Exploring the future of technology

Discover the fascinating world of Video Game Level Design in this concise and informative video. Join us as we delve into the origins of this rapidly evolving role and explore the crucial responsibilities of a level designer within a game development team. Whether you're a newcomer to the field or simply curious about the intricacies of game design, this video serves as the perfect introduction to our channel. Gain valuable insights and a brief overview of the level designer's job, and embark on an exciting journey into the realm of game creation.

The Nothing Phone 2 brings some innovative features like Glyph Interface and transparent design that could challenge Samsung's flagship Galaxy S23 Ultra. This video compares the specs, features, performance and camera quality of these two phones to determine if the Nothing Phone 2 can dethrone the smartphone king.

This video provides an explanation of query, key and value vectors, which are an essential part of the attention mechanism used in transformer neural networks. Transformers use multi-headed attention to learn contextual relationships between input and output sequences. The attention mechanism calculates the relevance of one element to another based on query and key vectors. The value vectors then provide contextual information for the relevant elements. Understanding how query, key and value vectors work can help in designing and optimizing transformer models for various natural language processing and computer vision tasks.

This video provides a simple and straightforward explanation of what layer normalization is and how it works in neural networks. Layer normalization is a technique used to speed up the training of deep neural networks by normalizing the inputs to each layer. We will cover: - What normalization means and why it is important for training neural networks - How layer normalization works by normalizing the inputs for each layer across ... samples in a batch - When to use layer normalization versus other techniques like batch normalization - The pros and cons of layer normalization Even if you are new to deep learning, by the end of this video you'll have a solid understanding of what layer normalization is and how it can help improve the performance of your neural networks.

Andrew Ng's Deep Learning Specialization on Coursera is one of the most popular ... certifications for learning deep learning online. In this video, I'll give you my honest review of the course after completing it myself. Here's what I'll cover: - An overview of what the specialization covers, including the 5 courses on neural networks, convolutional neural networks, sequence models, generative models and reinforcement learning. - The pros of the program: the high quality of the content from Andrew Ng and other experts, the hands-on projects and the reputation that can help with job applications. - The cons: the high cost, the lack of career services and the fact that the material is not the most cutting edge. - My overall assessment of whether the certification is actually worth it, based on my experience completing the program and applying deep learning in my career.

Maximizing your Digital SAT score requires a strategic approach. Unlike previous SATs with a curve, the Digital SAT awards the same number of points for every correct answer. To earn your highest possible score: • Focus your time on questions you're confident you can answer correctly. Avoid spending too much time on difficult questions that have a low chance of a correct answer. • Use any remaining time to revisit skipped questions or educated guesses. Even getting a few more correct changes can boost your score. • Review the test for careless errors. Even one or two avoidable mistakes can lower your score. • Practice taking full-length Digital SAT tests to improve your pacing and identify areas needing more study. Your stamina and timing are crucial. The Digital SAT scoring algorithm rewards accuracy and efficiency. With preparation and the right test-taking strategies on exam day, you can maximize your Digital SAT score and improve your chances of gaining admission to your dream school.

This video provides a step-by-step guide to using the Dataset app to manage storage and file permissions on TrueNAS Scale. The Dataset app is a web-based file manager that makes it easy to organize, share and secure your data. The video will likely cover: - Creating datasets to logically organize your storage - Adding shares to datasets to make data accessible over the network - Setting permissions for datasets and shares to control who can access them - Using groups and users to manage access in a scalable way - Setting quotas to limit how much space a dataset or share can use - Setting permissions inheritance, so changes apply to child datasets and shares - Using templates to quickly create datasets and shares with the same settings - Finding and managing datasets using search, tags and the dashboard By using the Dataset app, you can easily manage your TrueNAS Scale storage in an intuitive and organized way. Datasets allow you to logically separate data without modifying the underlying storage, while shares expose that data over the network.

Machine learning, artificial intelligence and deep learning are often used interchangeably but they are different concepts. This video provides a simple explanation of the differences and relationships between machine learning, artificial intelligence and deep learning: • Machine learning is a subset of artificial intelligence. It involves using algorithms to learn from data and improve automatically through experience. • Artificial intelligence is the broader field that refers to machines being able to carry out tasks in a way that we would consider "smart". • Deep learning is a specific type of machine learning that uses neural networks with many layers to learn representations and solve complex problems. We'll also discuss related topics like natural language processing, data science, emerging technologies and in-demand jobs in the machine learning field.

This video demonstrates an add-on for Blender that can be used to generate synthetic data for training deep learning models. The add-on simulates different types of depth sensors like LiDAR and sonar to capture point cloud data in virtual 3D environments. This allows for an automated and scalable process to create large amounts of semantically annotated training data. The add-on lets you customize sensor parameters, simulate environmental conditions, and export the data in formats suitable for deep learning applications. The synthetic data helps train models that can be deployed in the real world for tasks like autonomous driving and robotics.

This step-by-step tutorial shows you how to automatically identify trees in images using deep learning tools in ArcGIS Pro. We will use a pre-trained DeepForest model from the ArcGIS pretrained models website and the Detect Objects Using Deep Learning tool in ArcGIS Pro's Image Analyst extension. Specifically, we will cover: - Downloading the DeepForest pre-trained model - Adding image rasters to your ArcGIS Pro project - Running the Detect Objects tool to identify trees - Visualizing and analyzing the detection results By following along, you'll learn how to harness the power of deep learning to enhance your geospatial analysis. Identifying trees and other objects in images can provide valuable insights for land use planning, natural resource management and more.

Artificial Intelligence is transforming every industry and solving real-world problems at an unprecedented scale. If you want to gain in-demand skills and build a future-proof career, learning AI in 2023 is the perfect place to start. This video will discuss the immense opportunities that AI is creating, from high-paying jobs to solving global challenges. Our 40-day Urdu/Hindi AI bootcamp course is designed for beginners, covering essential AI topics like machine learning, deep learning and neural networks in an easy-to-understand way. Regardless of your background, we'll help you kickstart your AI journey and build a foundation for a career in this high-growth field.

In this lecture, Prof. M.K. Bhuyan from IIT Guwahati covers the fundamentals of machine learning and deep learning along with their applications. He discusses what machine learning and deep learning are, how they work, popular algorithms and techniques, and real-world use cases across industries. Whether you're just getting started or want to expand your knowledge, this lecture provides a comprehensive yet accessible overview of machine learning and deep learning.

Digital twins are virtual replicas of physical assets and processes that can be used to optimize performance, reduce costs, and drive innovation. This video likely demonstrates how companies like Siemens and ST are utilizing digital twins to improve factory automation, increase production efficiency, and enhance decision making through data insights. Key topics may include the benefits of digital twins for manufacturing, how they are implemented in practice, and real-world results companies are seeing.

In this interview with theCUBE, Bruno Aziza discusses data and analytics at Google Cloud. Bruno is the head of data and analytics at Google Cloud. Some of the topics discussed include: • The increasing demand from businesses for consistent cloud infrastructure to support their data-driven strategies • How embedded business intelligence is a key principle at Google Cloud, with analytics capabilities built into their various cloud products • Recent capabilities launched for BigQuery, Google Cloud's data warehouse and analytics service, to help customers gain insights from their data • The importance of machine learning and AI in helping organizations extract value from their data and automate data-driven processes • The role of data governance and security in ensuring customers can analyze data confidently in the cloud The discussion provides insight into Google Cloud's approach to data and analytics and how they are helping businesses make better decisions through data. Bruno's leadership perspective and expertise in the cloud data space offer valuable insights for organizations looking to leverage cloud technologies to power their data and analytics strategies.

According to a recent report, Meta is discontinuing production of its high-end VR/AR headset, the Meta Quest Pro. The Information claims Meta has decided not to order new components for the headset, indicating production will end once current supplies are depleted. Launched in October 2022, the $1,500 Meta Quest Pro aimed to be a productivity tool and showcase the future of immersive experiences. However, the headset received criticism for several issues: • The Passthrough AR feature was seen as lacking in quality • The absence of a depth sensor was viewed as a limitation for augmented reality applications • The cartoon-like avatars were criticized for not being realistic enough for collaboration • Existing apps made limited use of the headset's eye-tracking capabilities While the Quest Pro aimed to push the boundaries of VR and AR, it seems Meta has decided to halt production due to these issues and an underwhelming user experience. It remains to be seen if Meta will refine the design and reintroduce an updated Quest Pro in the future.

This video provides a gentle introduction to the fundamentals of machine learning and its applications. We'll cover what machine learning is, how it works, popular algorithms and techniques, and real-world use cases. Even if you have no previous experience, by the end of the video you'll have a solid understanding of the basics of machine learning and how it is transforming industries.

This video uses animations to provide an in-depth explanation of Adam optimization, an adaptive learning rate algorithm commonly used in deep learning. Adam stands for Adaptive Moment Estimation and is an optimization technique for gradient descent. It is efficient for large datasets and neural networks with many parameters because it requires less memory and computation. Adam works by calculating adaptive learning rates for each parameter from estimates of the first and second moments of the gradients. This makes it more robust to noisy gradient information and allows it to converge faster than standard stochastic gradient descent.

Synopsys Cloud is redefining the electronic design automation (EDA) industry with the first complete browser-based EDA-as-a-Service platform. This on-demand, pay-per-use, web-based portal brings many benefits to design teams: • Access to industry-leading EDA tools anytime from anywhere • Increased productivity with a simple browser interface • Lower upfront costs with a flexible pay-per-use model • Fast innovation cycles powered by scalable cloud compute In this video, Vikram Bhatia from Synopsys discusses how Synopsys Cloud is encouraging innovation across the semiconductor lifecycle. He covers the benefits of an always-available cloud platform for next-generation design.

Figma recently launched Dev Mode, bringing a host of useful features for developers. This includes rem units, a VS Code plugin, and other productivity enhancements. However, there are still some drawbacks. This video covers how to make the most of Dev Mode's positives while working around its current limitations.

While tokenized assets present new opportunities for institutional investors, transacting tokens across multiple blockchain networks remains challenging. Each network has different processes and standards, requiring institutions to connect to many blockchains to manage and trade digital assets. ANZ Bank is exploring an interoperability solution with over a dozen financial institutions to simplify this process. Experiments show that firms can leverage existing SWIFT infrastructure to efficiently manage tokens across public and private blockchains. Watch this Inside Innovation Live with host Nick Kerigan and Anurag Soin from ANZ Bank. They discuss the challenges of transacting digital assets today, how their interoperability solution could work in practice, and their experiences innovating on this collaborative project. This Rumble video is provided for entertainment purposes only. The images, clips, and content presented in this video may be dangerous or potentially harmful if attempted to replicate or imitate without proper caution and adequate supervision. The creators of this video are not responsible for any injury, damage, or negative consequence that may result from attempting to recreate or imitate the activities, tricks, or actions shown in this video. Viewers are strongly advised not to attempt any dangerous activity without proper training, appropriate equipment, and supervision from qualified professionals. Viewers assume all risks and liabilities associated with their participation in hazardous or high-risk activities. Enjoy the video, but always remember to prioritize your safety and well-being!

At the G20 Energy Ministers' Meeting in Goa, Prime Minister Modi highlighted India's efforts towards green growth and energy transition. He pointed out that despite being the most populous and fastest growing large economy, India is strongly committed to meeting its climate goals. The Prime Minister noted that India achieved its target of installing non-fossil fuel based electricity generation capacity nine years ahead of schedule and has set an even higher target for itself.

This video provides an overview of big data - what it means, why it's important and how it is impacting business and society. Big data refers to the massive volumes of data that are now being created and collected from a wide range of sources, including websites, apps, social media, sensors and machines. The key aspects of big data are often summarized as the 3Vs: volume, variety and velocity. Big data technologies allow us to collect, manage and analyze this data at a scale and speed that was not possible before. This enables new insights, innovations and efficiencies that can improve decision making, optimize processes and create new products and services. The video will discuss real-world examples of how big data is being used and the opportunities and challenges that organizations face in harnessing its full potential.

Companies are setting ambitious goals to build net-zero, environmentally friendly and socially responsible value chains. However, achieving these new targets means overcoming major implementation challenges and strengthening collaboration across industries and regions to make a real difference. Transitioning to sustainable value chains requires a holistic, systems-level approach that engages partners across the entire supply chain.

Egor Kuzmin and Yacine Hamdani present their innovative 3D printed shoe concept designed for Zellerfeld. The futuristic sneaker features an organic, biomimetic design inspired by nature and 3D printing technology. The concept demonstrates the potential of 3D printing to create customized, sustainable footwear of the future.