Toggle light / dark theme

New “Fast Forward” Algorithm Could Unleash the Power of Quantum Computers

Fast-forwarding quantum calculations skips past the time limits imposed by decoherence, which plagues today’s machines.

A new algorithm that fast forwards simulations could bring greater use ability to current and near-term quantum computers, opening the way for applications to run past strict time limits that hamper many quantum calculations.

“Quantum computers have a limited time to perform calculations before their useful quantum nature, which we call coherence, breaks down,” said Andrew Sornborger of the Computer, Computational, and Statistical Sciences division at Los Alamos National Laboratory, and senior author on a paper announcing the research. “With a new algorithm we have developed and tested, we will be able to fast forward quantum simulations to solve problems that were previously out of reach.”

Wormholes may be lurking in the universe — and new studies are proposing ways of finding them

Very interesting.


Albert Einstein’s theory of general relativity profoundly changed our thinking about fundamental concepts in physics, such as space and time. But it also left us with some deep mysteries. One was black holes, which were only unequivocally detected over the past few years. Another was “wormholes” – bridges connecting different points in spacetime, in theory providing shortcuts for space travellers.

Wormholes are still in the realm of the imagination. But some scientists think we will soon be able to find them, too. Over the past few months, several new studies have suggested intriguing ways forward.

Black holes and wormholes are special types of solutions to Einstein’s equations, arising when the structure of spacetime is strongly bent by gravity. For example, when matter is extremely dense, the fabric of spacetime can become so curved that not even light can escape. This is a black hole.

Stanford AI Technology Detects Hidden Earthquakes – May Provide Warning of Big Quakes

New technology from Stanford scientists finds long-hidden quakes, and possible clues about how earthquakes evolve.

Tiny movements in Earth’s outermost layer may provide a Rosetta Stone for deciphering the physics and warning signs of big quakes. New algorithms that work a little like human vision are now detecting these long-hidden microquakes in the growing mountain of seismic data.

Measures of Earth’s vibrations zigged and zagged across Mostafa Mousavi’s screen one morning in Memphis, Tenn. As part of his PhD studies in geophysics, he sat scanning earthquake signals recorded the night before, verifying that decades-old algorithms had detected true earthquakes rather than tremors generated by ordinary things like crashing waves, passing trucks or stomping football fans.

How Explainable Artificial Intelligence Can Help Humans Innovate

I like this idea. I don’t want AI to be a black box, I want to know what’s happening and how its doing it.


The field of artificial intelligence has created computers that can drive cars, synthesize chemical compounds, fold proteins, and detect high-energy particles at a superhuman level.

However, these AI algorithms cannot explain the thought processes behind their decisions. A computer that masters protein folding and also tells researchers more about the rules of biology is much more useful than a computer that folds proteins without explanation.

Therefore, AI researchers like me are now turning our efforts toward developing AI algorithms that can explain themselves in a manner that humans can understand. If we can do this, I believe that AI will be able to uncover and teach people new facts about the world that have not yet been discovered, leading to new innovations.

AI and Big Data Memory Solutions: Improving our everyday lives | Samsung

Samsung’s memory technology innovates artificial intelligence and Big Data analytics to bring impactful change to the way we live, work, and interact with each other. Through next-generation memory technology that enables faster and more complex tasks in AI and Big Data, Samsung takes part in the revolutionary advancement of technology that is enriching our everyday lives.

Healthy skin with OneSkin — Interview//Presentation with Carolina Reis Oliveira

Oneskin — the first skin cream that destroys senescent cells:


Longevity, Health, Long Lifespans, and Halthspans, Psychology, Spirituality — I and Carolina Reis Oliveira talk about all these things in relation to the skin. Find out how you can have very healthy skin with OneSkin!

Visit OneSkin’s website — https://www.oneskin.co/

0:00 — Logo & Title.
0:17 — H! & Intro.
1:40 — Presentation.
2:20 — Presentation | Skin Health — Longevity.
3:57 — Presentation | The Root Cause of Aging.
4:46 — Presentation | Senescent Cells.
5:49 — Presentation | Current solutions.
6:32 — Presentation | OneSkin Approach.
7:47 — Presentation | Let’s Dive Deeper into the Science.
9:51 — Presentation | Replicating Skin Aging.
11:42 — Presentation | Developing an Algorithm to Measure Skin Aging.
12:58 — Presentation | A Drug Discovery Process.
14:23 — Presentation | Senotherapeutic Compounds.
15:00 — Presentation | OS1
15:42 — Presentation | OS1 & UVB Radiation.
17:13 — Presentation | OS1 — Validate effects in 3D models.
19:33 — Presentation | OS1 — Treatment in Skin Biopsies.
20:55 — Presentation | OS1 — Safety.
21:43 — Presentation | OS1 — Clinical Study Results.
23:18 — Presentation | OS1 — Applications Beyond Skin.
26:14 — Presentation | Team.
28:07 — Q&A + the Conversation.
28:25 — Futuristic Psychology & Spirituality.
31:34 — Myths Regarding Immortality.
34:20 — The Collective Rejuvenation.
37:10 — Biologic Hygiene.
41:56 — Cellular Senescence.
46:00 — The Molecular Clock.
48:04 — Morphogenesis of a Scar.
51:15 — Differences Between Skin Types on a Body.
52:35 — Skin Types Regarding Different Races.
54:44 — Skin Conditions.
56:03 — Closing & Ending

New MIT Social Intelligence Algorithm Helps Build Machines That Better Understand Human Goals

A new algorithm capable of inferring goals and plans could help machines better adapt to the imperfect nature of human planning.

In a classic experiment on human social intelligence by psychologists Felix Warneken and Michael Tomasello (see video below), an 18-month old toddler watches a man carry a stack of books towards an unopened cabinet. When the man reaches the cabinet, he clumsily bangs the books against the door of the cabinet several times, then makes a puzzled noise.

Rethinking spin chemistry from a quantum perspective

Researchers at Osaka City University use quantum superposition states and Bayesian inference to create a quantum algorithm, easily executable on quantum computers, that accurately and directly calculates energy differences between the electronic ground and excited spin states of molecular systems in polynomial time.

Understanding how the natural world works enables us to mimic it for the benefit of humankind. Think of how much we rely on batteries. At the core is understanding molecular structures and the behavior of electrons within them. Calculating the energy differences between a molecule’s electronic ground and excited spin states helps us understand how to better use that molecule in a variety of chemical, biomedical and industrial applications. We have made much progress in molecules with closed-shell systems, in which electrons are paired up and stable. Open-shell systems, on the other hand, are less stable and their underlying electronic behavior is complex, and thus more difficult to understand. They have unpaired electrons in their ground state, which cause their energy to vary due to the intrinsic nature of electron spins, and makes measurements difficult, especially as the molecules increase in size and complexity.

A Language AI Is Accurately Predicting Covid-19 ‘Escape’ Mutations

Weird, right?

The team’s critical insight was to construct a “viral language” of sorts, based purely on its genetic sequences. This language, if given sufficient examples, can then be analyzed using NLP techniques to predict how changes to its genome alter its interaction with our immune system. That is, using artificial language techniques, it may be possible to hunt down key areas in a viral genome that, when mutated, allow it to escape roaming antibodies.

It’s a seriously kooky idea. Yet when tested on some of our greatest viral foes, like influenza (the seasonal flu), HIV, and SARS-CoV-2, the algorithm was able to discern critical mutations that “transform” each virus just enough to escape the grasp of our immune surveillance system.