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WatchGuard Report: 55% of Malware Attacks in Q4 2023 Were Encrypted, a 7% Rise from Q3 – The Fast Mode
WatchGuard Technologies on Wednesday announced the findings of its latest Internet Security Report, detailing the top malware trends and network and endpoint security threats analyzed by WatchGuard Threat Lab researchers.
Breakthrough in Quantum Computing: ETH Zurich Innovates with Static Fields in Ion Trapping – yTech
ETH Zurichs recent foray into the realm of ion trapping has yielded promising advancements for quantum computing. A team of researchers at the esteemed institution has developed a method for trapping ions that could potentially enable the creation of quantum computers with greater numbers of qubits than currently possible. Utilizing static electric and magnetic fields, the group has taken quantum operations a step further, signaling a leap forward in computing capabilities.
Could quantum computing be South Carolina’s next economic draw? This statewide initiative says yes – Columbia … – columbiabusinessreport.com
The future of cutting-edge computer technology in South Carolina is getting a huge boost from an initiative announced March 25. The South Carolina Quantum Association has launched an effort to develop quantum computing technology and talent in the state through $15 million approved by the South Carolina legislature in the fiscal year 2023-24 budget, the states largest ever investment in a tech initiative, according to information from SCQA.
Shaping the Future: South Carolina’s Quantum Computing Education Initiative – yTech
A summary of the new initiative by the South Carolina Quantum Association reveals the states forward-thinking investment in quantum computing expertise. South Carolina is funneling resources into a groundbreaking educational partnership aimed at equipping University of South Carolina students with real-world quantum computing skills. Backed by taxpayer dollars, this project is providing a platform for students to train on a cutting-edge quantum supercomputer, fostering their growth into in-demand tech professionals and invigorating local industries with innovative solutions.
Call for Participation in Workshop on Potential NSF CISE Quantum Initiative – HPCwire
Editors Note: Next month there will be a workshop to discuss what a quantum initiative led by NSFs Computer, Information Science and Engineering (CISE) directorate could entail.
Revolutionizing heart disease prediction with quantum-enhanced machine learning | Scientific Reports – Nature.com
This section portrays the various ML techniques that have been employed by various academicians for effective heart disease diagnosis. The major reason to utilize the ML algorithm is that it is capable of detecting hidden patterns and can operate with large datasets to make predictions. In13, Syed et al
AutoBNN: Probabilistic time series forecasting with compositional bayesian neural networks – Google Research
Posted by Urs Kster, Software Engineer, Google Research Time series problems are ubiquitous, from forecasting weather and traffic patterns to understanding economic trends.
Integrated smart dust monitoring and prediction system for surface mine sites using IoT and machine learning … – Nature.com
In mining operations, the generation of dust is a frequent phenomenon, leading to the presence of airborne dust suspended in the mine atmosphere. This airborne dust primarily comprises mineral particles and, in the presence of moisture, gives rise to particulate matter, which consists of a complex mixture of solid and liquid components.
Unraveling the Dynamics- Does AI Complicate or Simplify Cybersecurity? – CXOToday.com
By Gaurav Ranade The integration of artificial intelligence (AI) into cybersecurity has sparked intense debate and speculation in recent years. On one hand, theres the promise of AI revolutionizing defense capabilities, while on the other, concerns about its potential pitfalls loom large
Breakthrough AI Predicts Mouse Movement With 95% Accuracy Using Brain Data – SciTechDaily
A new end-to-end deep learning method for the prediction of behavioral states uses whole-cortex functional imaging that do not require preprocessing or pre-specified features. Developed by medical student AJIOKA Takehiro and a team led by Kobe Universitys TAKUMI Toru, their approach also allows them to identify which brain regions are most relevant for the algorithm (pictured). The ability to extract this information lays the foundation for future developments of brain-machine interfaces