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.

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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.

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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?!

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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.

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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.

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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.

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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 ⟩.

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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.

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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.

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AI News

MAY 15, 2024

Pro, it retains the ability for multimodal reasoning across vast amounts of information and features the breakthrough long context window of one million tokens. The company has developed prototype agents that can process information faster, understand context better, and respond quickly in conversation. While lighter-weight than the 1.5

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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?

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Mlearning.ai

MARCH 22, 2023

It is used to reduce the dimensionality of a dataset while retaining as much of the original information as possible. Unfortunately, this concept is complex and can’t be explained as well using the written word alone. I find the channel StatQuest is able to explain this concept quite well in the following video.

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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). Explainability techniques aim to reveal the inner workings of AI systems by offering insights into their predictions. What is Explainability?

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Towards AI

MAY 13, 2024

These AI supercomputers process information millions of times faster than standard desktop or server computers. Since the emergence of ChatGPT in 2022, AI has dominated discussions. However, behind the scenes, it’s the AI infrastructure that serves as the engine driving the market’s large GenAI models.

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Mlearning.ai

FEBRUARY 24, 2023

In this blog post, we will explain what PCA is and how it works and present five examples of PCA analysis. Principal Component Analysis (PCA) is extracting the most important information from a data set by reducing the number of variables. The eigenvalues represent the amount of variance explained by the corresponding eigenvector.

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Towards AI

JANUARY 27, 2023

Deep Learning Explained: Perceptron The key concept behind every neural network. Bias Earlier I intentionally skipped the explanation of the bias so as not to overload you with information. As explained above, the bias is a scalar value that is added to the net input z before passing through the activation function.

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Unite.AI

MARCH 14, 2024

For many institutional investors, the answer is likely to be no – that the potential benefits of AI just aren’t worth the risk associated with a process they aren’t able to understand, much less explain to their boards and clients. But there is a way out of this dilemma.

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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. Explainable AI not only resolves this for us.

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Marktechpost

JULY 14, 2023

However, existing metrics for free-text explanation evaluation are still mostly accuracy-based and narrowly focused on how well a justification can assist a (proxy) model in predicting the label it explains. For instance, even though they provide differing amounts of fresh and pertinent information, the two rationales r * 1 and r * 1 in Fig.

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Mlearning.ai

JULY 19, 2023

However, downsampling can lead to a significant loss of data, including valuable information necessary for accurate predictions, making it less preferable for handling imbalance. Submission Suggestions Handling Imbalanced Dataset-Explained! WRITER at MLearning.ai // Code Interpreter // AI’s Safe Deception Mlearning.ai

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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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DataRobot Blog

FEBRUARY 14, 2022

But just as important, you want it to be explainable. Explainability requirements continue after the model has been deployed and is making predictions. DataRobot offers end-to-end explainability to make sure models are transparent at all stages of their lifecycle. MLDev Explainability. Global Explainability .

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Marktechpost

JULY 2, 2023

Thus, there is a growing demand for explainability methods to interpret decisions made by modern machine learning models, particularly neural networks. SaneBox Vidon Audioread The post This AI Tool Explains How AI ‘Sees’ Images And Why It Might Mistake An Astronaut For A Shovel appeared first on MarkTechPost.

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Unite.AI

MAY 8, 2024

Mutual Information Maximization : Maximizing the mutual information between local node representations and a target representation like the global graph embedding. Beyond better text encoders, LLMs can be used to generate augmented information from the original text attributes in a semi-supervised manner.

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Towards AI

AUGUST 9, 2023

Similarly, MM-ReAct [2] incorporates visual information in the forms of image captioning, dense captioning, image tagging, etc., inside the prompt to feed to the LLM. Using this context, they generate 3 types of instruction datasets.

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AI News

APRIL 25, 2024

He outlined a litany of potential pitfalls that must be carefully navigated—from AI hallucinations and emissions of falsehoods, to data privacy violations and intellectual property leaks from training on proprietary information. Pryon also emphasises explainable AI and verifiable attribution of knowledge sources.

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Flipboard

DECEMBER 7, 2023

ChatGPT can explain key concepts and information that can help people make the most of their time locating, accessing and interpreting archives. But ChatGPT can also give false information.

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AI News

MAY 8, 2024

“People can still create deceptive content without this information (or can remove it), but they cannot easily fake or alter this information, making it an important resource to build trust,” OpenAI explained.

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Viso.ai

MARCH 19, 2024

The model employs iterative refinement, with each layer refining the mask based on visual features and prompt information. The post Grounded-SAM Explained: A New Image Segmentation Paradigm? Combined with inputs (points, bounding boxes, or textual descriptions) from a prompt encoder, it generates the various segmentation masks.

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Mlearning.ai

JULY 23, 2023

Similarly, review websites and e-commerce platforms use it to automatically analyze and summarize customer feedback, allowing potential customers to make informed decisions. I’m going to explain the detail of Text Classification using Naive Bayes algorithm (Naive Bayes Classifier). How it works?

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Unite.AI

MAY 17, 2024

Michelle Bak, a doctoral student in information sciences, and Professor Jessie Chin recently published their findings in the Journal of the American Medical Informatics Association. They're lacking information on how to control the environment to eliminate a stimulus that reinforces problem behavior.”

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IBM Journey to AI blog

SEPTEMBER 20, 2023

When implemented in a responsible way—where the technology is fully governed, privacy is protected and decision making is transparent and explainable—AI has the power to usher in a new era of government services. AI’s value is not limited to advances in industry and consumer products alone.

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Marktechpost

JULY 7, 2023

This malicious act aims to compromise the integrity and reliability of the LLM by injecting misleading or harmful information during the training process. A New Research Explains The Risk Factors Associated With Open-Source LLMs appeared first on MarkTechPost.

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Analytics Vidhya

AUGUST 26, 2021

This article was published as a part of the Data Science Blogathon “You can have data without information but you cannot have information without data” – Daniel Keys Moran Introduction If you are here then you might be already interested in Machine Learning or Deep Learning so I need not explain what it is?

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Unite.AI

AUGUST 25, 2023

Can focusing on Explainable AI (XAI) ever address this? To engineers, explainable AI is currently thought of as a group of technological constraints and practices, aimed at making the models more transparent to people working on them. For someone who is being falsely accused, explainability has a whole different meaning and urgency.

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AI News

NOVEMBER 21, 2023

So that’s a key area of focus,” explains O’Sullivan. Safeguarding data privacy is also paramount, with stringent measures needed to prevent the misuse of sensitive customer information. Concerns about hallucinations – where AI systems generate inaccurate or misleading information – must be addressed meticulously.

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Unite.AI

DECEMBER 13, 2023

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. Regulatory Compliance and Explainability Regulatory bodies are focusing on transparency and accountability.

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