- Tell us about the business you represent, what is their vision & goals?
- Can you share a little bit about yourself and how you got into the field of artificial intelligence?
- What do your day-to-day responsibilities look like at your organisation?
- Can you share some of the proudest achievements you've experienced in your career?
- Which industries and processes do you see as the greatest opportunities for applying artificial intelligence?
- What are the most significant changes you expect to see in business due to AI?
In the latest instalment of our interviews speaking to leaders worldwide in tech, we’ve welcomed Mady Mantha, CTO and co-founder of Happypillar.
I’m one of the founders of Happypillar, a digital therapeutic app that provides evidence-proven behavioural intervention, leveraging machine learning and the expertise of in-demand but expensive and waitlisted clinical play therapists to offer real-time personalized feedback. Our mission is to bring digital mental healthcare to families everywhere.
Can you share a little bit about yourself and how you got into the field of artificial intelligence?
I studied mathematics and computer science at college. As a child of immigrants, it was expected of me to go to graduate school. I was always interested in the intersection of law and technology so I applied to law school but the thought of working 100 hours a week for a Big Law firm for years before ever actually doing anything cool and interesting with technology seemed like a circuitous path.
I ended up not going to grad school, much to my parent’s chagrin. I joined a startup that was pushing the boundaries of intelligent search, natural language processing and language AI. I loved building, I loved the chaotic energy of a startup, and I loved working on something that I was passionate about. I learned a ton and I eventually worked on recommender systems, goal-oriented dialogue systems, and other machine-learning solutions to large-scale enterprise problems at other startups and multinational corporations.
As the CTO of Happypillar, my favorite part of my day is when I’m strategizing with our team about how to make our AI models as nuanced as necessary to support our families. Having worked on conversational AI for customers of large corporate entities, it’s so fulfilling to be working on problems that can have a deep impact on families, children and their futures.
But day-to-day, my responsibilities are varied. Because we offer a mobile app, often I’m developing or testing aspects of that app. In addition to architecting our technology, I also spend time analyzing our anonymized conversation data, to sharpen our models. And at other times, because we’re such a small organization, I’m involved with less technical aspects of our growth, like our go-to-market strategy, partnerships, and marketing.
If you’d asked me this question a few years ago, I may have told you my proudest moment was keynoting events like the Microsoft Conversational AI Summit in 2018, speaking for a crowd of over a thousand engineering leaders. After I spoke, the line to speak to me was dozens of people long. I might have thought my proudest moment was when my work on Walmart’s conversational AI strategy was featured in the Wall Street Journal. But after this year, I believe my proudest moment is when one of our Happypillar users delivered some feedback and included a picture of his daughter, and told us “Thanks for helping her.”
Which industries and processes do you see as the greatest opportunities for applying artificial intelligence?
AI is really good at any process or industry that has a lot of patterns or data. Things like forecasting financial projections, inventory, or weather patterns. It’s good at language translation, large computational problems, and sometimes even coding. Industries like manufacturing, banking, healthcare, eCommerce, cybersecurity, and customer service can benefit from AI in many ways.
I’m not so sure about applying AI to problems that require intuition and split-second pivots like driving, surgery writing, or open-ended and nuanced conversations. I’d also add that even if AI could be applied to these problems, we still need human supervision.
I think we’ll start to see more ways to use AI to enable data-driven decision-making in all major industries. We’ll also start to see AI being used to mitigate risk, like cyber threats, forecasting, and data modelling, in certain industries. AI will also augment human processes by automating mundane, repetitive tasks, thereby freeing up people to focus on innovation.
What is your experience with using AI-backed data analysis or log management tools? What do you think is the benefit of using a log management tool that has machine learning capabilities for an organisation?
I’ve used log management tools before when I consulted with several corporate entities. They can automatically detect anomalies, and help with predictive maintenance, streamlined troubleshooting, and root-cause analysis. Log management tools can identify security threats and suggest proactive measures to prevent said attacks.
Additionally, Machine learning can be used to monitor log data for compliance with regulations and industry standards, such as PCI DSS and HIPAA. Lastly, they can be more cost-effective than manual log analysis.