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What Is Artificial General Intelligence and How Does It Work?

Emily Lawson — Wed, 20 Mar 2024 12:21:33 +0000

Artificial General Intelligence (AGI) hasn’t become real yet. However, research into this type of artificial intelligence where machines think and learn as people continues in different parts of the world. The idea behind AGI is to have machines develop self-awareness and consciousness. These developments have already started manifesting in innovations like self-driving cars. Once developed fully, AGI can potentially blur the intellectual differences that currently exist between machines and humans.

Although it’s still too early to tell whether machines can simulate human intellectual capabilities fully, the concept of AGI is fascinating. In this article, we explore AGI further to help you understand how it differs from artificial intelligence (AI) and the technologies behind it.

What is Artificial General Intelligence?

Artificial General Intelligence is a theoretical form of AI that can learn, understand, and apply knowledge to perform intellectual tasks like humans. Although AGI isn’t a reality yet, its design incorporates adaptability, flexibility, and problem-solving skills. These skills will enable it to perform any intellectual task that a human can, or in some instances, outperform human abilities.

AGI is designed to address gaps in current AI systems. Currently, AI systems have limited scope. They cannot self-teach or complete tasks they are not trained to perform. AGI promises complete AI systems that utilize generalized human cognitive abilities to perform complex tasks across different domains. Artificial general intelligence examples already exist in self-driving cars.

Artificial General Intelligence vs Artificial Intelligence: What’s the Difference?

In decades past, computer scientists advanced machine intelligence to a point where machines perform specific tasks. For instance, AI text-to-speech tools use deep learning models to establish the link between linguistic elements and their acoustic features. These machine-learning models learn from huge volumes of audio and text data and then generate AI speech and voice patterns.

Today, AI systems are designed to perform specific tasks. They can’t be repurposed to work in other domains. Their computing algorithms and specifications are limited and they rely on real-time data for decision-making. This form of machine intelligence is considered narrow or weak AI.

AGI seeks to advance current AI capabilities. It seeks to diversify the tasks that machines can perform to enable them to solve problems in multiple domains instead of one. This makes AGI a hypothetical representation of a strong, full-fledged AI. Such AI will have general cognitive abilities that enable it to solve complex tasks, just like humans.

How Does General Artificial Intelligence Work?

The concept of AGI is based on the theory of mind that underpins the AI framework. This theory focuses on training machines to understand consciousness and learning as fundamental aspects of human behavior. Besides applying algorithms, AGI will incorporate logic into machine learning and AI processes to mirror human learning and development.

With a solid AI foundation, AGI is expected to learn cognitive abilities, make judgments, integrate learned knowledge in decision-making, manage uncertain situations, and even plan. General artificial intelligence will also facilitate machines to conduct imaginative, innovative, and creative tasks.

Technologies that Drive Artificial General Intelligence

The concept of AGI is still in the theoretical stage. Research on its viability and efforts to create AGI systems continue in different parts of the world. The following are the emerging technologies that will most likely characterize AGI:

1. Robotics

This is an engineering discipline that involves the creation of mechanical systems that automate physical tasks. In AGI, robotics facilitate the physical manifestation of machine intelligence. Robotics plays an important role in supporting the physical manipulation ability and sensory perception required by AGI systems.

2. Natural Language Processing

This AI branch enables machines to generate and understand human language. NLP systems convert language data into representations known as tokens using machine learning and computational linguistics.

3. Deep Learning

It’s an AI discipline that involves training multiple layers of neural networks to understand and extract complex relationships from raw data. Deep learning can be used to create systems that understand different types of information like audio, text, video, and images.

4. Computer Vision

A technology that supports extraction, analysis, and comprehension of spatial data from visual data. For instance, self-driving cars rely on computer vision models to analyze camera feeds in real time for safe navigation. Computer vision relies on deep learning technologies to automate object classification, recognition, and tracking among other image-processing tasks.

5. Generative AI

A subset of deep learning, this technology enables AI systems to generate realistic and unique content from knowledge learned. Generative AI models use huge datasets to train, which enables them to answer questions from humans in text, visuals, and audio formats that resemble natural human creations.

The Challenge Ahead

If it becomes a reality, there is no doubt artificial general intelligence will change how we work and live. But the journey to making it work isn’t smooth. In developing this emerging technology, computer scientists must find ways to make AGI models connect between domains the way humans do. Another challenge that needs to be overcome relates to emotional intelligence.

Neural networks cannot replicate the emotional thinking required to drive creativity and imagination. Humans respond to situations and conversations depending on how they feel. Considering the logic embedded in current AI models, replicating this ability and improving sensory perceptions to enable machines to respond and perceive the world the way humans do remains an uphill task.

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Implementing DevSecOps for Cloud Security

Noah Davidson — Wed, 13 Mar 2024 09:44:55 +0000

DevSecOps refers to development, security, and operations. It is a methodology that integrates security practices into the DevOps process, emphasizing the importance of security from the very beginning of software development.

DevSecOps is a relatively new idea. Cloud DevSecOps takes the Software Development Life Cycle (SDLC) one step further by integrating the security component, whereas DevOps merges development and operations in a continuous synchronized loop.

As a result, security is built right into the cloud application, saving a lot of time and money in the event of a cyberattack.

This strategy is necessary because DevSecOps in cloud security transpires to be a significant benefit for the widespread adoption of cloud computing. The method incorporates security testing and monitoring in addition to continuous development and deployment, making the cloud application secure from the start.

Understanding the breadth and advantages of cloud DevSecOps can be helpful if you intend to develop your software or application.

Importance of DevSecOps in Dealing with Cloud Security Challenges

While DevSecOps teams check on product security during development and launch, IT departments strive to guarantee the security of a company’s network and IT infrastructure.

Their responsibilities include process monitoring, risk analysis collection, security measure automation, and incident handling. DevSecOps helps businesses address cloud security concerns by assisting them to establish efficient risk management for cloud security.

1. Open Environment

DevSecOps’s introduction creates the framework for open dialogue between teams and business divisions. Once DevSecOps is the cornerstone of your development, tracking and monitoring complex initiatives—like cloud migration and security, for example—and keeping all stakeholders informed become non-issues.

Nonetheless, developing and implementing DevSecOps processes in a way that allows them to handle security threats and support the resilience of enterprises takes time.

2. Offering Cost-effective Security

Which is better, addressing a security breach’s consequences or trying to stop it from happening? Organizations that leverage DevSecOps neutralize such threats before they have a significant effect. Through the identification and prevention of events that may impact the internal IT environment, DevSecOps helps many firms reduce their business vulnerabilities.

It saves time and money by reducing the need to repeat a method to resolve security vulnerabilities thanks to DevSecOps’ quick and safe delivery. Because the integrated security code no longer includes pointless rebuilds or reviews, it is more secure. It is reasonably priced and effective.

3. Storing Data at A Single Location

Teams may quickly improve apps that are still in development by utilizing data management and the DevSecOps process suite to gather data from various sources and feed it back into the creative process. To put it briefly, the implementation of DevSecOps helps technical and operation teams to analyze collected data and transform it into meaningful insight.

The data insights are continuously improved under one roof, resulting in easy CI/CD that further helps save time during the product development cycle.

Strategies for DevSecOps that Can Transform Cloud Security

For a cloud DevSecOps deployment to be effective, the DevOps cloud security teams need to collaborate closely with other teams and monitor the code quality throughout the application’s lifetime. Here, we go over the six essential DevSecOps in cloud deployment techniques that have the potential to completely transform cloud security and cloud security solutions at your business:

1. Process Automation for Testing

Automated testing is unquestionably one of DevSecOps’ principles or best practices. It may be the impetus for cloud DevSecOps. Automated tests improve the testing process by repeating tests, documenting findings, and providing feedback to the team more quickly.

Automating tests throughout development can improve overall productivity by eliminating code errors. It is possible to expedite the entire cloud migration procedure, which facilitates the migration of more resources to the cloud.

2. Analysis of Code

Most businesses must be able to alter their software regularly to respond to changing market conditions. Short delivery cycles make traditional security models unsuitable, even though agile teams have adapted to this trend. As a result, they hinder your organization’s agile release cycles and expand software product offerings.

You may ensure excellent cloud security risk management and code production in short, frequent releases by using an agile approach to security operations within your teams. Using cloud technology for DevSecOps has two advantages: it incorporates code analysis into the quality control process and allows for rapid vulnerability screening.

3. Compliance Tracking

Cloud-based technologies are used to handle enormous volumes of data. Following stringent security laws such as HIPAA, GDPR, and SOC 2 could be difficult.

Adopting cloud DevSecOps could alter it and reduce the additional effort from regulatory audits. Every time new codes are generated or modified, development teams can gather instantaneous evidence of compliance. It would help the company be ready for any unanticipated circumstances.

4. Vulnerability Management

Finding, looking into, and fixing any threats or vulnerabilities that surface with every new code delivery is crucial to DevOps security. In addition to publishing and carrying out vulnerability checks, schedule regular, periodic security scans to aid in the discovery of new defects or vulnerabilities.

5. Change Management

It takes a deep comprehension of the change management procedure to implement a DecSecOps cloud computing approach. Giving your developers the knowledge and resources they need to recognize risks and take appropriate action before they become major problems enhances the effectiveness of change management.

Similarly, giving developers 24-hour clearance windows allows them to consistently propose proposals for security measures that are essential to the goal.

Conclusion

Cloud security protocols could undergo a revolution with the application of DevSecOps. Integrating security concerns into each software development lifecycle step allows organizations to guarantee the integrity of their cloud environments, protect sensitive data, and manage risks proactively.

Businesses may stay ahead of cyber risks and adhere to regulatory obligations by implementing DevOps managed services, which fosters cooperation, automation, continuous monitoring, and a security-first culture.

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Understanding the Dynamics of Digital Twin Technology

Olivia Carter — Wed, 28 Feb 2024 15:25:44 +0000

Digital twins are among the most sought-after business tools in the world today. One Internet-of-Things (IoT) analytics report shows that between 2020 and 2022, the digital twin technology market grew by 71%. The versatility that this technology offers, makes it attractive for varying businesses across industries. Digital twins are computer programs that utilize real-world data to develop simulations based on historical data and current conditions.

These programs can integrate with artificial intelligence, IoT, and software analytics to improve outputs. IoT sensors facilitate the transfer of real-world data needed to create virtual twins. Using the simulations, businesses can predict how a process or product will perform. But, virtual twins aren’t just about simulation. They span the entire product or process lifecycle and have service, engineering, and manufacturing use cases.

In this article, we delve deeper into the types of digital twin technology and its use cases.

What is Digital Twin Technology?

Digital twin refers to the technology that supports the creation of virtual representations of physical systems, processes, or objects. This digital twin is supported by various state-of-the-art technologies including artificial intelligence, IoT, big data, machine learning, IoT, and visualization technologies like augmented and virtual reality. Essentially, digital twins have three main components:

A virtual definition of their counterparts
Operational data of their components
Information model that gathers and presents data to inform decisions

Types of Digital Twin Technology

There are four types of digital twins namely:

1. Component Twins

Also referred to as part twins, component twins are the lowest levels of virtual twins. It corresponds with the tiniest elements within a specific part of a product or equipment like a switch or an IoT sensor. Component twins facilitate performance monitoring and allow for the simulation of real-world conditions for purposes of testing their efficiency, stability, or endurance.

2. Product/Asset Twins

Product twins feature several component twins or utilize the information that component twins generate to create complex assets like smart buildings, pumps, or engines. These twins analyze how well separate parts of a system perform and interact as part of the entire process or solution. Engineers use product twins to gather insights about equipment performance and identify potential flaws.

3. System Twins

These digital twins show how varying products combine to form functional units and duplicate product assets at the system level. They provide a large-scale view of plants or factories, allowing engineers to test varying systems for optimal effectiveness.

4. Process Twins

These constitute the highest level of virtual twins, connecting system twins into a single entity that supports synchronization and collaboration between systems. Process twins create solutions that offer a maximum view of workflows within manufacturing plants or factories for deeper and more versatile output analysis.

Key Industrial Use Cases of Digital Twin Technology

Virtual twinning has varying use cases. Below are the main use cases for this technology in businesses across industries:

1. Product Design

Digital twins allow companies to develop quality products, cities, processes, systems, or buildings. By simulating physical objects, product developers test varying designs, identify design flaws, and make adjustments to improve those flaws before commencing actual production.

2. Service Optimization

Companies can use digital twinning to identify service improvement opportunities and optimize the delivery of those services. Companies use virtual twinning to improve customer experience, optimize manufacturing processes, and improve operations.

3. Supply Chain Management

Industries can use digital twins to simulate and test scenarios that facilitate the identification of inefficiencies in supply chain management processes. This information enables them to optimize the flow of materials and products in supply chains. Digital twinning is also used to simulate supply chain disruptions like transportation problems or raw material delivery delays and their impact on the business. This allows suppliers to mitigate these issues before they occur.

4. Operations Management

In operations management, virtual twin technology facilitates real-time remote access and performance monitoring of systems, assets, and processes. This enables industries to test varying scenarios and find improvement opportunities. Digital twins also help companies identify and fix performance problems like energy consumption, uptime, and maintenance needs before they can result in production losses or downtime.

5. Entertainment

Another important digital twinning use is entertainment. Considering that mixed reality technologies are at the heart of virtual twins, the technology can be used to create immersive experiences for customers in the leisure industry.

One of the leading digital twin technology examples in the entertainment industry is the simulation of attractions and rides in amusement parks. This allows customers to experience the rides virtually even before they make actual visits to the parks. With this information, customers can plan their visits better and prioritize their preferred attractions for more satisfying experiences.

Final Thoughts

Digital twinning will continue to change the way industries build, design, and maintain systems and products. Its application will expand to new sectors beyond automobile, aerospace, health, and smart cities industries. Another trend we can expect in future is democratized access to the technology through the digital twin-as-a-service (DTaaS) model. Delivery of DTaaS via cloud-based solutions will make digital twin technology highly affordable and accessible to businesses of all sizes. Additionally, we’ll witness integration of virtual twinning technology with edge computing and the 5G network to support real-time analytics and facilitate flawless data transfer respectively.

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What Is Spatial Computing and How It Is Reshaping Industries?

Noah Davidson — Fri, 23 Feb 2024 15:40:31 +0000

The last few decades have been characterized by significant tech innovations like artificial intelligence, 3D printing, and driverless cars. As we progress into the current decade, another massive shift in computing is unfolding right before us – spatial computing. This new technology holds enormous potential to change how industries optimize their operations. In this article, we answer questions like what is spatial computing? What are the key elements of this technology, and how will it affect industries in future?

What is Spatial Computing?

This refers to digitization of activities that involve people, machines, objects, and environments where they take place. It merges the digital and real worlds to create a more immersive experience for users. Combining technologies like virtual reality (VR), augmented reality (AR), and mixed reality (MR), spatial analysis technology facilitates seamless interactions between computers and users in a 3-dimensional (3D) world.

What are the Main Elements of Spatial Computing?

Computing spatial analysis technologies have four main elements:

1. Augmented Reality (AR)

Space computing uses augmented reality to improve user perception and interaction by overlaying objects and digital information into the real world. AR applications leverage this technology to track user position and orientation for improved interaction with virtual objects.

2. Virtual Reality (VR)

Virtual reality immerses users in computer-generated environments. It’s ideal for simulating real-world activities. But, what is spatial computing technology with regard to virtual reality? Space computing utilizes VR to add natural interactions to virtual environments by tracking body and head movements.

3. 3-D Scanning

Computer spatial analysis leverages photogrammetry or 3D scanning to capture real-world objects and scenes. This results in the production of detailed 3D models with the right shape, texture, and color for immersive 3D user experiences.

4. 3-D Modeling

Mixed reality uses augmented reality to improve user perception and interaction by overlaying objects and digital information into the real world. AR applications leverage this technology to track user position and orientation to improve interactions with virtual objects.

Spatial Computing Use Cases that are Reshaping Industries

What is spatial computing enabling companies to do? We take an in-depth look at six use cases of computer vision spatial analysis and their application across industries:

1. Redefining Employee Training

Space computing is redefining employee training with its immersive and highly interactive capabilities. Using this technology, companies can develop virtual training environments that are very similar to scenarios in the real world. In such environments, employees learn by doing as opposed to observing. For example, pilots can acquire aircraft flying skills through virtual simulations that resemble real-life flight experiences. This hands-on, immersive approach accelerates employee learning and improves knowledge retention.

2. Improving Productivity

Mixed reality automates tedious tasks and optimizes workflows. Industries can use it to add intuitiveness to digital content interactions for enhanced efficiency and task completion. For example, the technology gives visual cues on AR glasses to enable factory workers to locate or identify the tools they need. In retail environments, technology can give buyers pleasant shopping experiences by leading them to the products they wish to buy. This blend between the physical world and digital data provides contextual information needed to fast-track decision-making and enhance productivity.

3. Virtual Product Prototyping

What is spatial computing to product development and how will it alter the way industries prototype their products? Companies incur huge costs conducting physical prototyping and testing on new products. Computer vision spatial analysis is changing this by enabling prototyping and testing of products virtually. Product designers and developers can develop, refine, and test product designs in digital environments before producing physical products. By facilitating simulation of real-world product usage and conditions, spatial computing technology allows companies to identify product design issues and resolve them early in the development process.

4. Improving Workplace Design

Companies in different industries can use spatial analysis computing to create workspaces that foster employee productivity and collaboration. Using this technology, organizations can simulate different office layouts, create digital replicas of real-world workspaces, and evaluate their impact on employee collaboration, workflow, and efficiency. Interior designers and architects use the spatial analysis technology to visualize workspace layouts in 3D, giving companies an office feel before implementing actual changes.

5. Fostering Collaboration

The immersive nature of computer spatial analysis technology gives buyers personalized experiences. For example, the technology can facilitate ‘try before purchase’ experiences for retail shoppers. Buyers can see how a dress would look on them or how furniture pieces would look in living spaces without trying or placing them physically.

6. Better Customer Service

Industrial enterprises can use spatial glasses to create shared digital spaces that allow teams to interact as if they were located in the same physical room. In such environments, teams can exchange digital objects, view each other’s avatars, and engage each other. This enables teams to build stronger relations and enhances collaboration, making it more immersive and highly interactive.

Final Thoughts

Industrial enterprises that understand space computing and its use cases can change their operations significantly. But, what is spatial computing in relation to extended reality technologies like augmented and virtual realities? Space computing leverages these technologies to recreate physical environments in digital spaces for immersive, highly engaging experiences. Industries can use this technology to enhance employee productivity, improve staff training and collaboration, and facilitate virtual product prototyping.

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Distributed Ledger Technology: A Comprehensive Overview

Emily Lawson — Tue, 13 Feb 2024 10:22:57 +0000

If you’ve been following cryptocurrencies and blockchain, you’ve heard about distributed ledger technology (DLT). Although the idea of distributed computing isn’t entirely new, the execution of distributed ledgers is one of the most ingenious inventions of our time.

Distributed ledgers didn’t gain popularity until 2008 when the first cryptocurrency was created. Since then, they have evolved into programmable and scalable platforms where tech solutions that use ledgers and databases can be created.

In very simple terms, distributed ledger technology may be defined as tech protocols and infrastructure that allow concurrent access to records, updates, and validations across a network of databases. In this article, we explore the differences between DLTs and blockchain and explain their benefits and limitations.

Distributed Ledger Technology vs Blockchain

Blockchain is a form of distributed ledger technology. However, there are many other types of DLT systems. As decentralized systems, blockchains and DLTs facilitate transparent and secure data storage and updating. However, major differences exist between the two.

DLT systems use different structures to manage and store data while blockchains use linear blocks to record, store, and verify transactions. Each block has transaction data, a time stamp, and a cryptographic hash for the previous block.

The other difference between blockchains and DLT systems is immutability. Blockchain does not allow alteration of data after recording it on the chain. This isn’t the case with DLT systems. Although some DLTs offer immutability, this feature does not apply to all distributed ledgers.

Blockchains are mostly permissionless and public. However, some are permissioned. This is different for DLTs. The permissioned blockchains are designed to provide high levels of security and privacy. They can be made permissionless where need arises.

The two systems have wide applications. However, blockchains are often used in applications like smart contracts and cryptocurrencies. DLTs, on the other hand, are mostly associated with healthcare, supply chain management, and voting systems.

Benefits of Distributed Ledger Technology

Distributed ledger technological solutions are important because they have the potential to change how companies, governments, and other entities record, store, and distribute information. Their value is demonstrated by the range of benefits they offer, which include:

1. Eliminating Fraud

There are no centralized points of control in distributed ledgers. This reduces their vulnerability to widespread system failures and enhances their resilience to cyberattacks. Some DLTs use cryptographic algorithms that make it impossible to forge or alter records. This feature makes DLT data trustworthy and reduces fraud risk.

2. Improving Efficiency

Distributed ledgers automate transactions and eliminate intermediaries. Since they facilitate automatic execution of transactions upon fulfillment of contract conditions, DLTs reduce human interaction in transactions. This streamlines organizational processes, increases efficiency, and reduces costs for organizations.

3. Immutability

Distributed ledgers allow users to make database entries without involving third-parties. Once records are entered into the ledgers, they cannot be altered. This means your records remain secure until the ledgers have been distributed.

4. Decentralization

DLT systems are highly decentralized. They store data across database networks in an accurate and consistent manner, which helps in reducing discrepancies and errors.

5. Greater Transparency

Distributed ledger technology enhances visibility of system operations for all users, which enhances transparency of transactions and data. With greater transparency, businesses, and governments enjoy stakeholder trust.

Limitations of Distributed Ledger Technology

Distributed ledgers have several limitations due to their infancy. These limitations include:

1. Complex Technology

Another limitation facing distributed ledgers is their complex technological nature. This complexity makes it challenging to maintain and implement. Businesses and governments that want to leverage DLT solutions must invest in specialized expertise. The technical complexity of DLTs also makes it challenging for developers to design new services and applications.

2. Lack of Regulatory Clarity

Regulation is among the major limitations of distributed ledger technologies. Across the world, governments struggle to regulate DLTs like blockchain. This lack of clarity in the regulatory environment causes confusion and uncertainty for business. Without clear regulation, distributed ledger solutions cannot reach their full potential.

3. Slow Adoption

Distributed ledgers can only transform business operations through widespread adoption. However, awareness of how these technologies work remains low. Additionally, most people hesitate to try new technologies, which further slows down their adoption rate.

4. The Interoperability Challenge

Most DLT systems run independently without communicating with each other. This makes it impossible for users to move information or assets from one system to the other. Although there are efforts to fix this operation issue. But it’ll take time before such a solution is developed.

Conclusion

Although the adoption of distributed ledgers by businesses and governments appears slow, the technology leaves a lasting impact on entities and industries that utilize it. The technology has the potential to change the way businesses operate and manage data. DLTs are becoming a necessity for modern enterprises and governments that need to prevent fraud, fix inefficiencies, and guarantee accuracy of supply chain and financial reporting data.

They improve efficiency and offer transparency and better security. However, these benefits are curtailed by the complexity of these technologies, unclear regulations, and slow adoption. As DLTs advance, these drawbacks will be addressed and the potential of these technologies realized.

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Hyperloop Technology: How It Can Revolutionize the Travel Industry?

Olivia Carter — Tue, 30 Jan 2024 14:20:31 +0000

The need for a fast, efficient ground transport system that connects cities and countries has been evident for a long time. The Hyperloop system promises to make this a reality by 2030. For over a decade, development of hyperloop technology has been a key topic of discussion in the transportation industry, with some companies commencing hyperloop technology tests. If commercialized, this transport system could have far-reaching economic and environmental benefits for passengers across the world.

Defining Hyperloop Technology

Hyperloop technology refers to a super-fast ground transport system that several companies are currently developing. This technology could see both cargo and passengers travel at ultra-high speeds inside floating pods either below or above ground. Electric propulsions and magnetic levitation tracks are used to move the pods through low-pressure tubes.

History of the Hyperloop

The idea of a vacuum tube transportation system has been around for at least two centuries. The earliest concept of a tunnel system was in 1799 when the idea of using air pressure to move goods via iron pipes was conceptualized.

This idea has developed over time as reflected in timeline below:

1844: A pneumatic railway station in London completed

1845: Proposal to construct a tube that propels trains at 70 miles per hour made but not implemented

1850s: Additional pneumatic railways constructed in London, Dublin, and Paris

1860s: An atmospheric railway known as Crystal Palace in South London constructed

1870s: The Beach Pneumatic Transit launched in New York City

1900s: Pneumatic Tubes adopted and used in key cities to transport mail and other
items/messages. Design of a vacuum-tube train system from New York to Boston

1910: Design of a train that would float on magnets within a vacuum tunnel developed

Early 2000s: Design of a pneumatic-maglev train with car-sized pods to travel in elevated tubes with completed

2010: Underground vacuum tube network to move food canisters, Foodtubes project unveiled in the UK

2013: A Hyperloop white paper published by Elon Musk. The design featured sealed pods whisking through vacuum tubes

2014: Hyperloop One is Launched

2016: Construction of a Hyperloop Test Track commenced in California

How Do Hyperloops Work?

A hyperloop system features three things- connecting movement hubs, a vacuum-tube network, and pods. Since hyperloops are designed to work in low-pressure environments, their energy efficiency is high due to the minimal aerodynamic drag.

Hyperloops differ from current travel options in several ways. Unlike conventional trains, hyperloop pods travel through near-vacuum tunnels or tubes. These tubes have little to no air to minimize friction. The absence of air in the tubes could cause hyperloop pods to move at speeds as high as 700 miles per hour. Unlike cars or trains, hyperloop pods don’t use wheels. They leverage magnetic levitation to float on air, which reduces friction and enhances their speed.

What is the Significance of Hyperloop Technology in the Travel Industry?

Hyperloop technologies will have a significant impact on the way passengers travel in the coming years. Here are 5 ways these technologies will change the way people travel:

1. Fast Movement of Passengers

When using conventional modes of travel like air and rail, passengers struggle with long waiting and travel times. Besides the actual travel time, they have to consider airport transfers, airport trekking, and long check-in queues when planning their trips.

Hyperloop will reduce travel time for passengers with their super-fast speeds. Their stations will be constructed in city centres. This means passengers won’t have to trek or use other means to access stations as they currently do with travel hubs like airports and rail stations. Hyperloop will utilize technology to facilitate fast loading and unloading of passengers, effectively reducing waiting time for passengers.

2. Better Travel Experiences for Passengers

Although passengers will only spend a short time in the travel pods, hyperloops are designed to provide passengers with positive travel experiences. Pod interiors feature comfortable, entertaining, and productive spaces to give passengers an office or living room feel throughout their journey.

3. Reducing the Cost of Travel

Proponents of hyperloop systems envision it as a more affordable and convenient mode of travel. The systems will have stations within city centers, which alleviates passenger costs and stress of accessing the cities.

4. Uninterrupted Travel

Hyperloops travel in near-vacuum tubes that protect them from extreme weather conditions like rain, snow, wind, ice, and fog. The construction of tubes were on pylons with adjustable dampers. In the event of an earthquake, the pylons adjust to new positions. These two aspects offer convenience to passengers, ensuring that their travel plans are not interrupted by extreme weather or earthquakes.

5. Reduced Exposure to Accidents

Compared to road, air, and rail travel, hyperloops travel at ultra-fast speeds, reducing the time that passengers spend on one journey. This reduction in journey duration significantly reduces passenger exposure to accident risks. Hyperloop pods travel in sealed tubes, which offers additional security against earthquakes and extreme weather.

Disadvantages of Hyperloop Systems

Hyperloop advancements have several downsides. The technology is still new and hasn’t been tested widely. It’ll take several years before hyperloops become a reality for passengers. Also, the risk factors associated with this transport system have not been analyzed fully. The technology is not designed to use existing infrastructure, which makes it extremely costly to set it up and launch.

Conclusion

Hyperloops are slowly gaining traction as tests begin around the world. The technology has been hailed as much safer than cars, faster than trains, and more environmentally friendly than aircraft. However, it’s still in the early stages of development and testing. Only time will tell whether the vision of revolutionizing the travel industry with this technology will be realized.

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How is Robotics Changing the EdTech Industry and Improving Learning?

Amy Watson — Thu, 18 Jan 2024 12:18:58 +0000

A few decades ago, robots were nothing more than fiction characters in science. This is no longer the case. As technology advances, robotics continues to push the envelope across different industries. The education industry is no different. Robotics in education has proven to be an invaluable resource for students, teachers, and parents.

Increasingly, robotics is used to enhance development of cognitive skills among students while empowering them with robotic and programming knowledge. This article explores educational robotics and unpacks the role it plays in improving learning.

What is Educational Robotics?

Educational robotics is a discipline that introduces students to the world of programming and robotics at a young age. Robotics in EdTech emphasizes practice rather than theory. Integrating robots in primary education means that students are provided with everything they need to build and program robots that can perform different tasks. In higher levels of education, advanced robots are used.

This education model is used to teach STEM (Science, Technology, Engineering, and Mathematics) education in schools.

Role of Robotics in Education

Robots are not just theories, they are already performing tasks in different industries. Robotics in education empowers students with requisite skills that are needed in a technological world. Besides helping in different industries, robots are innovative tools that help kids learn new concepts and acquire valuable skills through exciting recreational activities.

Since robotics is futuristic, robots stimulate curiosity. This encourages logical thinking and builds concentration in students. These skills prepare students for the world of work where automation and robotics are increasingly becoming prevalent.

What Types of Robots are Used in Education?

Robotics in education utilizes robots that are designed specifically for educational settings. Robots come in varying forms. Some are big and can interact socially with students. Others are small and programmable, students can code them. Robots that have been equipped with artificial intelligence are also used in the EdTech industry. AI allows such robots to respond to students in real-time and adapt to the learning environment.

There are four types of educational robots that are currently being used in classrooms today. Each comes with unique capabilities and features to support learning for varying age groups as follows:

Humanoid Robots

These are designed to mimic humans and are capable of performing different tasks. Humanoid robots help to teach robotic concepts like locomotion, balance, and motion.

Pre-built Robots

Unlike humanoid robots, pre-built robots are quite basic. They are fully programmed and easy-to-use robots designed for young children. Pre-built robots can be used to teach kids simple tasks like avoiding obstacles and following lines. They introduce children to foundational programming concepts.

Modular Robots

These are used to teach complex robotic concepts like dynamics, kinematics, and mechanical engineering. They utilize multiple modules that students can assemble into varying configurations.

Programmable Robots

These are used to teach students coding and robotic concepts like motors, sensors, and controllers. They have actuators and sensors to enable them to perform complex tasks. Students assemble and program them during learning.

How Robotics is Changing the EdTech Industry and Improving Learning

Robotics in EdTech is transforming how teachers teach and how students learn. Below are five ways this discipline is improving learning:

1. Supporting Interactive Learning

Educational robotics leverages interactive learning. Students work on robot projects together. This builds their communication, teamwork, and collaboration skills while helping them to appreciate individual strengths.

2. Making Education Accessible

Robots can be programmed to meet the individual needs of a child. This makes provision of special education accessible and easier. Through robotics children with special needs like autism, attention disorder, and other developmental challenges can focus and develop social and communication skills.

3. Generating Interest in STEM Subjects

The use of robots in the classroom builds student interest in STEM subjects and helps them see how those subjects apply in the real world.

4. Non-Judgmental Learning

The use of educational robotics in the classroom reduces judgment and embarrassment for students because, unlike humans, robots don’t judge or feel. Although their ability to act with intention or form opinions is low, robots have emotion recognition capabilities.

This enables them to provide non-judgmental outlets for emotional expression. This way, they can support children when they experience homesickness or cultural adjustment challenges.

5. Personalizing Learning

Robots help students and teachers overcome the one-size-fits-approach challenge. Since they are capable of adapting different teaching methods, they can be programmed to support students to learn or practice more depending on their learning styles and abilities. This personalized mode of learning allows students to get instructed in ways that resonate with their needs and preferences.

6. Higher Knowledge Retention

Educational robotics focuses more on practice than theory. It gives students global perspectives through virtual interactions, field trips, and exposure to issues in different parts of the world. These experiences help students to retain more knowledge than they would in conventional learning approaches.

What are the Benefits of Educational Robots?

Robotics in education offers numerous benefits for students, here are 3 major ones:

Promotes Hands-On Learning

Robotics allows students to learn by doing. Students are introduced to tech and science concepts in a practical way, empowering them with mechanical, electronic, and coding skills. This hands-on learning helps them understand theoretical concepts better.

Builds In-Demand Skills

Educational robots enable students to build skills like problem-solving, programming, and coding that are in demand in the job market in an engaging, fun way. Developing these skills early will help them succeed in their careers in future.

Prepares Students for the Workplace

Technology has become an integral part of the workplace. Robotics is already driving transformation in every sector. In the EdTech industry, robots give students a solid computational thinking and programming foundation that will enhance their understanding of emerging technologies in future.

Wrapping Up

Robotics in EdTech is changing the way students learn and retain knowledge rapidly. In the modern-day digital world, this approach can build STEM skills in students and adequately prepare them for future jobs. It can also expand opportunities for children with special needs and make education accessible to them based on their learning needs and styles.

In addition to providing technical skills, robotics in education also helps students develop a range of transferable skills like problem-solving, collaboration, teamwork, and logical thinking. These skills are what they need to succeed in life and the workplace.

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AI Advancements in 2024: What to Expect?

Emily Lawson — Thu, 04 Jan 2024 13:55:38 +0000

AI in 2024 has been predicted to be finer than what it was in 2023. ChatGPT, Bard, and Copilot got tremendous updates to ensure they were optimum and user-friendly. Many enterprises recognized the importance of AI and how it impacted their decision-making.

Moreover, tech giants invested heavily in AI startups to get ahead in the trend and keep up with the smooth functioning (Amazon to Compete in the AI Race With up to a $4 Billion Investment in Anthropic). However, governments across the globe paid serious attention to AI regulations to avoid exploitation(AI Regulation Meet: Top AI Firms to Visit the White House). So have we reached the top in the advancements in AI?

Before answering that question let’s see the AI trends and news that went viral in 2023.

2023 in Review

Starting from Pope’s image to Sam Altman getting fired from OpenAI, we have covered some of the biggest events that happened last year.

A Chicago man in March 2023 created an AI-generated image of Pope wearing a white puffer jacket using the AI image generator Midjourney, showcasing how powerful AI is in deceiving humans.
In March, Tech chiefs including Elon Musk and Steve Wozniak wrote an open letter requesting AI organizations to halt training for six months due to potential risks such as loss of civilization control, job destruction, and human annihilation.
Meta’s large language model, LLaMA, got leaked in the same month along with its weights, on 4Chan’s technology board and was available for download through torrents globally. This became a source of tools for the open-source community in the AI industry.
Since the launch of Bing Chat in February 2023, Microsoft kept bringing innovation. They introduced Copilot, a widespread application of AI. Microsoft integrated Copilot into Word, Teams, and Windows 11, automating tasks like image creation and meeting summarization, to highlight the capability of AI.
Reports suggested AI can take 300 million jobs if left in the dark. In addition to that, Hollywood authors went on strike over the use of AI in filmmaking. Moreover, writers in September filed a class action suit against AI organizations for using their works to teach their LLMs.
In November 2023, the OpenAI board fired CEO Sam Altman leading to resignations and chaos. However, Microsoft offered jobs to him and other employees who resigned. Altman was reinstated later and OpenAI got fresh board members.

5 Advancements To Look Forward in AI in 2024

AI advancements are continuous and we think more innovations are coming in AI in 2024. Let us take a look.

1. Businesses Will Incorporate AI Into More Products

In 2024, the growth of incorporating AI into products and services will accelerate. This is because of AI’s capability to enhance experience, decision-making, and automate tasks. It can drastically impact the data and analytics lifecycles. So most Big Data problems and data science projects will have efficiency.

AI in 2024 will be accessible for organizations as it will solve a complex problem of data quality checks with the help of augmented tools. With AI integration and automation, Business Intelligence tools will provide a more seamless and interactive experience, ensuring that users engage with data in a natural language interface.

2. Convergence of AI and IoT

When AI and IoT are infused into an organization, it brings scalability, security and privacy, synergism, and reliability. IoT is the network of physical devices, gadgets, sensors, appliances, and vehicles that are connected to the internet and can communicate with each other. Though it can collect a significant amount of data and analyze it, it also poses security threats.

This is why infusing IoT and AI in 2024 is ideal. AI can help IoT in processing and interpreting data with the help of techniques like Machine Learning, computer vision, natural language processing, and speech recognition. Moreover, AI can assist in creating new applications and services based on the data collected by IoT.

3. Combining AI and Cryptocurrency

Cryptocurrency is a type of digital currency designed to work as a medium of exchange through a computer network. It is not issued by a central authority like a government or bank but is based on a network of decentralized peer-to-peer transactions. In 2024, we will see AI and cryptocurrency combined which is known as AI Crypto.

It is paving new roads for users in the AI and crypto space. AI crypto will create a pattern of intelligence and systematic processes that can change various sectors and industries. With AI the transactions can be automated and users can have utmost security, without any third-party involvement.

4. A More Realistic and Higher Quality Generation

In 2023, we saw inclusivity and diversity in all sectors and industries but many AI organizations didn’t include them in their services. AI in 2024 will witness much more inclusivity and diversity. Most enterprises are trying to make it as realistic as possible for a higher user experience.

Transparency is another thing we can see in AI happening as many content creation and publishing websites use AI-generated content and don’t put a disclaimer for the same. This can be misleading and won’t provide accurate information to the people. So it is ideal that enterprises will practice diversity and transparency in 2024.

5. Enterprises Will Perform Responsible AI

In 2023, people around the world raised questions about AI harming students and employees. So many governments framed policies governing AI usage in 2023. It will be a noteworthy watch to see what changes will be made in AI in 2024 in these policies.

For enterprises, only the EU made AI Act and policies but by June 2024 two US states California and Colorado will adopt regulations addressing automated decision-making regarding consumer privacy. Enterprises will need to figure out the applicable laws and work according to them. While these regulations are for AI systems that are trained or collect personal information, both offer consumers the right to opt out of the use of these systems. So it will be significant to see enterprises navigate responsible AI.

On a Final Note

AI in 2024 will see some critical advancements and technological evolutions. In 2023, we didn’t reach the highest advancements but will reach new heights in 2024. It will increase productivity, efficiency, and scalability for people from all walks of life. Businesses have to adapt to many changes and keep bringing innovation to stay in the competition keeping the new AI regulations in mind. So the journey ahead may look rocky in the AI trends but it will make work, education, and other aspects simpler for users.

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Build Cyber Resilience Strategies for your Organization

Olivia Carter — Thu, 21 Dec 2023 11:13:48 +0000

In today’s highly interconnected world, organizations are constantly facing cyber threats.

Statistics from Marsh show that globally, 75% of businesses have experienced a cyber attack at one time or another. In quarter 3 of 2022, the rate of cyber-attacks grew by 28 percent– a strong pointer to the growing threat.

Cyber threats compromise organizational data, disrupt operations, and undermine the trust their clients have in the business. To mitigate these challenges, businesses must build a cyber resilience strategy. This means taking a more strategic approach in the way they navigate the dynamic threat landscape so they can recover from cyber-attacks quickly, if or when they occur.

In this article, we explore the concept and cyber resilience strategy your organization can adopt to strengthen its response to and recovery from cyber attacks.

But First, Let’s Define Cyber Resilience

Cyber resilience refers to the ability of an organization to foresee, respond, withstand, and recover from cyber threats while ensuring the integrity, confidentiality, and availability of its most vital information assets. It underscores the ability of a business to recover, adapt, and continue running in the event of cyber-attacks or incidents. With about 16,000 cyber-attacks (Source: Statista) being detected across the world between 2021 and 2022, having a solid strategy will help your organization recover quickly from a cyber attack and avert irreparable damages. The concept of cyber resilience transcends the conventional cybersecurity measures that focus primarily on cyber attack defense and prevention.

What’s a Cyber Resilience Plan?

A cyber resilience plan refers to a detailed strategy that highlights the critical measures your organization takes to identify, respond, and recover from cyber-attacks or threats. A cyber resilience strategy evaluates the cybersecurity context and aligns your business objectives, tolerance, risks, and regulatory requirements.

Compared to a resilience framework, a cyber resilience plan has a wider scope. It takes a strategic approach to building organizational resilience against cyber threats. By having a resilience strategy, your organization will be better prepared to deal proactively with cyber threats. This enables it to mitigate potential damage and ensure uninterrupted business operations.

10 Cyber Resilience Strategies for Your Organizations

The plans that organizations develop should highlight the various strategies they will implement to address the cyber threats. These cyber resilience strategy allow businesses to create the multiple layers of defense systems they need to detect and respond to cyber threats, address vulnerabilities, and recover swiftly from attacks. Below are 10 important strategies to help you build resilience in your business:

1. Craft a Cyber Resilience Framework

The first cyber resilience strategy on an organizational level is developing a solid cybersecurity framework. A framework identifies specific processes and actions an organization takes to maintain resilience. A good framework should indicate preventive measures, cyber threat detection capabilities, and the response protocols to be followed in the event of a threat.

It addresses a wide range of issues including business risk assessments, continuity plans, incident response plans, as well as continuous monitoring and evaluation of cyber threats. Some of the specific measures businesses include in their frameworks include antivirus, firewalls, and systems for detecting intrusion. Others are penetration tests and vulnerability assessments to identify and fix system weaknesses.

2. Implement Controls in Data Access and Management

When it comes to preventing unauthorized access to organizational data, establishing and implementing strict controls is critical. Limit access privileges and give access only to staff who are authorized to handle specific data. User permissions should be reviewed and updated regularly to ensure that access rights are based on individual responsibilities and roles. You should also implement strong password policies across the organization and use multi-factor authentication to improve data security.

3. Prioritize Cybersecurity Education/Training

Another cyber resilience strategy for an organization is educating employees. When it comes to cybersecurity, the actions that people take pose the highest cybersecurity threat. Educating your staff about the best data protection practices like identification of phishing attempts, use of strong passwords, and safe browsing is vital to curbing cyber threats. Schedule training sessions regularly to keep your employees updated on emerging cyber threats and equip them with the skills they need to strengthen resilience in your organization.

4. Execute Patch Management Procedures

Cybercriminals can use security loopholes in outdated software to gain unauthorized access to your systems. To prevent this, ensure the applications, software, and operating systems in your organization are updated with the latest security updates and patches. Reduce system vulnerabilities by implementing a patch management process to run timely updates across your organization’s IT infrastructure.

5. Gather Cyber Threat Intelligence

Another cyber resilience strategy building in your business is to keep abreast of emerging threats by gathering information and intelligence on cybersecurity. An excellent way to gather these insights and intelligence is to collaborate with government departments, industry peers, and cybersecurity communities. The collective knowledge shared in these interactions can help you improve your organization’s cyber resilience plan and framework.

6. Use Secure Backup Solutions

Regular backup of essential systems and data in cloud platforms or offsite locations is another strategy for building organizational resilience to cyber-attacks. Opt for secure backup solutions and test them periodically. The backups should also be reliable to minimize downtimes. Consider accessibility as well. Your backup solution should be easy to access to allow for quick data recovery and business continuity following a cyber incident.

7. Run Cyber Attack Simulations

Another way to build organizational cyber resilience to cyber-attacks is to simulate cyber-attack incidents. This involves taking employees through the different steps they need to take in the event of a cyber attack. Simulations should cover the entire response process, including identifying threats, investigating their cause, and reducing their impact on the business.

8. Monitor Cyber Threats Regularly

Regular monitoring of cyber threats helps in early detection and proactive response to thwart attack attempts. You can identify potential threats by deploying advanced threat monitoring detection tools. Identify anomalies or suspicious behavior in your system by keeping tabs on your network’s traffic, user activities, and systems logs regularly. Consider investing in a security information and event management system (SIEM) for your organization. A SIEM system gives you a comprehensive view of your network so you can detect and respond to cyber incidents promptly.

9. Have an Incident Response Plan

Cyber resilience recognizes the reality of cyber threats and ensures that organizations are prepared to respond in the event attacks occur. An important aspect of this preparation is the development of incident response plans that clearly show steps that should be taken when a threat materializes.

Set up a team to respond to incidents and assign each member specific roles and responsibilities. Establish clear communication channels for the response team for easy coordination. Your incident response plan should be tested and updated frequently to ensure that it remains effective and well-aligned to the evolving nature of cyber threats.

10. Assess Systems for Vulnerabilities

Cybercriminals exploit system vulnerabilities to launch attacks. An important part of strengthening your organization’s resilience is understanding the weaknesses in your systems and addressing them early. Assessing your system regularly is the best way to identify and fix system vulnerabilities. To do this, hire a cybersecurity professional to inspect your system and provide a comprehensive report. Alternatively, invest in vulnerability scanning tools to help with the assessment.

Conclusion

In today’s digital environment, cyber resilience strategy cannot be overlooked. With cyber-attacks becoming more prevalent and sophisticated, organizations must adopt a more strategic approach to avoid disruptions, data breaches, and revenue losses. Building threat resilience can reduce the impact of cyber-attacks on your business significantly. Implement the 10 strategies discussed above to safeguard your organization’s competitive advantage and ensure operations continue smoothly in case an attack occurs.

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Exploring 5G Technology: 7 Innovative Use Cases

Olivia Carter — Wed, 29 Nov 2023 15:10:50 +0000

The launch of fifth-generation mobile technology (5G) has brought a new era of connectivity that continues to change the way businesses operate and how people live.

The shift from 3G to 4G was about faster connections, that’s not the case with 5G. The latter combines speed with low latency, higher reach, reliability, flexibility, and responsiveness, offering the mix necessary to support mission-critical applications.

Across the world, businesses are positive about the potential of 5G technology. Existing studies show that globally, 80% of companies believe that 5G networks will impact their operations significantly.

In this article, we explore 7 innovative use cases of 5G technology you need to know.

But first, What’s the Difference Between 4G and 5G?

5G technology is the latest wireless network that improves on 4G technology. The main difference between 4G and 5G is in radio frequencies. 4G uses less than 6GHz while 5G uses 30GHz or more. This high radio frequency gives 5G networks higher capacity and faster speeds.

The other major difference between the two networks is in wavelengths. Compared to 4G, 5G technology uses shorter wavelengths. The shorter wavelength means a single 5G base station can hold a big number of directional antennas. This feature alone allows 5G networks to support 1000+ more devices per meter than what 4G can support.

What are 5G Technology Use Cases?

Here are 7 innovative use cases of 5G wireless networks:

1. Industry-based Internet of Things (IIoT)

Manufacturing firms were among the first businesses to implement private 5G networks, and they are reaping huge benefits. With the high cost of machine replacement, industries can’t afford downtimes. Manufacturers use Internet of Things (IoT) sensors to monitor machine performance and get alerts on maintenance issues that may be coming up. IIoT sensors can only work in the presence of wireless connections.

5G technology allows industries to set up the wireless network they need to support these sensors. By offering low latency and high capacity, 5G provides reliable support for thousands of robotic machines and IIoT sensors in highly complex industrial environments. Strategic planning of wireless networks allows industries to ensure that service levels for plants are always met and that machines remain free of dead zones. Other leading industry use cases for 5G technology include performance and product monitoring and connection of legacy machines.

2. Augmented Reality in Sports

Another innovative 5G use case is in the streaming and viewing of sports events. Connectivity has become an integral part of sporting events. Fans not only want to watch sports events, they also want to check video highlights, get details about events, and share content on social media.

4G and Wi-Fi networks don’t have the connectivity capacity to keep densely populated spaces like stadiums connected. The 5G network is changing this experience. With this network, sports event organizers can give fans access to real-time data insights. For instance, fans can watch how fast a player is running by leveraging augmented reality.

3. Supporting Healthcare Operations

Healthcare is another area of 5G-enabled innovation. Hospitals are highly complex spaces featuring numerous machines, applications, patient sensors, and monitoring devices. All these equipment operate in huge spaces. Medical devices must always be secure and accessible. Patient information must also be accessible to the right staff and confidential.

IoT sensors are used to monitor the location and performance of critical IT infrastructure like ventilators, insulin pumps, EKG machines and many others. These sensors ensure proper maintenance and detect repair needs in these equipment. 5G technology provides reliable connection in hospitals to support the running and maintenance of all devices and machines.

Other use cases of 5G wireless communication in the healthcare sector include inventory management, automatic creation of work orders and secure service for patients and staff.

4. Outdoor and Indoor Entertainment

Outdoor venues and theme parks need a reliable network to support the numerous devices deployed to give users and visitors positive entertainment experiences. The speed, wide reach, and reliability of 5G makes it ideal for this purpose.

Since 5G has a huge capacity to support network devices, entertainment companies can place cell towers across parks to keep their staff and visitors connected without overwhelming the network. Other 5G technology applications in the entertainment industry include proactive maintenance of equipment through IoT sensors and providing guests with reliable and secure connections via neutral host services.

5. Shipping and Transport Management

Another innovative 5G technology use case is in shipping and transportation. In the shipping industry, huge warehouses must be connected for managers to have real-time updates. 5G is used to support IoT sensors fitted on shipping containers and pallets to share departure and arrival data automatically. This data helps businesses to track performance and accurately predict arrival times for new shipments .

In public and transport sectors, 5G supports fleet tracking and provides companies with real-time data to help them understand utilization and efficiency of vehicles. Additional 5G use cases in shipping and transportation include inventory management and automated time-stamping on shipments.

6. Driverless Vehicles

Autonomous vehicles rely on data to make changes within very little time. The 5G network can be used to support the operation of remotely operated vehicles by providing real-time data on traffic, weather, and safety updates. Although these cars are not widespread, 5G’s high capacity, ultra-low latency, and wide coverage is increasingly being leveraged to support their functionality by sharing data with each other to reduce congestion, prevent accidents, and improve safety. Increasingly, vehicle manufacturers are updating their patch security, and firmware, and upgrading vehicle features to utilize 5G technology.

7. Building Smart Cities

The concept of smart cities may sound far-fetched, but it’s currently happening. Already, some city governments are leveraging 5G technology to keep tabs on public utilities, give better services, and proactively monitor infrastructure. Innovative 5G use cases in smart cities include monitoring garbage trucks and dumpsters to determine waste levels and identify areas with high accumulation. Other cities use 5G networks to track highway congestion, conduct video surveillance, and provide secure internet for city residents.

Final Thoughts

The 5G mobile network is designed for high-speed transmission, higher network capacity and super-low latency. These features give high potential to support use cases that have not been explored before. From supporting Internet of Things devices in healthcare facilities, industries, and shipping facilities to facilitating real-time data access for autonomous vehicles, 5G is set to change the way businesses operate and how people live.

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