?

18:40.252 --> 18:42.721
Next trip is going to be right around the corner.

18:42.721 --> 18:45.924
We're heading to Silicon Valley to talk to some of the major tech vendors out

18:45.924 --> 18:49.928
there, understand kind of what's top of mind for them and how we can utilize

18:49.928 --> 18:53.966
that technology to help improve the lives of our Fidelity clients as well

18:53.966 --> 18:55.234
as our internal stakeholders.

18:55.234 --> 18:58.570
Nice. And are you doing that trip with your emerging tech team or do you

18:58.570 --> 19:01.273
overlap with any of the portfolio managers and analysts when they do their

19:01.273 --> 19:02.241
trips?

19:02.241 --> 19:05.043
We're going to do that with ... we have an internal innovation committee,

19:05.043 --> 19:09.114
specializing on the latest and greatest and how do we bring that

19:09.114 --> 19:11.717
back into Fidelity Canada more broadly speaking.

19:11.750 --> 19:15.787
Once we've identified those trends the emerging tech team takes it over

19:15.787 --> 19:19.124
and really makes it tangible for our stakeholders.

19:19.124 --> 19:20.993
John, thank you so much for joining me today.

19:20.993 --> 19:25.230
I want to wrap up by quoting a chat bot who is writing an AI slop post

19:25.230 --> 19:28.500
for LinkedIn and say, I thought this conversation today was going to be good

19:28.500 --> 19:31.470
but I was wrong, it was great.

19:31.470 --> 19:32.938
I'm glad you feel that way.

19:32.938 --> 19:35.474
Thank you so much for joining me today.

19:35.474 --> 19:37.609
Thank you all for watching today as well.

19:37.609 --> 19:41.046
Here at Fidelity Canada we're releasing new content daily so please look up The

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To not miss a show head to fidelity.ca and sign up for the next webcast or

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The Upside newsletter. Thanks for watching today and I hope you'll join us

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again. I'm Kyle Cheropita.

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We'll wrap things up today with a quick disclaimer.

20:52.517 --> 20:56.255
The views and opinions expressed on this podcast are those of the participants

20:56.255 --> 21:00.325
and do not necessarily reflect those of Fidelity Investments Canada ULC or its

21:00.325 --> 21:04.329
affiliates. This podcast is for informational purposes only and should not

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21:07.232 --> 21:10.736
It is not an offer to sell or buy or an endorsement, recommendation or

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sponsorship of any entity or security cited.

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Read a fund's prospectus before investing. Funds are not guaranteed.

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Fees, expenses and commissions are all associated with fund investments.

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Thanks for tuning in. We'll see you next time.