Machine learning

ABYKMB Optical Memory and Neural Networks

Multitasking memory

The abilities and power of a type of transformer model with memory is greatly improved by learning several key tasks at once during training.

MBKAPB Animals

Adaptability speeds evo

Based on computer simulations, we argue developmental plasticity accelerates evolution and drives organisms towards ever-greater complexity.

Machine learning

MBMRAJ MIT Sloan Management Review

The limits of LLMs

Large language models like ChatGPT can generate human-like text but businesses that overestimate their abilities risk misusing the technology.

Machine learning

DZDKFIMTDE... Meeting for the Association of Computational Linguistics

DeepPavlov dream

A new open-source platform is specifically tailored for developing complex dialogue systems, like generative conversational AI assistants.

Computational linguistics

Arxiv

Cross-lingual knowledge

Models trained on a Russian topical dataset, of knowledge-grounded human-human conversation, are capable of real-world tasks across languages.

Machine learning

Nucleic Acids Research

Speaking DNA

A family of transformer-based DNA language models can interpret genomic sequences, opening new possibilities for complex biological research.

Machine learning

Proceedings of the AAAI Conference

BERT enhanced with recurrence

The quadratic complexity of attention in transformers is tackled by combining token-based memory and segment-level recurrence, using RMT.

AI-assisted maths

Neural Computation

Free energy and learning

Using the free energy principle to derive multiple theories of associative learning allows us to combine them into a single, unifying framework.