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Home›Japan company›California Machine Learning Company Using Quantum Computers at Mathlabs Ventures Builds First Q40 ME Fusion Energy Generator Using Advanced AI and Neural Networks

California Machine Learning Company Using Quantum Computers at Mathlabs Ventures Builds First Q40 ME Fusion Energy Generator Using Advanced AI and Neural Networks

By Jane R. Chase
January 10, 2022
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Harvard mathematicians using artificial intelligence, machine learning, blockchain and neural networks on a quantum computer have developed groundbreaking algorithms and simulations that will allow the world’s most efficient fusion power plants to be opened 20 years earlier than expected with a Q40 mechanical gain by Kronos Fusion Energy algorithms

KFEA – LOGO

KFEA – LOGO

KFEA – LOGO

IRVINE, Calif., Jan. 10, 2022 (GLOBE NEWSWIRE) – Kronos Fusion Energy Algorithms LLC (KFEA-Q40) and MathLabs Ventures today announced that after 60 years of global research, the fusion energy industry is Now Ready to Accelerate Growth Quickly build commercially viable power plants 20 years ahead of schedule due to three recent major technological advancements. The three major issues for achieving commercial success in fusion energy have recently been overcome with these three new technological advancements which together will enable efficient fusion energy power plants to be built on Earth by the mid-2000s. 2030. These innovations, pending contracts and patents place KFEA’s current valuation at $ 530 million with $ 1.2 billion in projected profits over the next 2 years.

“At Kronos, we 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, CEO of Kronos. Fusion energy algorithms

Recreating the power of the sun on earth in a controlled manner requires computational power, machine learning, artificial intelligence, blockchain, quantum computers, neural networks, and other technological advancements that are not yet unheard of. hadn’t even dreamed of 60 years ago when fusion energy research began on a global scale. But now, with these three technological breakthroughs, the global competition to design next-generation fusion power plants that are more efficient than today’s carbon-fired power plants is in full swing.

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

The second technological barrier that was overcome in September 2021 was the announcement of the most powerful magnet ever created on earth (https://news.mit.edu/2021/MIT-CFS-major-advance-toward- fusion-energy-0908). It is the first sufficiently powerful magnet capable of containing a rapidly moving plasma field at temperatures above 150 M degrees Celsius without touching or melting the containment barrier.

The third technological barrier that has been the most difficult to overcome is the 1% efficiency rate (mechanical gain Q1) of the best fusion energy demonstration reactors on earth today. The first two breakthroughs will allow the world’s best fusion energy designers to achieve an efficiency rate of 25% (Q25 mechanical gain) by 2050. This has been a major technological barrier as there is no reactor-to-energy solution. no merger has been proposed in the world. which exceeds 25% efficiency so far.

Kronos Fusion Energy Algorithms LLC announced that after five years of studying global fusion energy research, we have developed advanced algorithms and simulations to achieve 40% efficiency rate (mechanical gain Q40) for commercial fusion energy power plants, which will allow an advance in the launch dates of the world’s first fusion energy power plants that are more efficient than today’s coal-fired power plants. Our algorithms and simulations use artificial intelligence, machine learning, neural networks, blockchain, quantum computing, and other advancements to reduce the error rate in a fusion energy reactor relative to the rate 15% error known today at the International Thermodynamic Experimental Reactor (ITER) in France. at an error rate of 1% after our simulations have optimized the many variables to identify the disturbances causing 31% of ITER maintenance shutdowns.

Kronos fusion energy algorithms: development of ALGORITHMS and SIMULATIONS to build microfusion energy generators with Q40 mechanical gain for a CLEAN + LIMITLESS energy future

CONTACT WITH THE MEDIA:

GUÉ DE PRIYANCA

Founder and Chief Strategy Officer at Kronos Fusion Energy Algorithms

[email protected]

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Kronos Fusion Energy Algorithms Q40 Efficiency.png

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Image 1: KFEA – LOGO

Kronos fusion energy algorithms

This content was posted through the press release distribution service at Newswire.com.

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