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Cepsa Química enhances product stewardship accuracy and efficiency by utilizing Amazon Bedrock.

Artificial Intelligence, Customer Solutions, Energy, Generative AI, Partner solutions, UncategorizedAugust 3, 202434Views0Likes0Comments
In this article, co-authors Vicente Cruz Mínguez, Head of Data and Advanced Analytics at Cepsa Química, and Marcos Fernández Díaz, Senior Data Scientist at Keepler, discuss the implementation of generative Artificial Intelligence (AI) as a transformative force in business industries. They key focus is on the how it impacts the energy sector, specifically, Cepsa Química…

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The dilemma of AI monetization continues to escalate as the expenses of OpenAI soar.

Energy, Microsoft, OpenAI, Opinions & Analysis, UncategorizedJuly 31, 202426Views0Likes0Comments
OpenAI, a prominent AI research lab, is at risk of a $5 billion deficit by the end of 2024 according to a report by The Information. Despite an income of $3.5 billion to $4.5 billion annually, the company has reportedly expended approximately $7 billion on developing AI models and $1.5 billion on staff costs. The…

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Materials that conduct protons could potentially lead to the development of novel eco-friendly energy solutions.

Artificial Intelligence, DMSE, Energy, Machine learning, Materials science and engineering, Research, School of Engineering, Sustainability, UncategorizedJuly 24, 202438Views0Likes0Comments
MIT engineers have identified new materials that could be more efficient conductors of protons – the nucleus of a hydrogen atom – which could pave the way for a number of climate-protecting technologies. Today's proton-conducting materials require very high temperatures, but lower-temperature alternatives could boost new technologies such as fuel cells that produce clean electricity…

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The AI technique dramatically accelerates the prediction of thermal characteristics of materials.

Alternative energy, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Energy, Machine learning, Materials science and engineering, MIT Schwarzman College of Computing, Nuclear science and engineering, Renewable energy, Research, School of Engineering, UncategorizedJuly 17, 202434Views0Likes0Comments
An international team of researchers, including members from MIT (Massachusetts Institute of Technology), has developed a machine learning-based approach to predict the thermal properties of materials. This understanding could help improve energy efficiency in power generation systems and microelectronics. The research focuses on phonons - subatomic particles that carry heat. Properties of these particles affect…

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Obtaining hydrogen from stones.

Alternative energy, Artificial Intelligence, Climate change, Department of Energy (DoE), DMSE, Energy, Faculty, Funding, Geology, Grants, Mechanical engineering, Renewable energy, Robotics, School of Engineering, Sustainability, UncategorizedApril 9, 202440Views0Likes0Comments
Hydrogen, one of the most abundant elements in the Universe, mainly exists alongside other elements. However, the discovery of naturally occurring underground pockets of pure hydrogen is increasingly attracting attention as an unlimited source of carbon-free energy. In fact, the US Department of Energy recently awarded $20 million in research grants to 18 teams to…

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Artificial Intelligence encounters environment issues: MIT’s 2023 Climate and Energy Hackathon

Artificial Intelligence, Cleaner industry, Climate change, Contests and academic competitions, Energy, Hackathon, Innovation and Entrepreneurship (I&E), Students, Sustainability, UncategorizedMarch 7, 202438Views0Likes0Comments
The MIT Energy and Climate Hack is an annual event that calls together students around the globe to come up with innovative solutions to the huge environmental challenges of our time. This year's hackathon took place between the 10th and 12th of November, and it was conducted both virtually and in-person at MIT's campus. The…

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AI Generation for Intelligent Grid Simulation

Artificial Intelligence, Climate, Computer modeling, Electrical Engineering & Computer Science (eecs), Energy, Funding, Grants, Laboratory for Information and Decision Systems (LIDS), Lincoln Laboratory, Machine learning, MIT Schwarzman College of Computing, School of Engineering, UncategorizedMarch 7, 202446Views0Likes0Comments
The Laboratory for Information and Decision Systems (LIDS) at Massachusetts Institute of Technology (MIT) has received a grant of $1,365,000 from the Appalachian Regional Commission (ARC). The funding supports LIDS's role in the "Forming the Smart Grid Deployment Consortium (SGDC) and Expanding the HILLTOP+ Platform" project. Made available through ARC's Appalachian Regional Initiative for Stronger…

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