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    artificial intelligence tagged posts

    A new kind of AI that does its thinking cheaply without words

    September 3, 2026, Categories  Physics, Technology/Electronics

    A new kind of AI that does its thinking cheaply without words
    Representative held-out examples from the four controlled generalization families. From top to bottom: extend a seed to the boundary, copy a motif to every gray anchor, order bar colors from shortest to tallest, and recolor only cells inside every nested frame. Credit: arXiv (2026). DOI: 10.48550/arxiv.2608.09888

    There may soon be a new kind of artificial intelligence in town, one that uses a novel approach to thinking that could save massive amounts of computing power and money.

    The AI that most people use every day, like ChatGPT, Claude or Google Gemini, relies on large language models that can work through difficult problems step by step. While this may ultimately give us the answers we are searching for, the process can increase response times and use a lot of computing power.

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    Brain-inspired AI architecture could computing faster and far less power-hungry

    June 24, 2026, Categories  Physics, Technology/Electronics

    New brain-inspired architecture could process data more efficiently
    Dual memory pathway abstraction. At the algorithmic level, each layer maintains a shared, low-dimensional state that captures slow contextual dynamics and modulates fast spiking activity. At the hardware level, this separation is mirrored by a heterogeneous accelerator that keeps the compact state on-chip and fuses sparse and dense computations for efficient execution. Credit: Sun et al.

    Spiking neural networks (SNNs) are artificial intelligence (AI) models inspired by how biological neurons communicate with each other. While biological neurons exchange information in the form of electrical impulses, SNNs rely on brief signals known as spikes.

    SNNs have proved promising for reducing power consumption, as developers can ensure they do not process information continuously, but rather ...

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    A single real-world datapoint may stop AI model collapse, analysis suggests

    May 16, 2026, Categories  Physics, Technology/Electronics

    New work explaining the inner workings of artificial intelligence could provide a way around the threat of AI “model collapse,” potentially averting growing numbers of AI hallucinations in the future.

    First coined in 2024, “model collapse” refers to a scenario where an AI model trained on AI-produced data ceases to provide accurate results, instead producing inaccurate “gibberish” because of the poor quality of its training data.

    Some have warned that high-quality text data to train systems like Large Language Models (LLMs) is set to run out as early as this year, and so data produced by models themselves has taken a larger training role—inviting the threat of model collapse.

    Simple statistical models reveal a fix
    Through analysis of a simple yet powerful set of statistical ...

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    How everyday devices could train AI faster while keeping personal data on-device

    May 1, 2026, Categories  Physics, Technology/Electronics

    Irene Tenison, Lalana Kagal and Anna Murphy at desk with laptops
    Caption:Irene Tenison, Lalana Kagal and Anna Murphy of the Decentralized Information Group (DIG) developed a new method that could bring more accurate and efficient AI models to high-stakes applications like health care and finance.
    Credits:Credit: Adam Glanzman

    A new method developed by MIT researchers can accelerate a privacy-preserving artificial intelligence training method by about 81%. This advance could enable a wider array of resource-constrained edge devices, like sensors and smartwatches, to deploy more accurate AI models while keeping user data secure.

    The MIT researchers boosted the efficiency of a technique known as federated learning, which involves a network of connected devices that work together to train a shared AI model.

    In federated learning, the model is broad...

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