InfoWorld

Multi-token prediction technique triples LLM inference speed without auxiliary draft models

With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.

Bringing quantum ideas to the messy world of disordered proteins

Imagine trying to design a key for a lock that is constantly changing its shape. That is the exact challenge we face in ...
Wired

AI Models Are Starting to Learn by Asking Themselves Questions

An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence. Save this story Save this story Even the smartest artificial intelligence ...
C&EN

Research on Remaining Useful Life Prediction of PEMWE Stack Based on the LSTM-iTransformer Model

In the context of global energy shortages, traditional energy sources face issues of limited reserves and high prices. As a result, the importance of energy storage technology is increasingly ...
devdiscourse

AI-powered forecasting boosts retail efficiency: LSTM outshines traditional models

In a new comparative analysis of artificial intelligence applications in retail, researchers have revealed that advanced deep learning models can dramatically enhance the accuracy of demand ...
Forbes

Banking On Trust: FICO Launches Financial Foundation Models

While much of the activity in the AI markets are focused on the tech giants chasing ever-increasing model sizes and compute budgets, financial company FICO is going the other way with smaller, smarter ...
GitHub

Denovo-Chemical-Molecule-Generation-with-LSTM-RL

This project enables the generation of novel, valid, and drug-like molecules as SMILES strings, using a two-stage approach: Stage 1: Train an LSTM model on a large SMILES dataset for next-token ...
GEN

BindCraft AI Model Achieves One-Shot Functional Protein Design

For the field of drug development, hitting the right target with atomic precision to achieve therapeutic effect remains the core challenge. While traditional R&D pipelines are dependent on ...
GitHub

NCRF++: An Open-source Neural Sequence Labeling Toolkit

Sequence labeling models are quite popular in many NLP tasks, such as Named Entity Recognition (NER), part-of-speech (POS) tagging and word segmentation. State-of-the-art sequence labeling models ...
Frontiers

A hybrid VMD-LSTM-SVR model for landslide prediction

Landslides are one of the most prevalent natural geological disasters, causing significant economic losses, damaging public environments, and posing severe threats to human lives. Landslide ...
Frontiers

Forecasting sea level rise using enhanced deep learning models

Climate change has significantly impacted vulnerable communities globally, with rising temperatures caused by greenhouse gas emissions accelerating global Sea Level Rise (SLR), threatening coastal ...
IEEE

A Variational Inference-Based LSTM-Enhanced Deep Neural Model for Sequential Recommendations

Abstract: Long Short-Term Memory (LSTM) networks are particularly useful in recommender systems since user preferences change over time. Unlike traditional recommender models which assume static ...