Lifeboat Foundation

A large universal quantum computer is still an engineering dream, but machines designed to leverage quantum effects to solve specific classes of problems—such as D-wave’s computers—are alive and well. But an unlikely rival could challenge these specialized machines: computers built from purposely noisy parts.

This week at the IEEE International Electron Device Meeting (IEDM 2022), engineers unveiled several advances that bring a large-scale probabilistic computer closer to reality than ever before.

Quantum computers are unrivaled for any algorithm that relies on quantum’s complex amplitudes. “But for problems where the numbers are positive, sometimes called stochastic problems, probabilistic computing could be quite competitive,” says Supriyo Datta, professor of electrical and computer engineering at Purdue University and one of the pioneers of probabilistic computing.

Discusses the possibility of Femtotech and the technological possibilities it may unlock. Not long ago nanotechnology was a fringe topic; now it’s a flourishing engineering field, and fairly mainstream. For example, while writing this article, I happened to receive an email advertisement for the “Second World Conference on Nanomedicine and Drug Delivery,” in Kerala, India. It wasn’t so long ago that nanomedicine seemed merely a flicker in the eyes of Robert Freitas and a few other visionaries!

But nano is not as small as the world goes. A nanometer is 10–9 meters – the scale of atoms and molecules. A water molecule is a bit less than one nanometer long, and a germ is around a thousand nanometers across. On the other hand, a proton has a diameter of a couple femtometers – where a femtometer, at 10–15 meters, makes a nanometer seem positively gargantuan. Now that the viability of nanotech is widely accepted (in spite of some ongoing heated debates about the details), it’s time to ask: what about femtotech? Picotech or other technologies at the scales between nano and femto seem relatively uninteresting, because we don’t know any basic constituents of matter that exist at those scales. But femtotech, based on engineering structures from subatomic particles, makes perfect conceptual sense, though it’s certainly difficult given current technology.

Continue reading “Hugo de Garis — From Nanotech to Femtotech — There’s Plenty More Room at the Bottom” »

The software system competed against human coders in programming contests.

A novel system called AlphaCode uses artificial intelligence (AI) to create computer code, and has recently participated in programming competitions, using critical thinking, algorithms, and natural language comprehension. The AI system performed extremely well in competitions.

AlphaCode can create code quickly and efficiently

Continue reading “AlphaCode can solve complex problems and create code using AI” »

Cambridge scientists have created a comprehensive tool for predicting an individual’s risk of developing prostate cancer, which they say could help ensure that those men at greatest risk will receive the appropriate testing while reducing unnecessary—and potentially invasive—testing for those at very low risk.

CanRisk-Prostate, developed by researchers at the University of Cambridge and The Institute of Cancer Research, London, will be incorporated into the group’s CanRisk web tool, which has now recorded almost 1.2 million risk predictions. The free tool is already used by health care professionals worldwide to help predict the risk of developing breast and ovarian cancers.

Prostate cancer is the most common type of cancer in men. According to Cancer Research UK, more than 52,000 men are diagnosed with the disease each year and there are more than 12,000 deaths. Over three-quarters (78%) of men diagnosed with prostate cancer survive for over ten years, but this proportion has barely changed over the past decade in the U.K.

Google’s DeepMind AI division has tackled everything from StarCraft to protein folding. So it’s probably no surprise that its creators have eventually turned to what is undoubtedly a personal interest: computer programming. In Thursday’s edition of Science, the company describes a system it developed that produces code in response to programming typical of those used in human programming contests.

On an average challenge, the AI system could score near the top half of participants. But it had a bit of trouble scaling, being less likely to produce a successful program on problems where more code is typically required. Still, the fact that it works at all without having been given any structural information about algorithms or programming languages is a bit of a surprise.

As someone who’s very involved with tech, this discovery is both terrifying and exciting for me. The tech that I will be showing in this video has the potential to be extremely useful but also incredibly horrifying.

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Continue reading “It’s Official — GPT-3 Is Replacing Programmers…” »

The accuracy of pedestrian identification was reduced by 57% when the students tested the outfit on on-campus security cameras.

According to the South China Morning Post (SCMP), Chinese students have successfully developed a coat that can make people invisible to security cameras. So the SCMP story goes, the coat looks the same as regular camouflaged clothing, but it can trick digital cameras, especially ones with AI.

Continue reading “Student-made invisibility coat aims to hide wearers from AI cameras” »

There are serious indications from attempts to create a quantum theory of gravity that time must disappear completely from the description of the quantum universe. This has been known since 1967, when DeWitt discovered the Wheeler-DeWitt equation. I shall argue that this forces us to conceive explanation and causality in an entirely new way. The present can no longer be understood as the consequence of the past. Instead, I shall suggest that one may have to distinguish possible presents on the basis of their intrinsic structure, not on the basis of an assumed temporal ordering. If correct, this could have far-reaching implications. Hitherto, because the present has always been interpreted as the lawful consequence of the past, science has made no attempt to answer ‘Why’ questions, only ‘How’ questions. But if there is no past in the traditional sense, we must consider things differently. Thus, if we eliminate time, we may even be able to start asking “Why” questions.

Specification of a point and tangent vector in conformal superspace (CS) determines a slab of spacetime in CMC foliation and unique curve in CS.
Almost perfect implementation of Mach’s principle because local inertial frames, local proper distance and local proper time all emergent and determined by the universe’s shape and shape velocity.
The Mystery: Shape velocity, as opposed to shape direction, is last vestige of Newton’s absolute space and time. Responsible for expansion of the universe and perhaps perfect transformation theory in quantum theory of the universe.

Continue reading “Timeless Explanation: A New Kind of Causality, Julian Barbour” »

Check out the on-demand sessions from the Low-Code/No-Code Summit to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers. Watch now.

Since OpenAI launched its early demo of ChatGPT last Wednesday, the tool already has over a million users, according to CEO Sam Altman — a milestone, he points out, that took GPT-3 nearly 24 months to get to and DALL-E over 2 months.

The “interactive, conversational model,” based on the company’s GPT-3.5 text-generator, certainly has the tech world in full swoon mode. Aaron Levie, CEO of Box, tweeted that “ChatGPT is one of those rare moments in technology where you see a glimmer of how everything is going to be different going forward.” Y Combinator cofounder Paul Graham tweeted that “clearly something big is happening.” Alberto Romero, author of The Algorithmic Bridge, calls it “by far, the best chatbot in the world.” And even Elon Musk weighed in, tweeting that ChatGPT is “scary good. We are not far from dangerously strong AI.”