IBM Journey to AI blog

MAY 6, 2024

Key facets to spotlight in a protocol’s design include the investigational product’s nature, study design, endpoint definition, eligibility criteria, administrative burden, the presence of redundant processes, and the time that a patient would need to invest to participate. Grasping these dimensions sharpens the recruitment lens.

Convolutional Neural Networks 252

Convolutional Neural Networks Neural Network Computer Vision AI 252

Unite.AI

DECEMBER 1, 2023

Machine learning , a subset of AI, involves three components: algorithms, training data, and the resulting model. An algorithm, essentially a set of procedures, learns to identify patterns from a large set of examples (training data). The culmination of this training is a machine-learning model.

LLM 261

LLM Machine Learning Explainability Algorithm 261

AWS Machine Learning Blog

FEBRUARY 25, 2025

Instead of relying on predefined, rigid definitions, our approach follows the principle of understanding a set. Its important to note that the learned definitions might differ from common expectations. Instead of relying solely on compressed definitions, we provide the model with a quasi-definition by extension.

Chatbots 71

Chatbots Categorization LLM Algorithm 71

Towards AI

JANUARY 24, 2024

Using this simple concept, we can reformulate the definition ofNP-C problem as follows: a problem is NP-C if there is not enough information to significantly reduce the set of solutions. I love this definition because, in just a few lines, it makes us fully understand the problem.

Neural Network 118

Neural Network Artificial Intelligence Artificial Intelligence Algorithm 118

Flipboard

JUNE 20, 2023

All of the definitions were written by a human. Rather than humans programming computers with specific step-by-step instructions on how to complete a task, in machine learning a human provides the AI with data and asks it to achieve a certain outcome via an algorithm. Neural networks Neural networks are found in the human brain.

Neural Network 158

Neural Network Deep Learning Machine Learning Artificial Intelligence 158

ML Review

MARCH 31, 2019

Up to this point, machine learning algorithms simply didn’t work well enough for anyone to be surprised when it failed to do the right thing. We start with an image of a panda, which our neural network correctly recognizes as a “panda” with 57.7% This is, clearly, an optical illusion — but for the neural network.

Neural Network 52

Neural Network Machine Learning Deep Learning Explainability 52

Viso.ai

OCTOBER 10, 2024

Pattern recognition is the ability of machines to identify patterns in data, and then use those patterns to make decisions or predictions using computer algorithms. At the heart of a pattern recognition system are computer algorithms that are designed to analyze and interpret data.

Neural Network 98

Neural Network Computer Vision Deep Learning Machine Learning 98

Marktechpost

MARCH 20, 2025

Instead of simply matching exact words, semantic search systems capture the intent and contextual definition of the query and return relevant results even when they don’t contain the same keywords. Semantic search goes beyond traditional keyword matching by understanding the contextual meaning of search queries.

Natural Language Processing 57

Natural Language Processing Convolutional Neural Networks Neural Network Computer Vision 57

Towards AI

SEPTEMBER 10, 2023

This one is definitely one of the most practical and inspiring. So you definitely can trust his expertise in Machine Learning and Deep Learning. So you definitely can trust his expertise in Machine Learning and Deep Learning. Neural Network is a combination of linear functions and activations.

Deep Learning 124

Deep Learning Neural Network ML Computer Vision 124

Marktechpost

OCTOBER 3, 2023

There is a sizable body of academic literature devoted to scalable content-based algorithms for automatic music tagging in order to offer context. A neural network that has been trained to divide sounds into instrumental and non-instrumental categories is used for this investigation. Check out the Paper.

Artificial Intelligence 128

Artificial Intelligence Artificial Intelligence Neural Network Categorization 128

Marktechpost

MAY 8, 2024

DRL models, such as Deep Q-Networks (DQN), estimate optimal action policies by training neural networks to approximate the maximum expected future rewards. Extensions to the base DQN algorithm, like Double Q Learning and Prioritized replay, enhance its performance, offering promising avenues for autonomous driving applications.

Deep Learning 120

Deep Learning Neural Network Data Scarcity Natural Language Processing 120

Marktechpost

JULY 23, 2023

One key area of development is deep learning, where neural networks are trained on huge datasets of images to recognize and classify objects, scenes, and events. This unique library uses algorithms based on the laws and equations of physics to analyze pictorial data.

Computer Vision 98

Computer Vision Python Neural Network Algorithm 98

Robot Writers AI

JANUARY 12, 2025

Observes Aschenbrenner: Rather than a few hundred researchers and engineers at a leading AI lab, wed have more than one hundred thousand times that(AI agents) furiously working on algorithmic breakthroughs, day and night. Gratefully, Aschenbrenners tome is rendered in a conversational, engaging and enthusiastic writing style.)

Auto-complete 105

Auto-complete AI Engineer OpenAI ChatGPT 105

ML @ CMU

SEPTEMBER 13, 2024

The answer inherently relates to the definition of memorization for LLMs and the extent to which they memorize their training data. However, even defining memorization for LLMs is challenging, and many existing definitions leave much to be desired. We argue that such a definition provides an intuitive notion of memorization.

LLM 129

LLM Neural Network Large Language Models OpenAI 129

Towards AI

MARCH 17, 2024

First bringing together conflicting literature on what XAI is and some important definitions and distinctions. The current state of explainability … explained Any research on explainability will show that there is little by way of a concrete definition. Ultimately these definitions end up being almost circular!

Explainable AI 105

Explainable AI Explainability Neural Network AI 105

Viso.ai

DECEMBER 19, 2023

Today, the use of convolutional neural networks (CNN) is the state-of-the-art method for image classification. This means machine learning algorithms are used to analyze and cluster unlabeled datasets by discovering hidden patterns or data groups without the need for human intervention. How Does Image Classification Work?

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 98

PyImageSearch

NOVEMBER 13, 2023

For example, image classification, image search engines (also known as content-based image retrieval, or CBIR), simultaneous localization and mapping (SLAM), and image segmentation, to name a few, have all been changed since the latest resurgence in neural networks and deep learning. Object detection is no different.

Convolutional Neural Networks 119

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 119

Towards AI

SEPTEMBER 12, 2024

All resources listed in the guide are free, except some online courses and books, which are certainly recommended for a better understanding, but it is definitely possible to become an expert without them, with a little more time spent on online readings, videos, and practice. Read the complete LLM guide here! Our must-read articles 1.

Neural Network 111

Neural Network LLM NLP Algorithm 111

Viso.ai

DECEMBER 10, 2023

An introduction The basic concepts and how it works Traditional and modern deep learning image recognition The best popular image recognition algorithms How to use Python for image recognition Examples and deep learning applications Popular image recognition software About: We provide the leading end-to-end computer vision platform Viso Suite.

Convolutional Neural Networks 98

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 98

Towards AI

FEBRUARY 20, 2024

Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction Everyone is using mobile or web applications which are based on one or other machine learning algorithms. You might be using machine learning algorithms from everything you see on OTT or everything you shop online.

Machine Learning 109

Machine Learning ML Neural Network Algorithm 109

Towards AI

JULY 20, 2023

Machine Learning Engineering A Practical Methodology to Set the Most Important Hyperparameter in Deep Learning Photo by David Everett Strickler on Unsplash Problem Statement Training a Deep Neural Network can be a challenging task. Training a Neural Network means finding the set of weights that optimize some function.

Neural Network 98

Neural Network Deep Learning Machine Learning Algorithm 98

Towards AI

AUGUST 25, 2023

In ML, there are a variety of algorithms that can help solve problems. Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system. However, this does not mean you need to code the algorithms from scratch (roll your own). 12, 2014. [3]

Machine Learning 98

Machine Learning Software Engineer Neural Network Data Science 98

Marktechpost

SEPTEMBER 26, 2023

The way humans engage with technology has changed as a result of these complex algorithms, which are powered by enormous amounts of data and computer power. In conclusion, FFF’s design is definitely a groundbreaking method for enhancing neural networks’ computational effectiveness.

Neural Network 120

Neural Network Large Language Models Deep Learning Artificial Intelligence 120

Towards AI

AUGUST 1, 2023

Recently, engineers have been allured by certain natural processes, giving birth to such domains as artificial neural networks and evolutionary computation. The distinction between the axes cannot be easily drawn where nature is concerned, indeed, the definitions themselves may be subject to discussion. Sipper et al.,

Neural Network 98

Neural Network Algorithm AI AI 98

Towards AI

JULY 22, 2023

Now Algorithms know what they are doing and why! DEFINITION AND IMPORTANCE OF EXPLAINABLE AI (XAI): LOANS WITH AI: SOURCE: [link] Consider the following scenario: you wish to apply for a loan (be it a home loan, a vehicle loan, an educational loan, or anything else), and you are interacting with an AI system for the application process.

Explainable AI 98

Explainable AI Explainability Neural Network Artificial Intelligence 98

Unite.AI

APRIL 11, 2024

The founding team at Lemurian Labs combines expertise in AI, compilers, numerical algorithms, and computer architecture, united by a single purpose: to reimagine accelerated computing. We definitely employ a lot of first principles thinking at Lemurian. Can you walk us through your background and w hat got you into AI to begin with?

Robotics 157

Robotics Neural Network Algorithm AI 157

Viso.ai

DECEMBER 4, 2023

Artificial Neural Networks (ANNs) have been demonstrated to be state-of-the-art in many cases of supervised learning, but programming an ANN manually can be a challenging task. These frameworks provide neural network units, cost functions, and optimizers to assemble and train neural network models.

Neural Network 98

Neural Network Deep Learning Python Machine Learning 98

Pickl AI

JULY 22, 2024

Summary: Local Search Algorithms are AI techniques for finding optimal solutions by exploring neighbouring options. Local Search Algorithms in Artificial Intelligence offer an efficient approach to tackle such problems by focusing on incremental improvements to a current solution rather than exploring the entire solution space.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Algorithm Machine Learning 52

Marktechpost

SEPTEMBER 13, 2024

Third, they enhance the FLASHATTENTION2 algorithm with a sigmoid kernel, resulting in substantial reductions in kernel inference wall-clock time and real-world inference time. This implies that SigmoidAttn exhibits better regularity, potentially leading to improved robustness and optimization ease in neural networks.

Auto-classification 103

Auto-classification Neural Network Machine Learning Computer Vision 103

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. What are large language models?

Large Language Models 238

Large Language Models DevOps Data Science AI Modeling 238

AWS Machine Learning Blog

JUNE 22, 2023

The final ML model combines CNN and Transformer, which are the state-of-the-art neural network architectures for modeling sequential machine log data. ML methodology and model training In this section, we discuss our baseline model with AutoGluon and how we built a customized neural network with SageMaker automatic model tuning.

Neural Network 102

Neural Network Metadata ML Machine Learning 102

Topbots

OCTOBER 4, 2023

Generated with Bing and edited with Photoshop Predictive AI has been driving companies’ ROI for decades through advanced recommendation algorithms, risk assessment models, and fraud detection tools. The predictive AI algorithms can be used to predict a wide range of variables, including continuous variables (e.g.,

Generative AI 119

Generative AI Natural Language Processing Machine Learning Convolutional Neural Networks 119

Google Research AI blog

MAY 19, 2023

Gradient noise injection methods, like DP-SGD or DP-FTRL , and their extensions are currently the most practical methods for achieving DP guarantees in complex models like large deep neural networks. Further, some algorithms (e.g., ghost clipping , which is based on this paper ) avoid per-example gradient clipping altogether.

ML 102

ML Neural Network Algorithm Machine Learning 102

Viso.ai

DECEMBER 3, 2023

This article will explore the latest advances in pose analytics algorithms and AI vision techniques, their applications and use cases, and their limitations. Definition: What is pose estimation? Today, the most powerful image processing models are based on convolutional neural networks (CNNs).

Deep Learning 98

Deep Learning Computer Vision Neural Network Robotics 98

Heartbeat

MARCH 14, 2023

By incorporating computer vision methods and algorithms into robots, they are able to view and understand their environment. Object recognition and tracking algorithms include the CamShift algorithm , Kalman filter , and Particle filter , among others.

Computer Vision 97

Computer Vision Robotics Deep Learning Algorithm 97

Chatbots Life

APRIL 16, 2024

In this article, we will delve into the concepts of generative and discriminative models, exploring their definitions, working principles, and applications. Examples of Generative Models Generative models encompass various algorithms that capture patterns in data to generate realistic new examples.

Neural Network 59

Neural Network Convolutional Neural Networks Natural Language Processing Machine Learning 59

Unite.AI

JUNE 13, 2023

A lot of the assumptions that you make that these algorithms are based on, when they go to the real world, they don't hold, and then you have to figure out how to deal with that. I think that a lot of the difference is that, one, engineering, safety and so on, and maybe the other one of course is that your assumptions don't hold.

Machine Learning 246

Machine Learning AI AI Algorithm 246