Unite.AI

NOVEMBER 22, 2024

It helps explain how AI models, especially LLMs, process information and make decisions. By using a specific type of neural network called sparse autoencoders (SAEs) , Gemma Scope breaks down these complex processes into simpler, more understandable parts. How Does Gemma Scope Work?

Large Language Models 113

Large Language Models Neural Network AI AI 113

Unite.AI

AUGUST 28, 2024

in Information Systems Engineering from Ben Gurion University and an MBA from the Technion, Israel Institute of Technology. Along the way, I’ve learned different best practices – from how to manage a team to how to inform the proper strategy – that have shaped how I lead at Deep Instinct. He holds a B.Sc

Deep Learning 278

Deep Learning Explainability Neural Network Metadata 278

Unite.AI

JUNE 25, 2023

However, assimilating the understanding of physics into the realm of neural networks has proved challenging. Integrating physics into network architectures: This strategy involves running data through a network filter that codes physical properties into what cameras capture.

Computer Vision 361

Computer Vision Robotics Neural Network Hybrid AI 361

Towards AI

DECEMBER 12, 2024

We are diving into Mechanistic interpretability, an emerging area of research in AI focused on understanding the inner workings of neural networks. All your data will be transformed into embeddings, which well then use to retrieve information. So, its quite important to understand embedding models.

Neural Network 105

Neural Network LLM Explainability NLP 105

Towards AI

DECEMBER 12, 2024

We are diving into Mechanistic interpretability, an emerging area of research in AI focused on understanding the inner workings of neural networks. All your data will be transformed into embeddings, which well then use to retrieve information. So, its quite important to understand embedding models.

Neural Network 104

Neural Network LLM Explainability NLP 104

Unite.AI

FEBRUARY 10, 2025

Can you explain how NeuroSplit dynamically optimizes compute resources while maintaining user privacy and performance? NeuroSplit is fundamentally device-agnostic, cloud-agnostic, and neural network-agnostic. But AI shouldn't be limited by which end-user device someone happens to use. Think about what this means for developers.

Neural Network 232

Neural Network Hybrid AI AI Modeling Large Language Models 232

Towards AI

DECEMBER 12, 2024

We are diving into Mechanistic interpretability, an emerging area of research in AI focused on understanding the inner workings of neural networks. All your data will be transformed into embeddings, which well then use to retrieve information. So, its quite important to understand embedding models.

Neural Network 103

Neural Network LLM Explainability NLP 103

Towards AI

FEBRUARY 3, 2024

(Left) Photo by Pawel Czerwinski on Unsplash U+007C (Right) Unsplash Image adjusted by the showcased algorithm Introduction It’s been a while since I created this package ‘easy-explain’ and published on Pypi. A few weeks ago, I needed an explainability algorithm for a YoloV8 model. The truth is, I couldn’t find anything.

Explainability 126

Explainability Explainable AI Neural Network Algorithm 126

Unite.AI

NOVEMBER 25, 2023

By integrating these constraints, the AI not only mirrors aspects of human intelligence but also unravels the intricate balance between resource expenditure and information processing efficiency. More intriguing, however, was the shift in how individual nodes processed information.

Neural Network 342

Neural Network Artificial Intelligence Artificial Intelligence AI 342

NVIDIA

JANUARY 6, 2025

NVIDIA GPUs and platforms are at the heart of this transformation, Huang explained, enabling breakthroughs across industries, including gaming, robotics and autonomous vehicles (AVs). The latest generation of DLSS can generate three additional frames for every frame we calculate, Huang explained.

Robotics 144

Robotics Explainability AI AI 144

NVIDIA

MARCH 5, 2025

Ninety percent of information transmitted to the human brain is visual. Time Stamps 2:03 Nelson explains Roboflows aim to make the world programmable through computer vision. The importance of sight in understanding the world makes computer vision essential for AI systems. 22:15 How multimodalilty allows AI to be more intelligent.

Computer Vision 115

Computer Vision Neural Network Explainability Large Language Models 115

Unite.AI

SEPTEMBER 15, 2024

Their findings, recently published in Nature , represent a significant leap forward in the field of neuromorphic computing – a branch of computer science that aims to mimic the structure and function of biological neural networks. In conventional computers, information is processed and stored using binary states – on or off, 1 or 0.

Neural Network 263

Neural Network Natural Language Processing Artificial Intelligence Artificial Intelligence 263

Unite.AI

MARCH 11, 2024

While multimodal AI focuses on processing and integrating data from various modalities—text, images, audio—to make informed predictions or responses like Gemini model, CAS integrates multiple interacting components like language models and search engines to boost performance and adaptability in AI tasks.

AI Modeling 303

AI Modeling Neural Network Large Language Models AI 303

Unite.AI

NOVEMBER 8, 2024

It’s not enough to simply identify unhappy customers — we help explain why and offer recommendations for immediate improvement, keeping customers satisfied in the moment. Can you explain how the AI algorithm processes these physiological signals and translates them into actionable insights for retailers?

Emotion AI 147

Emotion AI Algorithm Explainability Neural Network 147

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?

Explainability 99

Explainability Neural Network Computer Vision Deep Learning 99

Marktechpost

JUNE 9, 2024

Explainable AI (xAI) methods, such as saliency maps and attention mechanisms, attempt to clarify these models by highlighting key ECG features. xECGArch uniquely separates short-term (morphological) and long-term (rhythmic) ECG features using two independent Convolutional Neural Networks CNNs.

Convolutional Neural Networks 122

Convolutional Neural Networks Neural Network Deep Learning Big Data 122

Marktechpost

JANUARY 19, 2024

Neural network-based methods in estimating biological age have shown high accuracy but lack interpretability, prompting the development of a biologically informed tool for interpretable predictions in prostate cancer and treatment resistance. The most noteworthy result was probably obtained for the pan-tissue dataset.

Neural Network 111

Neural Network Deep Learning Explainable AI Machine Learning 111

Marktechpost

SEPTEMBER 26, 2023

Microsoft researchers propose a groundbreaking solution to these challenges in their recent “Neural Graphical Models” paper presented at the 17th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2023). The dataset also included information on infant mortality.

Neural Network 135

Neural Network Categorization Data Scientist Data Analysis 135

IBM Journey to AI blog

AUGUST 9, 2024

In short, predictive AI helps enterprises make informed decisions regarding the next step to take for their business. 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.

Generative AI 301

Generative AI Explainability AI AI 301

Marktechpost

MARCH 23, 2024

Although deep features have many applications in computer vision, they often need more spatial resolution to directly perform dense prediction tasks like segmentation and depth prediction due to models that aggressively pool information by models over large areas. It provides sub-feature information to train the upsampler.

Computer Vision 130

Computer Vision Neural Network Machine Learning Algorithm 130

AI News

MAY 14, 2024

Pioneering capabilities The introduction of GPT-4o marks a leap from its predecessors by processing all inputs and outputs through a single neural network. This approach enables the model to retain critical information and context that were previously lost in the separate model pipeline used in earlier versions.

OpenAI 343

OpenAI Big Data Neural Network ChatGPT 343

Unite.AI

JUNE 26, 2023

Theoretical frameworks such as Integrated Information Theory (IIT), Global Workspace Theory (GWT), and Artificial General Intelligence (AGI) provide a frame of reference for how AI consciousness can be achieved. However, researchers are trying to take a step towards a human-like mind by adding a memory aspect to neural networks.

AI 348

AI AI Neural Network Natural Language Processing 348

Towards AI

JANUARY 4, 2024

Source from the author At least, that is my case, so I put together this post to explain the different concepts in graph neural networks (GNNs) in a way that is more intuitive and beginner-friendly, complemented with a code example.

Neural Network 111

Neural Network Explainability AI AI 111

Unite.AI

NOVEMBER 14, 2024

Can you explain the process behind training DeepL's LLM? And as a research-led company, everything we do is informed by our mission to break down language barriers, and the feedback we’re hearing from customers and businesses. Any organization considering AI tools should always ask these questions when evaluating models and companies.

Neural Network 130

Neural Network LLM Large Language Models AI Modeling 130

Unite.AI

NOVEMBER 6, 2023

Neural Network: Moving from Machine Learning to Deep Learning & Beyond Neural network (NN) models are far more complicated than traditional Machine Learning models. Advances in neural network techniques have formed the basis for transitioning from machine learning to deep learning.

Machine Learning 204

Machine Learning Neural Network Deep Learning Convolutional Neural Networks 204

NYU Center for Data Science

DECEMBER 3, 2024

The research revealed that regardless of whether a neural network is trained to recognize images from popular computer vision datasets like ImageNet or CIFAR, it develops similar internal patterns for processing visual information. The analogy to astrophysics is particularly apt.

Neural Network 73

Neural Network Computer Scientist Computer Vision Explainability 73

Unite.AI

APRIL 9, 2024

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. Explainability is essential for accountability, fairness, and user confidence. Explainability also aligns with business ethics and regulatory compliance.

Composite AI 182

Composite AI Explainability Black Box AI Explainable AI 182

AWS Machine Learning Blog

NOVEMBER 26, 2024

In this post, we discuss how to use LLMs from Amazon Bedrock to not only extract text, but also understand information available in images. Solution overview In this post, we demonstrate how to use models on Amazon Bedrock to retrieve information from images, tables, and scanned documents. 90B Vision model.

LLM 100

LLM Convolutional Neural Networks Metadata Explainability 100

Towards AI

MARCH 17, 2024

Alongside this, there is a second boom in XAI or Explainable AI. Explainable AI is focused on helping us poor, computationally inefficient humans understand how AI “thinks.” We will then explore some techniques for building glass-box or explainable models. Ultimately these definitions end up being almost circular!

Explainable AI 105

Explainable AI Explainability Neural Network AI 105

Unite.AI

APRIL 30, 2024

It includes deciphering neural network layers , feature extraction methods, and decision-making pathways. These systems rely heavily on neural networks to process vast amounts of information. During training, neural networks learn patterns from extensive datasets.

Chatbots 204

Chatbots Neural Network BERT OpenAI 204

Unite.AI

JUNE 4, 2024

With their advanced capabilities in processing and generating human-like text, LLMs perform intricate tasks such as real-time information retrieval and question answering. However, they operate as “ black boxes ,” providing limited transparency and explainability regarding how they produce certain outputs.

Large Language Models 221

Large Language Models Neural Network LLM Explainability 221

Unite.AI

AUGUST 1, 2023

Prompt 1 : “Tell me about Convolutional Neural Networks.” ” Response 1 : “Convolutional Neural Networks (CNNs) are multi-layer perceptron networks that consist of fully connected layers and pooling layers. They are commonly used in image recognition tasks. .”

Prompt Engineering 246

Prompt Engineering Prompt Engineer ChatGPT Convolutional Neural Networks 246

Marktechpost

AUGUST 7, 2024

The Role of Explainable AI in In Vitro Diagnostics Under European Regulations: AI is increasingly critical in healthcare, especially in vitro diagnostics (IVD). These AI systems must perform accurately and provide explainable results to comply with regulatory requirements.

Explainable AI 107

Explainable AI Explainability Neural Network Algorithm 107

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. consisted of 10 racks holding 90 servers, with a total of 2,880 processor cores.

Machine Learning 291

Machine Learning Neural Network Robotics Natural Language Processing 291

Unite.AI

NOVEMBER 8, 2023

It results in sparse and high-dimensional vectors that do not capture any semantic or syntactic information about the words. Recurrent Neural Networks (RNNs) became the cornerstone for these applications due to their ability to handle sequential data by maintaining a form of memory. However, RNNs were not without limitations.

BERT 298

BERT NLP Neural Network Natural Language Processing 298

Towards AI

SEPTEMBER 7, 2023

How is attention computed using Recurrent Neural Networks (RNNs)? Machine Translation We will look at Neural machine translation (NMT) as a running example in this article. NMT aims to build and train a single, large neural network that reads a sentence and outputs a correct translation.

Explainability 126

Explainability Neural Network Natural Language Processing NLP 126

Unite.AI

SEPTEMBER 4, 2024

Deep Neural Network (DNN) Models: Our core infrastructure utilizes multi-stage DNN models to predict the value of each impression or user. These signals provide valuable targeting information without requiring personal data. Each request has a wealth of contextual signals, providing us with a rich, privacy-compliant dataset.

Neural Network 261

Neural Network Machine Learning ML Continuous Learning 261