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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Dlabs.ai

AUGUST 16, 2022

One of the major hurdles to AI adoption is that people struggle to understand how AI models work. This is the challenge that explainable AI solves. Explainable artificial intelligence shows how a model arrives at a conclusion. What is explainable AI? Let’s begin.

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IBM Journey to AI blog

SEPTEMBER 20, 2023

Foundational models (FMs) are marking the beginning of a new era in machine learning (ML) and artificial intelligence (AI) , which is leading to faster development of AI that can be adapted to a wide range of downstream tasks and fine-tuned for an array of applications. What are large language models?

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Marktechpost

JULY 6, 2023

It is crucial to distinguish between IAI and XAI models because of their increasing popularity in the ML field in order to assist organizations in selecting the best strategy for their use case. In other words, it is safe to say that an IAI model provides its own explanation. Situations of this nature can be interpreted.

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Pickl AI

JANUARY 12, 2025

Data forms the backbone of AI systems, feeding into the core input for machine learning algorithms to generate their predictions and insights. For instance, in retail, AI models can be generated using customer data to offer real-time personalised experiences and drive higher customer engagement, consequently resulting in more sales.

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Towards AI

JULY 22, 2023

So, don’t worry, this is where Explainable AI, also known as XAI, comes in. HEALTHCARE WITH AI: SOURCE: [link] Let’s go through some instances to help you understand why Explainable AI is so important: Imagine a healthcare system in which, instead of speaking with a doctor, you interact with an AI system to assist you with diagnosis.

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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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Towards AI

NOVEMBER 15, 2024

With policymakers and civil society demanding reliable identification of AI content, SynthID represents an important development in addressing issues around AI-driven misinformation and authenticity. Community workshop on explainable AI (XAI) in education. The second network then scans for this pattern in […]

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Towards AI

JULY 24, 2024

Well, get ready because we’re about to embark on another exciting exploration of explainable AI, this time focusing on Generative AI. Before we dive into the world of explainability in GenAI, it’s worth noting that the tone of this article, like its predecessor, is intentionally casual and approachable.

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Towards AI

JULY 24, 2024

Well, get ready because we’re about to embark on another exciting exploration of explainable AI, this time focusing on Generative AI. Before we dive into the world of explainability in GenAI, it’s worth noting that the tone of this article, like its predecessor, is intentionally casual and approachable.

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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

JULY 6, 2023

Deep learning algorithms are neural networks modeled after the human brain. to learn more) In other words, you get the ability to operationalize data science models on any cloud while instilling trust in AI outcomes. Deep learning teaches computers to process data the way the human brain does.

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NVIDIA

DECEMBER 13, 2023

Financial Services Firms Embrace AI for Identity Verification The financial services industry is developing AI for identity verification. Harnessing Graph Neural Networks and NVIDIA GPUs GNNs have been embraced for their ability to reveal suspicious activity.

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Viso.ai

JULY 9, 2024

Understanding Generative AI Generative AI refers to the class of AI models capable of generating new content depending on an input. Text-to-image for example, refers to the ability of the model to generate images from a text prompt. Text-to-text models can produce text output based on a text prompt.

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ODSC - Open Data Science

DECEMBER 17, 2024

Types of Data Used in AILending One of AIs greatest strengths is its capacity to handle diverse datasets. Beyond traditional credit scores and income statements, AI models often incorporate behavioral data, transaction patterns, and online activity. For one, AI models inherit biases from the data they are trainedon.

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Defined.ai blog

AUGUST 10, 2023

Businesses can transform raw numbers into actionable insights by applying AI. For instance, an AI model can predict future sales based on past data, helping businesses plan better. Interpreting these requires a keen understanding of your business context and the specific problem the AI was set to solve.

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Viso.ai

MARCH 26, 2024

With advancements in machine learning (ML) and deep learning (DL), AI has begun to significantly influence financial operations. Arguably, one of the most pivotal breakthroughs is the application of Convolutional Neural Networks (CNNs) to financial processes. 1: Fraud Detection and Prevention No.2:

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Pickl AI

SEPTEMBER 17, 2024

This allows cybersecurity teams to focus on high-level strategy and decision-making, while AI handles the day-to-day monitoring and incident response. Moreover, AI enables cybersecurity solutions to adapt and learn from new threats, continuously improving their detection capabilities.

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Viso.ai

DECEMBER 6, 2023

Our solution enables leading companies to use a variety of machine learning models and tasks for their computer vision systems. Edge AI involves processing data near the source. Therefore, edge devices like servers or computers are connected to cameras and run AI models in real-time applications. Get a demo here.

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ODSC - Open Data Science

FEBRUARY 25, 2025

Generative AI TrackBuild the Future with GenAI Generative AI has captured the worlds attention with tools like ChatGPT, DALL-E, and Stable Diffusion revolutionizing how we create content and automate tasks. This track will cover the latest best practices for managing AI models from development to deployment.

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Viso.ai

MAY 10, 2024

Basic types of machine learning models Some common types of machine learning algorithms include: Regression models (e.g. Basic types of machine learning models Some common types of machine learning algorithms include: Regression models (e.g. text vs images) and (2) the desired output (e.g.

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Viso.ai

JANUARY 21, 2025

Generative AI Applications in 2025 Vision Transformers (ViTs) Now, heres something exciting to the computer vision trend in 2025: Vision Transformers. Vision Transformers (ViTs) are neural network architectures that process images using self-attention mechanisms. The world has already started setting boundaries for AI models.

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Heartbeat

SEPTEMBER 13, 2023

Source: ResearchGate Explainability refers to the ability to understand and evaluate the decisions and reasoning underlying the predictions from AI models (Castillo, 2021). For instance, human experts bring domain knowledge and expertise that can complement AI systems. However, there are slight differences between them.

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Bugra Akyildiz

MAY 25, 2024

Articles OpenAI has announced GPT-4o , their new flagship AI model that can reason across audio, vision, and text in real-time. The blog post acknowledges that while GPT-4o represents a significant step forward, all AI models including this one have limitations in terms of biases, hallucinations, and lack of true understanding.

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Pickl AI

APRIL 2, 2024

Deep Learning: Neural networks with multiple layers used for complex pattern recognition tasks. Explainable AI (XAI): As AI models become more complex, there’s a growing need for interpretability. XAI techniques will help us understand how models arrive at their decisions.

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The MLOps Blog

JUNE 27, 2023

Some model observability tools in the MLOps landscape in 2023 WhyLabs WhyLabs is an AI observability platform that helps data scientists and machine learning engineers monitor the health of their AI models and the data pipelines that fuel them. Evidently AI Evidently AI is an open-source ML model monitoring system.

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IBM Journey to AI blog

SEPTEMBER 3, 2024

And while organizations are taking advantage of technological advancements such as generative AI , only 24% of gen AI initiatives are secured. This lack of security threatens to expose data and AI models to breaches, the global average cost of which is a whopping USD 4.88 Choose energy-efficient AI models or frameworks.

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The MLOps Blog

AUGUST 11, 2023

OpenAI, on the other hand, has been at the forefront of advancements in generative AI models, such as GPT-3, which heavily rely on embeddings. Model Training : Embeddings enable neural networks to consume training data in formats that extract features from the data. This is where embeddings come into play.

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IBM Journey to AI blog

FEBRUARY 9, 2024

iii] “AI models haven’t had that kind of data before. Those models will just have a better understanding of everything.” The power of open models will continue to grow. They make AI more explainable: the larger the model, the more difficult it is to pinpoint how and where it makes important decisions.

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