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AI Singularity and the End of Moore’s Law: The Rise of Self-Learning Machines

Unite.AI

Unlike traditional computing, AI relies on robust, specialized hardware and parallel processing to handle massive data. What sets AI apart is its ability to continuously learn and refine its algorithms, leading to rapid improvements in efficiency and performance.

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How AI Agents Are Reshaping Security and Fraud Detection in the Business World

Unite.AI

A significant advantage of AI agents is their ability to constantly refine their models and stay ahead of fraudsters. These AI agents enhance cybersecurity by identifying and preventing phishing scams, scanning emails for malicious links, and recognizing suspicious communication patterns.

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Bayesian Deep Learning is Needed in the Age of Large-Scale AI [Paper Reflection]

The MLOps Blog

In his famous blog post Artificial Intelligence The Revolution Hasnt Happened Yet , Michael Jordan (the AI researcher, not the one you probably thought of first) tells a story about how he might have almost lost his unborn daughter due to a faulty AI prediction. It is 08:30 am, and you have to be at work by 09:00.

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This AI Research Revolutionizes Silicon Mach–Zehnder Modulator Design Through Deep Learning and Evolutionary Algorithms

Marktechpost

The results obtained are intriguing and demonstrate the potential of the proposed design method; however, the work could be expanded to more complex MZM models, such as including the electrode-related parameters, or to test other heuristic optimization algorithms, such as particle swarm optimization or genetic algorithms.

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Meet PyPose: A PyTorch-based Robotics-Oriented Library that Provides a Set of Tools and Algorithms for Connecting Deep Learning with Physics-based Optimization

Marktechpost

Deep learning is finding its utility in all aspects of life. The data-centric nature of deep learning impedes its ability to generalize effectively in the face of continually changing surroundings.’ PyPose is a powerful example of blending age-old robotics techniques with the latest innovations in deep learning.

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AI trends in 2023: Graph Neural Networks

AssemblyAI

What is the current role of GNNs in the broader AI research landscape? Let’s take a look at some numbers revealing how GNNs have seen a spectacular rise within the research community. We find that the term Graph Neural Network consistently ranked in the top 3 keywords year over year.

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Meet SPACEL: A New Deep-Learning-based Analysis Toolkit for Spatial Transcriptomics

Marktechpost

To overcome these limitations, a group of researchers headed by Prof. Qu Kun from the University of Science and Technology of the Chinese Academy of Sciences has created a solution called Spatial Architecture Characterization by Deep Learning (SPACEL). The first module, Sprint, tackles the cell-type deconvolution task.