Scientists at EPFL have developed a superconducting circuit optomechanical platform that demonstrates ultra-low quantum decoherence and high-fidelity quantum control. Their groundbreaking work with a “vacuum-gap drumhead capacitor” has led to the longest quantum state lifetime in a mechanical oscillator ever achieved, paving the way for new applications in quantum computing.
Performing computation using quantum-mechanical phenomena such as superposition and entanglement.
The Covid-19 pandemic has posed significant challenges to all industries, including humanoid robotics. Supply chain disruptions and labor shortages have affected development and production. However, the industry has shown resilience, finding ways to resume manufacturing and sustain revenue.
In the ever-evolving robotics industry, challenges like supply chain disruptions and labor shortages demand strategic solutions. Diversify suppliers, build strong relationships and adopt just-in-time manufacturing for resilience. Embrace remote work, upskill the workforce and leverage automation. Monitor risks, maintain buffer stock, foster innovation and network with peers. These strategies ensure the continued growth and success of robotics companies amidst adversity. By staying agile and proactive, the robotics industry can overcome obstacles and lead the way to a transformative future.
Looking ahead, the healthcare industry presents a promising avenue for the application of humanoid robots. From providing security to dispensing pharmaceuticals and assisting patients, humanoid robots could revolutionize healthcare delivery.
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The increasing use of artificial intelligence (AI) means a rapid increase in data use and a new era of potential data center industry growth over the next two years and beyond.
This shift marks the beginning of the “AI Era,” after a decade of industry growth driven by cloud and mobile platforms, the “Cloud Era.” Over the past decade, the largest public cloud service providers and internet content companies propelled data center capacity growth to unprecedented levels, culminating in a flurry of activity from 2020 to 2022 due to the surge in online service usage and low-interest-rate financing for projects.
Additionally, the strategy only works for mutations that have already been defined. Not all tumors have the same mutations, and some cancers manifest a wide array of mutations, but “it happens that colorectal cancer is one of those that has a small set of very common mutations,” said Cooper.
The technique must also translate to humans, though Cooper pointed out, “This is one of those cases where scaling up to humans might actually help it because everything is bigger, so there’s more target DNA and more biosensors you can fit into the gut.”
If further developed and approved for human use, the engineered bacterial biosensors could be used for other applications, such as rapid diagnosis of gut infections. Additionally, shifting from a detection model to a therapeutic mode, the same bacteria could be engineered to release anti-tumor agents upon detecting tumor DNA, rather than sending a signal that they’ve detected it.
After a highly lauded research campaign that successfully redesigned a hepatitis C drug into one of the leading drug treatments for COVID-19, scientists at the Department of Energy’s Oak Ridge National Laboratory are now turning their drug design approach toward cancer.
In their latest study, published in the journal Communications Chemistry, the team used neutrons and X-rays to draw a roadmap of every atom, chemical bond and electrical charge inside a key enzyme that belongs to a metabolic pathway that cancer cells dramatically overuse to reproduce.
This new information essentially helps pave the way for developing new drugs that act as roadblocks along the metabolic pathway to cut off the supply of vital resources to cancers cells. The drugs would be designed to target highly aggressive tumor-forming cancers that too often become terminal such as lung, colon, breast, pancreatic and prostate cancers.
Tesla says it will build new “1st of its kind” data centers. The automaker is hiring staff for it and snapping up some existing data centers.
The data center business is now massive with a market size of more than $250 billion.
Most of the biggest companies in the world, which are known to consumers for other products, are in it, like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and Meta Platforms (Facebook).
The ongoing AI revolution, set to reshape lifestyles and workplaces, has seen deep neural networks (DNNs) play a pivotal role, notably with the emergence of foundation models and generative AI. Yet, the conventional digital computing frameworks that host these models hinder their potential performance and energy efficiency. While AI-specific hardware has emerged, many designs separate memory and processing units, resulting in data shuffling and reduced efficiency.
IBM Research has pursued innovative ways to reimagine AI computation, leading to the concept of analog in-memory computing, or analog AI. This approach draws inspiration from neural networks in biological brains, where synapse strength governs neuron communication. Analog AI employs nanoscale resistive devices like Phase-change memory (PCM) to store synaptic weights as conductance values. PCM devices transition between amorphous and crystalline states, encoding a range of values and enabling local storage of weights with non-volatility.
A significant stride towards making analog AI a reality has been achieved by IBM Research in a recent Nature Electronics publication. They introduced a cutting-edge mixed-signal analog AI chip tailored for various DNN inference tasks. This chip, fabricated at IBM’s Albany NanoTech Complex, features 64 analog in-memory compute cores, each housing a 256-by-256 crossbar array of synaptic unit cells. Integrated compact, time-based analog-to-digital converters facilitate seamless transitions between analog and digital domains. Moreover, digital processing units within each core handle basic neuronal activation functions and scaling operations.
Michio Kaku is the latest expert to shut down AI fears saying the technology is not humanlike at this point.
Thoughts.
Some studies of fish oil supplements have shown a higher risk for atrial fibrillation with marine omega-3 fatty acids. Is it real? What are the implications for patients taking these capsules?
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Shielded by our thick skulls and swaddled in layers of protective tissue, the human brain is extremely difficult to observe in action. Luckily, scientists can use brain organoids — pencil eraser-sized masses of cells that function like human brains but aren’t part of an organism — to look closer. How do they do it? And is it ethical? Madeline Lancaster shares how to make a brain in a lab.
Lesson by Madeline Lancaster, animation by Adam Wells.
