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Blog – Page 136

By the end of 2024, artificial intelligence (AI) and machine learning (ML) had established themselves as the main transformative forces behind recent technological advancements in healthcare. A report by Silicon Valley Bank states that in 2024, the amount of VC investment in health AI in the U.S. was expected to reach $11.1 billion, the highest number since 2021.

In my experience, the main driver behind the AI investment and adoption craze is the measurable value technology offers healthcare providers. A 2023 National Bureau of Economic Research study indicates that integrating AI can save the U.S. healthcare system up to $360 billion annually. A 2023 survey by the AMA shows that physicians see AI as a way to reduce the administrative burden of documentation (54%) and improve workflow efficiency (69%).

But do these positive changes reflect on the quality of care, and do patients benefit from AI and ML-powered solutions? In this article, I share my take on the transformative potential of AI and ML in the modern care delivery process.

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In 2022, staff from Hanoi University purchased a selection of ’supergiant’ isopods at a seaford market in Quy Nhơn City in Vietnam, intrigued by a burgeoning market for the deep sea crustaceans as a delicacy.

Among them was a species unknown to science at the time. National University of Singapore carcinologist Peter Ng and colleagues have now formally described the novel sea bug in a new paper.

As the head of the animal’s carapace resembles the iconic scifi helmet adorned by Star Wars’ infamous Darth Vader, Ng and team named the giant woodlice relative Bathynomus vaderi.

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Multiagent Finetuning. Our self improvement approach constructs a multiagent set of language models over multiple rounds of finetuning. At each round of finetuning, models specialize to become generation and critic agents, and agents in each further specializing based off their generations in the previous round of finetuning.

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General Motors crushed it in 2024, moving just over 114,000 electric Cadillacs, GMCs and Chevrolets. That’s thanks to a stable of heavy-hitters that it was finally able to mass-produce in 2024 following battery-assembly and software snafus.

The Chevy Blazer EV and Cadillac Lyriq racked up over 50,000 sales combined. The Chevy Equinox EV was GM’s real MVP. Americans snapped up 29,000 of them last year, including a whopping 18,000 in the fourth quarter alone. That’s what happens when you give people what they want: EVs that look great, go over 300 miles per charge and won’t break your budget.

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In today’s AI news, Synthesia, a generative AI start-up based in Britain, has raised $180 million valuing it at $2.1 billion. The company uses artificial intelligence to create lifelike human faces and speech that are almost indistinguishable from real video but do not need cameras, actors or film studios.

And, shortly after OpenAI released o1, its first “reasoning” AI model, people began noting a curious phenomenon. The model would sometimes begin “thinking” in Chinese, Persian, or some other language — even when asked a question in English.

Then, MiniMax is perhaps today best known here in the U.S. as the Singaporean company behind Hailuo, a realistic, high-resolution generative AI video model. Today, for instance, it announced the release and open-sourcing of the MiniMax-01 series, a new family of models built to handle ultra-long contexts and enhance AI agent development.

Meanwhile, Google’s Gemini AI has quietly upended the AI landscape, achieving a milestone few thought possible: The simultaneous processing of multiple visual streams in real time. This breakthrough — which allows Gemini to not only watch live video feeds but also to analyze static images simultaneously — emerged from an experimental application called “AnyChat.”

In videos, IBM’s Luv Aggarwal discusses the importance of data creation, organization, storage, integration, and analytics in creating a seamless data flow that enables data-driven insights. Dive into the world of data flow and discover the key to harmonious business operations.

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Gamma oscillations in the brain reveal pain intensity, driven by PV interneurons in the somatosensory cortex. New research highlights their role as biomarkers and therapeutic targets for pain management.

Summary: Parvalbumin (PV) interneurons in the primary somatosensory cortex (S1) have been identified as key players in encoding pain intensity and driving gamma oscillations, according to a study. Cross-species experiments confirmed that gamma oscillations in S1 selectively reflect pain levels in humans and are linked to PV interneuron activity in rodents.

Optogenetic manipulation of these interneurons demonstrated their ability to modulate pain-related behaviors, solidifying their role in pain processing. The findings establish a direct connection between PV interneurons and gamma oscillations, highlighting their potential as a biomarker and target for pain therapies.

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