Fundamental emerges from stealth with first major foundation model trained for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...
Analytics Insight

Top LLM Books for Learning from Beginner to Advanced in 2026

Large language models power everyday tools and reshape modern digital work.Beginner and advanced books together create a ...
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 ...
Hosted on MSN

Build a deep neural network from scratch in Python

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...
InfoWorld

PythoC: A new way to generate C code from Python

PythoC lets you use Python as a C code generator, but with more features and flexibility than Cython provides. Here’s a first look at the new C code generator for Python. Python and C share more than ...
GitHub

DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research

DR Tulu-8B is the first open Deep Research (DR) model trained for long-form DR tasks. DR Tulu-8B matches OpenAI DR on long-form DR benchmarks. agent/: Agent library (dr-agent-lib) with MCP-based tool ...
VentureBeat

Meta’s new CWM model learns how code works, not just what it looks like

Meta’s AI research team has released a new large language model (LLM) for coding that enhances code understanding by learning not only what code looks like, but also what it does when executed. The ...
IEEE

Deep Learning Approaches for EEG-Motor Imagery-Based BCIs: Current Models, Generalization Challenges, and Emerging Trends

Abstract: This study critically examines the evolution of deep learning (DL) for electroencephalogram (EEG) based motor imagery (MI) decoding with a focus on real-time Brain Computer Interfaces (BCIs) ...
GitHub

Self-Learning-VAE-for-EEG-Artifact-Removal

This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...
IEEE

Deep Learning for Channel Code Type Recognition

Abstract: Channel code type recognition is critical for enabling receivers to discern codes without prior knowledge. Despite the promise of deep learning approaches in this field, they often encounter ...
Game Rant

Roblox Become a Deep Sea Explorer Codes

For over 5 years, Arthur has been professionally covering video games, writing guides and walkthroughs. His passion for video games began at age 10 in 2010 when he first played Gothic, an immersive ...