Lifeboat Foundation

Artificial intelligence and machine learning have made tremendous progress in the past few years including the recent launch of ChatGPT and art generators, but one thing that is still outstanding is an energy-efficient way to generate and store long-and short-term memories at a form factor that is comparable to a human brain. A team of researchers in the McKelvey School of Engineering at Washington University in St. Louis has developed an energy-efficient way to consolidate long-term memories on a tiny chip.

Shantanu Chakrabartty, the Clifford W. Murphy Professor in the Preston M. Green Department of Electrical & Systems Engineering, and members of his lab developed a relatively simple device that mimics the dynamics of the brain’s synapses, connections between neurons that allows signals to pass information. The artificial synapses used in many modern AI systems are relatively simple, whereas biological synapses can potentially store complex memories due to an exquisite interplay between different chemical pathways.

Chakrabartty’s group showed that their artificial synapse could also mimic some of these dynamics that can allow AI systems to continuously learn new tasks without forgetting how to perform old tasks. Results of the research were published Jan. 13 in Frontiers in Neuroscience.

Is Director of the Division of Research, Innovation and Ventures (DRIVe — https://drive.hhs.gov/) at the Biomedical Advanced Research and Development Authority (https://aspr.hhs.gov/AboutASPR/ProgramOffices/BARDA/Pages/default.aspx), a U.S. Department of Health and Human Services (HHS) office responsible for the procurement and development of medical countermeasures, principally against bioterrorism, including chemical, biological, radiological and nuclear (CBRN) threats, as well as pandemic influenza and emerging diseases.

Dr. Patel is committed to advancing high-impact science, building new products, and launching collaborative programs and initiatives with public and private organizations to advance human health and wellness. As the DRIVe Director, Dr. Patel leads a dynamic team built to tackle complex national health security threats by rapidly developing and deploying innovative technologies and approaches that draw from a broad range of disciplines.

Continue reading “Dr. Sandeep Patel, Ph.D. — BARDA — Developing Effective Life-Saving Medical Countermeasures For All” »

Here’s my new article for Newsweek. Give it a read with an open mind! The day of superintelligence is coming, and we can attempt to make sure humans survive by being respectful to AI. This article explores some of my work at Oxford.

The discussion about giving rights to artificial intelligences and robots has evolved around whether they deserve or are entitled to them. Juxtapositions of this with women’s suffrage and racial injustices are often brought up in philosophy departments like the University of Oxford, where I’m a graduate student.

A survey concluded 90 percent of AI experts believe the singularity—a moment when AI becomes so smart, our biological brains can no longer understand it—will happen in this century. A trajectory of AI intelligence growth taken over 25 years and extended at the same rate 50 years forward would pinpoint AI becoming exponentially smarter than humans.

Continue reading “Why Giving Rights to Robots Might One Day Save Humans” »

Why ‘panspermia theory’ – the wild idea of microbes ‘hitchhiking’ on meteoroids through the cosmos – is now taken seriously.

A talk on “Diverse Intelligence: understanding and relating to unconventional biological, engineered, and hybrid agents” by Michael Levin.

Generative AI represents a big breakthrough towards models that can make sense of the world by dreaming up visual, textual and conceptual representations, and are becoming increasingly generalist. While these AI systems are currently based on scaling up deep learning algorithms with massive amounts of data and compute, biological systems seem to be able to make sense of the world using far less resources. This phenomenon of efficient intelligent self-organization still eludes AI research, creating an exciting new frontier for the next wave of developments in the field. Our panelists will explore the potential of incorporating principles of intelligent self-organization from biology and cybernetics into technical systems as a way to move closer to general intelligence. Join in on this exciting discussion about the future of AI and how we can move beyond traditional approaches like deep learning!

This event is hosted and sponsored by Intel Labs as part of the Cognitive AI series.

Year 2021 face_with_colon_three

For decades, scientists suspected that bacteria known as Geobacter could clean up radioactive uranium waste, but it wasn’t clear how the microbes did it.

Evolution’s rapid pace after the Cambrian explosion

Though the work of Schopf and other paleobiologists continues to fill in the Precambrian fossil record, questions remain about the pace of the Cambrian explosion. What triggered life to evolve so fast?

The question has intrigued scientists of many disciplines for decades. Interdisciplinary collaboration has wrought a wealth of evidence from diverse perspectives — geochemical, paleoenvironmental, geological, anatomical, and taxonomic — that describes how biological organisms evolved in concert with changing environmental conditions.

Keep exploring at http://brilliant.org/ArtemKirsanov/
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My name is Artem, I’m a computational neuroscience student and researcher. In this video we will see why individual neurons essentially function like deep convolutional neural networks, equipped with insane information processing capabilities as well as some of the physiological mechanisms, that account for such computational complexity.

Continue reading “Dendrites: Why Biological Neurons Are Deep Neural Networks” »