Rising attention about generative AI prompts the question: Are we witnessing the birth of a new innovation platform? The answer seems to be yes, though it remains to be seen how pervasive this new technology will become. To have an innovation platform, there must be a foundational technology, such as a widely adopted personal computer or smartphone operating system, or the Internet and cloud-computing services with application programming interfaces (APIs) (see "The Cloud as an Innovation Platform for Software Development," Communications, October 2019). Third parties are then needed to access these APIs and start creating complementary products and services. More applications attract more users, which leads to more applications and then more users, and usually improvements in the foundational technology.

It's not news that Mark Zuckerberg wants to lead the charge in the emergent metaverse with his company, Meta (formerly Facebook). The recently concluded Meta event titled "Inside the lab: Building for the metaverse with AI" was another step in Meta's quest to unlock the metaverse with AI, after its previous announcement that it was developing a record-breaking supercomputer to power the metaverse. Experts have said that AI, VR, AR, blockchain and 5G will converge to power the metaverse, and Zuckerberg is keen on building several huge AI systems that will drive the nascent metaverse world. "We work on a lot of different technologies here at Meta -- everything from virtual reality to designing our own data centers. And we're particularly focused on foundational technologies that can make entirely new things possible. Today, we're going to focus on perhaps the most important foundational technology of our time: artificial intelligence," said Zuckerberg.

It's not news that Mark Zuckerberg wants to lead the charge in the emergent metaverse with his company, Meta (formerly Facebook). The recently concluded Meta event titled "Inside the lab: Building for the metaverse with AI" was another step in Meta's quest to unlock the metaverse with AI, after its previous announcement that it was developing a record-breaking supercomputer to power the metaverse. Experts have said that AI, VR, AR, blockchain and 5G will converge to power the metaverse, and Zuckerberg is keen on building several huge AI systems that will drive the nascent metaverse world. "We work on a lot of different technologies here at Meta -- everything from virtual reality to designing our own data centers. And we're particularly focused on foundational technologies that can make entirely new things possible. Today, we're going to focus on perhaps the most important foundational technology of our time: artificial intelligence," said Zuckerberg.

Austin Russell is the 25-year-old founder and CEO of Luminar, a startup in Silicon Valley that makes LIDAR sensors for self-driving cars. LIDAR technology had been used for short-distance mapping, but Luminar claims to have a functioning LIDAR that works at 250 meters, which is a breakthrough. Luminar recently went public, making Austin today's youngest self-made billionaire. And when it comes to self-driving cars, youth is definitely an advantage -- Austin told me we're still years if not decades away from fully self-driving cars, and there's a lot of work to be done to make them safe, effective, and ubiquitous. That work is racing ahead -- Luminar has deals with Volvo, Audi, Toyota, and others -- but building a complete self-driving car is still a long-term project. This transcript has been lightly edited for clarity. I'm very excited to talk to you. You are, as far as the last thing I read, the youngest self-made billionaire in America, your company just went public in a SPAC [special purpose acquisitions company]. And come Pi Day, 26. You were born on Pi Day? So, Luminar, it's a company that makes LIDAR sensors. You have a number of deals to supply LIDAR sensors to major automakers. I want to talk about all of that. One thing that I always get frustrated by in origin stories is no one ever really talks about act two. In 2012 you were at Stanford, you had this idea to do LIDAR sensors. I want to talk about act two for a little bit. Just that middle part of going from "I've got a great idea," to "This company is actually up and running and functional." So give me a sense of, at the beginning you were a student at Stanford, you got a Thiel Fellowship from Peter Thiel. What was the next step? Did you sit down and build a LIDAR sensor?

The general view is that the 2020-21 pandemic has been already accelerating the adoption of automation, and moves towards digital business. There is strong evidence for this, and for the trend to continue across the 2021–2025 period. And indeed the case for these technologies has been well made by our 2020 experiences. It provided alternative ways of working in a crisis. It allowed a high degree of virtuality, and all the upsides to that, in a world rendered physically semi-paralysed, albeit temporarily.

Previously I wrote about the Cyberworld that's coming – the world of extended reality, or XR, enabled by a confluence of maturing foundational technologies, with AI a central part – computer vision and graphics, 3D reconstruction, natural language processing and more. It goes without saying that this seamless overlay of digital and real worlds will be populated by digital humans and avatars, both realistic and stylistic, driven by real humans and/or artificial intelligence. Here I am going to dive deeper into one of these foundational technologies: the creation and animation of digital humans (mainly faces). The good news first – it won't take us another decade to get there. When I started the Disney Research Laboratory back in 2008, I launched a long-term research vision to find the Holy Grail of special effects in film; i.e. to create and animate digital human faces indistinguishable from reality.

Last December, China's top AI scientists gathered in Suzhou for the annual Wu Wenjun AI Science and Technology Award ceremony. They had every reason to expect a feel-good appreciation of China's accomplishments in AI. Yet the mood was decidedly downbeat. "After talking about our advantages, everyone mainly wants to talk about the shortcomings of Chinese AI capabilities in the near-term--where are China's AI weaknesses," said Li Deyi, the president of the Chinese Association for Artificial Intelligence. More than two years after the release of the New Generation Artificial Intelligence Development Plan (AIDP), China's top AI experts worry that Beijing's AI push will not live up to the hype.

Get expert knowledge on the tools and technologies you need to put your data strategies to work. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year. I will highlight the results of a recent survey on machine learning adoption, and along the way describe recent trends in data and machine learning (ML) within companies. This is a good time to assess enterprise activities, as there are many indications a number of companies are already beginning to use machine learning. For example, in a July 2018 survey that drew more than 11,000 respondents, we found strong engagement among companies: 51% stated they already had machine learning models in production.

Data presents an invaluable opportunity for firms to innovate, but only if they know what to do with it. In her latest research, Wharton professor of operations, information and decisions Lynn Wu looks at how different organizational structures influence the use of data analytics to spur innovation. Her paper, "Data Analytics Supports Decentralized Innovation," is forthcoming in the journal Management Science and was co-authored by Wharton operations, information and decisions professor Lorin Hitt and Wharton doctoral candidate Bowen Lou. Wu spoke with Knowledge@Wharton about the research. An edited transcript of the conversation follows.

When the US Library of Congress ranked history's most important innovations, it gave a foremost place to the printing press. While the mechanics behind the printing press weren't far more sophisticated than the other machines of its era, the consequences of its invention were world changing; finally, mankind had a means for the mass distribution of information, improving literacy and changing every industry in the world. Technologies such as these are known as foundational technologies, inventions that can be applied to solve a multitude of problems across a vast number of industries. More contemporary examples include the internet which is now used nearly constantly in all industries and in our personal lives and smartphones, which are so completely integrated with our lives it seems impossible to live without them. As we peer into the near future, we can already see some of the next great potential foundational technologies arising.