The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...

In an age which is as transformational as it is transforming, education needs to evolve to remain effective and productive. Traditional ...

Rules-based automation (RBA) and learning are two training mechanisms in robotics. While there are many others, these are two ...

Grammatical error correction (GEC) is a key task in natural language processing (NLP), widely applied in education, news, and ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting expertise.From neural networks to N ...

MemRL separates stable reasoning from dynamic memory, giving AI agents continual learning abilities without model fine-tuning ...

These strategies help teachers set up engaging and enriching opportunities for literacy exploration throughout the day.

Recent survey delivers the first systematic benchmark of TSP solvers spanning end-to-end deep learners, hybrid methods and brand-new LLM-based hybrids, revealing that hybrids give best-in-class routes ...

A massive new study comparing more than 100,000 people with today’s most advanced AI systems delivers a surprising result: ...

The findings, published in Scientific Reports, point to a major shift. Generative AI systems have now reached a level where they can outperform the average human on certain creativity measures. At the ...

Robotics is entering a new phase where general-purpose learning matters as much as mechanical design. Instead of programming ...

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method that aligns memristor hardware's noisy updates with neural network training, ...