In a novel study, researchers from the Icahn School of Medicine at Mount Sinai have introduced LoGoFunc, an advanced computational tool that predicts pathogenic gain and loss-of-function variants across the genome.
Unlike current methods that predominantly focus on loss of function, LoGoFunc distinguishes among different types of harmful mutations, offering potentially valuable insights into diverse disease outcomes. The findings are described in Genome Medicine.
Genetic variations can alter protein function, with some mutations boosting activity or introducing new functions (gain of function), while others diminish or eliminate function (loss of function). These changes can have significant implications for human health and the treatment of disease.
All living systems perpetuate themselves via growth in or on the body, followed by splitting, budding, or birth. We find that synthetic multicellular assemblies can also replicate kinematically by moving and compressing dissociated cells in their environment into functional self-copies. This form of perpetuation, previously unseen in any organism, arises spontaneously over days rather than evolving over millennia. We also show how artificial intelligence methods can design assemblies that postpone loss of replicative ability and perform useful work as a side effect of replication. This suggests other unique and useful phenotypes can be rapidly reached from wild-type organisms without selection or genetic engineering, thereby broadening our understanding of the conditions under which replication arises, phenotypic plasticity, and how useful replicative machines may be realized.
Artificial intelligence researchers claim to have made the world’s first scientific discovery using a large language model, a breakthrough that suggests the technology behind ChatGPT and similar programs can generate information that goes beyond human knowledge.
The finding emerged from Google DeepMind, where scientists are investigating whether large language models, which underpin modern chatbots such as OpenAI’s ChatGPT and Google’s Bard, can do more than repackage information learned in training and come up with new insights.
“When we started the project there was no indication that it would produce something that’s genuinely new,” said Pushmeet Kohli, the head of AI for science at DeepMind. “As far as we know, this is the first time that a genuine, new scientific discovery has been made by a large language model.”
Twenty-four years ago, Ray Kurzweil predicted computers would reach human-level intelligence by 2029. This was met with great concern and criticism. In the past six months technology experts have come around to agree with him. According to Kurzweil, over the next two decades, AI is going to change what it means to be human. We are going to invent new means of expression that will soar past human language, art, and science of today. All of the concepts that we rely on to give meaning to our lives, including death itself, will be transformed.\ \ Speakers:\ Ray Kurzweil\ Inventor, Futurist \& Best-selling author of ‘The Singularity is Near’\ \ Reinhard Scholl\ Deputy Director, Telecommunication Standardization Bureau\ International Telecommunication Union (ITU)\ Co-founder and Managing Director, AI for Good\ \ The AI for Good Global Summit is the leading action-oriented United Nations platform promoting AI to advance health, climate, gender, inclusive prosperity, sustainable infrastructure, and other global development priorities. AI for Good is organized by the International Telecommunication Union (ITU) – the UN specialized agency for information and communication technology – in partnership with 40 UN sister agencies and co-convened with the government of Switzerland.\ \ Join the Neural Network!\ 👉https://aiforgood.itu.int/neural-netw…\ The AI for Good networking community platform powered by AI. \ Designed to help users build connections with innovators and experts, link innovative ideas with social impact opportunities, and bring the community together to advance the SDGs using AI.\ \ 🔴 Watch the latest #AIforGood videos!\ / aiforgood \ \ 📩 Stay updated and join our weekly AI for Good newsletter:\ http://eepurl.com/gI2kJ5\ \ 🗞Check out the latest AI for Good news:\ https://aiforgood.itu.int/newsroom/\ \ 📱Explore the AI for Good blog:\ https://aiforgood.itu.int/ai-for-good…\ \ 🌎 Connect on our social media:\ Website: https://aiforgood.itu.int/\ Twitter: / aiforgood \ LinkedIn Page: / 26,511,907 \ LinkedIn Group: / 8,567,748 \ Instagram: / aiforgood \ Facebook: / aiforgood \ \ What is AI for Good?\ We have less than 10 years to solve the UN SDGs and AI holds great promise to advance many of the sustainable development goals and targets.\ More than a Summit, more than a movement, AI for Good is presented as a year round digital platform where AI innovators and problem owners learn, build and connect to help identify practical AI solutions to advance the United Nations Sustainable Development Goals.\ AI for Good is organized by ITU in partnership with 40 UN Sister Agencies and co-convened with Switzerland.\ \ Disclaimer:\ The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.
The mini-brain functioned like both the central processing unit and memory storage of a supercomputer. It received input in the form of electrical zaps and outputted its calculations through neural activity, which was subsequently decoded by an AI tool.
When trained on soundbites from a pool of people—transformed into electrical zaps—Brainoware eventually learned to pick out the “sounds” of specific people. In another test, the system successfully tackled a complex math problem that’s challenging for AI.
The system’s ability to learn stemmed from changes to neural network connections in the mini-brain—which is similar to how our brains learn every day. Although just a first step, Brainoware paves the way for increasingly sophisticated hybrid biocomputers that could lower energy costs and speed up computation.
US Customs and Border Protection (CBP) recently awarded Pangiam, a leading trade and travel technology company, a prime contract for developing and implementing Anomaly Detection Algorithms (ADA).
Pangiam, in collaboration with West Virginia University, aims to bring cutting-edge artificial intelligence (AI), computer vision, and machine learning expertise to enhance CBP’s border and national security missions, the company announced in a press release.
