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Feb 13, 2024

Engineers build robot swarm that can assemble and repair its shape in a distributed manner

Posted by in categories: information science, robotics/AI

Researchers have proposed a new strategy for the shape assembly of robot swarms based on the idea of mean-shift exploration: When a robot is surrounded by neighboring robots and unoccupied locations, it actively gives up its current location by exploring the highest density of nearby unoccupied locations in the desired shape.

The study, titled, “Mean-shift exploration in shape assembly of robot swarms,” has been published in Nature Communications.

This idea is realized by adapting the mean-shift algorithm, an optimization technique widely used in for locating the maxima of a density function.

Feb 13, 2024

Edge-Of-Network Computing And AI: How AI May Fill Gaps In 5G Tech

Posted by in categories: information science, internet, robotics/AI

The automotive industry has experienced rapid advancements due to the integration of edge computing and artificial intelligence (AI) in recent years. As vehicles continue developing self-driving capabilities, these technologies have become increasingly critical for effective decision-making and real-time reactions.

Edge computing processes data and commands locally within a vehicle’s systems, improving road safety and transportation efficiency. Combined with 5G, it enables real-time communication between vehicles and infrastructure, reducing latency and allowing autonomous vehicles to respond faster. AI algorithms enable cars to interpret visual data and make human-like driving decisions.

Edge computing and AI are transforming vehicles into true self-driving machines, filling any gaps in low-latency 5G tech and enabling companies to pioneer advanced autonomy.

Feb 11, 2024

The Game Changer: How AI Is Transforming The World Of Sports Gambling

Posted by in categories: entertainment, information science, robotics/AI

In the adrenaline-fueled arena of sports gambling, a revolution is unfolding — one powered by artificial intelligence (AI). This technological marvel is transforming the art of sports betting from a game of chance into a symphony of data-driven precision. Let us explore the burgeoning world where AI intersects with sports gambling, turning bettors from mere spectators into strategic players in a game where data, algorithms, and probabilities redefine the odds.

Sports gambling, a realm where intuition, experience, and sometimes sheer luck have traditionally dictated the rules, is undergoing a transformative shift. AI, with its unparalleled ability to analyze vast datasets and discern patterns beyond human capability, is emerging as the new MVP in this field. This transition from gut-driven bets to AI-powered predictions is not just about increasing the odds of winning; it’s about elevating sports gambling to an art of calculated strategies.

At the heart of AI’s influence in sports gambling lies predictive analytics. Companies like Stratagem and Stats Perform are harnessing the power of AI to analyze historical data, player statistics, and even weather conditions to predict game outcomes with astonishing accuracy. For instance, Stratagem uses advanced machine learning algorithms to turn data from thousands of past games into insightful betting strategies, offering gamblers an edge that was unimaginable a few years ago.

Feb 10, 2024

Quantum computers can still be beaten by traditional PCs with new method

Posted by in categories: computing, information science, quantum physics

Classical computers can sometimes outperform quantum computers thanks to new algorithms, challenging the idea that quantum always prevails.


NYU researchers have developed a new method that allows classical computers to perform certain tasks faster and more efficiently than quantum computers.

Feb 9, 2024

Researchers show classical computers can keep up with, and surpass, their quantum counterparts

Posted by in categories: computing, information science, quantum physics

Quantum computing has been hailed as a technology that can outperform classical computing in both speed and memory usage, potentially opening the way to making predictions of physical phenomena not previously possible.

Many see quantum computing’s advent as marking a paradigm shift from classical, or conventional, computing. Conventional computers process information in the form of digital bits (0s and 1s), while quantum computers deploy quantum bits (qubits) to store in values between 0 and 1.

Under certain conditions, this ability to process and store information in qubits can be used to design that drastically outperform their classical counterparts. Notably, quantum’s ability to store information in values between 0 and 1 makes it difficult for to perfectly emulate quantum ones.

Feb 9, 2024

SingularityNET’s Big AGI Plans for 2024

Posted by in categories: blockchains, information science, robotics/AI, singularity

SingularityNET’s community leaders reflect back on last year’s progress, ecosystem updates, as well as the massive push towards building beneficial AGI in 2024 and beyond.

Register for our BGI Summit today by visiting: https://bgi24.ai.

Continue reading “SingularityNET’s Big AGI Plans for 2024” »

Feb 9, 2024

General deep learning framework for emissivity engineering

Posted by in categories: information science, robotics/AI

Wavelength-selective thermal emitters (WS-TEs) have been frequently designed to achieve desired target emissivity spectra, as in typical emissivity engineering, for broad applications such as thermal camouflage, radiative cooling, and gas sensing, etc.

However, previous designs required prior knowledge of materials or structures for different applications, and the designed WS-TEs usually vary from application to application in terms of materials and structures, thus there is no general design for emissivity engineering across different applications. Moreover, previous designs fail to tackle the simultaneous design of both materials and structures, as they either fix materials to design structures or fix structures to select suitable materials.

In a new paper published in Light: Science & Applications, a team of scientists, led by Professor Run Hu from School of Energy and Power Engineering, Huazhong University of Science and Technology, China, and coworkers have proposed a general deep learning framework based on the deep Q-learning network algorithm (DQN) for efficient optimal design of WS-TEs across different applications.

Feb 8, 2024

Futuristic Finance: AI’s Seductive Power In Reshaping Private Equity

Posted by in categories: finance, information science, robotics/AI

In the dynamic and fast-paced world of private equity, AI integration is not just a passing trend; it’s a transformative force reshaping the landscape of the industry. As firms navigate the complexities of investments, market analysis, and financial predictions, AI emerges as a beacon of efficiency, insight, and innovation.

Currently, AI’s integration in private equity is impressive but not expansive. Most firms primarily focused on data analysis, deal sourcing, and risk assessment. Firms like KKR & Co. and Blackstone pioneered this industry revolution, leveraging AI to analyze market trends, evaluate potential investments, and enhance decision-making processes. For instance, consider how AI algorithms process vast amounts of data to identify promising investment opportunities. By sifting through global financial reports, news, and company data, AI provides a deeper understanding of risks and rewards, at level of volume and understanding that most human analysts would find overwhelming.

Additionally, private equity firms find AI-driven risk assessment models indispensable. These models predict market fluctuations, assess potential investment hazards, and offer a more nuanced understanding of various sectors. This predictive power allows firms to make more informed decisions, balancing risks with potential returns more effectively.

Feb 8, 2024

International research team develops new hardware for neuromorphic computing

Posted by in categories: biotech/medical, information science, robotics/AI

In the future, modern machines should not only follow algorithms quickly and precisely, but also function intelligently—in other words, in a way that resembles the human brain. Scientists from Dortmund, Loughborough, Kiev and Nottingham have now developed a concept inspired by eyesight that could make future artificial intelligence much more compact and efficient.

They built an on-chip phonon-magnon for neuromorphic computing which has recently been featured as Editor’s Highlight by Nature Communications.

The human sensory organs convert information such as light or scent into a signal that the brain processes through myriads of neurons connected by even more synapses. The ability of the brain to train, namely transform synapses, combined with the neurons’ huge number, allows humans to process very complex external signals and quickly form a response to them.

Feb 6, 2024

IBM and IonQ Researchers Design Classical Algorithm to Tackle Recent Harvard-Led Study’s Computational Task

Posted by in categories: computing, information science, quantum physics

Despite the Harvard 48 logical #qubits paper is perhaps the biggest leap in #quantum technologies, still the final circuit is classically simulable.


Politics makes strange bedfellows, apparently so does quantum benchmarking.

In a surprising development, IBM Quantum and IonQ researchers teamed up to reveal an alternative classical simulation algorithm for an impressive error correction study conducted by a Harvard and QuEra team and published recently in Nature. IBM is a leader in superconducting quantum computers, while IonQ is noted as a pioneer in trapped ion devices.

Continue reading “IBM and IonQ Researchers Design Classical Algorithm to Tackle Recent Harvard-Led Study’s Computational Task” »

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