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Your next bottle of red could come from seeds that orbited Planet Earth. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Researchers are interested in potential genetic mutations from exposure to cosmic radiation, but ultimately plan to make wine from those plants. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy .

Researchers have demonstrated they can make coffee comparable to conventional espresso using ultrasonic waves. Because the process doesn't need hot water, it consumes 75 percent less energy. What do you need to make a good espresso? Ground coffee, of course; a machine capable of generating pressure; and hot water, preferably heated to between 195 and 205 degrees Fahrenheit. But could one perhaps do without that last element?

Measuring the alignment between representations lets us understand similarities between the feature spaces of different models, such as Vision Transformers trained under diverse paradigms. However, traditional measures for representational alignment yield only scalar values that obscure how these spaces agree in terms of learned features. To address this, we combine alignment analysis with concept discovery, allowing a fine-grained breakdown of alignment into individual concepts. This approach reveals both universal concepts across models and each representation's internal concept structure. We introduce a new definition of concepts as non-linear manifolds, hypothesizing they better capture the geometry of the featurespace. A sanity check demonstrates the advantage of this manifold-based definition over linear baselines for concept-based alignment. Finally, our alignment analysis of four different ViTs shows that increased supervision tends to reduce semantic organization in learned representations.

Task planning under uncertainty is essential for home-service robots operating in the real world. Tasks involve ambiguous human instructions, hidden or unknown object locations, and open-vocabulary object types, leading to significant open-ended uncertainty and a boundlessly large planning space. To address these challenges, we propose Tru-POMDP, a planner that combines structured belief generation using Large Language Models (LLMs) with principled POMDP planning. Tru-POMDP introduces a hierarchical Tree of Hypotheses (TOH), which systematically queries an LLM to construct high-quality particle beliefs over possible world states and human goals. We further formulate an open-ended POMDP model that enables rigorous Bayesian belief tracking and efficient belief-space planning over these LLM-generated hypotheses. Experiments on complex object rearrangement tasks across diverse kitchen environments show that Tru-POMDP significantly outperforms state-of-the-art LLM-based and LLM-tree-search hybrid planners, achieving higher success rates with significantly better plans, stronger robustness to ambiguity and occlusion, and greater planning efficiency.1

The boss of Cadbury chocolate-maker Mondelez has defended its decision to continue doing business in Russia but admitted he is not pleased the firm's taxes are funding the war with Ukraine. Chief executive Dirk Van de Put said it was the right decision to stay after Russia invaded Ukraine in 2022, saying pulling out would risk thousands of jobs and leave Mondelez vulnerable to the Kremlin taking control of its local operations. Many Western companies such as McDonald's exited Russia after it launched a full-scale assault on its neighbour. Others remained but Mondelez said it had discontinued new investment in its Russian business and suspended spending on advertising. In an in-depth discussion as part of the BBC's Big Boss Interview series, Van de Put said: I think over time you try to be neutral in the whole conflict.

Things to Do in L.A. Tap to enable a layout that focuses on the article. This startup was supposed to revolutionize California's wine industry: 'It totally failed' Nilay Patel, left, interviews Monarch Tractor Chief Executive Praveen Penmetsa during Vox Media's 2023 Code Conference in Dana Point, Calif., in 2023. That year, Monarch was on a Forbes list of startups most likely to reach a $1-billion valuation. This is read by an automated voice. Please report any issues or inconsistencies here .

Use this WIRED-exclusive coupon code to get the best deal on this high-design machine and biodegradable pods. If I could only have one pod coffee maker for the rest of time, it would be the Bruvi BV-01 (an 8/10 WIRED Review). It's the pod coffee maker against which I compare every other pod coffee maker. The one to beat, and no competition has come close to taking the crown. It's what I use when I'm not testing a new coffee maker for research.

If this hasn't been said before, it should've been -- you can't hide in the bushes at a bachelorette pool party Shakira cranks up the heat with a World Cup song that has people dancing, buy Elvis' rhinestone jock & BBQ UCF graduates clobber commencement speaker with boos after she says AI is the'next Industrial Revolution' Hang gliding Lookout Mountain: What it's really like to be aero-towed 1,700 feet above Georgia Paige Spiranac and her mom stun the internet, Lane Kiffin's incredible shot at Ole Miss & the NFL did it again Maggie Sajak appears at Savannah Bananas game as Jackson Olson's girlfriend, e-bike near death & MEAT! Mike Pompeo: I've never seen anyone colder, more ruthless than Xi Jinping Trump to press Xi to'open up' China as tech CEOs join key summit South Carolina AG on overturned Murdaugh conviction: 'We have time to try him again' Former CDC director says'outside scientists' might have influenced COVID-19 origins findings Dr. Fauci's role in COVID cover-up was'INTENTIONAL,' CIA whistleblower says CIA calls COVID whistleblower hearing'political theater' in new statement Sen. Moreno warns Chinese cars pose data risks, could devastate US auto industry Olivia Dunne and her Baywatch co-stars are gearing up for a big season while Miller Lite continues to raise the bar. Fox News Flash top sports headlines are here. Check out what's clicking on FoxNews.com. We're halfway to June, somehow, and that means ... well, it means very little. It's a pretty slow(ish) time of year, which is fine with me.

When applying Bayesian optimization (BO) to scientific workflow, a major yet often overlooked source of uncertainty is the task itself -- namely, what to optimize and how to evaluate it -- which can evolve as evidence accumulates. We introduce Generate-Select-Refine (GSR), a open-ended BO framework that alternates between task generation and task optimization. Starting from a user-provided seed task, GSR generates new tasks in a coarse-to-fine manner while a task-acquisition function schedules optimization. Asymptotically, it concentrates evaluations on the best task, incurring only logarithmic regret overhead relative to single-task BO. We apply GSR to new product development, chemical synthesis scaling, algorithm analysis, and patent repurposing, where it outperforms existing LLM-based optimizers.