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A bio-inspired vision sensor that can detect spectrally distinctive features

The ability to detect objects in settings with unfavorable lighting, for example at night, in shadowed locations or in foggy conditions, could greatly improve the reliability of autonomous vehicles and mobile robotic systems. Most widely employed computer vision methods, however, have been found to perform under poor lighting.

Researchers at the Hong Kong Polytechnic University recently introduced a new bio-inspired vision sensor that can adapt to the spectral features of the environments it captures, thus successfully detecting objects in a wider range of lighting conditions. This newly developed sensor, introduced in a paper published in Nature Electronics, is based on an array of photodiodes arranged back-to-back.

“In a previous paper in Nature Electronics, we presented a simple in-sensor light intensity adaptation approach to improve the recognition accuracy of machine vision systems,” Bangsen Ouyang, co-author of the paper, told Tech Xplore.

My dream is for AI and brain organoids to explore each other’s capabilities

Image: Prof Thomas Hartung.

Over just a few decades, computers shrunk from massive installations to slick devices that fit in our pockets. But this dizzying trend might end soon, because we simply can’t produce small enough components. To keep driving computing forward, scientists are looking for alternative approaches. An article published in Frontiers in Science presents a revolutionary strategy, called organoid intelligence.

Broadcom is working to integrate optical connectivity directly into GPUs

Forward-looking: We’re approaching a point where traditional copper interconnections won’t be able to carry enough data to keep GPUs and other specialized chips fully utilized. The AI market is urgently demanding a next-generation solution to this interconnection bottleneck, and Broadcom appears to be working on an optics-based solution that is closer to the chip itself.

Broadcom is developing new silicon photonics technology aimed at significantly increasing the bandwidth available to GPUs and other AI accelerators. By utilizing co-packaged optics (CPOs), the fabless chip manufacturer aims to integrate optical connectivity components directly into GPUs, enabling higher data rates while simultaneously reducing power requirements.

The company has been working on CPO solutions for several years and showcased its latest advancements at the recent Hot Chips convention. Broadcom’s “optical engine” reportedly delivers a total interconnect bandwidth of 1.6 TB/sec, equivalent to 6.4 Tbit/sec or 800 GB/sec in each direction.

The AI chip startup that could take down Nvidia

Nvidia may have a sizable lead, but money is an excellent motivator, and tech companies old and new are striving to end its dominance of the AI chip market — or at least secure themselves a sizable slice of it.

While some of these groups, including AMD, are following Nvidia’s lead and optimizing GPUs for generative AI, others are exploring alternative chip architectures.

Intel, for example, markets field programmable gate arrays (FPGAs) — an architecture with reprogrammable circuitry — as AI accelerators. Startup Groq, meanwhile, is developing a brand new kind of AI chip architecture it calls a “language processing unit” (LPU) — it’s optimized for large language models (LLMs), the kinds of AIs that power ChatGPT and other chatbots.