Hult Prize Foundation, London
Mentoring student startups on the year's energy theme, aimed at improving the lives of ten million people.
deepkapha.ai was delighted to mentor over 40 startups, where the theme was energy and how it could improve the lives of at least ten million people worldwide.
We mentored startups focused on solar, wind, agriculture, water and marine life, sharing how AI is set to electrify industries at scale, and helping founders adopt the AI mindset as they built their hardware, software and services.
The flip charts survive, and they show the method. Every board opens the same way: "#1. Problem statement. Why is this problem here? What is the governing thought, the key question we want to answer? #2. Your hack." Then the founders had to answer it in front of everyone. One board works air pollution back to transportation waste and pre-manufacturing, and lands on a clever wrapper sold B2B with three to six months to market. Another splits into three columns, hardware, software and services, ticks hardware and a prediction and notification service, writes "marine life, machine learning, deep learning" in the margin, and draws a product roadmap that puts a working web app before any model at all. A third maps a utility from R&D through operations to customer touchpoints, with ML and AI entering at the point where the meter data does.
The mentoring roster for one room alone listed twenty-one ventures against three mentors, a session each. Askova, Phyta, SolenX, Empower Energy, Harvest, Impact Rays, Sulis, goTeff, Living Waters, Noor Medical, SunRice, mPower, Post-Harvest, TerraKer, Pro-Shield, Solartix, U-Light, Lumbrick, TechFarm and the rest. Almost none of them needed a lesson in machine learning. What they needed was someone to ask why the problem was there.
A fourth flip chart, the scoring board for one mentoring room, is held back: it ranks named ventures from top to bottom.
