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A neural-network-based artificial intelligence outperforms ChatGPT at quickly folding new words into its lexicon, a key aspect of human intelligence.

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A group of artificial intelligence researchers from the University of Science and Technology of China (USTC) and Tencent YouTu Lab have developed an innovative framework, coined as “Woodpecker”, designed to correct hallucinations in multimodal large language models (MLLMs).

The research paper outlining this groundbreaking approach was published on the pre-print server arXiv, under the title Woodpecker: Hallucination Correction for Multimodal Large Language Models.

The team estimates that their hardware can outperform the best electronic processors by a factor of 100 in terms of energy efficiency and compute density.

A team of scientists from Oxford University and their partners from Germany and the UK have developed a new kind of AI hardware that uses light to process three-dimensional (3D) data. Based on integrated photonic-electronic chips, the hardware can perform complex calculations in parallel using different wavelengths and radio frequencies of light. The team claims their hardware can boost the data processing speed and efficiency for AI tasks by several orders of magnitude.

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AI computing and processing power

The research published today in the journal Nature Photonics addresses the challenge of meeting modern AI applications’ increasing demand for computing power. The conventional computer chips, which rely on electronics, need help to keep up with the pace of AI innovation, which requires doubling the processing power every 3.5 months. The team says that using light instead of electronics offers a new way of computing that can overcome this bottleneck.

NVIDIA, which is well known for its GPUs that made possible the training of ChatGPT, has also been working on its development platform, Omniverse, for building 3D tools and applications. Earlier this year, the company unveiled its Voyager AI agent that could build tools 15 times faster than other AI agents in Minecraft.