about.subtitle
As systems grow more complex, the question of their expansion ceases to be purely technical and moves into the realm of fundamental laws. In this collection, we view scaling not merely as a quantitative increase in parameters, but as a process that yields new qualities and challenges. Here, we have gathered research dedicated to the empirical laws of growth, the limits of computing power, and how changes in scale influence the behavior of complex models.
AI consumes vast amounts of electricity and fuels global warming, yet it also offers solutions. We'll explore whether this is an absurdity or a genuine chance to escape the vicious cycle.
What if you could train a massive neural network using half the memory – without breaking anything? That's exactly what the creators of FlashOptim are exploring.
NXP and Hugging Face explain how to train robotic artificial intelligence on custom data and run it on a low-power embedded device.
AI: Events
Research
Researchers at Physical Intelligence have taught robots to combine long- and short-term memory, significantly altering their approach to solving complex tasks.
AI: Events
Technical context • Infrastructure
AMD has explained how to run distributed ML tasks on GPUs using Ray and ROCm 7 – from model training to creating agent-based systems.
Lab
Electrical Engineering & System Sciences
Researchers have developed a method for detecting failures in segmented antenna systems: each segment is assigned a unique tag, allowing for the precise identification of the failed element.
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