Protocol | Enterprise

Andrew Ng thinks your company is doing AI wrong

The former head of Google Brain says organizations should start smaller, not larger.

Andrew Ng of Landing.ai speaks at an Amazon event in 2019.

Andrew Ng of Landing.ai speaks at an Amazon event in 2019.

Photo: Mark Ralston/AFP/Getty Images

Andrew Ng knows a thing or two about artificial intelligence.

The former head of Google Brain and prior chief scientist at Baidu, Ng also co-founded Coursera and regularly teaches popular courses on the technology online and at Stanford. And he runs Landing AI, which provides manufacturers (and soon, other industries) with an AI platform to help developers more easily build and deploy computer vision models.

That experience has given Ng a deep understanding of the benefits that AI can produce — and the limitations of the tech. As Ng expands his work outside of consumer internet companies, he's seeing a pattern: Organizations are setting their AI ambitions too high.

"I still see companies jump in and make investments in projects that I would consider technically impossible or technically not feasible with today's technology or the near-term generations of technology," he told Protocol. "Learn to walk first. It's fine that the first project you do is not a $10 million AI project."

But even landing on a smaller project can be difficult due to the nature of AI initiatives, which often span departments and require cross-functional leadership that many organizations are still working to develop. It's why Ng says a central AI group is so paramount.

"That'll take some top-down leadership to put in place," he said.

Protocol talked to Ng to learn what he thinks enterprises are getting wrong about their AI strategy and why investments in MLOps should be the wave of the future.

This interview has been edited for brevity and clarity.

As we see the excitement around AI continue to grow, where do you think the broader market is? Is the tech more hype than reality at this point?

AI isn't one monolithic thing. So there are some segments where the hype is definitely disproportionate, but also some segments where there's a lot that's not as visible to the wider public. [Artificial general intelligence] still has a little bit too much hype, though it's come down a little bit. On the flip side, there's a lot of industrial, B2B applications of AI that are valuable but not as well understood compared to a B2C application, which is much more relatable.

Where would you say enterprises are at in this journey? I know there'll be differences, but it seems companies are now starting to take what were smaller pilot projects and expand those.

Very early. For the large companies, even the Fortune 500, some are further ahead but many have one AI project that was put into production through sheer heroics that is reaping substantial amounts of value and potentially dozens of pilot projects that could be promising but, at least on the current path, may take heroics again to put into production. The more traditional industries, where the digitization wave came a little bit later, are still very early.

You've been vocal about the need for quality data over investments in models. Are there sources of data that companies are ignoring?

I feel like the answer has got to be yes. The more common pattern is there are a lot of companies with data sitting around that [is] already good enough to create tremendous value. All data they can very easily create. Take ecommerce. Tons of companies have tons of user data already sitting in their data warehouse and an AI team would be able to go in and drive insights.

What is the best way for organizations to begin this AI journey? How do they have to be set up to be successful?

One of the most important steps is to deliver a quick win. Small pilot project and then take it to a successful outcome. And that initial quick win often teaches an organization lessons that would then be useful for the second, third and fourth projects. Too many companies start off wanting a grand plan. But until it's learned to walk, it's very difficult to plan out what to do when you cross the finish line of the marathon. Learn to walk first. It's fine that the first project you do is not a $10 million AI project. It's fine that the first project you do is a $200,000 project — or even a $50,000 project. The purpose of that is not necessarily to create massive ROI. The greater value is the learning.

Are there any other ways companies are getting their AI strategy wrong?

One of the challenges of AI is it takes a decent amount of technical knowledge to figure out what is and isn't technically feasible. I still see companies jump in and make investments in projects that I would consider technically impossible or technically not feasible with today's technology or the near-term generations of technology.

For example, building a chatbot that can handle all customer service requests in a fairly conversant way. It's clear that's not possible. Fairly recently, someone asked if I could help them build the equivalent of a self-driving car with six engineers in six months. I don't think I could do that.

Project selection is still really difficult, because it takes cross-functional business and technical judgement to prioritize projects. Only a centralized AI group can build horizontal platforms that span the entire company, so that'll take some top-down leadership to put in place.

What did you see in the manufacturing industry specifically that made you start Landing AI?

Speaking with a lot of C-suites about AI adoption, [I] saw many of the same problems over and over in terms of practical deployment. There are lots of $1 [million] to $3 million projects. And it's challenging to get the AI talent and the staffing to make the economics workout. Tons of projects were stuck in proof of concept, because even if a company developed an AI model, it's difficult to write all surrounding software — MLOps is sometimes what we call that — to take that system into production.

We ended up building LandingLens, which is a data-centric, MLOps platform for computer vision. We help companies — starting in manufacturing but we have interest in other computer vision vertical applications — be 10x more efficient and often much more successful as well in building and deploying computer vision systems.

It seems the prevailing notion for why companies adopt AI is to cut costs. Do you find that, based on where we are at in the life cycle of AI, that immediate outcomes should be around quality improvement? Does it make a difference in terms of success which metrics prioritize first?

Cutting cost is a worthy thing to do and improving revenues or improving margins is a worthy thing to do, but I find that the latter category of projects often has more momentum than just cost-cutting. It's easy to get momentum on projects that create value beyond cutting costs.

What would be your one piece of advice for enterprises struggling with their AI strategy?

Find the right philosophies and MLOps tooling, because that will give organizations a big boost in AI adoption and performance. We've moved past the era where it's about the engineer using their own tools. Until now, a lot of AI was developed using very broad tools. We did that for the past decade, we're now moving on. I don't write any code in assembly myself. In the future, we'll find that the tooling will make machine learning engineers much more efficient.

Protocol | Policy

New report shows kids see COVID-19 misinfo on TikTok in minutes

A new report finds that kids as young as 9 are being fed COVID-19 misinformation on TikTok, whether they engage with the videos or not.

NewsGuard researchers asked nine kids to create new TikTok accounts and record their experiences on the app.

Photo: Andrew Harrer/Bloomberg via Getty Images

TikTok is pushing COVID-19 misinformation to children and teens within minutes of creating a new account, whether they actively engage with videos on the platform or not, a new report has found.

The report, published Wednesday by the media rating firm NewsGuard, raises questions not only about how effectively TikTok is enforcing its medical misinformation policies, but also about how its own recommendation algorithms are actively undermining those policies.

Keep Reading Show less
Issie Lapowsky

Issie Lapowsky ( @issielapowsky) is Protocol's chief correspondent, covering the intersection of technology, politics, and national affairs. She also oversees Protocol's fellowship program. Previously, she was a senior writer at Wired, where she covered the 2016 election and the Facebook beat in its aftermath. Prior to that, Issie worked as a staff writer for Inc. magazine, writing about small business and entrepreneurship. She has also worked as an on-air contributor for CBS News and taught a graduate-level course at New York University's Center for Publishing on how tech giants have affected publishing.


Keep Reading Show less
Nasdaq
A technology company reimagining global capital markets and economies.
Protocol | China

Beijing meets an unstoppable force: Chinese parents and their children

Live-in tutors disguised as nannies, weekday online tutoring classes and adult gaming accounts for rent. Here's how citizens are finding ways to skirt Beijing's diktats.

Citizens in China are experienced at cooking up countermeasures when Beijing or governments come down with rigid policies.

Photo: Liu Ying/Xinhua via Getty Images

During the summer break, Beijing handed down a parade of new regulations designed to intervene in youth education and entertainment, including a strike against private tutoring, a campaign to "cleanse" the internet and a strict limit on online game playing time for children. But so far, these seemingly iron-clad rules have met their match, with students and their parents quickly finding workarounds.

Grassroots citizens in China are experienced at cooking up countermeasures when Beijing or governments come down with rigid policies. Authorities then have to play defense, amending holes in their initial rules.

Keep Reading Show less
Shen Lu

Shen Lu is a reporter with Protocol | China. Her writing has appeared in Foreign Policy, The New York Times and POLITICO, among other publications. She can be reached at shenlu@protocol.com.

Protocol | Policy

Google and Microsoft are at it again, now over government software

The on-again, off-again battle between the two companies flared up again when Google commissioned a study on how much the U.S. government relies on Microsoft software.

Google and Microsoft are in a long-running feud that has once again flared up in recent months.

Photo: Jens Tandler/EyeEm/Getty Images

According to a new report commissioned by Google, Microsoft has an overwhelming "share in the U.S. government office productivity software market," potentially leading to security risks for local, state and federal governments.

The five-page document, released Tuesday by a trade group that counts Google as a member, represents the latest escalation between the two companies in a long-running feud that has once again flared up in recent months.

Keep Reading Show less
Ben Brody

Ben Brody (@ BenBrodyDC) is a senior reporter at Protocol focusing on how Congress, courts and agencies affect the online world we live in. He formerly covered tech policy and lobbying (including antitrust, Section 230 and privacy) at Bloomberg News, where he previously reported on the influence industry, government ethics and the 2016 presidential election. Before that, Ben covered business news at CNNMoney and AdAge, and all manner of stories in and around New York. He still loves appearing on the New York news radio he grew up with.

People

Facebook wants to kill the family iPad

Facebook has built the first portable smart display, and is introducing a new household mode that makes it easier to separate work from play.

Facebook's new Portal Go device will go on sale for $199 in October.

Photo: Facebook

Facebook is coming for the coffee table tablet: The company on Tuesday introduced a new portable version of its smart display called Portal Go, which promises to be a better communal device for video calls, media consumption and many of the other things families use iPads for.

Facebook also announced a revamped version of its Portal Pro device Tuesday, and introduced a new household mode to Portals that will make it easier to share these devices with everyone in a home without having to compromise on working-from-home habits. Taken together, these announcements show that there may be an opening for consumer electronics companies to meet this late-pandemic moment with new device categories.

Keep Reading Show less
Janko Roettgers

Janko Roettgers (@jank0) is a senior reporter at Protocol, reporting on the shifting power dynamics between tech, media, and entertainment, including the impact of new technologies. Previously, Janko was Variety's first-ever technology writer in San Francisco, where he covered big tech and emerging technologies. He has reported for Gigaom, Frankfurter Rundschau, Berliner Zeitung, and ORF, among others. He has written three books on consumer cord-cutting and online music and co-edited an anthology on internet subcultures. He lives with his family in Oakland.

Latest Stories