Meta Has Its Muse
In this episode of Motley Fool Hidden Gems Investing, Motley Fool contributors Travis Hoium, Lou Whiteman, and Rachel Warren discuss:
- Meta Muse.
- Meta's data problem.
- Consumer AI.
- Adoption timelines.
- AlphaGenome.
- AI in health.
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A full transcript is below.
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Travis Hoium: Meta Muse is here, and Motley Fool Hidden Gems Investing starts now. Welcome to Motley Fool Hidden Gems Investing. I'm Travis Hoium, joined today by Lou Whiteman and Rachel Warren. Guys, the big news of the day is that Meta Platforms introduced the Muse app. This is their new Muse Spark model, which is apparently pretty good because this app looks pretty good. Meta's been behind in the consumer space in artificial intelligence, lost a lot of that mind share to companies like Anthropic and obviously ChatGPT, but this seemed like a pretty big announcement from them that they're really starting to take this seriously from a consumer side. Lou, I'm going to start with you. Does this make them a real player in AI consumer products again?
Lou Whiteman: I'm just so excited that my dream of an imaginary friend is not over. That someone is taking this seriously. Look, give credit where due. Meta was never going to win the enterprise. There is no way that people are going to dump Claude for the Facebook, guys. I'm sorry. Maybe that's too harsh, but I think it's true. Where is Meta's strength? It's into consumer, so I appreciate them focusing on the consumer. I don't know, though, if that's a good idea. For one, I feel like we've been hearing about this forever, and the results have always been underwhelming. Maybe this time is different. Maybe the technology will improve, but it's going to have to be insanely good for people to pay for it. At the end of the day, Meta is a for-profit business, and they need to be able to pay for it. I get why they're going for the consumer here. I don't think this is going to pay for all those data centers they're building.
Travis Hoium: Rachel, what's your take on this? I think the framing that I want from an investment angle is, is this the kind of thing that is going to fundamentally change the way that we particularly shop? Because it seems like that's what a lot of these outcomes potentially were. The things that they demoed was, you can just talk to it and say, "Hey, change my flight to tomorrow" or "Buy me some groceries based on this Instagram reel that I saw." Is that possibly something that's going to be mass adopted, and we're just going to be shopping on Facebook products through Muse in five or 10 years?
Rachel Warren: I do think the way that consumers are shopping is changing, and I think we are seeing that at the very least, consumers are more comfortable letting some of these models and agents at least complete part of the process for them, even if they want the ability as the human to have the final say, whether it's a flight being booked or a reservation being made, whatever the case may be. I think we're probably going to see more of that.
But going back to Lou's point, Meta has been behind in consumer AI for years. I think Muse might be one of many necessary steps to shift that paradigm. This model is essentially designed to handle a range of tasks. It doesn't just answer text prompts, and essentially it runs each agent inside an isolated environment called the Muse Secure VM, and this is this dedicated virtual machine, if you will, with its own browser. Essentially, that means that agents can navigate web tools and use app connectors for services like Google Workspace, Spotify, OpenTable. Now, the monetization angle of this is interesting. I do tend to think that this is not going to be something that moves the needle, at least not yet, but maybe it will be a precursor to something that does. They're testing a direct subscription model for Muse. There's going to be a free tier, they're going to have a $20 plan, there's going to be a $100 plan for really heavy users there.
The final note I would make and the core obstacle that I see for Meta is the data privacy trade-off. There's this idea, if you're operating an effective background agent, there needs to be deep access to personal communications, calendars, financial tools. Meta has said that there's this separate agent called Sentinel that approves sensitive actions. It never views that really sensitive consumer data. But we saw internal tests that actually flagged data handling issues right up to launch week. So I think there's going to still be consumer hesitancy there. I think Meta has a lot to prove for users to grant really this level of control to any single entity or model.
Travis Hoium: We're going to talk a little bit more about this consumer AI in a moment. But Lou, has Meta done enough to be able to be that trusted place for consumers? Because what they're asking is not just to give you a whole bunch of data based on what you're looking at on Instagram or what you're posting on Facebook, but also, hey, let us connect to your email. Let us connect to your calendar, and like Rachel said, your financial information. That seems like another big leap.
Lou Whiteman: It's a leap too far. Did you even notice in the demo, the AI seemingly knows the name of a person's kid, even though the kid's name wasn't in the prompt? It was like, "We found this great stroller for Jonah" or something like that. Meta needs to look in the mirror if they do not realize that they may not be the first choice when it comes to trusting. Let's be honest, even if they were, you don't have to opt in on a lot of these other companies. If there's going to be the imaginary friend, personal butler, shopping assistant, it's going to be Gemini and Siri. I keep coming back to this, but we underappreciate just what a good device the phone is and what a companion the phone is. The thing that is already on our phone is going to win here if there is a win. Again, how good is it going to have to be for me to pay for this?
Travis Hoium: Lots of questions for Meta, but we're going to talk about what the future of consumers using AI because these tools are getting better and better every day, but how is adoption actually going to play out? More on that in a moment.
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Travis Hoium: Welcome back to Motley Fool Hidden Gems Investing. All of these artificial intelligence companies are going deeper and deeper into our data, building agentic models that are going to do things for us. But some companies are going to be disintermediated potentially. We aren't going to need their services anymore. A company like Shopify was down almost 8% yesterday. There is going to be business applications, not to mention the ROI on all of the trillions of dollars worth of investment that we've seen over the past few years. But Lou, as we think about this, on the consumer side, I think the enterprise is a little bit different. Coding, we went from 0-100 in what? Three months. Consumer seems like a very different space. How quickly are we going to actually adopt some of these products? Because the agents are getting to be pretty interesting, pretty cool from all of these companies, but I don't know how much I'm going to be willing to connect my email, my wife, my parents. The adoption curve on the consumer side is very different than it is with enterprises, it seems.
Lou Whiteman: It is. Look here, theinvestment adviceup front, the way we're supposed to. Bet on the status quo, and bet on the status quo to remain in place longer than you'd think. A little perspective here. Well, let's fire up the Wayback Machine. The first credit card, Travis, do you know what year it came out?
Travis Hoium: I actually know this answer because we talked about it on one of the Friday shows a couple of months or so ago.
Lou Whiteman: 1950, a guy forgot his wallet and came up with the idea of just the Diners Club, that you could do it. First Visa, the Bank of America card, came along in 1958. I am not going to sit here and argue that that's not better than paying cash. I hate cash, so this should be innovation that takes off. Sixty years later, as of 2018, credit cards accounted for 18% of U.S. payments. Now yes, e-commerce has kickstarted that into overdrive. Seventy years later, we're up to 30% of payments today. Which is to say mass adoption takes time. That is just a convenience thing, credit cards. Credit cards are easier than carrying cash. I guess there's downsides, but you don't have to opt into things. You don't have to change your lifestyle. You don't have to trust companies that don't have a lot of trust, and that has taken that long. I believe all of this stuff is coming. I believe I will use some of them, and I think that they will become part of life over time. But again, I am taking the under on how quickly, and I am not going to sell off Shopify because somebody's got a new trick that they think everyone's going to adopt overnight.
Travis Hoium: I always like the examples, the demos that they give in these product releases, because it tells you what they think people want to see. The stroller example was fascinating to me because if you had kids, shopping for a stroller is one of the things that you go do with your partner. It is part of the process. You have tons of decisions to make. Do we like this size? Do we like how this feels? Is this going to fit in our car?
Lou Whiteman: For us, it was the cup holder. Is the cup holder big enough?
Travis Hoium: Yes. All those little things. That is not something I'm going to have an agent do for me, but it is always fascinating to see what Silicon Valley thinks we want to see. Rachel, when we think about this kind of technology, one of the things we've been talking about here on the show for quite a while is the difference between disruptive innovations and sustaining innovations, and it seems with this release in particular, it stuck in my mind that we now have these big tech companies that are leading in AI, and they're the same companies that were leading in the last generation. Maybe this is just the hammer that says this is a sustaining innovation, and the disruption is not going to come from small start-ups. Yes, Anthropic and OpenAI are out there, but they're well backed by these big tech companies, and they grew them themselves. Does that make sense as an investor that, you know what, like Lou said, the old companies are going to be the winners in the future too?
Rachel Warren: I think so, and I think that's also because that's where we're seeing a lot of the technology coming from, and that's also where a lot of the consumer trust lies as well. I think we're talking about trying to get consumers to let autonomous buying agents handle a lot of mundane transactions, and I think we're seeing that. Some of the things like tracking orders, checking inventory, processing returns on the backend, that's something where it's very useful for Shopify. For a human individual user, things like going through your emails, summarizing some of your admin tasks as a worker. There are a lot of ways in which this technology is very useful, but there's a real trust bottleneck there, and I think that there's also a regulatory bottleneck too. I think there's still a lot of uncertainty about how this is actually going to be applied in everyday life in the long term. I do think as we see a lot of the dominant tech companies like Meta, like Alphabet, like Microsoft, they're using their capital, their massive distribution networks to deploy the latest AI innovations as well as agents, they're making good products more efficient. That is essentially the definition of a sustaining innovation. Going back to the example of Shopify, I think this is one of those companies that is solving a lot of the problems that merchants around the world continue to encounter. They are continuing to leverage AI in their everyday processes behind the scenes, on the backend, solving a lot of the problems that merchants are facing, and I think that makes them a company that can sustain even in an age of innovation. There was a projection that came out from HubSpot that 95% of buyer journeys will be beginning inside an LLM chat within two years. I do think that we are seeing an adoption curve among consumers, but I just don't think it's necessarily going to be quite as fast an adoption as some of the big tech companies are saying.
Travis Hoium: It's interesting that the company that we have not mentioned here is Amazon. Amazon is the biggest e-commerce company, but they have not played nice with a lot of these agents and shopping tools in an AI age. Be interesting to see how they play this in the future. I know their Alexa keeps popping up when I open up the Amazon app, and it's not necessarily something I'm willing to use quite yet.
Lou Whiteman: That makes sense, doesn't it? Show me the incentive, I'll show you the results. They are the advantage company with the current status quo, so they are not going to look to disrupt. Again, all of your business plans or all of them that I've seen count on Amazon to just lean over and say, "Come on in." I think that should also factor into thoughts on the timetable for adoption.
Travis Hoium: Yes, lots to play out, and lots of investing implications. When we come back, we are going to talk about some huge advances in the world of medicine. You're listening to Motley Fool Hidden Gems Investing.
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Travis Hoium: Welcome back. One of the other big advancements in the world of AI came from Google's DeepMind. They released the Google AlphaGenome Atlas. This is apparently the next generation of AlphaFold. Rachel, all these words are too complicated, and the release and the videos are too complicated for me to understand. So give us the CliffsNotes version here.
Rachel Warren: The AlphaGenome Atlas, it takes the complexity of human DNA, and it computes the exact molecular impact of every possible change. The scientific community has understood for a long time that 2% of the genome codes for proteins. The remaining 98%, that is like a control panel for switching genes on and off, and that 98% has actually largely been a mystery. To solve this, Google DeepMind has utilized its AlphaGenome AI model to analyze sequences up to one million base pairs in a single pass. It's calculating essentially how individual mutations disrupt critical processes in the body, like gene expression. Then it assigns each mutation a score to rank how harmful or influential a specific genetic change is likely to be. Essentially, to break this down, human DNA is an incredibly long line.
We're going to make it analogous to software code that runs in our bodies. This means that for a long time, scientists only understood a small portion of that code that physically builds our organs and our tissues, and the other was a mystery. This tool essentially ran every single possible typo that could ever happen in that mysterious 98% of the code, and what acts like a broken power switch that causes a disease, which typos are harmless, just to give you a bit of an analogy there. Then essentially compiled all of these answers into a giant searchable library that's free for software developers, researchers. Now, there's a commercialization wave coming here. Pharmaceutical companies are soon going to have to license Atlas through Google Cloud to plug the database right into their drug discovery pipelines. But we're already seeing early validation here. You have Memorial Sloan Kettering Cancer Center, Stanford University. They are actively using the Atlas to solve complex medical cases. One example, researchers actually used this AVI score to uncover an overlooked mutation responsible for a rare form of epilepsy. We're already seeing the ways in which this is so valuable for researchers, for pharmaceutical companies. I think this could be a really, really valuable tool.
Travis Hoium: Lou, that sounds very cool. How investable is it? Or is this just one of these areas where the surplus ends up with consumers? We live healthier, better lives long term. This is a complicated space to be investing in.
Lou Whiteman: Right. I think it's impossible. I don't think it is investable, and I'm not a bio-researcher, and so on.
Travis Hoium: Although maybe more tailwinds for Google Cloud.
Lou Whiteman: Maybe. But I've been leaning heavily on Eli Lilly's CEO, David Ricks, last year, who wasn't dismissive of AI but was definitely trying to hit the brakes on the hype. The body's complicated. It's great to map and understand the genome, but there are very few diseases caused by a single gene. Cystic fibrosis, famously, is Chromosome 7, only Chromosome 7, and yet we still struggle with that. Most things, it's interactions between different things. This is a great starting point, but all this does is basically give researchers a head start at that first step, so maybe we do fewer dead ends. There's still a huge amount of progress.
One thing Ricks pointed out is that AI models speak English. They don't speak biology. Part of that is because humans don't speak biology. We still don't understand the language of biology, so we can't teach AI a language we don't understand. I think we'll get there in time, but these are incredibly complex problems. Root for it, because we all want to live healthy, and I do think that this is progress, and I celebrate that. But as an investor, you're talking a decade or so, I think, before there is anything coming out of here, just the nature of the science. Cheers to incremental progress, but do understand and don't just load up on the account of some biotech because they say they're licensing this. That is not a good investment, even if we're making real progress.
Travis Hoium: I think the takeaway from this was that hopefully this continues to accelerate progress from a human health standpoint, because if there is something positive that's coming out from AI as we talk about doom and gloom and consumer adoption and safety and all these kinds of things, it seems like there are some really positive things coming out of the world of AI in some of these labs today.
As always, people on the program may have interest in the stocks they talk about, and The Motley Fool may have formal recommendations for or against, so don't buy or sell stocks based solely on what you hear. All personal finance content follows The Motley Fool's editorial standards and is not approved by advertisers. Advertisements are sponsored content and provided for informational purposes only. To see our full advertising disclosure, please check out our show notes. For Lou Whiteman, Rachel Warren, and Kristi Waterworth behind the glass, I'm Travis Hoium. Thanks for listening. We'll see you here tomorrow.
Bank of America is an advertising partner of Motley Fool Money. Lou Whiteman has positions in Shopify. Rachel Warren has positions in Alphabet, Amazon, and Shopify. Travis Hoium has positions in Alphabet, Shopify, and Spotify Technology. The Motley Fool has positions in and recommends Alphabet, Amazon, Eli Lilly, HubSpot, Meta Platforms, Microsoft, Shopify, and Spotify Technology. The Motley Fool has a disclosure policy.
