Anthropic research reveals AI models perform worse with extended reasoning time, challenging industry assumptions about test-time compute scaling in enterprise deployments.

We consider a linear regression model with errors modelled by martingale difference sequences, which include heteroskedastic augmented GARCH processes. We develop asymptotic theory for two monitoring ...

The mathematics behind artificial intelligence (AI) and machine learning (ML) rely on linear algebra, calculus, probability, and statistics.

Chain-of-thought reasoning mirrors human problem solving by breaking down complex tasks into simpler, manageable sub-tasks. The use of scratchpad-like reasoning in large language models is not a ...

ESPN’s formula is not a total black box. The company has suggested that it calculates the live, in-game probability from the same kinds of data streams that other such models use.

MIT researchers use large language models to flag problems in complex systems The approach can detect anomalies in data recorded over time, without the need for any training. Date: August 13, 2024 ...

Olefin block copolymers (OBCs)─a new type of linear thermoplastic ethylene/1-olefin elastomer─are made via chain-shuttling polymerization using two catalysts with different reactivity ratios and a ...

Purpose: We tried to establish the normal tissue complication probability (NTCP) model of temporal lobe injury of recurrent nasopharyngeal carcinoma (NPC) patients after two courses of intensity ...

Handling uncertainty in model predictive control (MPC) comes with various challenges, especially when considering state constraints under uncertainty. Most methods focus on either the conservative ...

Zhou began his quest for the solution to this problem with a simple question posed to his introductory probability class for engineering students. In the class, he asked: “What is the probability of ...