A Marketplace for Artificial Intelligence
GenesisAI is creating a global network for Artificial Intelligence. This market, valued at $230 billion in 2017, is expected to reach $5.5 trillion by 2027.
Essentially, this company will soon enable anyone to buy and sell AI technologies at scale. It’s created a marketplace for AI-related products and services — an “Amazon for AI.”
This marketplace connects companies in need of AI services, data, and models with companies interested in monetizing their AI technology. Initially, GenesisAI is focused on the asset management space and, in the wake of Covid-19, the healthcare sector.
GenesisAI aims to lay the foundation of what’s known as Artificial General Intelligence, as opposed to Narrow AI. Here’s the difference:
Narrow AI consists of codes that perform a certain task, such as image or speech recognition, which are two tasks typical of the human brain. Artificial General Intelligence, or “AGI,” is the combination of these narrow tasks. The ultimate goal is creating a mastermind that can perform any task the human brain can.
The idea for its marketplace came when the team behind GenesisAI was scaling its previous startup called Palatine Analytics. This company sold AI-powered employee performance monitoring systems.
It was then that the team learned that AI development is hindered by two fundamental problems:
1. AI development is expensive.
2. Independent AI developers can’t monetize or share their code.
There are only about 10,000 AI developers in the world. And 99% of companies can’t afford to hire their own team of AI engineers to create in-house AI applications. Nor do they have enough technical capabilities to determine from which open-source options to use existing AI technologies.
The bottom line: there is no way for AI developers to exchange data, learn from each other, leverage their capabilities, and trade services. In other words, AI is operating in a closed environment — until now.
Neil Flanzraich, former President of Ivax Corporation (acquired for $10 billion) and an Executive Committee Member of Syntax Corporation (acquired by Roche for $5.3 billion) had this to say about GenesisAI:
“GenesisAI is fighting back against AI oligopolies by creating the first open access marketplace of AI that does not exclude or discriminate against anyone. Its benefits will be shared by all.”
With its marketplace, GenesisAI provides the protocol that enables people to make transactions on the platform. And it takes 30% of each transaction’s value.
GenesisAI has completed a beta version of its service. It has agreements with 20 supply-side firms who wish to place their products on its marketplace. It also has agreements with 25 demand-side firms who wish to purchase these products.
As mentioned, the company has recently joined the fight against Covid-19. It’s gathering AI technologies to develop detection, testing, diagnostic, and treatment capabilities. Its initial focus will be on:
• AI that identifies people who are at high risk of getting really sick if infected.
• AI that predicts future outbreaks.
• And AI that simulates the impact of different government policies.
Prior to starting GenesisAI, Archil was CEO of Palatine Analytics, a company applying Artificial Intelligence to employee performance analytics software.
Before that, he was Vice President of AI with IDFEC, a venture capital firm and startup incubator, and an advisor with Bridgewater Associates, an investment management company.
Archil earned his Bachelor’s degree in Economics from Harvard.
David earned his Bachelor’s degree in Applied Mathematics and Computer Science from Harvard.
After graduating, he worked for Dataminr, an internet services company. From there, he worked as a software engineer with Applied Predictive Technologies, a computer software company.
Notably, he spent nearly four years as a software engineer with Google. Most recently, he was a software engineer with Prelay, a computer software company.
Mina has published multiple scientific papers throughout his career and raised more than $1 million in research grants.
He earned a Master’s degree in Computational Science and Engineering, as well as a Ph.D. in Applied Physics, from Harvard.