Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities across various domains, propelling their evolution into multi-modal agents for human…
Machine Learning
Like humans, large language models (LLMs) often have differing skills and strengths derived from differences in their architectures and training…
In this tutorial, we demonstrate how to build an AI-powered PDF interaction system in Google Colab using Gemini Flash 1.5,…
Normalization layers have become fundamental components of modern neural networks, significantly improving optimization by stabilizing gradient flow, reducing sensitivity to…
LLMs are widely used for conversational AI, content generation, and enterprise automation. However, balancing performance with computational efficiency is a…
This is a guest post authored by the team at ByteDance. ByteDance is a technology company that operates a range…
In enterprise environments, organizations often divide their AI operations into two specialized teams: an AI research team and a model…
Brands today are juggling a million things, and keeping product content up-to-date is at the top of the list. Between…
LLMs have exhibited impressive capabilities through extensive pretraining and alignment techniques. However, while they excel in short-context tasks, their performance…
Comparing language models effectively requires a systematic approach that combines standardized benchmarks with use-case specific testing. This guide walks you…
Access to high-quality textual data is crucial for advancing language models in the digital age. Modern AI systems rely on…
In the rapidly evolving field of digital communication, traditional text-to-speech (TTS) systems have often struggled to capture the full range…
Vision-language models (VLMs) have demonstrated impressive capabilities in general image understanding, but face significant challenges when processing text-rich visual content…
Designing imitation learning (IL) policies involves many choices, such as selecting features, architecture, and policy representation. The field is advancing…
Efficient matrix multiplications remain a critical component in modern deep learning and high-performance computing. As models become increasingly complex, conventional…
This blog post is co-written with Gene Arnold from Alation. To build a generative AI-based conversational application integrated with relevant…
Troubleshooting infrastructure as code (IaC) errors often consumes valuable time and resources. Developers can spend multiple cycles searching for solutions…
This post is co-written with Xavier Vizcaino, Diego Martín Montoro, and Jordi Sánchez Ferrer from Applus+ Idiada. In 2021, Applus+…
Optimizing large-scale language models demands advanced training techniques that reduce computational costs while maintaining high performance. Optimization algorithms are crucial…
Pre-trained LLMs require instruction tuning to align with human preferences. Still, the vast data collection and rapid model iteration often…