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C. auris, a type of yeast that can cause severe illness, is a “global health threat”, according to experts.

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Hyundai’s CRADLE and Sundberg-Ferar join forces to create Elevate—an electric car with robotic legs, the ‘walking car,’ designed to tackle challenging terrains.

Mage: SonoCloud uses the therapeutic potential of pulsed ultrasound to temporarily disrupt the blood-brain barrier (Photo courtesy of Carthera) The blood-brain barrier (BBB) presents a significant…

A two-legged bot that’s shorter than a standard ballpoint pen just snatched the Guinness World Record for smallest humanoid robot.

The new Guinness World Record holder, engineered by the robotics team at Hong Kong’s Diocesan Boys’ School, stands just 5.5 inches tall and can dance and do kung-fu.

In the dynamic and fast-paced world of private equity, AI integration is not just a passing trend; it’s a transformative force reshaping the landscape of the industry. As firms navigate the complexities of investments, market analysis, and financial predictions, AI emerges as a beacon of efficiency, insight, and innovation.

Currently, AI’s integration in private equity is impressive but not expansive. Most firms primarily focused on data analysis, deal sourcing, and risk assessment. Firms like KKR & Co. and Blackstone pioneered this industry revolution, leveraging AI to analyze market trends, evaluate potential investments, and enhance decision-making processes. For instance, consider how AI algorithms process vast amounts of data to identify promising investment opportunities. By sifting through global financial reports, news, and company data, AI provides a deeper understanding of risks and rewards, at level of volume and understanding that most human analysts would find overwhelming.

Additionally, private equity firms find AI-driven risk assessment models indispensable. These models predict market fluctuations, assess potential investment hazards, and offer a more nuanced understanding of various sectors. This predictive power allows firms to make more informed decisions, balancing risks with potential returns more effectively.

Massachusetts startup Elemind has raised $12 million to read brainwaves and treat people for sleep disorders, long-term pain, tremors, and to speed up learning rates. Clinical trials show the company’s wearable device can accelerate sleep up to 70% faster, reduce tremors in patients with physiological shaking up to 50%, and boost learning rates.

“We use a wearable neurotech device to read the brain in real time and intercept it in real time with something called neurostimulation,” Elemind co-founder and CEO Meredith Perry told me on a recent TechFirst podcast. “That’s using sound or light or vibration or electricity to stimulate the brain. And when we do that, we can actually guide the brain precisely, and that leads to a behavior change. So like a drug, but much smarter and without the side effects.”

By connecting several less-advanced chips into one, Chinese companies could circumvent the sanctions set by the US government.

A team of researchers from Carnegie Mellon University has successfully developed a new program that enables robots to learn how to open doors independently.

A robot that can learn to open most types of doors, cabinets, drawers and refrigerators – without human direction – may pave the way for your future robot butler.

Continue reading “This robot can figure out how to open almost any door on its own” »

EPFL finds an advanced image compression technique.

EPFL researchers have developed a machine-learning approach for compressing image data more accurately than learning-free computation methods.