AI Insights, Insights

TurinTech Co-Founder and CEO Dr. Leslie Kanthan recently joined the Legislate Podcast  to discuss all things AI with podcast host Charles Brecque. Leslie dove into how TurinTech’s evoML platform is making machine learning models more sustainable, future plans of the company, and how AI technology can help make the legal processes more efficient. 

Continue reading to find out more about the topics that were discussed.


How does TurinTech Optimise AI?

TurinTech enables businesses and organisations to build efficient and scalable AI at speed through automating the whole data science life cycle. We optimise the underlying code through our evoML platform. Essentially, machine learning models can be broken down into code, and we perform the optimisation at the code level.

We also achieve optimisation by using parameter optimisation, and a lot of other techniques that encompass that end-to-end. We have published various research papers on code optimisation and use specific, one-of-a-kind AI techniques through the evoML platform, which we have developed. 


Why would companies want to optimise their machine learning models?

With the recent advance of big data, and the sheer volume of data, a lot of data scientists require efficient tools so that they can augment their capability. A data scientist’s job is to generate models, and the business analyst’s job is to use those models to get insights. A trader’s job is to use those models to develop profitable trading strategies. A lawyer’s job is to use those models to see if he can match some of the text data from the file to the correct fee earner. Everybody’s using models. It’s not just in the financial services or tech industry.


TurinTech essentially makes those models more accurate, and more efficient. One of those key areas is in terms of sustainability. To generate models is a very computational-intensive process, and that can be very costly, in terms of GPUs and electricity consumption, etc. TurinTech’s AI optimisation platform, evoML, has been scientifically proven to be able to successfully optimise code while reducing the energy consumption of the device or tool that is running that code. AI can therefore help improve companies’ sustainability goals. 


What is the best part of being an entrepreneur?

At TurinTech, we have some of the best PhD and professor-level machine learning scientists working with us to build out our IP, effectively making our optimisation even more accurate and efficient. That’s one of the best parts of leading the company, working with a talented team, and exchanging knowledge and ideas. 


What do you wish you knew before founding TurinTech?

There’s more to artificial intelligence than what we initially thought. There are a lot of people who may not have a technical background, or an AI background, who are very interested in learning more about AI and its applications. If we had known this earlier we would have had more opportunity to engage in earlier discussions and attend networking events, and know more about those use cases earlier on.


Where will TurinTech be in 3-5 years?

We see TurinTech becoming an AI workbench that empowers companies to build their own AI solutions. You have Microsoft Office for documentation processing, DocuSign for document signing, Tableau for charting. What do we have for building AI? Our vision is to meet all those needs through AI optimisation and our continuous research.


How can AI assist businesses when it comes to legal contracts?

Contract processes tend to be very long in general. There can be many pages that require a lot of interaction from many different people in the team. It can involve somebody from the tech side, most often the legal side, and interacting with lawyers. There’s a lot of back and forth with lawyers to understand some of the terms and to see if there are any terms that we want to change and propose.


You can make this entire process way more smooth and efficient with the help of AI technology. AI will assist in reading the text, and achieve customisation using natural language processing to adapt to the needs of a potential client. This will then limit or even avoid the need for a lawyer altogether. 

To find out more, listen to the full podcast episode here. To stay up to date and follow our progress, check out our LinkedIn and Twitter.