Towards AI

FEBRUARY 3, 2024

(Left) Photo by Pawel Czerwinski on Unsplash U+007C (Right) Unsplash Image adjusted by the showcased algorithm Introduction It’s been a while since I created this package ‘easy-explain’ and published on Pypi. A few weeks ago, I needed an explainability algorithm for a YoloV8 model. The truth is, I couldn’t find anything.

Explainability 109

Explainability Explainable AI Neural Network Algorithm 109

Analytics Vidhya

MARCH 23, 2023

This blog post will delve into the incident, its implications, and the essential steps required to ensure user privacy and trust in the age of AI. […] The post Navigating Privacy Concerns: The ChatGPT User Chat Titles Leak Explained appeared first on Analytics Vidhya.

Explainability 294

Explainability ChatGPT OpenAI AI 294

colah's blog

JANUARY 26, 2023

Information theory is a prime example of this. Information theory gives us precise language for describing a lot of things. I’ve had informal versions of these ideas since I was a young child, but information theory crystallizes them into precise, powerful ideas. How uncertain am I? Read more.

Explainability 130

Explainability Machine Learning 130

PyImageSearch

OCTOBER 14, 2024

This blog post is the 1st of a 3-part series on 3D Reconstruction: Photogrammetry Explained: From Multi-View Stereo to Structure from Motion (this blog post) 3D Reconstruction: Have NeRFs Removed the Need for Photogrammetry? 3D Gaussian Splatting: The End Game of 3D Reconstruction? To learn about 3D Reconstruction, just keep reading.

Explainability 115

Explainability Computer Vision Deep Learning Algorithm 115

Towards AI

OCTOBER 30, 2024

Microsoft’s OmniParser is thoroughly documented in an accompanying paper, which explains each component in a clear and accessible way. It simply provides instructions like “click here” or “navigate to that option” based on information from sources like Stack Overflow. Image from the author Now, we want to take this a step further.

Explainability 105

Explainability Large Language Models Algorithm ChatGPT 105

Pickl AI

AUGUST 23, 2024

Summary: This blog post delves into the importance of explainability and interpretability in AI, covering definitions, challenges, techniques, tools, applications, best practices, and future trends. For instance, if a model predicts that a loan application should be denied, explainability seeks to clarify the rationale behind this decision.

Explainability 52

Explainability Deep Learning Machine Learning Neural Network 52

Towards AI

FEBRUARY 13, 2024

Introduction It’s been a while since I created this package ‘easy-explain’ and published it on Pypi. GradCam is a widely used Explainable AI method that has been extensively discussed in both forums and literature. LayerCAM aggregates information across multiple layers for a more detailed heatmap. So, let’s import the libraries.

Explainability 90

Explainability Explainable AI AI AI 90

Marktechpost

OCTOBER 6, 2024

To address these challenges, researchers are exploring Multimodal Large Language Models (M-LLMs) for more explainable IFDL, enabling clearer identification and localization of manipulated regions. Although these methods achieve satisfactory performance, they need more explainability and help to generalize across different datasets.

Large Language Models 106

Large Language Models Explainability Explainable AI AI 106

Towards AI

OCTOBER 19, 2024

Quantization explained in plain English When BERT was released around 5 years ago, it triggered a wave of Large Language Models with ever increasing sizes. They are huge & bulky and have been shown to have sparse information. Last Updated on October 19, 2024 by Editorial Team Author(s): Allohvk Originally published on Towards AI.

Explainability 102

Explainability LLM BERT Large Language Models 102

Marktechpost

AUGUST 7, 2024

The Role of Explainable AI in In Vitro Diagnostics Under European Regulations: AI is increasingly critical in healthcare, especially in vitro diagnostics (IVD). These AI systems must perform accurately and provide explainable results to comply with regulatory requirements.

Explainable AI 106

Explainable AI Explainability Neural Network Algorithm 106

IBM Journey to AI blog

JUNE 1, 2023

Managing offsets and RECs If carbon offsets or renewable energy certificates (RECs) have been used, information about the carbon offsets or RECs, including the amount of carbon reduction represented by the offsets or the amount of generated renewable energy represented by the RECs, can be tracked in Envizi.

Explainability 166

Explainability ESG Categorization 166

Towards AI

MARCH 17, 2024

Alongside this, there is a second boom in XAI or Explainable AI. Explainable AI is focused on helping us poor, computationally inefficient humans understand how AI “thinks.” We will then explore some techniques for building glass-box or explainable models. Ultimately these definitions end up being almost circular!

Explainable AI 92

Explainable AI Explainability Neural Network AI 92

ODSC - Open Data Science

NOVEMBER 30, 2023

Explainable AI might be the solution everyone needs to develop a healthier, more trusting relationship with technology while expediting essential medical care in a highly demanding world. What Is Explainable AI? Explainable AI (XAI) refers to AI that explains how, where, and why it produces decisions.

Explainable AI 94

Explainable AI Explainability Data Scientist Data Mining 94

Marktechpost

AUGUST 13, 2024

Georgia Tech and IBM Research researchers have introduced a novel tool called Transformer Explainer. Transformer Explainer is an open-source, web-based platform allowing users to interact directly with a live GPT-2 model in their web browsers. This tool is designed to make learning about Transformers more intuitive and accessible.

Explainability 129

Explainability AI Modeling Natural Language Processing Machine Learning 129

Pickl AI

OCTOBER 8, 2024

Summary: This blog discusses Explainable Artificial Intelligence (XAI) and its critical role in fostering trust in AI systems. One of the most effective ways to build this trust is through Explainable Artificial Intelligence (XAI). What is Explainable AI (XAI)? What is Explainable AI (XAI)?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Explainability Explainable AI 52

Unite.AI

JUNE 19, 2023

Adam Asquini is a Director of Information Management & Data Analytics at KPMG in Edmonton. He's former Gartner and MIT, and it's a really good book to explain a monetization framework for data. We've seen significant work in consolidating supply contracts by just being able to better search and query and find information.

Generative AI 244

Generative AI Responsible AI Artificial Intelligence Artificial Intelligence 244

AssemblyAI

DECEMBER 7, 2023

  This problem is harder for audio because audio data is far more information-dense than text. A joint audio-language model trained on suitably expansive datasets of audio and text could learn more universal representations to transfer robustly across both modalities. 

Explainability 278

Explainability Large Language Models AI AI 278

Flipboard

NOVEMBER 12, 2024

What Is Artificial Intelligence (AI)? Artificial intelligence (AI) is a technology with human-like problem-solving capabilities. AI in action appears …

Artificial Intelligence 130

Artificial Intelligence Artificial Intelligence Explainability AI 130

Marktechpost

JULY 22, 2024

This lack of explainability is a gap in academic interest and a practical concern. This is a critical limitation as the demand for explainable AI grows. This dual capability is essential for advancing explainable artificial intelligence. Current AV models focus mainly on binary classification, which often lacks transparency.

Explainability 96

Explainability BERT Large Language Models Deep Learning 96

IBM Journey to AI blog

JULY 6, 2023

General disclosures encompass basic company information. Performance indicators include details of social impact assessments, information on projects involving rehabilitation and resettlement and details of procurement policies that favor marginalized or vulnerable groups.

ESG 185

ESG Explainability Automation 185

NVIDIA

MAY 1, 2024

enhances the performance of AI systems across various metrics like accuracy, explainability and fairness. The AI Podcast · Explainable AI: Insights from Arthur AI’s Adam Wenchel – Ep. Their conversation spans a range of topics, including AI bias, the observability of AI systems and the practical implications of AI in business.

Explainable AI 83

Explainable AI Explainability Computer Vision Large Language Models 83

AWS Machine Learning Blog

JULY 30, 2024

That’s why the company empowers millions of individuals and small businesses to comprehend tax-related information effortlessly and file with full confidence that their taxes are done right. Nhung explained. Tax filing can be a challenge, with its ever-changing regulations and intricate nuances. It is estimated that Americans spend 8.9

Explainability 112

Explainability Generative AI LLM ML 112

Towards AI

JUNE 17, 2024

Multimodal refers to handling different types of information — like audio, video, text, and images where each of it is called a mode. Today, we are diving into multimodal models thanks to Chameleon’s paper, which has very useful details for building such a powerful model. Hence the name multimodal, for multiple modes or modality.

Explainability 93

Explainability LLM AI AI 93

Towards AI

APRIL 10, 2024

It cost me way too much time and confusion to figure all this out, so in this blog post, I wanted to do my best to clearly explain what each of those ML jobs means. But what actually are the differences between a Data Engineer, Data Scientist, ML Engineer, Research Engineer, Research Scientist, or an Applied Scientist?!

ML Engineer 96

ML Engineer ML Explainability Machine Learning 96

IBM Journey to AI blog

APRIL 21, 2023

NFRD vs. CSRD: Key differences explained The EU CSRD builds on the existing NFRD to make reporting more thorough and relevant. On a larger scale, this facilitates a more equitable EU financial system as stakeholders will be able to make more informed decisions based on easily accessible and standardized sustainability data.

ESG 113

ESG Explainability Automation AI 113

Marktechpost

OCTOBER 21, 2024

MIND enables the generation of conversations in seven different styles, including settings like “Teacher-Student” and “Two Professors,” to explore various ways of presenting and explaining mathematical concepts. Check out the Paper. All credit for this research goes to the researchers of this project.

Large Language Models 106

Large Language Models Inference Engine AI AI 106

AI News

OCTOBER 8, 2024

“The question that I investigate is, how do we get this kind of information, this normative understanding of the world, into a machine that could be a robot, a chatbot, anything like that?” So, in this field, they developed algorithms to extract information from the data. ” Canavotto says.

Artificial Intelligence 274

Artificial Intelligence Artificial Intelligence Explainability Big Data 274

Pickl AI

OCTOBER 14, 2024

Each technique is explained with real-world use cases to illustrate its application. Understanding these methods enables organisations to gather accurate data, driving informed decision-making and enhancing strategies in various fields, from business to research. Insights gained can inform store layout and product placement strategies.

Explainability 52

Explainability Data Quality 52

Mlearning.ai

JULY 30, 2023

THE BASICS Introduction I haven’t had much time to write lately but I feel that there is growing interest in quantum information theory as of lately. On an abstract level, quantum information isn’t that difficult to grasp. In quantum information theory on the other hand those states are presented as | 0 ⟩ and | 1 ⟩.

Explainability 52

Explainability AI AI ML 52

AWS Machine Learning Blog

SEPTEMBER 14, 2023

This post takes you through the most common challenges that customers face when searching internal documents, and gives you concrete guidance on how AWS services can be used to create a generative AI conversational bot that makes internal information more useful. The cost associated with training models on recent data is high.

Generative AI 115

Generative AI LLM Large Language Models Software Engineer 115

Marktechpost

APRIL 28, 2024

In the ever-evolving field of machine learning, developing models that predict and explain their reasoning is becoming increasingly crucial. Traditionally, methods to increase model transparency have included various feature attribution techniques that explain predictions by assessing the importance of input variables.

Machine Learning 111

Machine Learning Explainability AI AI 111

Marktechpost

MARCH 22, 2024

There are major worries about data traceability and reproducibility because, unlike code, data modifications do not always provide enough information about the exact source data used to create the published data and the transformations made to each source. This information will then be indexed as part of a data catalog.

Machine Learning 134

Machine Learning Explainability Categorization ETL 134

Marktechpost

JANUARY 28, 2024

These studies, while informative, face significant limitations due to the high-dimensional nature of genotypes and the intricate, non-linear interactions of genetic components in determining an organism’s fitness. Fitness landscape studies have involved experimental methods to measure the fitness of various genotypes.

Explainability 111

Explainability Deep Learning Neural Network Machine Learning 111

Marktechpost

JANUARY 12, 2024

One of the most important areas of NLP is information extraction (IE), which takes unstructured text and turns it into structured knowledge. So, instead of extracting structural information from plain text, generative IE approaches that use LLMs to create structural information has recently become very popular.

Large Language Models 130

Large Language Models Chatbots BERT NLP 130

Marktechpost

JUNE 21, 2024

In this article we will explain a number of sophisticated prompt engineering strategies, simplifying these difficult ideas through straightforward human metaphors. In GoT, vertices are information units, sometimes known as LLM thoughts, and edges are the dependencies among these vertices.

Prompt Engineer 105

Prompt Engineer Prompt Engineering Explainability Large Language Models 105

Heartbeat

SEPTEMBER 7, 2023

In the ever-evolving landscape of machine learning and artificial intelligence, understanding and explaining the decisions made by models have become paramount. Enter Comet , that streamlines the model development process and strongly emphasizes model interpretability and explainability. Why Does It Matter?

Explainability 52

Explainability Machine Learning Data Scientist Deep Learning 52

AWS Machine Learning Blog

JANUARY 25, 2023

Model explainability refers to the process of relating the prediction of a machine learning (ML) model to the input feature values of an instance in humanly understandable terms. This field is often referred to as explainable artificial intelligence (XAI). In this post, we illustrate the use of Clarify for explaining NLP models.

Explainability 77

Explainability Natural Language Processing Algorithm Machine Learning 77