familiar ai

Prakash Narayanan’s Familiar AI is Helping Medical Researchers

Let’s face it: there’s no doubt that artificial intelligence will be a major part of our future. That’s not really in question. What is in question is what that future will actually look like. 

If you’re expecting a future of robot servants who all look like Robin Williams’ character in Bicentennial Man, then you’re probably going to be disappointed. 

Instead, it’s much more likely that various existing technologies and platforms will be infused with AI tech, making our interactions with these technologies and platforms seamless and drastically more efficient and helpful. 

The range of possibilities is enormous, but what we’d really like to do here is focus on one particular entrepreneurial application of modern-day AI technology. This tool distills mass amounts of medical research on behalf of medical researchers to aid in the sale of tools for cancer researchers. 

This tool is called Familiar AI, and the man behind the project is Prakash Narayanan, an entrepreneur, executive, and multi-disciplinary engineer who sees almost limitless possibilities on the horizon for AI and the business leaders willing to embrace these possibilities. 

Prakash Narayanan 

Before getting to the utility and benefits of Familiar AI, we need to give our guest a proper introduction. 

For more than twenty years, Narayanan has been building and developing companies across numerous industries, including tech, finance, infrastructure, and energy. He has always been interested in the value that advanced tech can introduce to existing industries, and in that vein, AI and machine learning tech have been behind some of the biggest projects of Narayanan’s career. 

One of these projects from a few years back provided undeniable proof that AI could be used to create win-win scenarios for businesses and customers alike. 

“At Sale Tech, a company I founded in 2018, we developed the first real-time machine learning credit scoring system in Indonesia, which ingested data from existing local data sources as well as Android to provide credit scores that were able to reduce default rates dramatically.”

Previous traditional credit scoring methods in use in Indonesia depended on limited manual data sources, which made the process of credit analysis quite expensive. 

“By using machine learning algorithms to process large amounts of data in real-time, we were able to significantly increase the accuracy and efficiency of credit scoring, ultimately making credit more accessible and affordable for more people.” 

For Narayanan, this scenario, and the clear gains resulting from the use of machine learning, solidified his belief that similar technology could revolutionize just about any industry. 

The seeds were sown for Narayanan’s future work in the biotech space via Familiar AI. 

Familiar AI

Ok, so what is Familiar AI? In a basic sense, Familiar AI solves problems. But what problem is that? 

“Our clients currently sell tools to cancer researchers. These tools dramatically increase the success rate of drug discovery for cancer, and the salespeople who communicate these benefits to researchers are themselves PhDs.”  

So the information being communicated is complex, and the overall sales process requires the involvement of human experts. 

“Something like one million papers are published to Pubmed every year, of which roughly 20%, or two hundred thousand, deal with cancer. Our clients have to communicate to a large number of researchers, explaining a highly technical product in a digestible manner, showing relevance and know-how.” 

That’s a difficult and slow process, or at least it used to be, because now Familiar AI is making this process far easier. Familiar AI reads and comprehends scientific research and then prepares communications that are sent to researchers. 

“We then expanded on this to other technical, complex fields, which have high thresholds for efficient and relevant communication.” 

This isn’t an instance of AI encroaching on work that human staff enjoyed. This is work that was tedious and time-consuming for staff members. Now, staff can focus on the work best suited to their skills. 

It’s a novel application within biotech, but as Narayanan pointed out, Familiar AI and many other contemporary AI technologies are building on existing digital infrastructure that has made it all possible. 

“Modern AI and NLP [natural language processing] are really standing on the shoulders of giants. We rely on underlying cloud services like Azure, chips from Nvidia, APIs from OpenAI, and a host of open-source and proprietary frameworks.” 

These are the building blocks of the myriad AI applications that have recently come to prominence, and we’re only going to see more and more of these tools and applications as time goes on. This brings us back to that primary question: how will AI shape our future, and what will that future look like?

Future AI assistance 

In Narayanan’s opinion, AI will likely be deployed just about everywhere in the near future, which will, in turn, alter the way in which we interact with technology and tech-based services. 

The result? Better products and better services. 

“I expect AI assistance to be everywhere within the next couple of years. It is really going to be a reversal of the trend in human-computer interaction where we have spent decades going from high-quality human touchpoints to terrible clunky web interfaces. We’re going to be able to go back to getting someone on the phone immediately who can assist, and if the AI can’t solve it, it’ll hand it off to a human in the loop.” 

Narayanan feels this will be the trend across basically all service industries, from medical and legal services to banking, accounting, and even the DMV. 

Of course, there will also be additional AI deployments that specifically assist in sales, similar to the purpose of Familiar AI. But beyond business and sales, Narayanan also sees clear utility in the education space.  

“I expect besides sales, the biggest value add is going to be in education. There’s a lot of research showing that one-on-one instruction with spaced repetition can do wonders, and those tutoring tools will likely emerge by the end of this year.” 

We know you’ve heard this a hundred times by now, but AI-based tech really does present nearly limitless opportunities, and because of the ability of this tech to “learn” different skills and processes, it’s not limited to the tech industry. 

This doesn’t mean that every application of AI will be flawless from the start, but every application will also be a chance to learn, not only about the tech itself but also about how best it can serve businesses and customers. 

But the tech won’t do all the work. Entrepreneurs will have to step up to plate and make key decisions to establish and support these new applications. 

The new entrepreneur 

Asked whether he thinks experienced entrepreneurs will be able to make the switch to AI services, Narayanan told us that, if anything, new entrepreneurs with a fresh perspective will be better able to take advantage of what this technology really offers. 

“I think AI brings down the barriers to entry for entrepreneurship, and I specifically feel more experienced entrepreneurs are at a disadvantage if they try to do things the way they have always been done.” 

This doesn’t mean that all experienced entrepreneurs are bound to be left behind, but it does mean that relying on more traditional techniques could put those entrepreneurs, and their businesses, in jeopardy. 

For Narayanan, supporting AI efforts isn’t simply about being fascinated by the underlying technology. Instead, it’s very much about focusing on results. Right now, AI can provide better experiences and products to customers. 

“As an entrepreneur, you really have to de-fetishize any single technology in order to do the best thing for your customer, regardless of technology. If there’s a technology that benefits my customers, then I’m interested.” 

In a way, this summarizes Narayanan’s commitment to AI and his enduring belief that it will continue to be a focus for the tech industry and tech industry professionals for the next ten years.  

But you don’t need to wait that long to see the value of AI in action. Outside of ChatGPT and the wide range of image-generation services already available to the public, many services are now integrating AI to aid in sales and customer service. 

Entrepreneurs and entire industries are eager to make use of AI and machine learning, and Familiar AI is just one example of how the tech can make services better for service providers and for us as well.