Distributed systems comprise a network of independent computing nodes that collaborate to achieve shared objectives despite challenges such as network latency, asynchrony and process failures. At the ...
Machine learning's transformative shift mirrors the MapReduce moment, revolutionizing efficiency with decentralized consensus ...
In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing, ...
Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...
Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...
Can we ever really trust algorithms to make decisions for us? Previous research has proved these programs can reinforce society’s harmful biases, but the problems go beyond that. A new study shows how ...
The following essay is reprinted with permission from The Conversation, an online publication covering the latest research. People’s daily interactions with online algorithms affect how they learn ...
Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...
People’s daily interactions with online algorithms affect how they learn from others, with negative consequences including social misperceptions, conflict and the spread of misinformation, my ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results