Quantum’s Leap Into Public Markets

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[00:00:34] Welcome to Tech News Briefing. It's Tuesday, April 28th. I'm Imani Moise for The Wall Street Journal. Are tech companies trading their employees for computing power? Last month, nearly 46,000 tech workers were laid off, while tech firms ramp up spending on chips and data centers that could put them in the lead of the AI race. We'll break down why some of the companies might come to regret the cuts.

[00:00:58] And quantum computing companies are racing to go public, pitching a still-nascent technology as the next AI. Investors are lining up. We're exploring what's behind the hype. But first, as big tech companies go all in on chips, they're also betting on needing fewer employees.

[00:01:23] Just last week, Meta announced plans to cut 10% of its workforce next month, and Microsoft offered its first-ever voluntary buyout packages to thousands of staff, with potential layoffs to come if not enough employees take them up on the offer. But while job cuts might make the companies look better to investors, they're not without some risks. WSJ columnist Dan Gallagher joins us now to explain what the shift could mean for Silicon Valley.

[00:01:50] So Dan, when Meta and Microsoft announced cuts last week, the market for tech jobs was already looking bleak. Can you set the scene for us? We've seen over the past couple months just an increasing number of these layoffs. But according to one tracking service, March had the most layoffs of tech employees ever since a little over two years prior, which is when there were a lot of cuts happening. If you recall, COVID, a lot of companies were hired, and then afterwards, a lot of them were bringing their numbers back down.

[00:02:20] But this new wave, these companies are trying to either free up more resources to invest in AI, or in some cases, they're claiming that AI lets them do more with less. And so they don't need as many workers. What are tech executives saying? How are they framing these cuts? It does depend on the company a little bit. But you don't have the companies saying, hey, we're doing this because our business is having trouble.

[00:02:43] So Block, the company that used to be called Square, they were really upfront about, you know, they cut down about 40% of their workforce and said, this is to basically get us ready for AI. This new technology allows us to do a lot more, and we're going to be really aggressive with it. And then in the case of Meta, they starkly said part of this is that we're freeing up more resources to invest in AI. And Meta is spending a lot of money on AI. And so I think they're trying to get other parts of their operating expenses a little bit more in line.

[00:03:12] And what are some of the risks associated with the layoffs for these companies? That remains to be seen because investments in AI are consuming a lot of capital. And it's on the premise that these services will be super, super valuable in the years to come and produce more revenue and more earnings. And I think the risk that companies are dealing with here is that if you've created this state of fear amongst your employees about what's going to happen to me, you create an incentive for your employees to start looking elsewhere.

[00:03:41] Especially the employees that are talented that might have good options. They might think, why would I stick around here and work for a company that's trying to eliminate my job? And then what this does to the whole image of AI, these companies are trying to get these massive data centers built. That's part of their investments. And if you build on the image that AI is this job killer, you're going to push more opposition to it into communities and governments and so forth.

[00:04:07] You're seeing more public opposition to the big data centers these companies want to build in certain communities. And you're seeing a lot of fears expressed about what AI is going to do to the future. And so if you're reading newspapers like ours and seeing news of, you know, thousands and thousands of people getting pink slipped because of AI somehow, that certainly doesn't help that. What's been the investor reaction so far to this latest round of cuts? Typically, if a company says, oh, we're bringing down costs, doing all these layoffs, sometimes you see the stock go up.

[00:04:37] I haven't seen that in every case this time because in a lot of cases, it's not necessarily bringing down costs. So if you're an investor trying to figure out, OK, what impact is this going to have on the financial statements? It's a little bit hard to model. And in terms of do they help a company's broader AI mission? I think that remains to be seen. So we have a lot of tech earnings coming up this week. What are you going to be listening out for on those calls? The four companies that are reporting Wednesday, Meta, Microsoft, Amazon and Google.

[00:05:04] These are the companies that are spending the most on their AI investments. And I think the thing everybody wants to see is, are we starting to see payoffs from that yet? Or is this more a story of just more money is going to keep going out the door? The last few, you know, running cycles we've seen, that's been the dominant story. It's been less about the AI business they're seeing, more about what they're spending. And so is that story going to change this quarter? I don't know. But that's something we're watching for. Do you think we're going to hear that more layoffs are coming?

[00:05:33] Usually companies don't tend to put those in their calls because they want to focus on the numbers and to tell a good story in the earnings. So I don't think we're going to see necessarily more of that. That was WSJ columnist Dan Gallagher. Are you worried about AI layoffs affecting your job this year? If you're a listener on Spotify, leave us a comment with your thoughts. Coming up, quantum computing has the potential to revolutionize everything from drug discovery to trading. But it's not quite here yet. That isn't stopping investors.

[00:06:03] We'll get into it after the break. With AI mania in full swing, some investors are already looking for the next big thing. A breakthrough in quantum computing has been waiting in the wings for decades. But that's not stopping some companies from racing to go public.

[00:06:34] And investors are ready to take the leap. According to one analyst, these days, even just putting the word quantum in your company's name can attract a $1 billion valuation. WSJ reporter Isabel Busquets joins us now to unpack quantum's mad dash to market. So Isabel, maybe we could start by explaining what quantum computing is and why people are so excited about it. Absolutely.

[00:07:00] So quantum computing is a fundamentally new form of computing. And the idea is that it leverages some principles of quantum physics to theoretically perform calculations that are not possible even on today's largest supercomputers. Math that it would take today's computers hundreds of years to run could be done in seconds on a quantum computer.

[00:07:28] It could just be a lot faster at speeding up certain types of problems. And that has huge applications for a lot of businesses. It could have huge applications in drug discovery, for example, in finance. Portfolio optimization is a huge use case. Honestly, optimization use cases across the board. Anything in shipping or logistics or materials discovery. It could really transform a lot of businesses like that.

[00:07:59] But building these computers is not easy. We've seen early iterations of them, but nothing so far yet that can really deliver on the full promise. Mainstream quantum computing is still potentially years away. But there's been some encouraging signs of progress recently. Can you tell us about those? What's exciting about this industry is that a lot of the companies will actually publish their roadmaps for how they intend to get to these large-scale commercial-grade quantum computers.

[00:08:26] And the idea is they'll build smaller computers along the way and slowly scale up and demonstrate milestones. And they have been hitting those targets. And a lot of those roadmaps are putting that commercial application date in the 2029, early 2030s range. You know, we've also seen interest from the U.S. government in funding these companies.

[00:08:49] We've seen companies like NVIDIA get on board with contributions to helping build the models and algorithms that are ultimately going to run on these computers. That said, healthy dose of skepticism. This is something that's been in development for many, many decades. And it has gone through periods of feeling like it's just around the corner. And so I don't think it's exactly clear exactly when this is going to happen.

[00:09:17] But the experts I talk to in this space are clear on the fact that this has shifted from an if question to a when question. Would a breakthrough in quantum computing have implications for AI? 100%. AI and quantum can and will feed off each other in a lot of ways. Quantum computers could provide a huge speed up in the types and capabilities of AI models that we might want to run.

[00:09:47] And at the same time, quantum computers could play a huge role in developing much larger, more mature, more complex AI models, especially in areas like materials discovery and drug discovery. They will both supercharge each other. So there's a lot of momentum and a lot of interest, and investors are getting more opportunities to buy in. Tell us about that. This is a wild year for quantum companies going public.

[00:10:17] Before this year, there were basically four big quantum computing companies that were publicly traded. So far this year, we've seen another three enter the market. That's Inflection, Xanadu, and Horizon Quantum. And another five have announced plans to go public probably later this year. So we're seeing the amount of pure play public quantum stocks triple this year.

[00:10:42] You know, that said, there are also big quantum projects in development at Microsoft, at Amazon, at Google, at IBM. So these are just a pure quantum companies, but they are racing headlong into public markets. And how have the companies that have already gone public performed so far? The CEOs of those companies have made it pretty clear that they are getting a lot more in the public markets than they could have gotten staying private.

[00:11:08] The CEO of Xanadu was telling me they were in the midst of raising a private round, and it was kind of a slog. And he said, we would have gotten there eventually, but going public was just a much faster and more efficient way to get more money on a shorter time frame, which is what these companies want, because they need that money to build these really big, complex computers. That was WSJ reporter Isabel Busquets. And that's it for Tech News Briefing.

[00:11:37] If you're a listener on Spotify, be sure to leave us a comment. Today's show was produced by Danny Lewis with supervising producer Katie Ferguson. I'm Imani Moise for The Wall Street Journal. We'll be back later this morning with TNB Tech Minute. Thanks for listening.