1Mby1M Virtual Accelerator Investor Forum: With T.M. Ravi of The Hive (Part 2)

Sramana Mitra: Can you take us through a couple of your portfolio companies that are really interesting? What can we learn from them?

T.M. Ravi: In the Internet of Things space, the big shift is the growing commoditization of devices. Much of the value is moving to applications and data. That commoditization is not just happening on the consumer level but also on the industry level.

As economies like China become better and better at manufacturing, companies like GE realize that the $50-million rotating devices like turbines are being produced with pretty good quality in other countries also. There’s the general shift towards applications and data. One of our companies, FogHorn, is basically going after the second phase of the Internet of Things.

In the first phase, devices will be connected directly to the Internet and tend to send all their data through the Internet. Applications will process it there. Analytics will reside in the cloud. That will generally work for consumer devices. The challenge with industrial devices is that they produce a lot of data. There isn’t an opportunity to send all that data to the cloud.

FogHorn basically is an ambient computing solution. It’s a solution that plays in the edge, very close to the sensor or the machine. It’s doing analytics and applications right next to the device. You can locally process a large subset of the data before it goes to the cloud. Only a small subset of data goes to the cloud. It’s very important for bandwidth and real-time responsiveness.

Sramana Mitra: Where is FogHorn finding traction? What kinds of customers are at the cutting-edge of adopting a technology like this?

T.M. Ravi: Much like many of our companies, we try to find a strong go-to market partner. FogHorn has partnered with GE and has now been adopted as part of GE Predict, which is GE’s end-to-end solution for the industrial Internet. Because it is part of Predict, it is going after a lot of GE business units as well as non-GE business units both as part of Predict and then selling it directly.

Sramana Mitra: You said you have another case study that you want to share.

T.M. Ravi: Yes, it’s in the security space called E8 Security. They assume that the threats are already inside the enterprise, which happens to be the case with 100% of enterprises. What they’re doing is taking a variety of different sources of data in the enterprise – network data, endpoint data, user behavior data – and putting it all in a big data infrastructure, such as Hadoop. They run different analytic models to score threats and to be able to detect, using machine learning techniques, potential breaches in the enterprise.

Sramana Mitra: Switching a little bit, I’d like to look at some of the broader issues that society is facing going forward. What is your estimate of the timeframe in which artificial intelligence deeply penetrates industry and society at all levels?

T.M. Ravi: I see that happening very soon – in the next five to ten years, whether it’s service robots or autonomous vehicles. There was this BPO wave where a lot of the jobs went from US to other countries where there was a cost advantage. Now you’re seeing a lot of that done by software robots. This is not just on the consumer side. You’re also seeing it in the enterprise.

I think that change is happening much faster than a lot of people think. We’re going to see very real use cases in our lives in the next three to five years. These are going to be clunky and not very intelligent in the beginning. We’ll really substantially improve over the next 10 years.

Sramana Mitra: Everybody is talking about self-driving cars. Technically, self-driving cars are far along at this point. It is within striking distance to put self-driving cars on the road. I’m not convinced that, from a regulatory point of view, this is going to go through. What do you think?

T.M. Ravi: It’s not just cars or drones. You’re going to see significant regulatory, ethical, and societal issues and challenges with many of these applications of AI. In the case of self-driving cars, the next big frontier is navigation in the midst of obstacles and dynamic environment – navigation that is computer vision-based but uses other sensors also. There’re a lot of advances there. I totally agree with you. The whole regulatory framework has to catch up.

This segment is part 2 in the series : 1Mby1M Virtual Accelerator Investor Forum: With T.M. Ravi of The Hive
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