Nicole Lamoureaux (2:49)

It's hard to, to crystal ball more. And many saw the announcement that we made that we are tripling entry level hiring in an era where so many people are pulling back completely doing zero, or where they're shaving it a little bit half as they're figuring this out. But this idea of hey, we want to start thinking about talent, human talent, about where are we going to go deploy that to drive growth, that is what we've got to think about.

Host/Interviewer (3:25)

I'm so intrigued by that entry level hiring call. It got a lot of attention. What's the business case for that? And if it is such a smart move to bring in more entry level people right now, why are so few companies doing that?

Nicole Lamoureaux (3:37)

It's because they're in this productivity mindset versus the growth mindset. So I will acknowledge if I look at our entry level hiring of, you know, and the jobs that we had two years ago, AI can do almost all of it. So I acknowledge it's a very logical discussion. If you are in a productivity mindset of driving cost savings, generating profit, then you are going to say I don't need this. It's a logical decision in the short term. But I'd argue that there's maybe a better decision definitely in the medium term. What do you drive to? How can your software developers, rather than maintain products, given they know code, can you put them on squads where they're actually developing and interacting with clients about new products, new features? It's a growth mentality. But I also think that it will ensure that we are successful a few years from now. Because what's going to happen three, four, five years from now, Middle managers retire, leave, get promoted, move on and you've got to fill that part of the organization. So to me this is a business proposition. This is not just a benevolent good for society. Bring in entry level hires. There's a business proposition when you think about deploying this talent to the growth areas and new areas of business. But it also then helps in your longer term talent strategy.

Julie Chang (5:04)

That was WSJ reporter Chip Cutter speaking with IBM's Chief Human Resources Officer Nicola Moreau at the WSJ Leadership Institute's Chief People Officer Summit. You can find the full chat linked in the show notes. How do you think AI is changing entry level work? If you're a listener on Spotify, leave us a comment with your thoughts coming up. OpenAI's video generation app Sora was supposed to make a big splash in pop culture and entertainment. Instead, it got scrapped like last week. We'll explain why after the break.

Host/Interviewer (5:43)

AI PCs are increasingly where sensitive data is acted on in real time. How should enterprise security leaders address that? Here's Magna Petwarden, corporate Vice president of Product Management Client business unit at AMD, with some thoughts.

Magda Petwarden (5:57)

People are going to use AIPCs, and enterprises have to think about AIPCs as a natural extension of their zero trust policies. They have to embrace this idea of security that is distributed versus centralized with sort of a moat built around it, because there are no more moats.

Julie Chang (6:16)

Last September, OpenAI's video generation app Sora shot to the top of the Apple Store the week of its launch. In just a few minutes, users could create a short video of whatever they typed as a prompt. The app quickly hit 1 million downloads, and at the end of last year, it announced a multi year licensing partnership with Disney. But last week, just six months later, OpenAI pulled the plug. WSJ reporter Berber Jin spoke with people familiar with the matter for an exclusive look behind the scenes of that decision, and he's with me now to discuss how it all shook out. And a quick note before we jump in. News Corp, owner of the Wall Street Journal, has a content licensing partnership with OpenAI. So Berber, what was OpenAI CEO Sam Altman's vision with Sora?

Berber Jin (7:05)

He's always envisioned AI to be more than a basic chatbot or a productivity tool that can do scheduling tasks for you and build a PowerPoint. He always had a vision of AI reshaping popular culture, reshaping entertainment, and Sora very much fit into that vision. He wanted OpenAI to have a social media app similar to Meta with Instagram, and he just wanted OpenAI to enter into popular culture. And with Sora, he had this vision of enabling the creativity of its users. So a lot of people would probably say Sora is the opposite of that. People don't create their own art, they just outsource it to AI. And obviously Sora is very tied with this idea of AI slop. But I think in Sam's mind, he really felt like this could have been almost like a ChatGPT moment for the creative space.

Julie Chang (7:59)

Okay, so that ChatGPT moment never really came to be. How did OpenAI arrive at the decision to shut down Sora?

Berber Jin (8:07)

OpenAI is a very different company today than it was six months ago when they released Sora. OpenAI is preparing to go public later this year. They need to grow their revenue very quickly. And what's happened in the past few months is that it's become very clear that the easiest and fastest way to make money in AI right now is to sell these so called productivity tools to businesses and to developers. So the thing that really has taken off in the past few months is Claude Code, which, which was released by Anthropic. It's kind of the tool of choice for software engineers. And Anthropic also released Cloud Cowork, which is a work productivity tool for AI. So these are more boring tools, right? Like they are designed to help you code, to help you outsource the more monotonous back office tasks. But businesses are willing to pay a lot of money right now for those tools. And Anthropic has really just been ahead of OpenAI. And so OpenAI is kind of in the middle of this really big strategy shift to focus on deploying as many resources and specifically their computing resources towards catching up in building these productivity tools. So earlier this month they announced a new kind of super app which they hope will be this AI assistant on steroids for businesses. And what happened was that SORA really just, it no longer made sense within the kind of strategic roadmap of OpenAI, right, because it wasn't generating much money and it was incredibly computationally intensive. And so OpenAI just decided that they couldn't really afford to keep SORA alive because they're in this precarious moment where they have to devote as many computing resources as possible towards winning that coding and enterprise business.

Julie Chang (9:53)

What does pulling the plug on Sora tell us more broadly about where the industry is heading?

Berber Jin (9:59)

So the thing that's really interesting with these labs is that they all started off as research labs, like kind of funding big, bold, ambitious research projects and they weren't super concerned with revenue. But now with OpenAI and Anthropic both trying to IPO by the end of this year, that research culture has gone away because now the executives at those companies are just looking at research that will produce a very specific return on investment. So in the current environment, what that means is basically funding research that makes AI better at coding and makes AI better at completing productivity related tasks. It definitely isn't funding research into video generation. The death of Sora also symbolizes the death of the kind of more academic or research first culture of these labs and encapsulates how they very much are focused on making money and the commercial aspects of AI over the more pure research aspects of it. As OpenAI interest towards an IPO. It'll be interesting to see what else they choose to cut and if there are any other signs that Sam Altman's sort of grand vision for the company is getting a pretty harsh reality check.

Julie Chang (11:16)

That was WSJ reporter Berber Jen and that's it for Tech News Briefing. If you're a listener on Spotify, don't forget to leave us a comment. Today's show was produced by me, Julie Chang, with supervising producer Katie Ferguson. We'll be back later this morning with your TNB Tech Minute. Thanks for listening.

Host/Interviewer (11:41)

How can enterprise security leaders protect AI PCs? Here again is AMD's Magna Pet Warden.

Magda Petwarden (11:47)

You have to think about security as foundational and not something that comes after the fact. That and that has to be anchored in hardware. Hardware protecting software is more superior from a security strategy perspective and creates sort of an immutable trust even before the operating system drivers and AI models ever load. These protections really create the root of trust for AI enabled workloads so that they can confidently run. And as AI moves onto the device, then the more sensitive data and decision making shifts to closer to the hardware and that means that software only is no longer sufficient.

Host/Interviewer (12:23)

Learn more about how AMD Protects AI PCs from Silicon to Software@amd.com this content

Nicole Lamoureaux (12:30)

was created by Custom Content from WSJ,

Julie Chang (12:33)

a unit of the Wall Street Journal advertising department.