IBM Journey to AI blog

AUGUST 9, 2024

Generative adversarial networks (GANs) consist of two neural networks: a generator that produces new content and a discriminator that evaluates the accuracy and quality of the generated content. Conversely, predictive AI estimates are more explainable because they’re grounded on numbers and statistics.

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Marktechpost

MARCH 23, 2024

To reduce the memory footprint and further speed up the training of FeatUp’s implicit network, the spatially varying features are compressed to their top k=128 principal components. Check out the Paper and MIT Blog. All credit for this research goes to the researchers of this project. Also, don’t forget to follow us on Twitter.

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PyImageSearch

OCTOBER 28, 2024

Home Table of Contents NeRFs Explained: Goodbye Photogrammetry? Block #A: We Begin with a 5D Input Block #B: The Neural Network and Its Output Block #C: Volumetric Rendering The NeRF Problem and Evolutions Summary and Next Steps Next Steps Citation Information NeRFs Explained: Goodbye Photogrammetry? How Do NeRFs Work?

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Marktechpost

DECEMBER 18, 2023

In a groundbreaking study, MIT researchers have delved into the realm of deep neural networks, aiming to unravel the mysteries of the human auditory system. The foundation of this research builds upon prior work where neural networks were trained to perform specific auditory tasks, such as recognizing words from audio signals.

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Towards AI

JANUARY 22, 2025

GradCAM is one of the simplest techniques to get explainability insights into model prediction. I was surprised to find that while there are many blogs on Medium about using GradCAM with ResNet, there arent any specifically for GradCAM with 3D images (eg. for ResNet3D); and almost none in Pytorch.

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IBM Journey to AI blog

AUGUST 13, 2024

Where it all started During the second half of the 20 th century, IBM researchers used popular games such as checkers and backgammon to train some of the earliest neural networks, developing technologies that would become the basis for 21 st -century AI. Elevate your AI with IBM watsonx. Train, deploy and scale models effortlessly.

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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? The second blog post will introduce you to NeRFs , the neural network solution.

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Heartbeat

JUNE 27, 2023

Photo by Resource Database on Unsplash Introduction Neural networks have been operating on graph data for over a decade now. Neural networks leverage the structure and properties of graph and work in a similar fashion. Graph Neural Networks are a class of artificial neural networks that can be represented as graphs.

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Pickl AI

SEPTEMBER 3, 2024

Summary: Artificial Neural Network (ANNs) are computational models inspired by the human brain, enabling machines to learn from data. This blog explores their core components, responsibilities, and applications across various industries. What is an Artificial Neural Network?

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Pickl AI

AUGUST 14, 2024

Summary: Neural networks are a key technique in Machine Learning, inspired by the human brain. Different types of neural networks, such as feedforward, convolutional, and recurrent networks, are designed for specific tasks like image recognition, Natural Language Processing, and sequence modelling.

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Heartbeat

JUNE 14, 2023

Introduction Deep neural network classifiers have been shown to be mis-calibrated [1], i.e., their prediction probabilities are not reliable confidence estimates. For example, if a neural network classifies an image as a “dog” with probability p , p cannot be interpreted as the confidence of the network’s predicted class for the image.

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Viso.ai

MAY 17, 2024

Neural Networks have changed the way we perform model training. Neural networks, sometimes referred to as Neural Nets, need large datasets for efficient training. So, what if we have a neural network that can adapt itself to new data and has less complexity? What is a Liquid Neural Network?

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Mlearning.ai

FEBRUARY 25, 2023

How does the Artificial Neural Network algorithm work? In the same way, artificial neural networks (ANNs) were developed inspired by neurons in the brain. ANN approach is a machine learning algorithm inspired by biological neural networks. Neural networks were trained faster with GPUs.

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Towards AI

OCTOBER 3, 2024

In this blog, we’ll explore emerging frontiers that promise to overcome these limitations, highlight what has been achieved so far, delve into the promising research, and discuss the ongoing challenges that researchers are tackling to bring these innovations to fruition. Liquid AI (started at MIT CSAIL) is working on Liquid Neural Networks.–

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Towards AI

DECEMBER 18, 2024

They chase the hype Neural Networks, Transformers, Deep Learning, and, who can forget AI and fall flat. You're not ready for neural networks if you cant explain Linear Regression or Decision Trees. … Read the full blog for free on Medium. More about me here. The secret?

Machine Learning 105

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IBM Journey to AI blog

JANUARY 10, 2024

AI can also work from deep learning algorithms, a subset of ML that uses multi-layered artificial neural networks (ANNs)—hence the “deep” descriptor—to model high-level abstractions within big data infrastructures.

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Pickl AI

SEPTEMBER 5, 2024

Summary: Convolutional Neural Networks (CNNs) are essential deep learning algorithms for analysing visual data. Introduction Neural networks have revolutionised Artificial Intelligence by mimicking the human brai n’s structure to process complex data. What are Convolutional Neural Networks?

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Flipboard

MARCH 27, 2023

Project Structure Accelerating Convolutional Neural Networks Parsing Command Line Arguments and Running a Model Evaluating Convolutional Neural Networks Accelerating Vision Transformers Evaluating Vision Transformers Accelerating BERT Evaluating BERT Miscellaneous Summary Citation Information What’s New in PyTorch 2.0?

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IBM Journey to AI blog

SEPTEMBER 24, 2024

“AI could lead to more accurate and timely predictions, especially for spotting diseases early,” he explains, “and it could help cut down on carbon footprints and environmental impact by improving how we use energy and resources.” We get tired, lose our focus, or just physically can’t see all that we need to.

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IBM Journey to AI blog

JUNE 14, 2023

With a foundation model, often using a kind of neural network called a “transformer” and leveraging a technique called self-supervised learning, you can create pre-trained models for a vast amount of unlabeled data. But that’s all changing thanks to pre-trained, open source foundation models.

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Marktechpost

NOVEMBER 30, 2023

Researchers from Lund University and Halmstad University conducted a review on explainable AI in poverty estimation through satellite imagery and deep machine learning. The review underscores the significance of explainability for wider dissemination and acceptance within the development community.

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Towards AI

DECEMBER 18, 2024

They chase the hype Neural Networks, Transformers, Deep Learning, and, who can forget AI and fall flat. You're not ready for neural networks if you cant explain Linear Regression or Decision Trees. … Read the full blog for free on Medium. More about me here. The secret?

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Heartbeat

AUGUST 21, 2023

In this guide, we’ll talk about Convolutional Neural Networks, how to train a CNN, what applications CNNs can be used for, and best practices for using CNNs. What Are Convolutional Neural Networks CNN? CNNs are artificial neural networks built to handle data having a grid-like architecture, such as photos or movies.

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Towards AI

DECEMBER 19, 2023

For example, a deep neural net used for a loan application scorecard might deny a customer, and we will not be able to explain why. This is where an explainable neural network based on generalized additive models with structured interactions (GAMI-Net) comes into the picture. So, without further ado, let’s dive in!

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IBM Journey to AI blog

JANUARY 15, 2024

This technology excels at applying foundation models, which are large neural networks trained on extensive unlabeled data and fine-tuned for various tasks. Learn more about AI can transform government services The post 5 key areas for governments to responsibly deploy generative AI appeared first on IBM Blog.

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Unite.AI

JULY 25, 2023

For instance, many blogs today feature AI-generated text powered by LLMs (Large Language Modules) like ChatGPT or GPT-4. Functional Approximation Error: This error stems when the models, such as neural networks, fail to capture the true underlying function that has to be learned from the data.

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AssemblyAI

JUNE 27, 2023

In this article, we take an overview of some exciting new advances in the space of Generative AI for audio that have all happened in the past few months , explaining where the key ideas come from and how they come together to bring audio generation to a new level. This blog post is part of a series on generative AI.

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Towards AI

FEBRUARY 16, 2024

Machine learning algorithms, especially neural networks, are effective at identifying complex patterns in chemical data, which can lead to new insights and speed up processes that were previously dependent on traditional, more time-consuming methods. Join thousands of data leaders on the AI newsletter.

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NVIDIA

DECEMBER 4, 2023

Three technical reasons, and many stories, explain why that’s so. A RedHat software engineering team put it succinctly in a blog : “GPUs have become the foundation of artificial intelligence.” An AI model, also called a neural network, is essentially a mathematical lasagna, made from layer upon layer of linear algebra equations.

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IBM Journey to AI blog

JULY 15, 2024

The problem is further compounded by the “suboptimal selection of the architecture and size of the neural network (e.g., ” Download the eBook: Generative AI + ML for the enterprise The post Taming the Wild West of AI-generated search results appeared first on IBM Blog.

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Heartbeat

DECEMBER 20, 2023

This blog aims to equip you with a thorough understanding of these powerful neural network architectures. In a typical neural network, you flatten your input one vector, take those input values in at once, multiply them by the weights in the first layer, add the bias, and pass the result into a neuron.

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Heartbeat

MARCH 1, 2023

Tracking your image classification experiments with Comet ML Photo from nmedia on Shutterstock.com Introduction Image classification is a task that involves training a neural network to recognize and classify items in images. A dataset of labeled images is used to train the network, with each image given a particular class or label.

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Towards AI

MARCH 29, 2024

It covers a wide range of topics, from optimizing Neural Networks for a particular hardware platform to new fabrication methods for building new hardware for AI applications. In the first one, Robert Dimond from ARM presented their chiplet… Read the full blog for free on Medium. The DATE 2024 conference programme.

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IBM Journey to AI blog

SEPTEMBER 20, 2023

Large language models (LLMs) are a class of foundational models (FM) that consist of layers of neural networks that have been trained on these massive amounts of unlabeled data. This enables enterprises to scale AI deployments at the edge, reducing the time and cost to deploy with faster response times. What are large language models?

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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. It highlights the significance of transparency and accountability in AI systems across various sectors.

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Towards AI

JULY 22, 2023

So, don’t worry, this is where Explainable AI, also known as XAI, comes in. In this blog, we’ll get headlong into XAI theory, expose its nuts and bolts, investigate numerous methodologies, and, of course, offer a variety of relevant and interesting examples that will make the magic of XAI crystal evident! SOURCE: [link] A.

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Towards AI

AUGUST 11, 2023

IMAGE SOURCE: BY AUTHOR INTRODUCTION: GANs, Generative Adversarial networks, let’s first understand what GANs are. So I have already written a blog on Generative AI where we discuss many types of AI, the hype of AI, and why AI is tending nowadays in every sector like Healthcare, Finance, Trading, marketing, and many more.

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