A Machine Learning Company In California Using Quantum Computers At Mathlabs Ventures Is Building The First Q40 ME Fusion Energy Generator Using Advanced AI & Neural Networks

Harvard Mathematicians using Artificial Intelligence, Machine Learning, Blockchain and Neural Networks on a Quantum Computer have developed breakthrough algorithms and simulations that will enable the world’s most efficient Fusion Energy Power Plants to be opened 20 years earlier than planned with a Q40 Mechanical Gain by Kronos Fusion Energy Algorithms

Kronos Fusion Energy Algorithms LLC (KFEA-Q40) and MathLabs Ventures announced that after 60 years of global research, the Fusion Energy industry is now poised to accelerate their growth rapidly to build commercially viable power plants 20 years earlier than planned because of three recent major advances in technology. The three major problems with reaching commercial success in Fusion Energy have recently been overcome with these three new technological advancements that together will make it possible to build efficient Fusion Energy Power Plants on Earth by the mid-2030s. These innovations, ongoing contracts & patents put KFEA’s current valuation at $530m with $1.2B in projected earnings over the next 2 years.

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“We at Kronos are building a world-class team of mathematicians, physicists, scientists and other professionals whose mission is to reverse global warming by helping to make  Fusion Energy commercially viable in the near future,” said Michael Pierce Hoban, the CEO of Kronos Fusion Energy Algorithms

Recreating the power of the sun on earth in a controlled manner takes computing power, machine learning, artificial intelligence, blockchain, quantum computers, neural networks, and other technological advances that were not even dreamed of 60 years ago when Fusion Energy research began globally. But now, with these three technological breakthroughs, the global competition to design the next-generation Fusion Energy Power Plants that are more efficient than today’s carbon-burning power plants is underway in full swing.

The first technological barrier that was overcome is that the computing power now exists to model the sun in simulations more accurately with the launch of the Summit Supercomputer in Oak Ridge that set the world record in 2018, and in June 2021, Japan’s Fugaka Supercomputer set a new world record of 422 petaflops.

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The second technological barrier that was overcome in September 2021 was the announcement of the most powerful magnet ever created on earth. This is the first magnet with enough power capable of containing a fast-moving plasma field at heats in excess of 150M degrees Celsius without touching and melting the containment barrier.

The third technological barrier that has been the most difficult to overcome is the 1% efficiency rate (Q1 Mechanical Gain) of the top fusion energy demo reactors on earth today. The first two breakthroughs will enable the world’s top Fusion energy designers to reach a 25% efficiency rate (Q25 Mechanical Gain) by 2050. This has been a major technological barrier because there has been no fusion energy reactor solution that has been proposed in the world that exceeds 25% efficiency until now.

Kronos Fusion Energy Algorithms LLC announced that after five years studying the global research in Fusion Energy, we have developed advanced algorithms and simulations to achieve a 40% efficiency rate (Q40 Mechanical Gain) for Commercial Fusion Energy Power Plants that will enable a 20-year advancement in the launch dates of the world’s first Fusion Energy Power Plants that are more efficient than today’s carbon burning power plants. Our algorithms and simulations use Artificial Intelligence, Machine Learning, neural networks, blockchain, quantum computing and other advances to reduce the error rate at a Fusion Energy Reactor from the 15% error rate experienced today at the International Thermodynamic Experimental Reactor (ITER) in France to a 1% error rate after our simulations have optimized the numerous variables to identify the disruptions that cause 31% of the maintenance shutdowns at ITER

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