Lifeboat Foundation

Will artificial intelligence serve humanity — or will it spawn a new species of conscious digital beings with their own agenda?

It’s a question that has sparked scores of science-fiction plots, from “Colossus: The Forbin Project” in 1970, to “The Matrix” in 1999, to this year’s big-budget tale about AI vs. humans, “The Creator.”

The same question has also been lurking behind the OpenAI leadership struggle — in which CEO Sam Altman won out over the nonprofit board members who fired him a week earlier.

Sumit Rana, head of research and development, discusses how the EHR giant’s system uses AI to generate progress notes, create draft responses to patient questions and assist with medical coding. And how AI sometimes can be more empathetic than a person.

Summary: Dopamine, a neurotransmitter, plays a vital role in encoding both reward and punishment prediction errors in the human brain.

This study suggests that dopamine is essential for learning from both positive and negative experiences, enabling the brain to adapt behavior based on outcomes. Using electrochemical techniques and machine learning, scientists measured dopamine levels in real-time during a computer game involving rewards and penalties.

The findings shed light on the intricate role of dopamine in human behavior and could have implications for understanding psychiatric and neurological disorders.

Researchers at Tufts University and Harvard University’s Wyss Institute have created tiny biological robots that they call Anthrobots from human tracheal cells that can move across a surface and have been found to encourage the growth of neurons across a region of damage in a lab dish.

The multicellular robots, ranging in size from the width of a human hair to the point of a sharpened pencil, were made to self-assemble and shown to have a remarkable healing effect on other cells. The discovery is a starting point for the researchers’ vision to use patient-derived biobots as new therapeutic tools for regeneration, healing, and treatment of disease.

Continue reading “Anthrobots: Scientists build tiny biological robots from human tracheal cells” »

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A Nature special on how AI is transforming the scientific enterprise.

Regenerative medicine might just have had a new tool added to its arsenal: Scientists have created tiny biological robots out of living human cells. Though they may be small, the self-assembling bots are mighty, with a study demonstrating their potential for healing and treating disease.

The team had already proven their biological robotics chops back in 2020 with the creation of Xenobots, made from frog embryonic cells. They even managed to design Xenobots so that they could reproduce in a way that no living animal or plant does, something that had never been seen before.

Continue reading “These Tiny, Wound-Healing Robots Start Life As Just 1 Human Cell” »

A recent study published in IEEE Transactions on Control of Network Systems discusses how artificial intelligence (AI) can be used to control microgrids in the event of a long-term power outage caused by natural disasters or human error. This study was conducted by a team of researchers at UC Santa Cruz and holds the potential to improve power restoration techniques, which are traditionally controlled by local utility companies. One benefit of microgrids is they can function to power a small area, such as a town, until the primary utility source comes back online.

“Nowadays, microgrids are really the thing that both people in industry and in academia are focusing on for the future power distribution systems,” said Dr. Yu Zhang, who is an assistant professor of electrical and computer engineering at UC Santa Cruz and co-author on the study.

For the study, the researchers used an AI-based approach to develop a novel method where microgrids could draw power from renewable energy sources while being disconnected from the primary utility source, known as “islanding mode”, but can also function while being connected to the source, as well. This new method, which they refer to as constrained policy optimization (CPO), uses a machine learning algorithm that learns from outside input, such as real-time changes in environmental or power conditions, and makes the best-informed decisions on what to do next.

Meta AI researchers announced on Thursday that they have developed a new suite of artificial intelligence models called Seamless Communication that aim to enable more natural and authentic communication across languages — essentially making the concept of a Universal Speech Translator a reality. The models were publicly released this week along with research papers and accompanying data.

The flagship model, called Seamless, merges capabilities from three other models — SeamlessExpressive, SeamlessStreaming, and SeamlessM4T v2 — into one unified system. According to the research paper, Seamless is “the first publicly available system that unlocks expressive cross-lingual communication in real-time.”

The Seamless translator represents a new frontier in the use of AI for communication across the blog. It combines three sophisticated neural network models to enable real-time translation between over 100 spoken and written languages while preserving the vocal style, emotion, and prosody of the speaker’s voice.