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Improvements in Scalability and Memory Management in Training Strategies
The alternative training strategy shows noticeable improvements in scalability, with increased flops leading to better performance in next word prediction accuracy. Unlike transformers, the memory approach allows for continuous updating akin to an infinite context window but faces challenges of overload and loss of information over time.
Our 174rd episode with a summary and discussion of last week's big AI news!
With hosts Andrey Kurenkov (https://twitter.com/andrey_kurenkov) and Jeremie Harris (https://twitter.com/jeremiecharris)
In this episode of Last Week in AI, we delve into the latest advancements and challenges in the AI industry, highlighting new features from Figma and Quora, regulatory pressures on OpenAI, and significant investments in AI infrastructure. Key topics include AMD's acquisition of Silo AI, Elon Musk's GPU cluster plans for XAI, unique AI model training methods, and the nuances of AI copying and memory constraints. We discuss developments in AI's visual perception, real-time knowledge updates, and the need for transparency and regulation in AI content labeling and licensing.
See full episode notes here.
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