Specifically, we lay the foundation within the Bayesian framework.

The grand challenge facing global agriculture today is the need to increase food production to feed a rapidly growing population, amid diminishing natural and human resources and climate pressures. With the global population expected to exceed 9.5 billion by 2050, and with several key resources being depleted (see sidebar), the agricultural community is turning to a digital revolution to secure the future of our food production. Touted Agriculture 4.0, this new movement is deploying digital technologies at scale, including field and aerial sensing, automation, and other smart devices to monitor and track resources and to improve operational efficiency. Artificial intelligence (AI) technologies are playing a central role in driving this revolution: enabling real-time decision support using spatiotemporal data collected on farms, augmenting human labor with automated decision making and robotics, estimating and forecasting risks due to extreme weather, and aiding in longer-term planning under climate-imposed uncertainties. To propel the development and deployment of AI tools and technologies for U.S. agriculture, since 2020 the U.S. Department of Agriculture's National Institute of Food and Agriculture (USDA NIFA) has made a strategic investment in five AI institutes.

When you purchase through links in our articles, we may earn a small commission. Google's Gemini for Home users just got a paywall scare Even Gemini is confused about which Google Home features now cost extra. Gemini for Home has only been working on Google's Nest smart speakers for a month, and users are still getting used to what costs extra and what doesn't. But Gemini surprised some Google Home users recently when it suggested an upsell for an old Google Assistant feature that should be free. A Gemini for Home user complained on Reddit that Gemini on their Nest Mini speaker declined to give a definition of a word, saying instead that "Live conversations are only available if you buy the Premium subscription."

Computational models of sequence memory have been proposed where recurrent Hopfield-like neural networks are trained with temporally asymmetric Hebbian rules.

Warning: This paper contains model outputs that are offensive in nature.

To this end, we propose evaluating the robustness of open-source large VLMs in the most realistic and high-risk setting, where adversaries have only black-box system access and seek to deceive the model into returning the targeted responses.

Why quasicrystals shouldn't exist but are turning up in strange places Matter with "forbidden" symmetries was once thought to be confined to lab experiments, but is now being found in some of the world's most extreme environments In autumn 1945, Lincoln LaPaz crouched over a patch of scorched ground in the Jornada del Muerto desert of New Mexico. LaPaz, an astronomer, was out hunting for meteorites. He had spotted something in the dust: a strange, glittering crust of blood-red glass. This was no meteorite, but it was striking enough that he held onto it. It wasn't until decades later that anyone would realise quite how special LaPaz's chance find was.

Try gene edited, meat-like fungi. Using CRISPR, researchers made a protein packed fungi that's easier to stomach. Breakthroughs, discoveries, and DIY tips sent every weekday. It might not seem so obvious when walking past rows of vacuum-sealed Butterball turkeys at the supermarket, but the world is on the brink of a protein shortage . Global demand for animal-based protein is expected to double by 2050 and while plant-based alternatives exist, enthusiasm around them has wavered in recent years .

Gunmen attacked Christ Apostolic Church in Eruku, Nigeria, killing two people and kidnapping the pastor and worshippers during a Tuesday evening service.

Google's Gemini 3 model keeps the AI hype train going - for now Google's latest model reportedly beats its rivals in several benchmark tests, but issues with reliability mean concerns remain over a possible AI bubble Gemini 3 is Google's latest AI model Google's latest chatbot, Gemini 3, has made significant leaps on a raft of benchmarks designed to measure AI progress, according to the company. These achievements may be enough to allay fears of an AI bubble bursting for the moment, but it is unclear how well these scores translate to real-world capabilities. What's more, persistent factual inaccuracies and hallucinations that have become a hallmark of all large language models show no signs of being ironed out, which could prove problematic for any uses where reliability is vital. AI may blunt our thinking skills - here's what you can do about it In a blog post announcing the new model, Google bosses Sundar Pichai, Demis Hassabis and Koray Kavukcuoglu write that Gemini 3 has "PhD-level reasoning", a phrase that competitor OpenAI also used when it announced its GPT-5 model . As evidence for this, they list scores on several tests designed to test "graduate-level" knowledge, such as Humanity's Last Exam, a set of 2500 research-level questions from maths, science and the humanities.