Google’s Circle to Search can now translate text as you scroll

https://www.engadget.com/ai/googles-circle-to-search-can-now-translate-text-as-you-scroll-171555663.html?src=rss

Google’s Circle to Search tool just got a bit more useful, as it can now continuously translate text while scrolling. Until now, people had to restart the process every time the content on the screen changed. The update ensures the translation feature will keep on ticking along.

Google says this is great for getting "more context for social posts from creators who speak a different language" or when browsing "menus when you’re booking restaurant reservations while traveling abroad." Just tap the "Translate" icon and look for the menu option "scroll and translate."

This update not only keeps the translation tool going as you scroll, but it even keeps working when switching to another app. Google says "there’s no interruption" in these cases, which sounds pretty darned useful to me.

The update is rolling out now to Android users, but Samsung Galaxy devices are getting it first. Everyone else will have to wait a little bit.

This is just the latest update for Circle to Search. The tool also now lets users conduct one-tap actions on phone numbers, emails and URLs.

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September 4, 2025 at 12:24PM

AI is transforming weather forecasting ? and that could be a game changer for farmers around the world

https://www.geeksaresexy.net/2025/09/04/ai-is-transforming-weather-forecasting-%e2%88%92-and-that-could-be-a-game-changer-for-farmers-around-the-world/

Weather forecasts help farmers figure out when to plant, where to use fertilizer and much more. Maitreya Shah/Studio India

Paul Winters, University of Notre Dame and Amir Jina, University of Chicago

For farmers, every planting decision carries risks, and many of those risks are increasing with climate change. One of the most consequential is weather, which can damage crop yields and livelihoods. A delayed monsoon, for example, can force a rice farmer in South Asia to replant or switch crops altogether, losing both time and income.

Access to reliable, timely weather forecasts can help farmers prepare for the weeks ahead, find the best time to plant or determine how much fertilizer will be needed, resulting in better crop yields and lower costs.

Yet, in many low- and middle-income countries, accurate weather forecasts remain out of reach, limited by the high technology costs and infrastructure demands of traditional forecasting models.

A new wave of AI-powered weather forecasting models has the potential to change that.

A farmer in a field holds a dried out corn stalk.
A farmer holds dried-up maize stalks in his field in Zimbabwe on March 22, 2024. A drought had caused widespread water shortages and crop failures. AP Photo/Tsvangirayi Mukwazhi

By using artificial intelligence, these models can deliver accurate, localized predictions at a fraction of the computational cost of conventional physics-based models. This makes it possible for national meteorological agencies in developing countries to provide farmers with the timely, localized information about changing rainfall patterns that the farmers need.

The challenge is getting this technology where it’s needed.

Why AI forecasting matters now

The physics-based weather prediction models used by major meteorological centers around the world are powerful but costly. They simulate atmospheric physics to forecast weather conditions ahead, but they require expensive computing infrastructure. The cost puts them out of reach for most developing countries.

Moreover, these models have mainly been developed by and optimized for northern countries. They tend to focus on temperate, high-income regions and pay less attention to the tropics, where many low- and middle-income countries are located.

A major shift in weather models began in 2022 as industry and university researchers developed deep learning models that could generate accurate short- and medium-range forecasts for locations around the globe up to two weeks ahead.

These models worked at speeds several orders of magnitude faster than physics-based models, and they could run on laptops instead of supercomputers. Newer models, such as Pangu-Weather and GraphCast, have matched or even outperformed leading physics-based systems for some predictions, such as temperature.

A woman in a red sari tosses pellets into a rice field.
A farmer distributes fertilizer in India. EqualStock IN from Pexels

AI-driven models require dramatically less computing power than the traditional systems.

While physics-based systems may need thousands of CPU hours to run a single forecast cycle, modern AI models can do so using a single GPU in minutes once the model has been trained. This is because the intensive part of the AI model training, which learns relationships in the climate from data, can use those learned relationships to produce a forecast without further extensive computation – that’s a major shortcut. In contrast, the physics-based models need to calculate the physics for each variable in each place and time for every forecast produced.

While training these models from physics-based model data does require significant upfront investment, once the AI is trained, the model can generate large ensemble forecasts — sets of multiple forecast runs — at a fraction of the computational cost of physics-based models.

Even the expensive step of training an AI weather model shows considerable computational savings. One study found the early model FourCastNet could be trained in about an hour on a supercomputer. That made its time to presenting a forecast thousands of times faster than state-of-the-art, physics-based models.

The result of all these advances: high-resolution forecasts globally within seconds on a single laptop or desktop computer.

Research is also rapidly advancing to expand the use of AI for forecasts weeks to months ahead, which helps farmers in making planting choices. AI models are already being tested for improving extreme weather prediction, such as for extratropical cyclones and abnormal rainfall.

Tailoring forecasts for real-world decisions

While AI weather models offer impressive technical capabilities, they are not plug-and-play solutions. Their impact depends on how well they are calibrated to local weather, benchmarked against real-world agricultural conditions, and aligned with the actual decisions farmers need to make, such as what and when to plant, or when drought is likely.

To unlock its full potential, AI forecasting must be connected to the people whose decisions it’s meant to guide.

That’s why groups such as AIM for Scale, a collaboration we work with as researchers in public policy and sustainability, are helping governments to develop AI tools that meet real-world needs, including training users and tailoring forecasts to farmers’ needs. International development institutions and the World Meteorological Organization are also working to expand access to AI forecasting models in low- and middle-income countries.

A man sells grain in Dawanau International Market in Kano, Nigeria on July 14, 2023.
Many low-income countries in Africa face harsh effects from climate change, from severe droughts to unpredictable rain and flooding. The shocks worsen conflict and upend livelihoods. AP Photo/Sunday Alamba

AI forecasts can be tailored to context-specific agricultural needs, such as identifying optimal planting windows, predicting dry spells or planning pest management. Disseminating those forecasts through text messages, radio, extension agents or mobile apps can then help reach farmers who can benefit. This is especially true when the messages themselves are constantly tested and improved to ensure they meet the farmers’ needs.

A recent study in India found that when farmers there received more accurate monsoon forecasts, they made more informed decisions about what and how much to plant – or whether to plant at all – resulting in better investment outcomes and reduced risk.

A new era in climate adaptation

AI weather forecasting has reached a pivotal moment. Tools that were experimental just five years ago are now being integrated into government weather forecasting systems. But technology alone won’t change lives.

With support, low- and middle-income countries can build the capacity to generate, evaluate and act on their own forecasts, providing valuable information to farmers that has long been missing in weather services.The Conversation

Paul Winters, Professor of Sustainable Development, University of Notre Dame and Amir Jina, Assistant Professor of Public Policy, University of Chicago

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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September 4, 2025 at 12:12PM

This Unlikely Chemical Could Be a Powerful Weapon Against Climate Change

https://gizmodo.com/this-unlikely-chemical-could-be-a-powerful-weapon-against-climate-change-2000653025

Year after year, humans pump more carbon dioxide (CO2) into the atmosphere than nature can remove, fueling global warming. As the need to mitigate climate change becomes increasingly urgent, scientists are developing ways to actively remove CO2 from the atmosphere in addition to cutting emissions.

One of the biggest hurdles to scaling current carbon capture technologies is the vast amount of energy they consume, but what if there was an alternative that uses an abundant, cheap power source? A team of researchers at Harvard University recently took a major step toward that goal. Their technique, outlined in a Nature Chemistry study published August 13, harnesses sunlight to efficiently trap CO2.

They’re not talking about slapping solar panels on direct air capture systems that run on heat and electricity. This approach is based on specially designed molecules that use light to change their chemical state and reversibly trap CO2.

Harnessing the power of photochemistry

The methodology the researchers developed is a significant departure from leading direct air capture technologies. These systems tend to rely on chemical solvents or porous sorbents that readily bond to CO2, pulling it out of the air. But the ability to reuse those materials—and harness the carbon for practical use—requires a huge input of energy (usually heat) to release the trapped carbon into a container.

“If you want a practical way to pull carbon dioxide out of the atmosphere and then release it into a tank where you can use it, you need the solution—or whatever medium you’re going to use—to be able to both capture and release. That’s the key,” co-author Richard Liu, an assistant professor of chemistry and chemical biology at Harvard, told Gizmodo.

“Our innovation here is that we began thinking about whether you could use light directly to do that,” he explained.

To that end, Liu’s team synthesized organic molecules called “fluorenyl photobases” that do exactly that. When exposed to sunlight, they rapidly release hydroxide ions that capture CO2 from ambient air by chemically binding to it. In the absence of light, the reaction reverses, releasing the trapped CO2 and reverting the photobase back to its original state.

Scaling a new solution

Through a series of experiments, the researchers determined that the most effective fluorenyl photobase for CO2 capture was PBMeOH. This molecule showed no CO2 capture in the dark but the highest capture rate when exposed to light. What’s more, testing showed that a PBMeOH-based carbon capture system is stable and can complete many cycles with minimal loss of efficiency.

“They only fade about 1% per cycle, so you could imagine only replenishing every 100 cycles,” Liu explained.

This work demonstrates a reversible system for carbon capture that relies solely on sunlight as the direct energy input, highlighting photobases as a promising alternative to traditional sorbents.

The results are encouraging, but Liu and his colleagues will need to clear several hurdles before they can turn their framework into real-world technologies. They’re already working to address several challenges, such as the engineering aspects of how the system will expose these compounds to light and dark.

While the “best” approach is still unknown, photochemical systems present some key advantages over existing technologies, Liu said. Exploring new ways to remove CO2 from the atmosphere is more urgent than ever before. “Because we can’t get rid of every source in the short term, carbon capture from the atmosphere—and from point sources, especially—is going to be an important part of the solution.

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September 4, 2025 at 04:08AM

LinkedIn will require recruiters and executives to verify their identity to cut down on scams

https://www.engadget.com/social-media/linkedin-will-require-recruiters-and-executives-to-verify-their-identity-to-cut-down-on-scams-130040435.html?src=rss

LinkedIn will now require some users to verify their identity before they change job titles in an attempt to cut down on scams on the platform. The new identity verification rules will specifically apply to executives and recruiters who interact with job seekers or represent a company in one form or another.

As part of these changes, LinkedIn says users who add or update their title to anything recruiter-related (recruiter, talent acquisition, etc.) will have to verify their workplace on their profiles. The same identity verification rules will apply to executives, as well, which LinkedIn says covers titles like "Executive Director, Managing Director, and Vice President." Verifying your workplace requires you to provide an official email address that uses your company’s domain name. The new requirement only applies to people changing roles, existing recruiters and executives won’t have to verify.

The new workplace verification feature that will appear when recruiters and executives update their LinkedIn profiles.
LinkedIn

LinkedIn has offered similar verification tools to select companies upon request, but now the platform says it’ll open up the option to every company with a LinkedIn page via a new "Premium Company Page subscription." A verified company should be easier to trust when paired with verified employees.

While LinkedIn is best known as a home for thought leadership and a necessary evil in job hunts, it’s also the site of a large amount of fraud. Scammers impersonate company employees to collect data from fake job postings or conduct elaborate investment schemes, as CNBC reported in 2022. LinkedIn has automated systems for weeding out fake accounts, and rolled out an earlier wave of anti-scam features focused on job postings in 2023, but this new system should offer even more security.

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September 4, 2025 at 08:11AM