Lifeboat Foundation

New work from Gero, conducted in collaboration with researchers from Roswell Park Comprehensive Cancer Center and Genome Protection Inc. and published in Nature Communications, demonstrates the power of AI combined with analytical tools borrowed from the physics of complex systems to provide insights into the nature of aging, resilience and future medical interventions for age-related diseases including cancer.

Longevity. Technology: Modern AI systems exhibit superhuman-level performance in medical diagnostics applications, such as identifying cancer on MRI scans. This time, the researchers took one step further and used AI to figure out principles that describe how the biological process of aging unfolds in time.

The researchers trained an AI algorithm on a large dataset composed of multiple blood tests taken along the life course of tens of thousands of aging mice to predict the future health state of an animal from its current state. The artificial neural network precisely projected the health condition of an aging mouse with the help of a single variable, which was termed dynamic frailty indicator (dFI) that accurately characterises the damage that an animal accumulates throughout life [1].

Neura Pod is a series covering topics related to Neuralink, Inc. Topics such as brain-machine interfaces, brain injuries, and artificial intelligence will be explored. Host Ryan Tanaka synthesizes informationopinions, and conducts interviews to easily learn about Neuralink and its future.

Twitter: https://www.twitter.com/ryantanaka3/

Continue reading “SUPERCUT: Neuralink Show & Tell Event (23 Minutes)” »

This video is a thought experiment about artificial intelligence, the choices we make, and how much (or how little) we’ll delegate such choices in the future.

The stock footage used in this video comes courtesy of various free stock footage channels on YouTube and through Creative Commons.

Continue reading “Thought Experiment: What Major Decisions Would You Trust An Artificial Intelligence To Make For You?” »

Danielle Boyer knew she was interested in robotics from a young age. But with limited learning resources — a problem many Native American students face — Boyer, who is Ojibwe, said she had to take things into her own hands.

She taught herself through watching YouTube videos, flipping through old electrical engineering books, examining maker kits on Amazon, and then “reverse engineering” everything.

Now, as the founder of the nonprofit The STEAM Connection, Boyer, 22, is on a mission to promote technical and cultural educational opportunities among Native American youth like herself — sometimes combining both in the form of robots that teach Indigenous languages, as they face risks of dying out.

Physicists at Google Quantum AI have used their quantum computer to study a type of effective particle that is more resilient to environmental disturbances that can degrade quantum calculations. These effective particles, known as Majorana edge modes, form as a result of a collective excitation of multiple individual particles, like ocean waves form from the collective motions of water molecules. Majorana edge modes are of particular interest in quantum computing applications because they exhibit special symmetries that can protect the otherwise fragile quantum states from noise in the environment.

The condensed matter physicist Philip Anderson once wrote, “It is only slightly overstating the case to say that physics is the study of symmetry.” Indeed, studying physical phenomena and their relationship to underlying symmetries has been the main thrust of physics for centuries. Symmetries are simply statements about what transformations a system can undergo—such as a translation, rotation, or inversion through a mirror—and remain unchanged. They can simplify problems and elucidate underlying physical laws. And, as shown in the new research, symmetries can even prevent the seemingly inexorable quantum process of decoherence.

When running a calculation on a quantum computer, we typically want the quantum bits, or “qubits,” in the computer to be in a single, pure quantum state. But decoherence occurs when external electric fields or other environmental noise disturb these states by jumbling them up with other states to create undesirable states. If a state has a certain symmetry, then it could be possible to isolate it, effectively creating an island of stability that is impossible to mix with the other states that don’t also have the special symmetry. In this way, since the noise can no longer connect the symmetric state to the others, it could preserve the coherence of the state.

Your weekly news from the AI & Machine Learning world.

OUTLINE:
0:00 — Introduction.
0:25 — AI reads brain signals to predict what you’re thinking.
3:00 — Closed-form solution for neuron interactions.
4:15 — GPT-4 rumors.
6:50 — Cerebras supercomputer.
7:45 — Meta releases metagenomics atlas.
9:15 — AI advances in theorem proving.
10:40 — Better diffusion models with expert denoisers.
12:00 — BLOOMZ & mT0
13:05 — ICLR reviewers going mad.
21:40 — Scaling Transformer inference.
22:10 — Infinite nature flythrough generation.
23:55 — Blazing fast denoising.
24:45 — Large-scale AI training with MultiRay.
25:30 — arXiv to include Hugging Face spaces.
26:10 — Multilingual Diffusion.
26:30 — Music source separation.
26:50 — Multilingual CLIP
27:20 — Drug response prediction.
27:50 — Helpful Things.

Continue reading “[ML News] GPT-4 Rumors | AI Mind Reading | Neuron Interaction Solved | AI Theorem Proving” »

Artificial intelligence could help create transparency and consistency in the legal system – our model shows how.

In our cells, the language of DNA is written, making each of us unique. A tandem repeat occurs in DNA when a pattern of one or more nucleotides—the basic structural unit of DNA coded in the base of chemicals cytosine ©, adenine (A), guanine (G) and thymine (T)—is repeated multiple times in tandem. An example might be: CAG CAG CAG, in which the pattern CAG is repeated three times.

Now, using state-of-the-art whole-genome sequencing and machine learning techniques, the UNC School of Medicine lab of Jin Szatkiewicz, Ph.D., associate professor of genetics, and colleagues conducted one of the first and the largest investigations of tandem repeats in schizophrenia, elucidating their contribution to the development of this devastating disease.

Published in the journal Molecular Psychiatry, the research shows that individuals with schizophrenia had a significantly higher rate of rare tandem repeats in their genomes—7% more than individuals without schizophrenia. And they observed that the tandem repeats were not randomly located throughout the genome; they were primarily found in genes crucial to brain function and known to be important in schizophrenia, according to previous studies.

The goal of achieving what is called artificial general intelligence — or the capacity of an engineered system to display human-like general intelligence — is still some time off into the future. Nevertheless, experts in the field of AI have no doubt accomplished some major milestones along the way, including developing AI capable of deep neural reasoning, tactile reasoning, and even AI with rudimentary social skills.

Now, in yet another step toward AI with more human-like intelligence, researchers from IBM, the Massachusetts Institute of Technology and Harvard University have developed a series of tests that would evaluate an AI’s ability to use a machine version of “common sense” — or a basic ability to perceive, understand, and judge in a manner that is shared by nearly all humans.