Lifeboat Foundation

This video is about How ChatGPT/ AI can disrupt healthcare.

ChatGPT is an AI-powered chat platform developed by OpenAI. It allows users to ask questions in a conversational format and build on previous conversations, which allows for improved learning over time. Microsoft has invested billions of dollars in ChatGPT, integrating it into their search engine Bing and web browser Edge. Although the rise of AI has caused concern over job security, ChatGPT currently requires human input to generate questions and diagnose patients, making it a tool to augment human abilities in healthcare. The technology can be used for diagnosis, research, medical education, and radiographs. It can assist healthcare professionals in diagnosing and researching diseases, visualizing anatomy and procedures, and analyzing medical images.

Continue reading “ChatGPT AI in HEALTHCARE? Innovation and disruption” »

A quickie about E5.

Hello, i am back! Blood, sweat and tears have been shed these past months of absence. But enough sweating was done during the summer, tears have already been shed, so that just leaves me with blood. And whether taking a part of blood (plasma) and injecting it into old animals is enough for rejuvenation. That’s right, many of you may remember, earlier this year i made a video on the oldest living rat.- and now we have some updates: in particular, (i) what actually were the rats given, and (ii) what changes were seen, showing both some DNAm and glycan age data.

Continue reading “Pig plasma to live longer?” »

Artificial intelligence is changing health care. It promises better diagnoses and fewer mistakes and all in less time. While some associate AI with a frightening dystopian future, many doctors see it as a source of support.

To help them care for patients, doctors are programming apps and supplying AI with data. At Berlin’s Charité hospital, Professor Surjo Soekadar is researching how neurotechnology might support paralysis patients in their everyday lives — for example, via assistance systems that are controlled via their thoughts.

Continue reading “Doctors, apps and artificial intelligence — The future of medicine” »

This is a sci-fi documentary, looking at the 100 years it will take a nuclear fusion spacecraft to travel to Proxima Centauri b. The closest habitable planet to Earth, with a distance of 4.24 light years.

A journey venturing far beyond Earth’s solar system, showing the future science of space travel, exploration, and future space technology.

Continue reading “The 100 Year Journey to Proxima Centauri B (Sci-Fi Documentary)” »

Over the past few years, we have taken a gigantic leap forward in our decades-long quest to build intelligent machines: the advent of the large language model, or LLM.

This technology, based on research that tries to model the human brain, has led to a new field known as generative AI — software that can create plausible and sophisticated text, images and computer code at a level that mimics human ability.

Businesses around the world have begun to experiment with the new technology in the belief it could transform media, finance, law and professional services, as well as public services such as education. The LLM is underpinned by a scientific development known as the transformer model, made by Google researchers in 2017.

The use of artificial intelligence has played an important role in science teaching and learning. The purpose of this study was to fill a gap in the current review of research on AI in science education (AISE) in the early stage of education by systematically reviewing existing research in this area. This systematic review examined the trends and research foci of AI in the science of early stages of education. This review study employed a bibliometric analysis and content analysis to examine the characteristics of 76 studies on Artificial Intelligence in Science Education (AISE) indexed in Web of Science and Scopus from 2013 to 2023. The analytical tool CiteSpace was utilized for the analysis.

The Impact of chatGPT and other large language models on physics research and education (2023)
Event organizers: Kevin Burdge, Joshua Borrow, Mark Vogelsberger.
Session 3: “The use of large language models in teaching/administration”

Capstone talk: “LLMs for Physics, and Physics for LLMs“
Speaker: Dr Stephen Wolfram (Wolfram Research)

Bill Gates said he used to think leaders filled every minute of their days working toward success, until he saw Warren Buffett’s calendar.

The more physicists use artificial intelligence and machine learning, the more important it becomes for them to understand why the technology works and when it fails.

The advent of ChatGPT, Bard, and other large language models (LLM) has naturally excited everybody, including the entire physics community. There are many evolving questions for physicists about LLMs in particular and artificial intelligence (AI) in general. What do these stupendous developments in large-data technology mean for physics? How can they be incorporated in physics? What will be the role of machine learning (ML) itself in the process of physics discovery?

Before I explore the implications of those questions, I should point out there is no doubt that AI and ML will become integral parts of physics research and education. Even so, similar to the role of AI in human society, we do not know how this new and rapidly evolving technology will affect physics in the long run, just as our predecessors did not know how transistors or computers would affect physics when the technologies were being developed in the early 1950s. What we do know is that the impact of AI/ML on physics will be profound and ever evolving as the technology develops.