Dlabs.ai

AUGUST 16, 2022

This is the challenge that explainable AI solves. Explainable artificial intelligence shows how a model arrives at a conclusion. What is explainable AI? Explainable artificial intelligence (or XAI, for short) is a process that helps people understand an AI model’s output. Let’s begin.

Explainability 52

Explainability Explainable AI AI Modeling Artificial Intelligence 52

Mlearning.ai

DECEMBER 31, 2023

Principles of Explainable AI( Source ) Imagine a world where artificial intelligence (AI) not only makes decisions but also explains them as clearly as a human expert. This isn’t a scene from a sci-fi movie; it’s the emerging reality of Explainable AI (XAI). What is Explainable AI?

Explainable AI 52

Explainable AI Explainability Black Box AI Neural Network 52

Unite.AI

JUNE 26, 2023

Similarly, what if a drug diagnosis algorithm recommends the wrong medication for a patient and they suffer a negative side effect? At the root of AI mistakes like these is the nature of AI models themselves. Most AI today use “black box” logic, meaning no one can see how the algorithm makes decisions.

Black Box AI 297

Black Box AI Explainable AI Explainability AI 297

Towards AI

JULY 22, 2023

Last Updated on July 24, 2023 by Editorial Team Author(s): Data Science meets Cyber Security Originally published on Towards AI. Now Algorithms know what they are doing and why! Let us go further into the enigmas of Artificial Intelligence, where AI is making waves like never before! SOURCE: [link] A.

Explainable AI 92

Explainable AI Explainability Neural Network Artificial Intelligence 92

Aiiot Talk

JULY 7, 2023

AI is today’s most advanced form of predictive maintenance, using algorithms to automate performance and sensor data analysis. Aircraft owners or technicians set up the algorithm with airplane data, including its key systems and typical performance metrics. One of the main risks associated with AI is its black-box nature.

Black Box AI 130

Black Box AI Algorithm Automation Explainable AI 130

IBM Journey to AI blog

JANUARY 25, 2024

Yet many AI creators are currently facing backlash for the biases, inaccuracies and problematic data practices being exposed in their models. These issues require more than a technical, algorithmic or AI-based solution. Consider, for example, who benefits most from content-recommendation algorithms and search engine algorithms.

AI 236

AI AI Explainability Algorithm 236

Unite.AI

OCTOBER 20, 2023

In addition, they can use group and individual fairness techniques to ensure that algorithms treat different groups and individuals fairly. Promote AI transparency and explainability: AI transparency means it is easy to understand how AI models work and make decisions.

Responsible AI 283

Responsible AI Generative AI AI AI 283

Unite.AI

DECEMBER 13, 2023

Ultimately, staying updated empowers enthusiasts to leverage the full potential of AI and make confident decisions in their professional and personal pursuits. AI-Powered Threat Detection and Response AI takes the lead in making the digital world safer.

AI 290

AI AI Responsible AI Explainability 290

Unite.AI

MARCH 18, 2024

Some of key ingredients of such an approach are highlighted below: Robust Data Verification : This step entails implementation of stringent processes to validate the accuracy, relevance, and quality of the data, filtering out harmful AI-generated content before it reaches AI models.

AI 189

AI AI Data Integration Generative AI 189

Dlabs.ai

JULY 19, 2023

Example: Algorithmic Bias in the UK A-level Grading To illustrate, consider a real-world example that occurred during the COVID-19 pandemic in the UK. With the traditional A-level exams canceled due to health concerns, the UK government used an algorithm to determine student grades.

Explainable AI 97

Explainable AI Explainability Auto-complete Algorithm 97

IBM Journey to AI blog

JUNE 26, 2023

What is generative AI? Generative AI uses an advanced form of machine learning algorithms that takes users prompts and uses natural language processing (NLP) to generate answers to almost any question asked. You can start by learning more about the advances IBM is making in new generative AI models with watsonx.ai

Generative AI 188

Generative AI Explainability Explainable AI Natural Language Processing 188

NVIDIA

MARCH 1, 2024

They have a simple goal: to enable trust and transparency in AI and support the work of partners, customers and developers. Privacy: Complying With Regulations, Safeguarding Data AI is often described as data hungry. Often, the more data an algorithm is trained on, the more accurate its predictions.

AI 135

AI AI AI Modeling Algorithm 135

Unite.AI

SEPTEMBER 13, 2023

Mystery and Skepticism In generative AI, the concept of understanding how an LLM gets from Point A – the input – to Point B – the output – is far more complex than with non-generative algorithms that run along more set patterns. Additionally, the continuously expanding datasets used by ML algorithms complicate explainability further.

Explainability 278

Explainability Generative AI AI Tools AI 278

Marktechpost

APRIL 24, 2024

To ensure practicality, interpretable AI systems must offer insights into model mechanisms, visualize discrimination rules, or identify factors that could perturb the model. Explainable AI (XAI) aims to balance model explainability with high learning performance, fostering human understanding, trust, and effective management of AI partners.

Explainable AI 114

Explainable AI Explainability Neural Network Data Scientist 114

Unite.AI

APRIL 22, 2024

AI-driven telehealth platforms, employing tools like chatbots, autonomously handle patient interactions, schedule appointments, and deliver medical information. With more than 13 million global users, Ada Health exemplifies transparent, explainable AI in healthcare, providing clear insights into the diagnostic process.

Chatbots 182

Chatbots Artificial Intelligence Artificial Intelligence Natural Language Processing 182

NYU Center for Data Science

JUNE 16, 2023

Home to both a thriving tech ecosystem and pioneering efforts on regulating algorithm decision-making systems, New York City provides a vibrant research environment and a plethora of interdisciplinary collaborators,” said Umang. For these reasons, I am excited to start my academic journey at NYU. By Meryl Phair

Machine Learning 107

Machine Learning Explainability Artificial Intelligence Artificial Intelligence 107

IBM Journey to AI blog

JULY 6, 2023

Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention. Deep learning algorithms are neural networks modeled after the human brain. Some people worry that AI and machine learning will eliminate jobs.

Data Science 158

Data Science Machine Learning Big Data Data Mining 158

Marktechpost

JANUARY 19, 2024

Epigenetic clocks accurately estimate biological age based on DNA methylation, but their underlying algorithms and key aging processes must be better understood. Epigenetic mechanisms, particularly DNA methylation, play a role in aging, though the specific biological processes remain unclear.

Neural Network 111

Neural Network Deep Learning Explainable AI Explainability 111

Dlabs.ai

JULY 25, 2023

In an era where AI and machine learning have streamlined everything, including hiring processes, the balance between efficiency and equity comes into question. With algorithms, machine learning, and statistical modeling defining who gets hired or promoted, are these decisions genuinely fair? Who do AEDT Regulations address?

Automation 98

Automation Algorithm Machine Learning Explainability 98

Pickl AI

APRIL 8, 2024

Summary: AI’s immense potential is undeniable, but its journey riddle with roadblocks. This blog explores 13 major AI blunders, highlighting issues like algorithmic bias, lack of transparency, and job displacement. 13 AI Mistakes That Are Worth Your Attention 1.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Algorithm AI 52

ODSC - Open Data Science

OCTOBER 24, 2023

Then, how to essentially eliminate training, thus speeding up algorithms by several orders of magnitude? My NoGAN algorithm, probably for the first time, comes with the full multivariate KS distance to evaluate results. Indeed, the whole technique epitomizes explainable AI. It is adjusted for dimension.

Categorization 98

Categorization Data Science Neural Network Algorithm 98

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. The plotting functionality is also included, so you only need to run a few lines of code.

Explainability 104

Explainability Explainable AI AI AI 104

Pickl AI

JANUARY 29, 2024

Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. The collective strength of both forms the groundwork for AI and Data Science, propelling innovation. Key takeaways Data Science lays the groundwork for Machine Learning, providing curated datasets for ML algorithms to learn and make predictions.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

IBM Journey to AI blog

APRIL 11, 2023

The new rules, which passed in December 2021 with enforcement , will require organizations that use algorithmic HR tools to conduct a yearly bias audit. This means that processes utilizing algorithmic AI and automation should be carefully scrutinized and tested for impact according to the specific regulations in each state, city, or locality.

AI Strategy 259

AI Strategy Algorithm Automation AI 259

Heartbeat

SEPTEMBER 13, 2023

Through several " Explainable Models ," explainability enables users to achieve insights into the inner workings of the models and understand the factors that influence their output. Algorithmic Accountability: Explainability ensures accountability in machine learning and AI systems.

Explainability 52

Explainability Machine Learning Deep Learning Explainable AI 52

IBM Journey to AI blog

JULY 17, 2023

While traditional AI approaches provide customers with quick service, they have their limitations. Currently chat bots are relying on rule-based systems or traditional machine learning algorithms (or models) to automate tasks and provide predefined responses to customer inquiries. Watsonx.ai

Generative AI 154

Generative AI Auto-complete AI AI 154

Towards AI

OCTOBER 7, 2023

Balancing Ethics and Innovation: An Introduction to the Guiding Principles of Responsible AI Sarah, a seasoned AI developer, found herself at a moral crossroads. One algorithm could maximize efficiency but at the cost of privacy. If you were Sarah, which algorithm would you choose? These kinds of decisions are made daily.

AI 64

AI AI Explainability Algorithm 64

Pickl AI

JULY 14, 2023

The following blog will emphasise on what the future of AI looks like in the next 5 years. Evolution of AI The evolution of Artificial Intelligence (AI) spans several decades and has witnessed significant advancements in theory, algorithms, and applications.

Neural Network 52

Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

Data Science 153

Data Science DevOps Machine Learning Data Scientist 153

Heartbeat

FEBRUARY 2, 2024

As AI strives to emulate human-like understanding, VQA plays a pivotal role by demanding systems to recognize objects and scenes in images and comprehend and respond to human-generated questions about those images. It's remarkable diversity and scale position it as a cornerstone for evaluating and benchmarking VQA algorithms.

Computer Vision 52

Computer Vision Natural Language Processing Artificial Intelligence Artificial Intelligence 52

Defined.ai blog

AUGUST 10, 2023

AI refers to computer systems capable of executing tasks that typically require human intelligence. On the other hand, ML, a subset of AI, involves algorithms that improve through experience. These algorithms learn from data, making the software more efficient and accurate in predicting outcomes without explicit programming.

Business Intelligence 52

Business Intelligence Data Analysis Neural Network AI 52

Viso.ai

FEBRUARY 12, 2024

True to its name, Explainable AI refers to the tools and methods that explain AI systems and how they arrive at a certain output. Artificial Intelligence (AI) models assist across various domains, from regression-based forecasting models to complex object detection algorithms in deep learning.

Explainable AI 52

Explainable AI Explainability Deep Learning Neural Network 52

Marktechpost

AUGUST 24, 2023

r/computervision Computer vision is the branch of AI science that focuses on creating algorithms to extract useful information from raw photos, videos, and sensor data. r/learnmachinelearning The subreddit is dedicated to learning the latest machine-learning algorithms. There are about 68k members.

Artificial Intelligence 97

Artificial Intelligence Artificial Intelligence Machine Learning Computer Vision 97

ODSC - Open Data Science

FEBRUARY 22, 2024

Join this upcoming training session which will demonstrate how you can use low-code/no-code programming platforms to effectively integrate geospatial analysis with a variety of AI algorithms, including machine learning, deep learning, and Explainable AI.

Machine Learning 52

Machine Learning Data Science Python ML 52

Dlabs.ai

MAY 22, 2022

It’ll help you get to grips with the fundamentals of ML and its respective algorithms, including linear regression and supervised and unsupervised learning, among others. That’s why it helps to know the fundamentals of ML and the different learning algorithms before you do any data science work.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Neural Network 52

ML @ CMU

MARCH 31, 2023

However, while numerous explainable AI (XAI) methods have been developed, XAI has yet to deliver on this promise. The stages of evaluation are adapted from Doshi-Velez and Kim (2017); we introduce an additional stage, use-case-grounded algorithmic evaluations, in a recent Neurips 2022 paper [ 2 ]. Our contributions.

ML 98

ML Explainability Algorithm Machine Learning 98

Unite.AI

APRIL 9, 2024

As organizations strive for responsible and effective AI, Composite AI stands at the forefront, bridging the gap between complexity and clarity. The Need for Explainability The demand for Explainable AI arises from the opacity of AI systems, which creates a significant trust gap between users and these algorithms.

Composite AI 182

Composite AI Explainability Black Box AI Explainable AI 182