Perhaps not a surprising figure, given the talk of $100 million signing bonuses.
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Stable Diffusion 3.0 Medium image generator will run locally on AMD processors
Recently, AMD and Stability AI announced that they managed to port the Stable Diffusion 3.0 Medium AI model to the Amuse image generator, which runs locally on the NPU module AMD chip.
The AI arms race with China demands scale. The West must think bigger
Size matters. Economists have long known that; economies of scale are among the building blocks of their science. In the digital era, it quickly became apparent that value was directly proportional to the size of the network (the number of users linked by a particular technology or system).
The race to create scale is critical amid the sizzling geopolitical competition over leadership in new technologies. It has assumed even greater urgency in Western capitals in the wake of China’s success in that race. They’ve had to reconceptualize scale to overcome the advantages China has a result of the size of its economy and its population. It’s a work in progress and the results are mixed, at best.
For those who’ve forgotten their introductory economics, economies of scale are cost advantages created by expanding operations. As companies build more products, they become more efficient, reducing cost per unit. This allows them to produce even more of that product, reinforcing their competitive advantage and keep the virtuous circle turning.
Earth is spinning faster, leading timekeepers to consider an unprecedented move
Earth is spinning faster this summer, making the days marginally shorter and attracting the attention of scientists and timekeepers.
July 10 was the shortest day of the year so far, lasting 1.36 milliseconds less than 24 hours, according to data from the International Earth Rotation and Reference Systems Service and the US Naval Observatory, compiled by timeanddate.com. More exceptionally short days are coming on July 22 and August 5, currently predicted to be 1.34 and 1.25 milliseconds shorter than 24 hours, respectively.
The length of a day is the time it takes for the planet to complete one full rotation on its axis —24 hours or 86,400 seconds on average. But in reality, each rotation is slightly irregular due to a variety of factors, such as the gravitational pull of the moon, seasonal changes in the atmosphere and the influence of Earth’s liquid core. As a result, a full rotation usually takes slightly less or slightly more than 86,400 seconds — a discrepancy of just milliseconds that doesn’t have any obvious effect on everyday life.
Inside Trump’s Long-Awaited AI Strategy
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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.
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.