Artificial Intelligence as a Service (AIaaS)

AI as a service has allowed individuals and companies to experiment with AI for various purposes without large initial investment and with lower risk.

Could 2020 be the year AI as a Service takes off?

Get insights on how AI leads to greater efficiencies and better customer insights for businesses in nearly every industry.

Conversation with Bindu Reddy (CEO & Co-Founder, moderated by Milind Kopikare (President – North America, Great Learning) on how AI as a service can improve a company’s odds of experiencing success.

Watch the full webinar here:

Excerpts from the interview:

[Milind]: 08:32 

Could you help give us an idea about what is AI as a service, especially for the novices amongst us?

[Bindu]: 8:42

Let’s take an instance from a decade or so ago about how people built a website or how they built any kind of software. Basically, they had to rent some servers from somewhere, buy their own servers, and then start building all of the software packages you need on that machine. Then they started building all the applications required on top of those software packages. All this would take 40-50 engineers at that time and today it hardly takes three-four engineers. But now as we fast forward to 2020, to do the same you go to AWS, swipe your credit card, and you get started right there!

You can get your machines on a second per hour basis as well and you no longer need to set up your Oracle database. You can simply use Amazon’s service and save millions of dollars. So what I am trying to say here is that the next generation is not just about building your application, it is actually going to be about creating a string of machine learning models. Today’s applications are rule-based, tomorrow’s applications are going to be powered by a bunch of machine learning models which are going to make decisions on real-time data. Companies like Netflix, Airbnb, and YouTube are great examples of this.

[Milind]: 16:08  

As we all see the influx of folks coming from non-technical backgrounds in the healthcare or financial services industry, and we can see that companies are increasingly adopting AI as a service, but is there any one industry that you think stands out in this scenario?

[Bindu]: 16:39

It’s obvious that companies like Google, Facebook, and Amazon have taken a very AI-first approach. This is one of the main reasons why these top tech companies are at a trillion dollar evaluation. They get a virtuous feedback cycle which kicks in and we recently saw a customer who tried out an A/B test on one of our recommendation models, and they literally saw a 25% increase in their revenue based on one model! 

So yes, deep tech has adopted AI as a service in a big way but apart from it, the other sector which has adopted machine learning quite a bit is Finance. I mean obviously, a lot of our banks use some machine learning model like hedge funds are right up there in terms of really trying to crunch numbers or predict stock prices. But, I’d still say that for banks and finance companies, it’s a little bit of a double-edged sword because unlike big tech that has managed to keep up with the evolution and innovation that is happening in AI, banks have suffered from a very interesting phenomenon and even though they adopted the approach early, they have not evolved at the same pace as the tech giants and are struggling in some ways to move to the modern deep learning techniques. 

On the other hand, if you look at digital media and eCommerce, even though they are old school in some ways as compared to the big tech, they are actually beginning to adopt the more modern kinds of AI techniques like Churn Reduction and User Engagement Revenue.

[Milind]: 21:09 

With Amazon’s AWS, Google’s Cloud, and now with Abacus throwing so much money at building ready to go services and everyone saying that this landscape will see more growth. How do you think that landscape is evolving? Do you think there is a cloud in these big cloud wars that’s going to just build every single AI algorithm and be the one-stop shop for AI as a service?

[Bindu]: 22:10 

It’s a very good question. Even I’ve thought about it a lot and wanted to give you the same type of analogy. Let’s go back a little in the past and look at the evolution of enterprise software. We started with the king of enterprise software: Oracle, and the reason Oracle became what it did was because it had their database which was their flagship product, but if anybody goes to their website, you’ll see that they had two or three hundred products, not just the database! They also had a big sales force and they’d make use of that to get into a particular company, sell them the database but also all of the other enterprise products. Some of their products were great and some were just about okay, but people still bought them because you had the purchase order open. Companies had a way to get software from Oracle and overtime what happened was that the clouds took over. 

Now you have Amazon, Azure, Google which perform phenomenal tasks. But in the case of these big three, once you go into one cloud, it’s very difficult for you to move from like AWS to GCP to Azure but startups actually operate on all three clouds so it is a multi-cloud strategy. So, I actually see a big opening for startups to be cloud infrastructure startups in AI, analytics, database, and of course, Abacus is one of them.

Want to know more about this interesting conversation? Watch the full video to learn more about AI as a service in different industries and its future.

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