Series

Recent advancements in (self) supervised learning models have been driven by empirical scaling laws, where a model's performance scales with its size. However, such scaling laws have been challenging to establish in reinforcement learning (RL). Unlike...
Large Language Models (LLMs) have significantly evolved in recent times, especially in the areas of text understanding and generation. However, there have been certain difficulties in optimizing LLMs for more effective human instruction delivery. While LLMs...

Semper Maior: Improving Video Decoding with Machine Learning (How Machine Learning ML is used in Video EncodingĀ Part 4)

Encoding the source video to a compressed representation is the first part of the video encoding pipeline. The other part is getting that encoded...

Semper Ad Meliora: Towards Better Video Codecs with Machine Learning (How Machine Learning ML is used in Video EncodingĀ Part 3)

Increasing demand for video content and stable upgrades in display technology, such as higher resolution, increases the importance of designing efficient video codecs. That...

The Clavis Aurea of Internet Video Delivery: HTTP Adaptive Streaming (How Machine Learning ML is used in Video EncodingĀ Part 2)

We discussed what a video is, why it is essential to reduce its size, and how this compression is done via video encoding. One...

The Sine Qua Non of Video Delivery: Video Encoding (How Machine Learning ML is used in Video EncodingĀ Part 1)

Video has become an essential part of the Internet, and numbers support this statement. Video content was responsible for 82% of the total Internet...

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