A team of computer scientists at the University of Massachusetts Amherst working on two different problems—how to quickly detect damaged buildings in crisis zones and how to accurately estimate the size of bird flocks—recently announced an AI framework that can do both. The framework, called DISCount, blends the speed and massive data-crunching power of artificial intelligence with the reliability of human analysis to quickly deliver reliable estimates that can quickly pinpoint and count specific features from very large collections of images.A team of computer scientists at the University of Massachusetts Amherst working on two different problems—how to quickly detect damaged buildings in crisis zones and how to accurately estimate the size of bird flocks—recently announced an AI framework that can do both. The framework, called DISCount, blends the speed and massive data-crunching power of artificial intelligence with the reliability of human analysis to quickly deliver reliable estimates that can quickly pinpoint and count specific features from very large collections of images.[#item_full_content]
High-quality, defect-free, and perfectly dimensioned metal components. Quantum computing power looks set to optimize production processes in the metalworking industry.High-quality, defect-free, and perfectly dimensioned metal components. Quantum computing power looks set to optimize production processes in the metalworking industry.[#item_full_content]
How do we know what a quantum computer is good for when it hasn’t been built yet? That’s what Ph.D. candidate Casper Gyurik investigated by combining two terms you often hear: quantum computing and machine learning.How do we know what a quantum computer is good for when it hasn’t been built yet? That’s what Ph.D. candidate Casper Gyurik investigated by combining two terms you often hear: quantum computing and machine learning.[#item_full_content]
The human brain, with its remarkable general intelligence and exceptional efficiency in power consumption, serves as a constant inspiration and aspiration for the field of artificial intelligence. Drawing insights from the brain’s fundamental structure and information processing mechanisms, brain-inspired computing has emerged as a new computational paradigm, poised to steer artificial intelligence from specialized domains towards broader applications in general intelligence.The human brain, with its remarkable general intelligence and exceptional efficiency in power consumption, serves as a constant inspiration and aspiration for the field of artificial intelligence. Drawing insights from the brain’s fundamental structure and information processing mechanisms, brain-inspired computing has emerged as a new computational paradigm, poised to steer artificial intelligence from specialized domains towards broader applications in general intelligence.[#item_full_content]
The increasing demand in the embedded field has led to the emergence of several impressive Instruction Set Architectures (ISAs). However, when processors migrate from one ISA to another, software compatibility issues are unavoidable.The increasing demand in the embedded field has led to the emergence of several impressive Instruction Set Architectures (ISAs). However, when processors migrate from one ISA to another, software compatibility issues are unavoidable.[#item_full_content]
The concept of Waddington landscape, originally proposed by British developmental biologist Conrad Hal Waddington in 1957, has been influential in describing the dynamical evolution of cellular development.The concept of Waddington landscape, originally proposed by British developmental biologist Conrad Hal Waddington in 1957, has been influential in describing the dynamical evolution of cellular development.[#item_full_content]
Nonlinear systems have applications in many diverse fields from robotics to economics. Unlike linear systems, the output is not proportional to the input is such systems. A classic example is the motion of a pendulum. Due to the inherent nature of nonlinear systems, their mathematical modeling and, consequently, control is difficult.Nonlinear systems have applications in many diverse fields from robotics to economics. Unlike linear systems, the output is not proportional to the input is such systems. A classic example is the motion of a pendulum. Due to the inherent nature of nonlinear systems, their mathematical modeling and, consequently, control is difficult.[#item_full_content]
The biological brain, especially the human brain, is a desirable computing system that consumes little energy and runs at high efficiency. To build a computing system just as good, many neuromorphic scientists focus on designing hardware components intended to mimic the elusive learning mechanism of the brain.The biological brain, especially the human brain, is a desirable computing system that consumes little energy and runs at high efficiency. To build a computing system just as good, many neuromorphic scientists focus on designing hardware components intended to mimic the elusive learning mechanism of the brain.[#item_full_content]
A research team from the Empirical Research Support (ERS) at CISPA Helmholtz Center for Information Security has conducted a systematic comparison of the most popular transcription services. The comparison involved 11 providers of manual as well as AI-based transcriptions.A research team from the Empirical Research Support (ERS) at CISPA Helmholtz Center for Information Security has conducted a systematic comparison of the most popular transcription services. The comparison involved 11 providers of manual as well as AI-based transcriptions.[#item_full_content]
There’s a race underway to build artificial general intelligence, a futuristic vision of machines that are as broadly smart as humans or at least can do many things as well as people can.There’s a race underway to build artificial general intelligence, a futuristic vision of machines that are as broadly smart as humans or at least can do many things as well as people can.[#item_full_content]
