Nvidia CEO: “Software is eating the world, but AI is going to eat software”
- by 7wData
Tech companies and investors have recently been piling money into Artificial Intelligence—and plenty has been trickling down to chip maker Nvidia. The company’s revenues have climbed as it has started making hardware customized for machine-learning algorithms and use cases such as autonomous cars. At the company’s annual developer conference in San Jose, California, this week, the company’s CEO Jensen Huang spoke to MIT Technology Review about how the machine-learning revolution is just starting.
Nvidia has benefitted from a rapid explosion of investment in Machine Learning from tech companies. Can this rapid growth in the use cases for Machine Learning continue?
We’re very early on. Very few lines of code in the enterprises and industries all over the world use AI today. It’s quite pervasive in Internet service companies, particularly two or three of them. But there's a whole bunch of others in tech and other industries that are trying to catch up. Software is eating the world, but AI is going to eat software.
What industry will be transformed by machine learning next?
One is the automotive industry. Ten of the world’s top car companies are here with us at the conference. The second is health care, and the impact on society is going to be very great. Health information is messy and unstructured, but now computers can understand it to augment doctors’ diagnoses and predictions.
Recent research results from applying machine learning to diagnosis are impressive (see “An AI Ophthalmologist Shows How Machine Learning May Transform Medicine”). But it’s not clear how regulators will test and approve these new kinds of systems.
When we're talking about human lives, there are always regulatory challenges. But we can't ignore the impact of a technology that brings 10 or 1,000 times better results. I have confidence that reasonable minds will realize the benefits of this technology and put it in the hands of doctors and clinicians and radiologists so that they can do better work. Arterys recently got FDA approval for their cardiac imaging [which annotates scans of the heart], and I know of many others that are in the pipeline.
Using machine learning in cars will also create new challenges for regulators. Nvidia has demonstrated software that learns to drive just by watching what a human driver does—but it’s difficult to explain exactly how it works or would behave in different scenarios (see “The Dark Secret at the Heart of AI”).
[Social9_Share class=”s9-widget-wrapper”]
Upcoming Events
Strategies for simplifying complex Salesforce data migrations – Free Webinar
27 March 2024
5 PM CET – 6 PM CET
Read MoreCategories
You Might Be Interested In
Machine learning and microbes: How big data is redefining biotechnology
30 Dec, 2016Machine learning and artificial intelligence are all the rage today in venture capital circles. We’ve seen spectacular exits in the …
The Ultimate Guide to Delivering BI Solutions
21 Feb, 2017Imagine that you’re at the very end of a long development process of a BI solution for internal users within …
How Blockchain Is Changing the Way We Protect and Track Our Identities
24 Dec, 2017Although we are very much still in the early stages, blockchain technology is already beginning to show signs of its …
Recent Jobs
Do You Want to Share Your Story?
Bring your insights on Data, Visualization, Innovation or Business Agility to our community. Let them learn from your experience.