Lifeboat Foundation

With the release of the most power Artificial Intelligence Accelerator Chip, future AI models like OpenAI’s GPT-4 will be able to surpass the Human Brain by supporting more than 100 Trillion Parameters. This new Chip made by Cerebras Systems is also be biggest Chip ever made by a longshot and thus can support ExaFlop Supercomputers for AI Model Training.

Cerebras Systems is an American semiconductor company with offices in Silicon Valley, San Diego, Toronto, and Tokyo. Cerebras builds computer systems for complex artificial intelligence and deep learning applications.
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TIMESTAMPS:
00:00 The biggest AI Chip ever made.
01:29 The world of AI Acceleration Chips.
02:33 An Artificial Brain.
03:53 How does Cerebas’ Technology work.
06:12 What does this enable?
07:56 Last Words.
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#gpt #openai #ai

Quantum physicists at the University of Copenhagen are reporting an international achievement for Denmark in the field of quantum technology. By simultaneously operating multiple spin qubits on the same quantum chip, they surmounted a key obstacle on the road to the supercomputer of the future. The result bodes well for the use of semiconductor materials as a platform for solid-state quantum computers.

One of the engineering headaches in the global marathon towards a large functional quantum computer is the control of many basic memory devices – qubits – simultaneously. This is because the control of one qubit is typically negatively affected by simultaneous control pulses applied to another qubit. Now, a pair of young quantum physicists at the University of Copenhagen’s Niels Bohr Institute –PhD student, now Postdoc, Federico Fedele, 29 and Asst. Prof. Anasua Chatterjee, 32,– working in the group of Assoc. Prof. Ferdinand Kuemmeth, have managed to overcome this obstacle.

The brain of the quantum computer that scientists are attempting to build will consist of many arrays of qubits, similar to the bits on smartphone microchips. They will make up the machine’s memory.

Quantum physicists at the University of Copenhagen are reporting an international achievement for Denmark in the field of quantum technology. By simultaneously operating multiple spin qubits on the same quantum chip, they surmounted a key obstacle on the road to the supercomputer of the future. The result bodes well for the use of semiconductor materials as a platform for solid-state quantum computers.

One of the engineering headaches in the global marathon towards a large functional quantum computer is the control of many basic memory devices—qubits—simultaneously. This is because the control of one qubit is typically negatively affected by simultaneous control pulses applied to another qubit. Now, a pair of young quantum physicists at the University of Copenhagen’s Niels Bohr Institute working in the group of Assoc. Prof. Ferdinand Kuemmeth, have managed to overcome this obstacle.

Global qubit research is based on various technologies. While Google and IBM have come far with quantum processors based on superconductor technology, the UCPH research group is betting on semiconductor qubits—known as spin qubits.

Taiwan Semiconductor Manufacturing Company makes 24% of all the world’s chips, and 92% of the most advanced ones found in today’s iPhones, fighter jets and supercomputers. Now TSMC is building America’s first 5-nanometer fabrication plant, hoping to reverse a decades-long trend of the U.S. losing chip manufacturing to Asia. CNBC got an exclusive tour of the $12 billion fab that will start production in 2024.

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Continue reading “Secretive Giant TSMC’s $100 Billion Plan To Fix The Chip Shortage” »

The goal of tackling global warming by turning carbon dioxide into fuel could be one step closer with researchers using a supercomputer to identify a group of “single-atom” catalysts that could play a key role.

Researchers from QUT’s Centre for Materials Science, led by Associate Professor Liangzhi Kou, were part of an international study that used theoretical modelling to identify six metals (nickel, niobium, palladium, rhenium, rhodium, zirconium) that were found to be effective in a reaction that can convert carbon dioxide into sustainable and clean energy sources.

The study published in Nature Communications involved QUT researchers Professor Aijun Du, Professor Yuantong Gu and Dr. Lin Ju.

The future of package delivery, taxis, and even takeout in cities may be in the air—above the gridlocked streets. But before a pizza-delivery drone can land safely on your doorstep, the operators of these urban aircraft will need extremely high-resolution forecasts that can predict how weather and buildings interact to create turbulence and the resulting impacts on drones and other small aerial vehicles.

While scientists have been able to run simulations that capture the bewilderingly complex flow of air around buildings in the urban landscape, this process can take days or even weeks on a supercomputing system—a timeline far too slow (and a task far too computationally expensive) to be useful to daily weather forecasters.

Continue reading “GPUs open the potential to forecast urban weather for drones and air taxis” »

Using far more advanced imaging techniques than those of their earlier contemporaries, researchers at the DOE’s Argonne National Laboratory are working to develop a brain connectome — an accurate map that lays out every connection between every neuron and the precise location of the associated dendrites, axons, and synapses that help form the communications or signaling pathways of a brain.

Sept. 24 2021 — As part of the Aurora Early Science Program, Nicola Ferrier of Argonne National Laboratory is leading a project that will use exascale computing power to help advance efforts to develop a brain connectome.

An Australian/German company is developing powerful quantum accelerators the size of graphics cards. They work at room temperature, undercutting and outperforming today’s huge, cryo-cooled quantum supercomputers, and soon they’ll be small enough for mobile devices.

Dementia has many faces, and because of the wide range of ways in which it can develop and affect patients, it can be very challenging to treat. Now, however, using supercomputer analysis of big data, researchers from Japan were able to predict that a single protein is a key factor in the damage caused by two very common forms of dementia.

In a study published this month in Communications Biology, researchers from Tokyo Medical and Dental University (TMDU) have revealed that the protein HMGB1 is a key player in both frontotemporal lobar degeneration and Alzheimer disease, two of the most common causes of dementia.

Frontotemporal lobar degeneration can be caused by mutation of a variety of genes, which means that no one treatment will be right for all patients. However, there are some similarities between frontotemporal lobar degeneration and Alzheimer disease, which led the researchers at Tokyo Medical and Dental University (TMDU) to explore whether these two conditions cause damage to the brain in the same way.