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Artificial Intelligence and computer vision are revolutionizing the architecture industry. From generative design to heritage restoration, let's explore how AI and CV are reshaping architecture

It's likely that after a couple of decades, humans will be banned from driving cars altogether: because AI in smart cars will handle it better.

Smart machines are making decisions in people's life death and taxes, — and let's be honest, they don't always do it well or transparently

How smart machines make learning easier and cheating harder

Let's explore how AI for agriculture improving the lives of animals, plants, and humans alike

Let's talk about how cities are getting smarter, greener, safer, more dynamic — right now

A few examples of how modern technology makes it possible to produce things faster, cheaper — and more environmentally friendly

Smart machines don't just heal, work in warehouses and stores — they also help make our world a safer place. Let us tell you how!

AR (Augmented Reality) and VR (Virtual Reality) are often associated with gaming. However, these technologies hold significant potential in warehouse management.

AI is already better at diagnosing diseases, can perform minimal intervention surgeries — and make sure patients get better faster. Let's take a look at how VR and AR in medicine is actually done.

Amazon has about 1 million robots working in its warehouses alone — far more than human employees.

Everyone wants clothes that fit better and cost less.

Robots can't do the dishes or clean our house yet, but they can already create a symphony.

In the previous article, we talked about the importance of the camera calibration process, which is employed by computer vision and machine learning algorithms. We discussed how to do this by placing a pattern or, in some cases, using surrounding objects as a pattern in the camera's field of view. But if there is more than one camera, things get complicated!

The cameras are used to capture the world around us. But frames are just representations of the world, and the actual relationship between the flat image and the real thing is not always obvious. In order to extract meaningful insights about the real objects from the images, developers and users of computer vision systems need to understand camera characteristics — with the help of the calibration solutions

Without the suitable and well-organized data, one is bound to face the dreaded "Garbage in, Garbage out" problem — even the most perfect AI model will perform poorly if the input data is poor. Here's how to refine the "fuel" that powers your advanced AI engine!

Football is not only the most popular sport, watched by more than 4 billion people around the world — it is also a huge market. Some of the strongest clubs in Europe are businesses with annual revenues of $8 billion and more than 100,000 employees in different countries. Football is also a competition field for the latest technologies in computer vision and artificial intelligence. Let's take a look at what AI and CV are doing in football!

At the upcoming 2024 Olympic Games in Paris, the world will see the most advanced AI and computer vision systems for sports developed by Intel. These systems will not only help capture athletic performance with millimeter and millisecond accuracy but also create 3D models of athletes for replays and analyzing complex situations. The data and models will be available to both referees and spectators. Artificial intelligence and computer vision systems in sports are no longer a high-tech novelty but an everyday reality. People train, challenge, and watch others compete — and hundreds of tech companies are helping to make it safer and more efficient. And more fun, too!

In the field of CV, selecting the appropriate hardware can be tricky due to the variety of usable machine-learning models and their significantly different architectures. Today’s article explores the criteria for selecting the best GPU for computer vision, outlines the GPUs suited for different model types, and provides a performance comparison to guide engineers in making informed decisions.

Dive into the latest OpenCV AI Weekly Insights Digest for concise updates on computer vision and AI. Explore OpenCV's distribution for Android, iPhone LiDAR depth estimation, simplified GPT-2 model training by Andrej Karpathy, and Apple's ReALM system, promising enhanced AI interactions.

This article offers a comprehensive guide to budgeting for computer vision AI solutions, focusing on critical software factors. It covers key aspects such as task analysis, data collection, annotation, model development, and pipeline implementation, providing insights for making informed financial decisions.

The OpenCV.ai team, creators of the essential OpenCV library for computer vision, has launched version 4.9.0 in partnership with ARM Holdings. This update is a big step for Android developers, simplifying how OpenCV is used in Android apps and boosting performance on ARM devices.

The article examines the iPhone's LiDAR technology: its depth measurement for improved photography, augmented reality, and navigation. LiDAR contributes to digital experiences by mapping environments.

Discover the latest in AI: Hume AI's EVI introduces emotional intelligence to technology, OpenAI's Voice Engine offers realistic voice cloning with ethical safeguards, RadSplat pushes VR rendering speeds, and xAI's Grok-1.5 advances in understanding complex contexts.

Explore how reversible residual networks save GPU memory during neural network training.

Discover the latest in AI: Nvidia's groundbreaking Blackwell B200 GPU and GB200 superchips, Google's innovative VLOGGER AI that animates avatars from photos, insights into GPT-5 from Sam Altman, and Elon Musk's commitment to open AI with the release of Grok-1. Stay informed with our summary of these advancements.

Explore the impact of AI on healthcare, showcasing advances in drug development, robotic surgery, personalized medicine, disease detection, and wearable devices.

Explore the impact of computer vision in logistics, driving advancements in warehousing efficiency, accuracy, and customer satisfaction.

Check out this week's top AI news in our digest! Learn about OpenAI's new video-making AI, a brain chip that controls computers with thoughts, a better way to create digital art, and a big investment in robots that could take over tough jobs.

This article outlines the AI Act requirements and how they impact product companies.

Our article reviews key AI methods in animal behavior recognition and animal pose detection, showing their application in fields from neurobiology to veterinary medicine.

Keep at the forefront of technology and AI with our latest insights, featuring Adobe's pioneering fashion tech, Brilliant Labs' advanced AR glasses, and the groundbreaking Gemini Ultra by Google.

Explore the capabilities of computer vision techniques for facial enhancement in our thorough review.

Dive into the intersection of art, technology, and AI with our latest exploration, where we review how generative AI tools like Stable Diffusion create art.

Read about the latest on the multi-GPT ChatGPT update, groundbreaking developments in humanoid robotics, and existing dream technology – delve into the full digest now.

This comprehensive guide offers insights into the latest YOLO models and algorithms comparison, helping developers and researchers choose the most effective solution for their projects.

This week's digest covers the Rabbit R1 AI gadget for voice control, OpenAI's GPT Store for custom bot sharing, Anthropic's study on AI deception, and new AI e-commerce services from Google and Microsoft. These stories highlight key developments and concerns in the evolving field of AI.

In 2024, as more companies integrate AI, many business owners face challenges. Discover the essential considerations for integrating AI into your business with OpenCV.ai's expert insights. From choosing the right camera for computer vision solutions to navigating diverse computing platforms, this article provides practical guidance. Explore the nuances of network and power optimization, and take the first step toward AI-driven success.

The article explains the technology behind self-driving cars, focusing on computer vision and machine learning. It discusses how cars use cameras, LIDAR, and algorithms like YOLO and Deep SORT for detecting and tracking objects. The article also covers challenges and future trends in autonomous vehicle technology, including safety, public trust, and smart city integration.

Discover how your smartphone is more than just a communication tool – it's a gateway to cutting-edge computer vision technology, transforming every interaction and enhancing security. It covers facial recognition for unlocking phones, augmented reality filters in social media apps, text recognition in images, and organizing photos by recognizing faces. These technologies improve phone security and user experience.

This week's OpenCV AI Weekly Insights Digest covers key AI developments, including Stability AI's new Stable Video Diffusion model for video generation, Tesla's Full Self-Driving v12 update testing, a U.S. investigation into UAE's AI firm G42 for data risks linked to China, and a study showcasing AI's advancements in microscopy image analysis.

This week's OpenCV AI Weekly Insights Digest covers major developments in AI, including DeepMind's new music generation model Lyria, NVIDIA's H200 GPU enhancing AI performance, Meta's innovative video and image editing tools, and significant leadership changes at OpenAI and Microsoft.

The retail sector is evolving with the help of artificial intelligence and computer vision, leading to the development of stores without cashiers. This technology helps in managing inventory and tracking stock levels automatically. It also analyzes customer behavior in stores, in order to improve store arrangement and marketing, making shopping easier and more tailored to individual preferences.

In this week's AI update, we consider the following news: the historic AI summit, where over 25 countries unite to collectively govern AI risks; Elon Musk introduces Grok, an AI chatbot; Apple's plans for the 2024 Apple Watch with new health features; and The Beatles' surprise release of "Now and Then" using AI technology.

In this week's AI update, we bring you the latest developments in the tech world: Boston Dynamics' integration of OpenAI's GPT-4 into Spot, the robot dog, enhancing its conversational capabilities; Amazon's beta testing of AI image generation tools for advertisers; Google's $2 billion investment in Anthropic, and more.

Meet AI and fitness combination: pose tracking technology analyzes and improves exercise routines in real-time.

Here you will find a recap of last week and what's happened in the digital AI world: Highly-skilled robots by Nvidia, Apple plans to incorporate AI into their products, a comprehensive study about LLMs bias in medicine, and more.

Computer vision is helping the agriculture industry with close monitoring of crops and soil, early detection of diseases, forecasting and even livestock management, improving efficiency and sustainability. Explore the use of synthetic data in agriculture to enhance real-world datasets, making computer vision models more robust and adaptable to various conditions like diverse weather scenarios and lighting conditions.

Check the latest news in the AI field: from Google Search image generation feature to AI celebrity avatars, which replace traditional influencers!

Here's our weekly roundup of newsworthy developments from the world of computer vision and AI.

In this special blog article, we will document our visit to the ICCV convention.

Here's our weekly roundup of newsworthy developments from the world of computer vision and AI.

What happened in the AI world this week? Let's find out! From groundbreaking headlines to jaw-dropping breakthroughs, we've got the scoop.

What happened in the AI world this week? Let's find out! ChatGPT Fine-Tuning, Facebook released AI tool for coding, and more!

What happened in the AI world this week? Let's find out! NVIDIA's Open-Source 3D Tool Release, San Francisco's Autonomous Driving Pause, and more!

Join us in a reveal of our collaboration with Snap, to create a real-time and accurate Text Recognition tool!

What happened in the AI world this week? Let's find out! From groundbreaking headlines to jaw-dropping breakthroughs, we've got the scoop.

Discover the future of media processing with MediaPipe. This open-source framework empowers you to harness machine learning for video and audio, operating in real time on diverse devices.

Keeping pace with the evolution of technology and utilizing it judiciously, this blog explores how ChatGPT can serve for code development debugging.

NeRF is an innovative technology that generates photorealistic images of scenes from novel viewpoints using a neural network and volume rendering techniques. This article explores NeRF components, training, strengths and limitations, and advancements in modern NeRF-based solutions.

Fast SAM, an innovative approach to the Segment Anything Task, drastically increases SAM model speed by 50 times. It introduces prompts to facilitate a broad range of problem-solving, breaking barriers of traditional supervised learning. This blog post will briefly explain the segment anything task and the Fast SAM approach.

In the vast world of 3D object pose estimation, one group of tasks demands a distinct spotlight. This is where we delve into predicting the position of rigid objects in 3D.

The "Tracking Everything Everywhere All at Once" paper, a collaborative work by Cornell University, Google Research, and UC Berkeley, offers a breakthrough solution to the problem of tracking any point in video footage. The method maps each pixel from every frame into a common 3D space, tracing its trajectory across time. This method is not designed for real-time tracking but for in-depth recorded video analysis. In this article, we highlight the most exciting points of this paper.

At OpenCV.ai, we have been developing cutting-edge AI-based analytic algorithms for tennis, aiming to reshape the way professional athletes train and perform in various sports. The growing influence of AI in the sports industry has led to significant advancements in training methods and analytics, providing invaluable insights for athletes and coaches alike. Here, we break down the key benefits and applications of AI and Computer Vision in tennis, showcasing our expertise in this domain.

At OpenCV.ai, we believe that computer vision (CV) has the potential to revolutionize businesses of all sizes, from ambitious startups to Fortune100 companies. Our for-profit arm leverages the same expertise that made OpenCV the most popular CV library in the world. In this post, we'll give you a glimpse into our consulting process, complete with timelines, and how it can help you harness the power of CV to transform your business.

In today's deep learning era, AI and computer vision (CV) have enabled us to tackle complex challenges with remarkable speed and accuracy. In this article, we'll explore the world of multi-object tracking in CV and discuss its applications, challenges, and breakthroughs.