IEEE

An Adaptive Multistrategy Algorithm Based on Extent of Environmental Change for Dynamic Multiobjective Optimization

Abstract: The most obvious characteristic of dynamic multiobjective optimization problems (DMOPs) is the time-varying Pareto-optimal set (POS) or/and Pareto-optimal front (POF). This kind of problem ...
Computer Weekly

Interview: Researching quantum algorithms for today’s devices

While the billion-dollar question is about when quantum computing will become commercially viable, among the problems being tackled at the moment is how to make the ...
IEEE

An Iterated Greedy Algorithm With Reinforcement Learning for Distributed Hybrid Flowshop Problems With Job Merging

Abstract: The distributed hybrid flowshop scheduling problems (DHFSPs) widely exist in various industrial production processes, and thus have received widespread attention. However, the existing ...
TechCrunch

Google unveils TurboQuant, a new AI memory compression algorithm — and yes, the internet is calling it ‘Pied Piper’

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...
VentureBeat

Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...
Ars Technica

Google’s TurboQuant AI-compression algorithm can reduce LLM memory usage by 6x

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...