It was exciting to attend the "Codex World's Top 50 Innovators 2024". Most of today's day was spent on artificial intelligence and robotics. Meeting and listening to the world’s top #11 Innovators in 2024 out of the #50 was fascinating. The event was supported by The University of Chicago Booth School of Business in London and Blancpain. https://lnkd.in/e87ruAas
In picture:
Toby Lewis, Global Head Threat Analysis, Darktrace, Pinar Ozcan, Professor of Entrepreneurship and Innovation, University of Oxford, Edward Challis, Head of AI Strategy, UiPath, Dinesh Nayar, Managing Director, Creator Studio | H&M Group, Maryam Fayaz-Torshizi, CEO, DeepSearch Labs, Maksim Sipos, Chief Scientific Officer, causaLens, Dr. Robin Tuluie, Founder and Co-CEO, PhysicsX, Philip Davies, President, EMEA, Siegel+Gale, Kurt House, CEO, KoBold Metals, Michael Brown, Chairman and CEO, Skyline Robotics, John Hutt, Head of Culinary Engineering, REMY Robotics, Zaki Hussein, CEO, Touchlab Limited
A few predictions included:
“The world will move to AI-enabled defender vs AI-enabled attackers, and the good guys will win” - Toby Lewis
“Open banking and data-driven competition in finance will increase the Big Tech prominence in this and other fields.” - Pinar Ozcan
Fragmented and incomplete internal data, limiting complete analysis, was an issue. With a large amount of public data, finding essential information and reaching conclusions were equally challenging. In contrast, data issues that hurt the reliability of machine learning algorithms and the lack of privacy and understanding of how they work are considered problems today.
Maryam Fayaz-Torshizi predicted that human-created content will be at a premium in the next five years. Original discovery will become so important. Original content watermarking will become a norm, and AI-generated content classification will become necessary. At the same time, new architecture will be required for large generative algorithms that current models were too dense and costly. Decentralised models are the future for large models, while small models will be more critical. Encryption will become even more vital for companies that like to upload their data into systems. Mano-Amano, who owns the data, will be even more critical. Maksim Sipos pointed out that AI and machine learning models had fundamental problems in that they are pattern-matching machines, and they mistake correlation for causation, which can lead to devastating consequences. The concept of causual AI models differentiates cause and effect. They are robust, explainable, fair, and trustworthy, providing information to help us make correct decisions. The future is not #GenAI but #CausalAI.
Thank you Michael Charles Borrelli CoCEO/COO, AI & Partners for inviting me to the event.
#aiforall #aiforbusiness #aiinnovators #aiforgood