Concept – Up As Pro

This exploration into AI advancement covers PyTorch’s num_workers and pin_memory for data processing, Stability AI’s Stable Code Instruct 3B for AI-driven code generation, and the efficiencies and complexities of Mixture of Experts (MoE) models in AI development. It outlines how these innovations are reshaping the computational landscape for developers and businesses, indicating a stride towards superior efficiency and scalability in machine learning models.

Code Concept paper Series

May 31, 2024 admin

Top papers: Deleting 40% Without Accuracy Drop, Turbo Sketch, AnimateDiff

Recent research by Meta, Cisco, and MIT shows that pruning 40-50% of Large Language Model layers can maintain accuracy, offering faster, cost-effective AI. Novel techniques like Img2Img Turbo Sketch and AnimateDiff-Lightning demonstrate efficient image creation and rapid video generation from text. These developments suggest smaller AI models can be equally effective, heralding a potential shift in resource utilization and training methods.

UpasPro, Pedram Agand personal blog. AI and financial advice

Code Concept paper

May 22, 2024 admin

1-bit LLMs by Microsoft | Implementing GPT in 60 Lines

Microsoft released BitNet b1.58, a new Large Language Model (LLM) using 1.58 bits per parameter, reducing computational demands significantly while

Academic Code Concept Technology

May 17, 2024 admin

Large word model and YOLOV9

A new open-source bomb dropped when researchers from the Berkeley AI research lab, led by Prof Pieter Abbeel, released Large

Academic Code Concept

May 15, 2024 admin

Self-Rewarding Language Models

Self-Rewarding Language Models (Self-Rewarding LMs) show remarkable performance by using an LLM-as-a-Judge mechanism during Iterative DPO training, outpacing models like

Academic Algorithm Code Concept Machine Learning

May 7, 2024 admin

Better Images, Less Training

The longer text-to-image models train, the better their output — but the training is costly. Researchers built a system that

Algorithm Code Concept

April 28, 2024 admin

Deep dive: Knowledge distillation

In this deep dive seri, we are going over Knowledge distillation (KD), Partial Function Application, Learning rate Scheduler for LLM

Academic Algorithm Code Concept FEATURED Machine Learning

April 26, 2024 admin

QLoRA: efficiently LLM Fine-Tuning

Parameter-efficient training (PEFT) techniques offer a way to fine-tune large language models (LLMs) on custom datasets with minimal computational resources.