Computer Sciences news

Computer Sciences

Popular vs. reliable sources—a blind spot in how LLMs assess information

Large language models (LLMs), the artificial intelligence (AI) systems underpinning ChatGPT and similar conversational platforms, are now used by many people worldwide to find and summarize information and generate different ...

Computer Sciences

EAR-Sys could reduce airport computing delays by 14% during major disruptions

Airports could become better able to withstand major operational disruptions under a new computing system designed to keep digital services running during periods of intense pressure. Details are reported in the International ...

Computer Sciences

AI gains a tool to identify Kinyarwanda propaganda, with promise for 600 Bantu languages

A new study led by Fabrice Niyigaba '27 reports the first digital tool for identifying online propaganda in Kinyarwanda, the national language of Rwanda's 15 million people—and possibly the first for any of the Bantu languages ...

Computer Sciences

New tool identifies the sources of fake videos

Artificial intelligence can generate videos so realistic that distinguishing them from authentic footage is becoming increasingly difficult. But a computer science team led by researchers at UC Riverside has developed a tool ...

Computer Sciences

Professor pushes computers to solve 'unsolvable' problems

Don't underestimate the power of a yes-or-no question. Some of the toughest computing problems boil down to thousands of tiny yes-or-no decisions. Finding the best combination of answers could be the key to anything from ...

Computer Sciences

Researchers develop key technology to make personalized AI safer

The era of building "personalized AI" by training AI models on individual or corporate documents and data is beginning. However, while such customization can improve task performance, it can also weaken a model's existing ...

Computer Sciences

Testing the limits of what's possible (and what isn't) with AI

When can we trust the results we get from AI, and when is learning impossible? Researchers have shown that there are some problems that even the most powerful AI cannot reliably solve, no matter how much data it is given.

Computer Sciences

Building out the quantum computing toolkit

Quantum computers lack useful functionality without the right algorithms to facilitate their operation. Currently, there are few simple, standardized operations, known as "primitives," in the quantum toolkit that can help ...

Computer Sciences

Easier parameter tuning for prediction using echo state networks

Neural networks, a fascinating technology inspired by the human brain, form the basis of artificial intelligence. These networks consist of layers of interconnected nodes, or artificial neurons, that learn patterns from data ...

Robotics

Sheepdogs reveal a better way to guide robot swarms

Sheepdogs, bred to control large groups of sheep in open fields, have demonstrated their skills in competitions dating back to the 1870s. In these contests, a handler directs a trained dog with whistle signals to guide a ...

Computer Sciences

What flocking birds can teach AI about reducing noise

Among the primary concerns surrounding artificial intelligence is its tendency to yield erroneous information when summarizing long documents. These "hallucinations" are problematic not only because they convey falsehoods, ...

Computer Sciences

Shortest paths research narrows a 25-year gap in graph algorithms

Most of you have used a navigation app like Google Maps for your travels at some point. These apps rely on algorithms that compute shortest paths through vast networks. Now imagine scaling that task to calculate distances ...

Computer Sciences

The AI that taught itself: How AI can learn what it never knew

For years, the guiding assumption of artificial intelligence has been simple: an AI is only as good as the data it has seen. Feed it more, train it longer, and it performs better. Feed it less, and it stumbles. A new study ...

Computer Sciences

Improving AI models' ability to explain their predictions

In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept bottleneck modeling is one ...

Computer Sciences

Deep AI training gets more stable by predicting its own errors

Artificial intelligence now plays Go, paints pictures, and even converses like a human. However, there remains a decisive difference: AI requires far more electricity than the human brain to operate. Scientists have long ...

Computer Sciences

Don't panic: 'Humanity's last exam' has begun

When artificial intelligence systems began acing long-standing academic assessments, researchers realized they had a problem: the tests were too easy. Popular evaluations, such as the Massive Multitask Language Understanding ...

Computer Sciences

Adaptive drafter model uses downtime to double LLM training speed

Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller steps. These powerful models are particularly good at challenging tasks like advanced programming ...