AI News caught up with president of Ikigai Labs, Kamal Ahluwalia, to discuss all things gen AI, including top tips on how to adopt and utilise the tech, and the importance of embedding ethics into AI design.

Could you tell us a little bit about Ikigai Labs and how it can help companies?

Ikigai is helping organisations transform sparse, siloed enterprise data into predictive and actionable insights with a generative AI platform specifically designed for structured, tabular data.  

A significant portion of enterprise data is structured, tabular data, residing in systems like SAP and Salesforce. This data drives the planning and forecasting for an entire business. While there is a lot of excitement around Large Language Models (LLMs), which are great for unstructured data like text, Ikigai’s patented Large Graphical Models (LGMs), developed out of MIT, are focused on solving problems using structured data.  

Ikigai’s solution focuses particularly on time-series datasets, as enterprises run on four key time series: sales, products, employees, and capital/cash. Understanding how these time series come together in critical moments, such as launching a new product or entering a new geography, is crucial for making better decisions that drive optimal outcomes. 

How would you describe the curren