Unite.AI

JANUARY 20, 2025

Transparency = Good Business AI systems operate using vast datasets, intricate models, and algorithms that often lack visibility into their inner workings. This opacity can lead to outcomes that are difficult to explain, defend, or challengeraising concerns around bias, fairness, and accountability.

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Unite.AI

DECEMBER 27, 2024

Its because the foundational principle of data-centric AI is straightforward: a model is only as good as the data it learns from. No matter how advanced an algorithm is, noisy, biased, or insufficient data can bottleneck its potential. Another promising development is the rise of explainable data pipelines. Why is this the case?

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Unite.AI

NOVEMBER 22, 2024

This “black box” nature of AI raises concerns about fairness, reliability, and trust—especially in fields that rely heavily on transparent and accountable systems. It helps explain how AI models, especially LLMs, process information and make decisions. Finally, Gemma Scope plays a role in improving AI safety.

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Towards AI

MARCH 17, 2024

It is also garnering massive popularity in organizations and enterprises, with every corner of every business implementing LLMs, Stable Diffusion, and the next trendy AI product. Alongside this, there is a second boom in XAI or Explainable AI. Interpretability — Explaining the meaning of a model/model decisions to humans.

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ODSC - Open Data Science

NOVEMBER 30, 2023

Healthcare systems are implementing AI, and patients and clinicians want to know how it works in detail. 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?

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Unite.AI

DECEMBER 13, 2023

The future involves human-AI collaboration to tackle evolving trends and threats in 2024. Importance of Staying Updated on Trends Staying updated on AI trends is crucial because it keeps you informed about the latest advancements, ensuring you remain at the forefront of technological innovation.

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IBM Journey to AI blog

AUGUST 9, 2024

What is predictive AI? Predictive AI blends statistical analysis with machine learning algorithms to find data patterns and forecast future outcomes. In short, predictive AI helps enterprises make informed decisions regarding the next step to take for their business.

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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.

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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.

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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.

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IBM Journey to AI blog

OCTOBER 12, 2023

But the implementation of AI is only one piece of the puzzle. They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Checkpoints can be created throughout the AI lifecycle to prevent or mitigate bias and drift.

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Unite.AI

MARCH 18, 2024

On the other hand, it has also led to challenges, including the misuse of AI-generated content by individuals with harmful intentions. Beyond these widely recognized dangers, AI-generated contents pose a subtle yet profound challenge to the integrity of AI systems.

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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.

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Pickl AI

JANUARY 12, 2025

A generative AI company exemplifies this by offering solutions that enable businesses to streamline operations, personalise customer experiences, and optimise workflows through advanced algorithms. On the other hand, AI-based systems can automate a large part of the decision-making process, from data analysis to obtaining insights.

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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.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

These safeguards can be created for multiple use cases and implemented across multiple FMs, depending on your application and responsible AI requirements. Such words can include offensive terms or undesirable outputs, like product or competitor information.

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Marktechpost

MAY 8, 2024

Among the main advancements in AI, seven areas stand out for their potential to revolutionize different sectors: neuromorphic computing, quantum computing for AI, Explainable AI (XAI), AI-augmented design and Creativity, Autonomous Vehicles and Robotics, AI in Cybersecurity and AI for Environmental Sustainability.

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Unite.AI

SEPTEMBER 20, 2024

Its real-time trend analysis, investment evaluations, risk assessments, and automation features empower financial professionals to make informed choices efficiently. Key milestones in this evolution include the advent of algorithmic trading in the late 1980s and early 1990s, where simple algorithms automated trades based on set criteria.

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TransOrg Analytics

FEBRUARY 11, 2025

These are just a few ways Artificial Intelligence (AI) silently influences our daily lives. As AI continues integrating into every aspect of society, the need for Explainable AI (XAI) becomes increasingly important. What is Explainable AI? Why is Explainable AI Important?

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Towards AI

OCTOBER 3, 2024

Yet, despite these advancements, AI still faces significant limitations — particularly in adaptability, energy consumption, and the ability to learn from new situations without forgetting old information. As we stand on the cusp of the next generation of AI, addressing these challenges is paramount.

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Unite.AI

APRIL 22, 2024

This article explores how the integration of AI and telehealth is ushering in a new era of medical practices, transforming accessibility and efficiency of healthcare delivery. Telehealth refers to the delivery of healthcare services and information via telecommunications and digital communication technologies. What is Telehealth?

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IBM Journey to AI blog

JULY 6, 2023

Machine learning can then “learn” from the data to create insights that improve performance or inform predictions. 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.

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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.

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Pickl AI

FEBRUARY 17, 2025

Algorithmic bias can result in unfair outcomes, necessitating careful management. Transparency in AI systems fosters trust and enhances human-AI collaboration. This capability allows businesses to make informed decisions based on data-driven insights, enhancing strategic planning and risk management.

Machine Learning 52

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NVIDIA

MARCH 1, 2024

In addition to complying with privacy and consumer protection laws, trustworthy AI models are tested for safety, security and mitigation of unwanted bias. Principles of Trustworthy AI Trustworthy AI principles are foundational to NVIDIA’s end-to-end AI development. But data has to come from somewhere.

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ODSC - Open Data Science

JANUARY 29, 2025

Multimodal Learning Multimodal learning leverages diverse data sourcestext, images, audio, and videoto provide AI systems with a comprehensive understanding of the world. This approach enriches the models perspective by allowing it to correlate information across different modalities.

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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.

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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

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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

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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. CpG methylation beta values enter the input layer, and information propagates through the network, connecting nodes based on shared annotations in ReactomeDB.

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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.

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ODSC - Open Data Science

FEBRUARY 24, 2023

Algorithm-visualizer GitHub | Website Algorithm Visualizer is an interactive online platform that visualizes algorithms from code. The project was inspired by a group of coders looking to visualize what they’re working on, thus creating a tool that can show algorithms and descriptions of algorithms in real time.

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How to Learn Machine Learning

APRIL 4, 2025

People will have to reskill in new domains like data science, ethics of AI, or human-AI teamwork. It will improve decision making: AI is bound to transform decision making processes. The AI will process and learn a significant amount of information in record time and with great precision.

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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?

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IBM Journey to AI blog

AUGUST 11, 2023

The information can deepen our understanding of how our world works—and help create better and “smarter” products. Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. MLOps is the next evolution of data analysis and deep learning. What is MLOps?

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Flipboard

JUNE 20, 2023

Understanding AI’s mysterious “opaque box” is paramount to creating explainable AI. This can be simplified by considering that AI, like all other technology, has a supply chain. When you dissect AI’s supply chain, at the root, you will find algorithms. What factors does it weigh?

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Marktechpost

MAY 12, 2024

Greip provides an AI-powered fraud protection solution that utilizes ML modules to validate each transaction in an app and assess the possibility of fraudulent behavior. The tool also incorporates IP geolocation information, which enhances the user experience by tailoring website content to the visitor’s location and language.

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