Unite.AI

AUGUST 7, 2023

Amir Hever is the CEO and co-founder of UVeye , a deep learning computer vision startup that is setting the global standard for vehicle inspection with fast and accurate anomaly detection to identify issues or threats facing the automotive and security industries. UVeye is Hever’s third venture. Who doesn’t trust their doctor?

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Towards AI

NOVEMBER 16, 2024

Keswani’s Algorithm introduces a novel approach to solving two-player non-convex min-max optimization problems, particularly in differentiable sequential games where the sequence of player actions is crucial. Keswani’s Algorithm: The algorithm essentially makes response function : maxy∈{R^m} f (.,

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Algorithm ML Deep Learning Machine Learning 105

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? Real-time human pose tracking with deep learning – Using Viso Suite What is 3D Human Pose Estimation?

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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.

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Marktechpost

DECEMBER 10, 2023

Advancements in Artificial Intelligence (AI) and Deep Learning have brought a great transformation in the way humans interact with computers. The post Meet DeepCache: A Simple and Effective Acceleration Algorithm for Dynamically Compressing Diffusion Models during Runtime appeared first on MarkTechPost.

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Heartbeat

FEBRUARY 6, 2023

How do Object Detection Algorithms Work? There are two main categories of object detection algorithms. Two-Stage Algorithms: Two-stage object detection algorithms consist of two different stages. Single-stage object detection algorithms do the whole process through a single neural network model.

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Algorithm Convolutional Neural Networks Neural Network Computer Vision 90

AssemblyAI

NOVEMBER 9, 2023

The models are powered by advanced Deep Learning and Machine Learning research. In Natural Language Processing, or NLP, Text Summarization refers to the process of using Deep Learning and Machine Learning models to synthesize large bodies of texts into their most important parts.

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BAIR

JUNE 29, 2023

RDKit, a commonly used Cheminformatics library, uses a cheap distance geometry-based algorithm, followed by an inexpensive physics-based optimization, to achieve reasonable conformer approximations. For an in-depth definition and discussion on the methods of maintaining equivariance, please see the full paper.

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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.

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Flipboard

JUNE 20, 2023

All of the definitions were written by a human. Machine learning Machine learning is when computers use experience to improve their performance. Deep learning Deep learning is a specific type of machine learning used in the most powerful AI systems.

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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.

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Marktechpost

NOVEMBER 23, 2023

Artificial Intelligence and Deep learning have brought about some great advancements in the field of technology. It basically focuses on algorithms that allow machines to interpret complicated patterns and correlations found in datasets by automating the search for analytic expressions.

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Pickl AI

DECEMBER 15, 2024

These processes include learning (the acquisition of information and rules for using it), reasoning (using rules to reach approximate or definite conclusions), and self-correction. AI technologies encompass Machine Learning, Natural Language Processing , robotics, and more.

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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. How does Pattern Recognition Work?

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IBM Journey to AI blog

SEPTEMBER 6, 2023

Here are some key definitions, benefits, use cases and finally a step-by-step guide for integrating AI into your next marketing campaign. AI marketing platforms can create AI marketing strategies and analyze data faster than humans using ML algorithms and recommend actions informed by sentiment analysis from historical customer data.

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NVIDIA

JUNE 15, 2024

He shared how, over a decade ago, NVIDIA — a small company at the time — bet on deep learning, investing billions of dollars and years of engineering resources to reinvent every computing layer. “No No one knew how far deep learning could scale, and if we didn’t build it, we’d never know,” Huang said.

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PyImageSearch

APRIL 7, 2025

Mathematical Definition In an matrix, can be diagonalized and expressed in the following form: where: is an orthogonal matrix (i.e., ) is an diagonal matrix whose diagonal elements are non-negative real numbers (known as singular values). Figure 6: Image compression using the SVD algorithm (source: ScienceDirect ).

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Algorithm Explainability Computer Vision Deep Learning 56

PyImageSearch

NOVEMBER 13, 2023

Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al.

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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.

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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.

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Viso.ai

DECEMBER 10, 2023

Image recognition with deep learning is a key application of AI vision and is used to power a wide range of real-world use cases today. When we visually see an object or scene, we automatically identify objects as different instances and associate them with individual definitions.

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Viso.ai

DECEMBER 19, 2023

Image Classification Using Machine Learning CNN Image Classification (Deep Learning) Example applications of Image Classification Let’s dive deep into it! It uses AI-based deep learning models to analyze images with results that for specific tasks already surpass human-level accuracy (for example, in face recognition ).

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Marktechpost

MAY 8, 2024

Quantum algorithms could dramatically speed up the training of machine learning models and handle problems involving complex systems and large datasets—tasks currently challenging or infeasible for traditional computers. In the automotive industry, companies like Tesla and Waymo are pioneering the use of AI for autonomous driving.

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AWS Machine Learning Blog

JANUARY 22, 2025

Before joining Cato, he held multiple positions across diverse deep learning projects, ranging from publishing a paper on discovering new particles at the Weizmann Institute to advancing computer networks and algorithmic trading. You are only allowed to output text in JSON format. He completed an M.Sc.

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Pickl AI

JULY 22, 2024

Summary: Local Search Algorithms are AI techniques for finding optimal solutions by exploring neighbouring options. Applications include route optimization, scheduling, and Machine Learning. What are Local Search Algorithms? Its efficiently optimised but can get stuck at local optima.

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Towards AI

AUGUST 25, 2023

Machine learning (ML) is a subset of AI that provides computer systems the ability to automatically learn and improve from experience without being explicitly programmed. In ML, there are a variety of algorithms that can help solve problems. Any competent software engineer can implement any algorithm. 12, 2014. [3]

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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. Check out the Paper and Github.

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Heartbeat

JULY 25, 2023

Introduction When it comes to practicing deep learning at home vs. industry, there’s a huge disconnect. Every course, tutorial, and YouTube video presents you with a nicely prepared dataset to feed any DL algorithm for any DL framework. We may discuss gRPC client/server definitions later. python_out=.

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ODSC - Open Data Science

MARCH 3, 2023

Recently, we spoke with Pedro Domingos, Professor of computer science at the University of Washington, AI researcher, and author of “The Master Algorithm” book. In the interview, we talked about the quest for the “ultimate machine learning algorithm.” We are definitely close than when I wrote the book.

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Marktechpost

JULY 7, 2024

Deep neural networks (DNNs) come in various sizes and structures. The specific architecture selected along with the dataset and learning algorithm used, is known to influence the neural patterns learned. Currently, a major challenge faced in the theory of deep learning is the issue of scalability.

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ODSC - Open Data Science

FEBRUARY 2, 2023

Much of what we found was to be expected, though there were definitely a few surprises. Just as a writer needs to know core skills like sentence structure, grammar, and so on, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and so on.

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Flipboard

JULY 10, 2023

Figure 3 illustrates the visualization of the latent space and the process we discussed in the story, which aligns with the technical definition of the encoder and decoder. This can be helpful for visualization, data compression, and speeding up other machine learning algorithms. Or requires a degree in computer science?

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Computer Vision Deep Learning Neural Network Machine Learning 132

Viso.ai

DECEMBER 4, 2023

As a result, frameworks such as TensorFlow and PyTorch have been created to simplify the creation, serving, and scaling of deep learning models. With the increased interest in deep learning in recent years, there has been an explosion of machine learning tools. Hence it is referred to as a low-level API.

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AWS Machine Learning Blog

MAY 16, 2024

In this post, we share how LotteON improved their recommendation service using Amazon SageMaker and machine learning operations (MLOps). Therefore, we decided to introduce a deep learning-based recommendation algorithm that can identify not only linear relationships in the data, but also more complex relationships.

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Flipboard

AUGUST 25, 2023

But, depending on your definition of AI, these early technologies don’t even qualify as such. An MIT article defines machine learning as a machine’s ability to “imitate intelligent human behavior.”) The “deep learning revolution” — a time when development and use of the technology exploded — took off around 2014, Zhavoronkov said.

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The Stanford AI Lab Blog

FEBRUARY 24, 2022

In this first post, we’ll analyze self-training , which is a very impactful algorithmic paradigm for semi-supervised learning and domain adaptation. In Part 2, we will use related theoretical ideas to analyze self-supervised contrastive learning algorithms, which have been very effective for unsupervised representation learning.

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NYU Center for Data Science

NOVEMBER 26, 2024

CDS Faculty Fellow Umang Bhatt l eading a practical workshop on Responsible AI at Deep Learning Indaba 2023 in Accra In Uganda’s banking sector, AI models used for credit scoring systematically disadvantage citizens by relying on traditional Western financial metrics that don’t reflect local economic realities.

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