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Blog – Page 2069

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.

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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.”

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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.

By Jeremy Hsu

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While combing through the human genome in 2007, computational geneticist Pardis Sabeti made a discovery that would transform her research career. As a then-postdoctoral fellow at the Broad Institute of MIT and Harvard, Sabeti discovered potential evidence that some unknown mutation in a gene called LARGE1 had a beneficial effect in the Nigerian population.

Other scientists had discovered that this gene was critical for the Lassa virus to enter cells. Sabeti wondered whether a mutation in LARGE1 might prevent Lassa fever—an infection that is caused by the Lassa virus, is endemic in West Africa, and can be deadly in some people while only mild in others.

To find out, Sabeti decided later in 2007, as a new faculty member at Harvard University, that one of the first projects her new lab at the Broad would take on would be a (GWAS) of Lassa susceptibility. She reached out to her collaborator Christian Happi, now the Director of the African Center of Excellence for Genomics of Infectious Diseases (ACEGID) at Redeemer’s University in Nigeria, and together they launched the study.

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