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In recent years, there has been a growing trend in higher education to incorporate modern technologies and practices in order to improve the overall educational experience. Learning management systems, gamification, video assisted learning, virtual and augmented reality, are some examples of how technology has improved student engagement and education planning. Let’s talk about AI in education. The classroom response system allowed students to answer multiple-choice questions and engage in real-time discussions instantly.

Despite the many benefits that technology has brought to education, there are also concerns about its impact on higher education institutions. With the rise of online education and the growing availability of educational resources on the internet, many traditional universities and colleges are worried about the future of their institutions. As a result, many higher education institutions need help to keep pace with the rapid technological changes and are looking for ways to adapt and stay relevant in the digital age.

Continue reading “Artificial Intelligence (AI) in education: Impact & Examples” »

Machines don’t have eyes, but you wouldn’t know that if you followed the progression of deep learning models for accurate interpretation of medical images, such as x-rays, computed tomography (CT) and magnetic resonance imaging (MRI) scans, pathology…

Hacksmiths are continuing to improve their lightsaber designs.

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Continue reading “We BUILT a 4000° Lightsaber Staff (IT’S CORDLESS!)” »

Vanderbilt researchers have developed a way to more quickly and precisely trap nanoscale objects such as potentially cancerous extracellular vesicles using cutting-edge plasmonic nanotweezers.

The practice by Justus Ndukaife, assistant professor of electrical engineering, and Chuchuan Hong, a recently graduated Ph.D. student from the Ndukaife Research Group, and currently a postdoctoral research fellow at Northwestern University, has been published in Nature Communications.

Optical tweezers, as acknowledged with a 2018 Physics Nobel Prize, have proven adept at manipulating micron-scale matter like biological cells. But their effectiveness wanes when dealing with nanoscale objects. This limitation arises from the diffraction limit of light that precludes focusing of light to the nanoscale.

When people program new deep learning AI models — those that can focus on the right features of data by themselves — the vast majority rely on optimization algorithms, or optimizers, to ensure the models have a high enough rate of accuracy. But one of the most commonly used optimizers — derivative-based optimizers— run into trouble handling real-world applications.

In a new paper, researchers from DeepMind propose a new way: Optimization by PROmpting (OPRO), a method that uses AI large language models (LLM) as optimizers. The unique aspect of this approach is that the optimization task is defined in natural language rather than through formal mathematical definitions.

The researchers write, “Instead of formally defining the optimization problem and deriving the update step with a programmed solver, we describe the optimization problem in natural language, then instruct the LLM to iteratively generate new solutions based on the problem description and the previously found solutions.”

ChatGPT went down on Wednesday morning — and the timing of its outage couldn’t have been more unfortunate. While OpenAI’s world-beating chatbot suffered its second major outage in as many weeks, big tech executives were convening in Washington to plead their case to lawmakers over the future of AI.

Among several notable figures in attendance was Sam Altman, CEO of the AI startup — who probably hoped to put on a better face amidst increased scrutiny over ChatGPT’s falling user traffic for the past several months.

This was yet another notable outage that ChatGPT has suffered in the past several weeks as user traffic falls.

The CEO of Polish drinks company Dictador is an AI-powered humanoid robot who works 7 days a week. The AI boss, named Mika, told Reuters that she doesn’t have weekends and is “always on 24/7.” Mika helps to spot potential clients and selects artists to design the rum producer’s bottles.

The humanoid robot CEO of a Polish drinks company is one busy boss.

Continue reading “The humanoid robot CEO of a drinks company says she doesn’t have weekends and is ‘always on 24/7’” »

Imagine living in a cool, green city flush with parks and threaded with footpaths, bike lanes, and buses, which ferry people to shops, schools, and service centers in a matter of minutes.

That breezy dream is the epitome of urban planning, encapsulated in the idea of the 15-minute city, where all basic needs and services are within a quarter of an hour’s reach, improving public health and lowering vehicle emissions.

Artificial intelligence could help urban planners realize that vision faster, with a new study from researchers at Tsinghua University in China demonstrating how machine learning can generate more efficient spatial layouts than humans can, and in a fraction of the time.

Get up to speed on the rapidly evolving world of AI with our roundup of the week’s developments.

In a move that should surprise no one, tech leaders who gathered at closed-door meetings in Washington, DC, this week to discuss AI regulation with legislators and industry groups agreed on the need for laws governing generative AI technology. But they couldn’t agree on how to approach those regulations.

“The Democratic senator Chuck Schumer, who called the meeting ‘historic,’ said that attendees loosely endorsed the idea of regulations but that there was little consensus on what such rules would look like,” The Guardian reported. “Schumer said he asked everyone in the room — including more than 60… More.