10 Important Blogs to Stay Updated with LLM Research & News
Author(s): Youssef Hosni Originally published on Towards AI. Staying up-to-date with the rapidly evolving world of Large Language Model (LLM) research and news can be a challenging task. With countless resources and endless streams of information, itβs easy to get overwhelmed. Luckily, …
Reinforcement Learning: Introducing Deep Q* Networks β Part 6
Author(s): Tan Pengshi Alvin Originally published on Towards AI. An adjusted framework combining Deep Q-Networks with a trainable exploration heuristic and supervisionPhoto by Chantal & Ole on Unsplash You may have heard of Project Q*, a leaked idea from OpenAI in the …
AI Hallucinations
Author(s): Paul Ferguson, Ph.D. Originally published on Towards AI. Where Artificial Intelligence Meets Artificial ImaginationImage generated by Dall-E In an age where AI can outperform humans in complex tasks, itβs also spinning tales that would make Baron Munchausen blush. Large Language Models …
Adversarial Machine Learning: Defense Strategies
Author(s): MichaΕ Oleszak Originally published on Towards AI. Know thine enemy and protect your machine learning systems. The growing prevalence of ML models in business-critical applications results in an increased incentive for malicious actors to attack the models for their benefit. Developing …
Demystifying the Black Box: Advanced Techniques in Interpretable AI with SHAP and LIME
Author(s): saeed garmsiri Originally published on Towards AI. Photo by Andrea De Santis on Unsplash Demystifying the Black Box: Advanced Techniques in Interpretable AI with SHAP and LIME Hey ML Engs out there! Ever felt like youβve created a brilliant machine learning …
Generative AI Foundations: Training a Vanilla GAN for Fashion
Author(s): Amit Kharel Originally published on Towards AI. Photo by Mateusz WacΕawek on Unsplash GAN learning to generate Images [By Author] (Not a member? Read the article for free.) Letβs step back and take a break from the over-hype of LLMs/Transformers and …
#32 Understanding AdaBoost From Its Original 1997 Paper
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, I have a very exciting announcement to make. I have partnered with OβReilly to create two specific βshortcutβ video series on LLMs and GenAI research. The …
Bayesian analysis and decision theory: application to determine a decision point for classification problems
Author(s): Greg Postalian-Yrausquin Originally published on Towards AI. A dilemma often presented in classification problems where the output is a number is determining the cutout point between the categories. For example, the output of a neural network might be a number between …
A Complete Guide to Descriptive Statistics β Central Tendency and Dispersion
Author(s): Anmol Tomar Originally published on Towards AI. A one-stop solution for understanding Descriptive StatisticsImage generated through AI by Author In a world filled with data, statistics is the compass guiding us through the huge seas of numbers. Statistics play an important …
From Concept to Creation: U-Net for Flawless Inpainting
Author(s): Dawid KopeΔ Originally published on Towards AI. From Concept to Creation: U-Net for Flawless Inpainting Introduction Image inpainting is a powerful computer vision technique for restoring missing or damaged parts of images. This article goes deeper into building and implementing a …
Important LLMs Papers for the Week from 08/07 to 14/07
Author(s): Youssef Hosni Originally published on Towards AI. Stay Updated with Recent Large Language Models Research Large language models (LLMs) have advanced rapidly in recent years. As new generations of models are developed, researchers and engineers need to stay informed on the …
Revolutionizing Named Entity Recognition with Efficient Bidirectional Transformer Models
Author(s): Chien Vu Originally published on Towards AI. The light NER model outperforms both ChatGPT and fine-tuned LLMs in zero-shot evaluations on various NER benchmarks.Image by author Named Entity Recognition (NER) is an important task in Natural Language Processing (NLP) that involves …
Fine-Tuning LLMs with Synthetic Data for High-Quality Content Generation
Author(s): Vin Busquet Originally published on Towards AI. Evaluation data analysis featured in this article. (Photo of the authorβs monitor) Table of Contents Β· Table of ContentsΒ· The POC Trek BeginsΒ· Fine-Tuning VS RAG β What is fine-tuning? β So, what is …
Quantization: Post Training Quantization, Quantization Error, and Quantization Aware Training
Author(s): JAIGANESAN Originally published on Towards AI. Photo by Jason Leung on Unsplash Most of us used open-source Large Language Models, VLMs, and Multi-Modal Models in our system, colab, or Kaggle notebook. You might have noticed that most of the time we …
GraphRAG Is the Logical Step From RAG β So Why the Sudden Hype?
Author(s): Daniel Voyce Originally published on Towards AI. Photo by Steve Johnson on Unsplash It seems like everyone is currently talking about GraphRAG as the successor to RAG (Retrieval-Augmented Generation) in the Generative AI / LLM world right now. But is it …
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