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CHIPS2AI is a powerful working group formed to better understand how modern labor markets and education and training providers can operate in a multi-dimensional hyper-change oriented talent ecosystem. We are developing what we call “whole sector analysis” modeling to move beyond traditional talent, training and placement and, instead, to look at variable and quick-turnaround methodologies to meet employer needs. We believe with AI and participating employers and institutions, the models can vastly improve.
Overview
The world as we know it is being remade in ways that were not imaginable a few years ago and is unprecedented. While we see small changes daily, these mask the huge changes coming about since all of human knowledge and much of human deception is now readily available as part of the foundational generative AI base of human activity ranging from gathering information, shopping to defense and deterrence.
This puts the leading nations of the world into a new arms race based on semiconductor innovation and AI re-making of critical parts of the economy, medicine, education and much more. As a national R & D nonprofit, NLET has formed the CHIPS2AI working group to help transform how talent, labor and education can support national efforts to get better chips faster to fuel better AI developments.
There are good reasons to model these changes within the semiconductor sector. First, the sector is collegial and there is a great deal of shared knowledge. Second, a great deal of federal funding will come into the sector with very little guidance in terms of training. Third,
while some companies are building their plants, others are speeding ahead and others laying piece off. All of this needs to be modeled in the most sophisticated and reliable ways aimed at servicing an industry at the highest end of technology and AI usage.
From 2011 to 2018, federal funding totaling $1.9 billion was spent in the Federal DOL—administered TAACCCT program designed to align community college courses and certification to regional employer needs. The program did not succeed at scale largely because of misalignment between course production and the changing nature of employer needs. NLET participated in several aspects of these projects and is cognizant of
needing not to repeat what failed and to search for models that move forward, not hold back, the sector.
Core Members
The CHIPS2AI Working Group is composed of companies, nonprofits and institutions.
