Lifeboat Foundation

Implementing error correction in a quantum computer requires putting together a lot of different things. Of course, you want to start with good physical qubits that have as low a physical error rate that you can achieve. You want to add in an error correction algorithm, like the surface code, color code, q-LDPC, or others that can be implemented in your architecture, and you need a fast real time error decoder that can look at the circuit output and very quickly determine what the error is so it can be corrected. The error decoder portion doesn’t get as much attention in the media as the other things, but it is a very critical portion of the solution. Riverlane is concentrating on providing products for this with a series of solutions they name Deltaflow which consists of both a classical ASIC chip along with software. The Deltaflow solution consists of a powerful error decoding layer for identifying errors and sending back corrective instructions, a universal interface that communicates with the computer;s control system, and a orchestration layer for coordinating activities.

Riverlane has released its Deltaflow Error Correction Stack Roadmap that show yearly updates to the technology to support an increase in the number of QuOps (error free Quantum Operations) by 10X every year. We reported last year on a chip called DD1 that is part of their Deltaflow 1 solution that is capable of supporting 1,000 QuOps using a surface code error correction algorithm. And now, Riverlane is defining solutions that will achieve 10,000 QuOps with Deltaflow 2 later this year, 100,000 QuOps with Deltaflow 3 in 2025, and 1,000,000 QuOps, also called MegaQuops in 2026, with their Deltaflow Mega solution.

One characteristic that Riverlane is emphasizing in these designs is to perform the decoding in real time in order to keep the latencies low. Although it is fine for an academic paper to send the ancilla data off to a classical computer and have it determine the error, it might take milliseconds for the operation to complete. That won’t cut it in a production environment running real jobs. With their Deltaflow chips, these operations can be performed at megahertz rates and Riverlane has implemented techniques such as a streaming, sliding window, and parallized decoding approaches to increase the throughput of the decoder chips as much as possible. In future chips they will be implementing “fast logic” capabilities for Clifford gates using approaches including lattice surgery and transversal CZ gates.

Where do we stand with artificial intelligence? Might machines take over our jobs? Can machines become conscious? Might we be harmed by robots? What is the future of humanity? Professor Giorgio Buttazzo of Scuola Superiore Sant’Anna is an expert in artificial intelligence and neural networks. In a recent publication, he provides considered insights into some of the most pressing questions surrounding artificial intelligence and humanity.

A Brief History of Neural Networks and Deep Learning

In artificial intelligence (AI), computers can be taught to process data using neuron-like computing systems inspired by the mechanisms used by the human brain. These so-called neural networks represent a type of machine learning (‘deep learning’) in which interconnected nodes or neurons are able to adapt and learn from data to recognise patterns and solve complex problems.

Meta, which owns Facebook and WhatsApp, announced plans for a sprawling $800 million data center in the rural US county.

They were gradually replaced by AI.

A hot potato: CEOs, bosses, and the those who make the technology love to assure people that artificial intelligence isn’t going to replace everyone’s jobs; it will merely augment them – working alongside humans to make life easier. Yet we keep hearing stories like the one about a writer whose employer fired his 60-person team and replaced them with an AI.

A writer using the pseudonym Benjamin Miller told the BBC that his company wanted to use AI to cut costs in early 2023. He led a team of more than 60 writers and editors who published blog posts and articles to promote a tech company that packages and resells data.

Continue reading “Company cuts costs by replacing 60-strong writing team with AI” »

A new Citi report says finance will be “at the forefront” of changes due to artificial intelligence.

Liquid neural networks, spiking neural networks, neuromorphic chips. The next generation of AI will be very different.
#ainews #ai #agi #singularity #neuralnetworks #machinelearning.

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Mentally stimulating activities and life experiences can improve cognition in memory clinic patients, but stress undermines this beneficial relationship. This is according to a new study from Karolinska Institutet published in Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association.

In the late 1980s, researchers discovered that some individuals who showed no apparent symptoms of dementia during their lifetime had brain changes consistent with an advanced stage of Alzheimer’s disease. Since then it has been postulated that so-called cognitive reserve might account for this differential protective effect in individuals.

Cognitively stimulating and enriching life experiences and behaviors such as higher educational attainment, complex jobs, continued physical and leisure activities, and healthy social interactions help build cognitive reserve. However, high or persistent stress levels are associated with reduced social interactions, impaired ability to engage in leisure and physical activities, and an increased risk of dementia.

As EV sales surge in China, BYD’s workforce has expanded rapidly, adding nearly 500,000 employees since 2019. BYD’s workforce is now roughly double that of Toyota’s as China’s EV leader expands overseas.

Privately-owned firms, such as BYD and others in the EV industry, are accelerating job growth in China.

According to filings, there were about 30.57 million employees in China at the end of 2023. That’s up 13% from 2019. Private companies accounted for 81% of the growth, or 2.85 million jobs.

“These are things that are superhuman, and we think this will be in every industry, will probably replace 50% of human jobs, create a huge amount of wealth for mankind and wipe out poverty,” https://www.cnbc.com/2017/04/27/kai-fu-lee-robots-will-repla…jobs.html” rel=“noopener” class=””>Lee told CNBC at the time, later forecasting that it would happen in the next 10 years.

Fast forward seven years to the Fortune Innovation forum in Hong Kong this past March, when he sat down with Fortune editor-in-chief Alyson Shontell.

Continue reading “Top China VC Kai-Fu Lee says his prediction that AI will displace 50% of jobs by 2027 is ‘uncannily accurate’” »