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Inside Trump’s Long-Awaited AI Strategy

Welcome back to In the Loop, TIME’s new twice-weekly newsletter about the world of AI.

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President Trump will deliver a major speech on Wednesday at an event in Washington, D.C., titled “Winning the AI Race,” where he is expected to unveil his long-awaited AI action plan. The 20-page, high-level document will focus on three main areas, according to a person with knowledge of the matter. It will come as a mixture of directives to federal agencies, with some grant programs. “It’s mostly carrots, not sticks,” the person said.

Bifacial thin-film solar cells harness sunlight from both sides for higher output

A research team successfully implemented CuInSe2 thin-film solar cells composed of copper (Cu), indium (In), and selenium (Se) on transparent electrode substrates. Furthermore, the team developed a “bifacial solar cell technology” that receives sunlight from both the front and back sides to generate power. This technology can be fabricated at low temperatures, enabling a simpler production process, and is broadly applicable to building-integrated solar power, agricultural solar power, and high-efficiency tandem solar cells in the future.

Audacious Idea That America Is Going To Have An Unnerving Sputnik Moment When It Comes To Attaining AGI And AI Superintelligence

Will the United States be the first to attain AGI and ASI? Most assume so. But that’s not guaranteed. Here’s what people are saying. It’s the inside scoop.

AI vision, reinvented: Vision-language models gain clearer sight through synthetic training data

In the race to develop AI that understands complex images like financial forecasts, medical diagrams and nutrition labels—essential for AI to operate independently in everyday settings—closed-source systems like ChatGPT and Claude currently set the pace. But no one outside their makers knows how those models were trained or what data they used, leaving open-source alternatives scrambling to catch up.

Now, researchers at Penn Engineering and the Allen Institute for AI (Ai2) have developed a new approach to train open-source models: using AI to create scientific figures, charts and tables that teach other AI systems how to interpret complex visual information.

Their tool, CoSyn (short for Code-Guided Synthesis), taps open-source AI models’ coding skills to render text-rich images and generate relevant questions and answers, giving other AI systems the data they need to learn how to “see” and understand scientific figures.

Translating the m6A epitranscriptome for prostate cancer

Mapping the N6-methyladenosine (m6A) transcriptome in prostate cancer has established its clinical potential value as a prognostic biomarker for this disease. A multidisciplinary approach that integrates genomics, transcriptomics, epitranscriptomics, proteomics and clinical oncology is essential to translate the intricacies of m6A modification into tangible benefits for patients.

Goodbye plastic? Scientists create new supermaterial that outperforms metals and glass

Scientists at Rice University and University of Houston have developed an innovative, scalable approach to engineer bacterial cellulose into high-strength, multifunctional materials. The study, published in Nature Communications, introduces a dynamic biosynthesis technique that aligns bacterial cellulose fibers in real-time, resulting in robust biopolymer sheets with exceptional mechanical properties.

Plastic pollution persists because traditional synthetic polymers degrade into microplastics, releasing harmful chemicals like bisphenol A (BPA), phthalates and carcinogens. Seeking sustainable alternatives, the research team led by Muhammad Maksud Rahman, assistant professor of mechanical and aerospace engineering at the University of Houston and adjunct assistant professor of materials science and nanoengineering at Rice, leveraged bacterial cellulose — one of Earth’s most abundant and pure biopolymers — as a biodegradable alternative.