Lifeboat Foundation

Circa 2019

Google claims it has designed a machine that needs only 200 seconds to solve a problem that would take the world’s fastest supercomputer 10,000 years to figure out.

The speed achieved by the computer represents a breakthrough called “quantum supremacy,” according to a blog post from the company and an accompanying article in the scientific journal Nature.

Continue reading “Google claims its quantum computer can do the impossible in 200 seconds” »

Circa 2015

University of Utah engineers have taken a step forward in creating the next generation of computers and mobile devices capable of speeds millions of times faster than current machines.

The Utah engineers have developed an ultracompact beamsplitter—the smallest on record—for dividing light waves into two separate channels of information. The device brings researchers closer to producing silicon photonic chips that compute and shuttle data with light instead of electrons. Electrical and computer engineering associate professor Rajesh Menon and colleagues describe their invention today in the journal Nature Photonics.

Continue reading “Computing at the speed of light: Team takes big step toward much faster computers” »

Researchers in Europe and the UK have managed to connect biological and artificial neurons together – and allow them to communicate long distances through the internet. The biological neurons were grown in one country, sent signals through an artificial synapse located in another to electronic neurons in a third country.

As advanced as supercomputers get, the human brain still utterly leaves them in the dust. It’s made up of neurons that communicate with each other through pulses of electrical signals, passed across tiny gaps known as synapses. These neurons can both process and store information, unlike computers that require separate types of memory for each task.

Artificial versions of neurons and synapses have shown to be far more powerful than traditional computer chip designs, but they’re still in the experimental stage. And now, a team of researchers has taken the next step and connected the artificial and biological versions between three different countries.

QuTech has resolved a major issue on the road toward a working large-scale quantum computer. QuTech, a collaboration of TU Delft and TNO, and Intel have designed and fabricated an integrated circuit that can controlling qubits at extremely low temperatures. This paves the way for the crucial integration of qubits and their controlling electronics in the same chip. The scientists have presented their research during the ISSCC Conference in San Francisco.

Quantum computers

“This result brings us closer to a large-scale quantum computer which can solve problems that are intractable by even the most powerful supercomputers. Solutions to those problems can make a strong impact on everyday life, for instance in the fields of medicine and energy,” said team lead Fabio Sebastiano from QuTech and the Faculty of Electrical Engineering, Mathematics and Computer Science.

Moving ever closer to the Web v.5.0 – an immersive virtual playground of the Metaverse – would signify a paramount convergent moment that MIT’s Rizwan Virk calls ‘The Simulation Point’ and I prefer to call the ‘Simulation Singularity’. Those future virtual worlds could be wholly devised and “fine-tuned” with a possibility to encode different sets of “physical laws and constants” for our enjoyment and exploration.

We are in the “kindergarten of godlings” right now. One could easily envision that with exponential development of AI-powered multisensory immersive technologies, by the mid-2030s most of us could immerse in “real virtualities” akin to lifestyles of today’s billionaires. Give it another couple of decades, each of us might opt to create and run their own virtual universe with [simulated] physics indistinguishable from the physics of our world. Or, you can always “fine-tune” the rule set, or tweak historical scenarios at will.

How can we be so certain about the Simulation Singularity circa 2035? By our very nature, we humans are linear thinkers. We evolved to estimate a distance from the predator or to the prey, and advanced mathematics is only a recent evolutionary addition. This is why it’s so difficult even for a modern man to grasp the power of exponentials. 40 steps in linear progression is just 40 steps away; 40 steps in exponential progression is a cool trillion (with a T) – it will take you 3 times from Earth to the Sun and back to Earth.

Continue reading “Nearing the Simulation Singularity: What Would Immersive Computing Mean to the Human Mentality?” »

This story begins in 1985 when at age 22, I became the World Chess Champion after beating Anatoly Karpov.

We must face our fears if we want to get the most out of technology — and we must conquer those fears if we want to get the best out of humanity, says Garry Kasparov. One of the greatest chess players in history, Kasparov lost a memorable match to IBM supercomputer Deep Blue in 1997. Now he shares his vision for a future where intelligent machines help us turn our grandest dreams into reality.

Continue reading “Don’t fear Intelligent Machines. Work with them: Kasparov” »

Amid mounting concern about a novel coronavirus spreading from China, Lawrence Livermore National Laboratory (LLNL) researchers have developed a preliminary set of predictive 3D protein structures of the virus to aid research efforts to combat the disease.

The models are based on the genomic sequence of the novel coronavirus and a protein found in the virus that causes Severe Acute Respiratory Syndrome (SARS), which closely resembles the new virus.

The researchers plan to use the models to accelerate countermeasure design, using a combination of machine learning, biological experiments and simulation on supercomputers.

Continue reading “Lawrence Livermore researchers release 3D protein structure predictions for the novel coronavirus” »

“Think what we can do if we teach a quantum computer to do statistical mechanics,” posed Michael McGuigan, a computational scientist with the Computational Science Initiative at the U.S. Department of Energy’s Brookhaven National Laboratory.

At the time, McGuigan was reflecting on Ludwig Boltzmann and how the renowned physicist had to vigorously defend his theories of statistical mechanics. Boltzmann, who proffered his ideas about how atomic properties determine physical properties of matter in the late 19th century, had one extraordinarily huge hurdle: atoms were not even proven to exist at the time. Fatigue and discouragement stemming from his peers not accepting his views on atoms and physics forever haunted Boltzmann.

Today, Boltzmann’s factor, which calculates the probability that a system of particles can be found in a specific energy state relative to zero energy, is widely used in physics. For example, Boltzmann’s factor is used to perform calculations on the world’s largest supercomputers to study the behavior of atoms, molecules, and the quark “soup” discovered using facilities such as the Relativistic Heavy Ion Collider located at Brookhaven Lab and the Large Hadron Collider at CERN.

Circa 2017

Thousands of years of human knowledge has been learned and surpassed by the world’s smartest computer in just 40 days, a breakthrough hailed as one of the greatest advances ever in artificial intelligence.

Google DeepMind amazed the world last year when its AI programme AlphaGo beat world champion Lee Sedol at Go, an ancient and complex game of strategy and intuition which many believed could never be cracked by a machine.

Continue reading “AlphaGo Zero: Google DeepMind supercomputer learns 3,000 years of human knowledge in 40 days” »