IEEE

Solving Scalable Multiagent Routing Problems With Reinforcement Learning

Abstract: Multiagent routing problems, arising from practical applications, such as logistics, transportation, and emergency response, face challenges due to the exponential growth of the search space ...
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

Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization

Abstract: In this survey, we introduce Meta-Black-Box-Optimization (MetaBBO) as an emerging avenue within the Evolutionary Computation (EC) community, which incorporates Meta-learning approaches to ...
GitHub

find_graph_symmetries_test.cc

#include "absl/strings/str_cat.h" #include "absl/strings/str_join.h" #include "absl/strings/str_split.h" #include "ortools/algorithms/dynamic_partition.h" #include ...
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 ...