Tech Xplore

Lowering barriers to explainable AI: Control technique for LLMs reduces resource demands by over 90%

Large language models (LLMs) such as GPT and Llama are driving exceptional innovations in AI, but research aimed at improving ...

How can Canada become a global AI powerhouse? By investing in mathematics

AI shapes daily life but remains unreliable and costly. Canada can lead by investing in the mathematics that make these ...

Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
InfoQ

Meta Details GEM Ads Model Using LLM-Scale Training, Hybrid Parallelism, and Knowledge Transfer

Meta released details about its Generative Ads Model (GEM), a foundation model designed to improve ads recommendation across ...

Nvidia: Transition To Long Thinking Models Is Beyond Traditional AI Growth Patterns

Nvidia's revenue momentum is underpinned by a $0.5 trillion Blackwell/Rubin pipeline. Click here to read more about NVDA stock and why it is a Strong Buy.
IEEE

Non-linear Dynamic System Identification on Application of Industrial Control

Abstract: System identification is a vital aspect of modern control and automation, offering a pathway to develop mathematical models from observed input-output data of dynamic systems. This paper ...

Target Test Prep GRE and GMAT Review

Learn about Target Test Prep GMAT and GRE courses, their quant-first approach, custom study plans, and tools that help improve exam scores.
IEEE

A Review on the Applications of Machine Learning and Deep Learning Algorithms for Image Recognition

Abstract: Modern image recognition has experienced dramatic improvements because of Machine Learning and Deep Learning algorithms together. This study investigates CNNs and SVMs for recognition ...