MIT Technology Review

Making AI operational in constrained public sector environments

Purpose-built small language models provide a practical solution for government organizations to operationalize AI with the ...
Hackaday

TurboQuant: Reducing LLM Memory Usage With Vector Quantization

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the ...
Berkman Klein Center

Understanding algorithms — and how to make them work for you

Noah Giansiracusa asks: How nutritious is your social media diet? Containing too much social media 'junk food,' he notes for Science News Explores, can have deleterious effects, and so individuals ...

From LLMs to hallucinations, here’s a simple guide to common AI terms

The rise of AI has brought an avalanche of new terms and slang. Here is a glossary with definitions of some of the most ...
Scientific Research Publishing

Predicting Stock Price Movements Using Deep Learning Techniques ()

Stock Price Prediction, Deep Learning, LSTM, GRU, Attention Mechanism, Financial Time Series Share and Cite: Kirui, D. (2026) ...
Baseball Prospectus

PECOTA Projections

PECOTA, which stands for Player Empirical Comparison and Optimization Test Algorithm, is BP’s proprietary system that projects player and team performance PECOTA is a system that takes a player’s past ...
EDN

Self-correcting codes conquer noise, part one: Viterbi codecs

FEC (forward-error-correction) techniques correct errors at the receiver end of digital communications systems. In contrast with error-detection and retransmission ...