Quantum computers offer powerful ways to improve cybersecurity, communications, and data processing, among other fields. To realize these full benefits, however, multiple quantum computers must be connected to build quantum networks or a quantum internet. Scientists have struggled to come up with practical methods of building such networks, which must transmit quantum information over long distances.
Now, researchers at the University of Chicago Pritzker School of Molecular Engineering (PME) have proposed a new approach—building long quantum channels using vacuum sealed tubes with an array of spaced-out lenses. These vacuum beam guides, about 20 centimeters in diameter, would have ranges of thousands of kilometers and capacities of more than 1,013 qubits per second, better than any existing quantum communication approach. Photons of light encoding quantum data would move through the vacuum tubes and remain focused thanks to the lenses.
“We believe this kind of network is feasible and has a lot of potential,” said Liang Jiang, professor of molecular engineering and senior author of the new work. “It could not only be used for secure communication, but also for building distributed quantum computing networks, distributed quantum sensing technologies, new kinds of telescopes, and synchronized clocks.”
Researchers from the Smart and Wireless Applications and Technologies Group (SWAT-UGR) have conducted two scientific studies aimed at answering a common question: understanding how electromagnetic waves propagate in the medium.
The increase in network speed opens the door to new possibilities, such as robotic surgery or virtual reality services.
A team of UGR researchers has examined the propagation of electromagnetic waves with the goal of enhancing the deployment of 5G and 6G networks. Additionally, the study results contribute to the development of Industry 4.0, which seeks to automate processes in factories using wireless technologies.
With their ability to generate human-like language and complete a variety of tasks, generative AI has the potential to revolutionise the way we communicate, learn and work. But what other doors will this technology open for us, and how can we harness it to make great leaps in technology innovation? Have we finally done it? Have we cracked AI?
Join Professor Michael Wooldridge for a fascinating discussion on the possibilities and challenges of generative AI models, and their potential impact on societies of the future.
Michael Wooldridge is Director of Foundational AI Research and Turing AI World-Leading Researcher Fellow at The Alan Turing Institute. His work focuses on multi-agent systems and developing techniques for understanding the dynamics of multi-agent systems. His research draws on ideas from game theory, logic, computational complexity, and agent-based modelling. He has been an AI researcher for more than 30 years and has published over 400 scientific articles on the subject.
This lecture is part of a series of events — How AI broke the internet — that explores the various angles of large-language models and generative AI in the public eye.
This series of Turing Lectures is organised in collaboration with The Royal Institution of Great Britain.
Researchers have developed a breakthrough method for quantum information transmission using light particles called qudits, which utilize the spatial mode and polarization properties to enable faster, more secure data transfer and increased resistance to errors.
This technology could greatly enhance the capabilities of a quantum internet, providing long-distance, secure communication, and leading to the development of powerful quantum computers and unbreakable encryption.
Scientists have made a significant breakthrough in creating a new method for transmitting quantum information using particles of light called qudits. These qudits promise a future quantum internet that is both secure and powerful.
1/ Cloudflare analyzed the most active AI web crawlers on the Internet based on their query volume.
An analysis by Cloudflare shows that Bytespider, Amazonbot, and ClaudeBot are among the most active AI crawlers on the web.
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Over the past year, Cloudflare has analyzed which AI crawlers with known user agent strings have the highest request volume. Bytedance’s Bytespider crawler tops the list of most active AI web crawlers, followed by Amazonbot, ClaudeBot, and OpenAI’s GPTBot.
Microsoft’s CEO of AI said that content on the open web can be copied and used to create new content.
Speech recognition, weather forecasts, smart home applications: Artificial intelligence and the Internet of Things are enhancing our everyday lives. Systems based on reservoir computing are a very promising new field.
The research group led by Prof Dr. Karin Everschor-Sitte at the University of Duisburg-Essen (UDE), is conducting research in this area. They are primarily investigating new possibilities for reservoir computing, for example using magnetic materials.
Now, together with specialists from the field of ferroelectric materials, the team has shown that these systems are also suitable for processing complex data faster and more efficiently. Their results have been published in Nature Reviews Physics.
Scientists have made a significant breakthrough in creating a new method for transmitting quantum information using particles of light called qudits. These qudits promise a future quantum internet that is both secure and powerful. The study is published in the journal eLight.
Traditionally, quantum information is encoded on qubits, which can exist in a state of 0, 1, or both at the same time (superposition). This quality makes them ideal for complex calculations but limits the amount of data they can carry in communication. Conversely, qudits can encode information in higher dimensions, transmitting more data in a single go.
The new technique harnesses two properties of light—spatial mode and polarization—to create four-dimensional qudits. These qudits are built on a special chip that allows for precise manipulation. This manipulation translates to faster data transfer rates and increased resistance to errors compared to conventional methods.