1. Types of Artificial Intelligence

Although there are several criteria for differentiating between the types of Artificial Intelligence, the most common one divides the systems according to the degree to which they perform tasks similar to a human.

Following this criterion, four types of Artificial Intelligence appear :

2.1. Reactive Systems

These are the most basic systems, and they can interpret information and make decisions based on forecasts, choosing the optimal option. However, reactive systems do not have “memory,” They do not take into account data or experiences from the past that can serve as a guide for making decisions in the present. A typical example of this type of Artificial Intelligence is the automatic programs in video games when games are played ‘against the machine.’

2.2. Limited Memory

Memory-limited systems advance over the first category because they can use historical data to make decisions. An example is autonomous cars that, in addition to observing the current context (for example, possible obstacles or the direction and speed of the car), also retain information “learned” in the past (for example, road safety regulations or even routes to take). In this way, the system takes all this information into account when making a decision.

However, memory-limited systems” forget this information has passed for a while, and they are not able to incorporate experience that helps them in making decisions. In other words, their “memory” depends on the “external” data that humans feed into them.

23. Theory Of Mind

The following type of Artificial Intelligence is not yet fully developed, although progress is being made. These are systems capable of creating representations of the world without human input. In this way, they can understand the thoughts, behaviors, and emotions of the agents that surround them (humans and objects). From this understanding, they are also able to interact with them appropriately. An example of this type of Artificial Intelligence is a chatbot capable of understanding a user’s intention or emotions you are experiencing (anger, frustration.) and reacting to help you more effectively.

2.4. Self-Awareness

The latest development in the types of Artificial Intelligence is still a project towards which it is moving forward. In this case, it is about the systems capable of generating representations about themselves. Thus, their interactions with the environment and their surroundings will be even more efficient. For example, this type of system will be able to detect what information is missing to make a decision and provide the means to achieve it.

2. Tips To Apply Artificial Intelligence To Your Business

Experts predict that the development of the different types of Artificial Intelligence will entail extraordinary improvements in productivity and the quality of products and services. A study published in Statista confirmed that companies also think this: most respondents believe that Artificial Intelligence will transform their organization in the next three years.

But the application of the different types of Artificial Intelligence is not just a question of the future: companies are already using this possibility at various levels, highlighting its use in professional digital marketing strategies. Two of the most important uses in this field include:

• Make better data-driven sales and marketing decisions. For example, Customer Relationship Management (CRM) systems that incorporate AI are already making recommendations to tailor the right decisions to what customers want. The idea is thus to let the system collect and analyze data and then develop action proposals based on that information.
• In this sense, and although the search for Big Data has dominated recent years, the consulting firm Gartner predicts a paradigm shift towards Small Data (smaller amounts of data but more useful) and Wide Data (data from a wide variety of sources): By 2025, 70% of organizations will only be interested in this type of data.
• Use of chatbots. Although they continue to evolve in their capabilities, chatbots with Artificial Intelligence are already here. By using these tools, companies are managing to improve the customer experience and free the human team from repetitive tasks.

Also Read: What Goodies To Choose To Promote Your High Tech Business

The post What Are The Types Of Artificial Intelligence And How Are They Applied appeared first on Trends Tech Blog.

AI is already part of the day today. This technology generates the recommendations we receive when using, for example, audiovisual platforms or when buying in online stores; Scientific bodies use it to advance their studies, and even the NBA relies on it to measure the qualities of the players offer personalized broadcasts to its fans.

Today, AI can be present in any company that wants to make the most of and maximize the value of the huge amount of data that comes from both internal and external sources. Deploying Artificial Intelligence solutions is the best way to stop seeing Big Data as a problem rather than a generator of opportunities.

Keys To Supporting AI Applications And Workloads

To implement an Artificial Intelligence project successfully, it is necessary to audit and update the IT infrastructure. Traditional DataCenters do not respond to the demands of an environment where the volume of data is continually scaling and must move agilely between systems.

AI demands data-intensive workloads that demand specific storage, networking, computing, preparation/cleaning, governance, access, and security. Thus, it is necessary to clearly define where the data will be stored, how it will be moved, how it will be processed and how it must be prepared so that it is suitable.

Optimizing corporate IT resources takes considerable effort and requires in-depth knowledge. Few companies can carry out the planning, implementation and connection of all the right systems in the minimum time and with the maximum efficiency to apply the benefits of AI in the business as soon as possible.

Partnering with experts who have the appropriate training to lead this IT modernization, such as the professionals, ensures the deployment and maintenance to support any AI initiative: Machine Learning, Deep Learning, and natural language processing.

What Storage Do I Need For Artificial Intelligence

Storage is a priority resource in any AI project. It has to guarantee its robustness in a scenario of continuous data growth and its agility to provide it to the appropriate systems. When choosing the best storage for AI, you must consider its scalable capacity, IOPS values ​​to determine latencies and throughputs, and BigData management capabilities.

The choice of storage systems will depend on how the AI ​​applications are used. In those scenarios in which it is necessary to make decisions in real-time, flash storage systems are the most demanded. But some companies choose to analyze the data after its processing without so much haste, so other options are opened, including services in the Cloud.

What is necessary is to know where the data resides and assign them to systems with one or other characteristics depending on the use that the Artificial Intelligence solutions will make of them. AI itself is one of the most advanced storage resources to distribute data in different locations based on its frequency of use and value.

What Kinds Of Networks Are Needed For AI

The quality of communications is critical to guarantee the flow of algorithms and data that feed the different Artificial Intelligence technologies. For this reason, in IT architectures focused on AI, everything that provides high bandwidth and low latency must be prioritized. And here, the networks are fundamental.

The high exchange of large volumes of data between different systems requires advanced corporate IT network design. In this scenario, it is best to opt for solutions that automate the management of IT networks. The network defined by software SDN (Software Defined Network) allows network requests to anticipate, detect threats and act in real-time.

Processing, Data Cleaning And Security

Traditional CPU-based computing is not enough to apply the various varieties of Artificial Intelligence, and it needs to be accelerated by GPUs (Graphics Processing Units). IT vendors from both fields have come together to provide AI-oriented equipment capable of processing large volumes of data in a scalable and energy-efficient way.

But no matter how much computing, storage and networks are improved, if the data you work with does not have quality, it will be impossible to benefit from AI because the results will not be reliable. Therefore, before optimizing these resources, it is mandatory to prepare the data eliminating duplications, inconsistencies, outdated, etc. For this, solutions must be implemented that automate the cleaning of data based on rules and algorithms.

At the endpoint of a plan to implement AI in the company, the safe and efficient delivery of data must always be placed. In other words, they are guaranteeing their accessibility through any device to be available whenever they are needed. The management solutions, identity and access, and encryption tools data secure protected and controlled deliveries.

Also Read: What Impact Can Integrating A Visual Assistance Solution Into A CRM

The post Update IT Infrastructure For AI What Resources Must Be Optimized appeared first on Trends Tech Blog.

Today, there’s a growing tech market before us and tech giants are in search of individuals, who can make the most out of their roles as Artificial Intelligence experts. You don’t necessarily need to have software skills to learn Artificial Intelligence, but if you can take out your time to learn the basics of mathematics, statistics, programming languages, Artificial Intelligence can be a good option for you to work on, whether as a passion or a career, as always.

In general, anyone who is interested in the field of Artificial Intelligence can start learning artificial intelligence from top universities. But, here’s the tricky part of it.

One should have these below qualifications to start with the AI program:

• Bachelors Degree
• Strong knowledge of Mathematics
• Good command over programming languages
• Good Analytical Skills
• Ability to understand complex algorithms
• Basic knowledge of Statistics and modeling

Today, almost every Artificial Intelligence is anyway related to computer programming language/software language, whether it’s R, MATLAB, Python, and also, it requires you to have some basic knowledge of applied mathematics, which includes multivariable calculus, linear algebra, probability, and statistics. So, learning these basic technologies from free courses such as Great Learning Academy, YouTube channels might help you to understand the basic requirements for artificial intelligence.

But, to be on the bitter side Artificial Intelligence is not a cup of tea for anyone. You will have to devote your time, to learn the prerequisites like a programming language, mathematics to get the best out of your Artificial Intelligence learning experience.

In the meantime, look at some excellent resources to help you get started:

1. Coursera

Coursera is a well-off known site for online free education, and yes it does so. It provides plenty of free-ed courses to you, no matter your field. Whether you are a tech enthusiast, or a person who loves psychology, or maybe both, Coursera has everything for you, if you have that fire to learn. You can get here the AI-ML courses from top-notch sources.

2. PG program In Artificial Intelligence And Machine Learning -Great Learning

This AIML course is offered by Great Learning in collaboration with TexasMcCombs provides both an Online and weekend classroom program for 12 months. The curriculum and learning content has been designed by faculty from Great Lakes and therefore the University of Texas at Austin-McCombs.

3. edX

edX is again, one of the top online ed platforms where you are going to find plenty of tech courses. It offers paid as well as some courses at no charges. For learning Artificial Intelligence, here you can learn from the best and be the best because here you are going to find the best of AI-ML courses and certifications from Harvard University, IBM, etc.

4. Udemy

Udemy is a platform where you are going to access some of the favorite courses from the AI and ML courses, including making your personal AI for real-world applications. The sole thing which will stop you from accessing a number of these courses is money. Udemy provides paid courses, and they are worth it. For those of you who are thinking of a what-if case, the good news is that you get a 30-day money-back guarantee, in case you are unsatisfied with what you got. Sounds fair, right?

5. MIT OpenCourseWare

A great place for quality learning, MIT OpenCourseWare is a place for tech geeks as well. Herein, you can get the AI certification in a featured tap, which makes it a favorite for learners.

How To Start With AI

There’s no surprise if you experience certain difficulties in learning AI . If you grind to a halt , we propose trying to find an answer on the Good Learning Artificial Intelligence course to reinforce your skill. It’s also important to know what to specialize in and what to try to to first.

1. Pick a topic you are interested in
2. Find a quick solution
3. Improve your simple solution
4. Share your solution
5. Repeat steps 1-4 for different problems
6. Use Artificial Intelligence professionally

Conclusion

The basic understanding of AI becomes more valuable in any area of business and profession. Thanks to various online courses, which are helping you to upskill your domain knowledge at your fingertip. Even if you’re from a non-IT background, you’ll learn AI from home and begin applying your knowledge in creating simple AI solutions and making first steps towards your new profession.

Also Read: How To Know If You Need A Dedicated Server For Your eCommerce Site

The post Who Can Learn Artificial Intelligence? appeared first on Trends Tech Blog.

The following paragraphs allow you to learn about the advantages of artificial intelligence.

It Allows You To Do Advanced Searches

By using a specific platform or a B2B search engine, you can obtain relevant information that can be useful to you in your work. This platform uses artificial intelligence to give you quick access to the most difficult to find content. This kind of research can be done securely. The intelligent search that this kind of platform offers can be a very good solution for companies specializing in data.

The link between artificial intelligence, the Cloud, and the IoT continues to develop on the internet. And as companies that are present online compete, this competitiveness must go through data analyses in real-time. It is thanks to the power of these tools that information can be both fast and accurate. Some platforms available online have the main goal to offer you different tools set up with artificial intelligence. These allow you to set up intelligent applications with essential data and information stored in the Cloud.

It Makes Everyday And Professional Tasks Easier

On the internet, there are different AI applications. These are present to allow you to make various daily tasks easy. These tools are common nowadays and can save you a lot of time daily. Currently, everything can be connected, and everything can become smart. Indeed, whether you want to perform data research or you need to see your programs on your Outlook calendar, you can use artificial intelligence.

This type of intelligence can also help you perform better. Indeed, some companies carry out videoconference meetings with employees who are in rather distant cities. It is also possible to make tasks easier with smart machines. This can enable all businesses to increase their productivity. It is important to know that companies in different industries can use artificial intelligence to move their business forward. In short, all the elements that can be used today can be based on artificial intelligence. Therefore, the latter is part of the daily life of humans and companies wishing to develop and follow technology.

Also Read: How To Enhance The User Experience By Implementing Sticky Element

The post What Are The Advantages Of Artificial Intelligence appeared first on Trends Tech Blog.

A marketing channel may work great for one type of business and bad for another type. That’s why you have to test them out and choose the right one for you. The most interesting thing yet is that all of these platforms are developed with the use of Artificial Intelligence (or AI).

If you’re looking for a short-time solution, then Ads are the right answer for you. They’re fast and efficient, the conversion rate is decent and it can bring you lots of revenue. For this, you have to call the marketing experts who specialize in Facebook, Instagram, LinkedIn, Pinterest or Google Ads. Those are the most popular channels. However, as we said before, Facebook Ads may not work for your industry at all so don’t be disappointed if the results don’t meet your expectations.

For the long-run solutions, we recommend getting organic (non-paid) traffic. This implies social media traffic (unpaid social media traffic) and organic Google traffic. The first one involves posting high-quality content, content which your followers can’t help sharing. As for the SEO part, there are many factors you should take into consideration and apply before you can even begin to think of ranking on any search engine.

The first step to having success with Internet Marketing is to have a website. You should get a good hosting provider right from the start and choose a domain name, which users will recognize and search for later. As for the hosting providers, there are tons of great companies out there which supply top quality services, for instance , GoDaddy.  Once you’ve got these two steps found out , you’ll begin creating your site.

We recommend you choosing WordPress for the construction of your dream, because it is simple to use and you can do it yourself. The most used builder is Elementor, because of its ease to use. There are many addons for Elementor, but be careful which ones you choose to install, because many of them can break your site.

Then you should perform an audit for your site to see what errors you have on it & solve them. Remember that your users’ experience is the most crucial part of your SEO process so keep this in mind when you solve the errors. “Our client, our lord”.

Even in PPC they take into consideration this and they take it very seriously. That’s why PPC campaigns have a quality score component which focuses on your landing page’s experience and effectiveness. As Placebo would “say”, “without users I’m nothing”.

In conclusion, Internet Marketing can incredibly speed up your journey of success. If you want short-time solutions, you can go for the PPC strategies, but these tend to be a little pricey. Otherwise, definitely hire an SEO agency, which is more beneficial in the long run. Also remember that AI is the one that made it possible for Internet Marketers to have a job of this kind. Now that you know more about Internet Marketing, you can start your AI journey and deep learning training with a gpu rent online service!

Also Read: Elegant And Reliable Tissot Watches For Different Personality

The post Which Is The Best Marketing Strategy appeared first on Trends Tech Blog.

It’s used in everything, from AI chatbots on social media to Google search page results, even to what data we see on our social media profiles; it’s all chosen and recommended to us by an AI trying to give us what we want. However, with the use of this technology, there are threats and dangers that begin to arise.

Things like physical human safety when working with machinery or using tools like self-driving cars. Privacy and data protection are huge when you have an AI having access to literally millions of private accounts, with little human interaction. So when things do go wrong, or leaks happen, who is to blame?

Who Is Legally Responsible?

It’s shockingly true, and perhaps obvious to some that the current legal frameworks of our global societies are not cut out for dealing with the complexities of AI. This means that as we progress into the future, governments and officials need to figure out what they’re doing to do and how AI is going to be regulated, and they need to do it fast.

So far, parliaments, especially those in Europe, have broken down what is essential to think about into six main categories, and these apply to both AI systems and smart robots. These are;

• Ethics
• Liability
• Connectivity of intellectual property
• Education and employment
• Coordination and oversight
• Safety and security

So, what do we mean by a ‘legal personality’? Well, as lawmanaging explains, if you go into a court of law because you’ve committed a crime, or at least you’ve been accused of committing a crime, you have a legal personality as a human being, which entitles you to rights and kinds of treatment.

For example, if you’re a US citizen, then you have a US-legal personality, which entitles you to the rights of a US citizen, as defined by law. However, if you’re a US citizen, but you’re in Russia, Europe, Australia, and so on, then you’ll have different rights to go by.

So Should AI Have It’s Own?

While it’s true that humans are creating AI, it’s just as true that nobody really knows how it works. If something goes wrong, should the designers and coders be held accountable for something they don’t really understand? Should the AI be charged for doing something it wasn’t supposed to or for breaking the law? How would such an AI be punished or penalized? And here lies the problem.

Conclusion

An AI cannot, as of yet, be penalized or punished as a criminal would. Only humans can be. So instead, the responsibility of these systems need to be in the hands of the company’s and organizations who are using them. When contracts are made between humans and companies using AI, it’s the humans that need to be held accountable for what happens.

Also Read: What Do You Need To Know About IoT As A PCB Designer

The post Should Artificial Intelligence Be Awarded Its Own Legal Personality ? appeared first on Trends Tech Blog.

Software Features And Ergonomics

To choose an intervention report software, it is essential to take into account its practical functions. Indeed, this software data much characterizes its capabilities and performance. With ideal and well-developed software, you undoubtedly enjoy better benefits. Thus, a useful intervention management software must have given functionalities. These include:

• Planning
• Invoicing
• Reporting
• Stock Management

Also, your choice must take into account the ergonomics on each feature. Given the individual specific needs of your company, you will also have to take into consideration the supports available on the software.

Artificial Intelligence

An intervention management software generally allows you to save time on your various operations. However, for software to perform this function properly, it must necessarily use artificial intelligence and have automation capabilities. This is the condition that will allow the software to process data and business processes. Therefore, you must ensure that the work order reporting software you choose can handle all of the schedules. Whether the programs are constrained or preventive, the software must be able to manage them without any exceptions.

Is The Software An API

To benefit from the best performance of such software, it must necessarily be integrated into the computer system already available. Thus, the software auditor must have APIs, web services and other useful connectors available. The API is an English acronym which means “Application Programming Interface”.

APIs represent a set of definitions and protocols that support the design and integration of application software. Thus, if your intervention report software is an API, you will be able to benefit from a good programming interface. In summary, the API embodies a salient point in the process of choosing your software.

Intuitive Planning

Route planning is a crucial point for any reliable service report software. If some companies continue to use Excel spreadsheets, others wanting to be modern and efficient opt ​​for intervention management software. Indeed, the latter is more efficient, given the continually growing workforce of interventions and technicians.

Thanks to this type of software, it is possible to optimize technicians schedules. Moreover, a good intervention report software must be able to provide a very good cartographic visualization of the technicians rounds. Thanks to this parameter, you will be able to perceive at a glance the entire route carried out by the technicians. Besides, the cartographic mode simplifies emergency management.

The Managing Notifications

The call management software creates absolute ease in the process of customer relationship management. Indeed, it allows the operations manager to send a notification to customers by email or SMS instantly. These are used in particular to brief on the level of execution of each intervention.

Also Read: Ethical Hacking: Legality, Stages And Benefit

The post Important Points For Choosing An Intervention Report Software appeared first on Trends Tech Blog.

Recently an article published on the website of the World Health Organization, WHO acknowledges that Artificial Intelligence (AI) is used more and more in healthcare and adds that it promises greater efficiency and more free time for professionals so that they can focus more on the human side of care, including fostering relationships of trust and treating patients with empathy and compassion.

The development of AI has placed it at the center of healthcare digitization. This technology has enabled health professionals to be trained, to involve patients, to transform information processing and to optimize clinical and operational efficiency. In short, it is helping to improve health care and the lives of patients.

The potential of AI is undeniable and has excellent potential for growth and integration in healthcare. The situation generated by the current health crisis has also contributed to its development. Among the advantages of Artificial Intelligence, are the improvement of results for patients, the reduction of the cost of treatments and the elimination of unnecessary hospital processes, say its defenders.

Confidence-inspiring tools the celebration of the World Digital Event, according to the E-Health Report, has shown that trust, transparency and attention to the human factor are some of the keys to the development of AI. In this sense, one of the participants in the debate thinks that these technologies have to inspire confidence in doctors to use them, as well as the data they offer.

This paradigm shift that AI is promoting requires the commitment of all the actors involved: doctors, patients, IT technicians and health personnel. Numerous experiences in the United States are demonstrating the challenges and advantages of AI in automating healthcare processes: digitization of clinical documentation, reduction of errors among healthcare professionals, diagnosis of diseases through algorithms or automation of healthcare processes are just some of the opportunities of AI.

Also Read: Benefits Of Enacting Customer Queuing Management Systems

The post Artificial Intelligence Drives Digitization In The Health Sector appeared first on Trends Tech Blog.

Without An Effective Big Data Strategy There Is Neither Analytics Nor Artificial Intelligence

The upgrade of the IT infrastructure is needed to access structured data and unstructured data. It is no longer enough to consult the data of corporate business solutions, and now it is necessary to incorporate the flow from emails, photos or videos to chat conversations, social media publications. The problem is that this new scenario demands greater capacities in three essential IT resources: storage, computing and network.

Only with the modernization of the data center focused on Big Data will it allow decision-makers to have a wide range of data to combine in their analytical solutions to get the most right. Moreover, without an IT restructuring, it will be impossible to apply Artificial Intelligence and easily access automated proposals with which to make decisions in real-time that allow everything from customer loyalty or discover new business opportunities, to avoid risks or optimize processes.

It is necessary to have an agile, flexible and scalable IT architecture to avoid bottlenecks in the delivery of the information requested by users, and at the same time capable of adapting to changing business requirements, aligning with market trends. All this without incurring in continuous and excessive costs.

Choosing The Best It Resources For Big Data

Mass data processing demand robust and efficient systems. IT vendors offer multiple valid options, but their choice is difficult without an internal technology team with sufficient knowledge and expertise. Trusting the process of consulting and deployment in Orbit Consulting Group simplifies this task and allows any company to have a Big Data & Analytics successful strategy.

Many organizations rely on IT infrastructure services in public Cloud to establish their Big Data IT architecture, taking advantage of its ease of scaling and avoiding large investments in on-premises solutions and complexities in deployment. But directing Big Data only to the Cloud is not a magic solution to meet your needs. The cloud environment has its limitations, as discussed below.

Public Cloud Issues For Big Data

The first stumbling block is that 100% compliance with all data privacy and confidentiality requirements required by both sectoral and general GDPR- type regulations is practically impossible in public clouds. Suppliers are the ones who set the rules, and it is difficult for them to fully adjust to the particularities of each company (SLAs, SLOs.).

On the other hand, the search for specific plans that adapt to existing budgets and the changing needs of the business and departments leads to the contracting of multiple cloud services from different providers. They are multi-cloud environments. But managing multi-cloud infrastructures is quite complex. Harmonizing each of the services so that corporate IT acts as a whole, securing it and, at the same time, containing costs so that they do not skyrocket difficult.

Deploy Hybrid Environments For Big Data And Analytics

This scenario is causing the majority to opt for Big Data strategies in hybrid IT environments. The combination of private Cloud and public Cloud makes it possible to rationalize the use of resources based on their criticality and the type of data being processed, placing in physical those instances of greater value that require greater protection, and overflowing in the public Cloud what is needed as a compliment.

Nobody is aware that managing and monitoring the Big Data infrastructure requires enough knowledge and experience in IT systems to balance teams according to workloads, seeking a continuous and agile flow between resources on-premises and in the Cloud. 

Also Read: Best Apps For Voice Chat On Android Auto

The post Implement An Efficient And Profitable Big Data Infrastructure appeared first on Trends Tech Blog.

Currently building the fifth generation of mobile communications, research is already working on optimizing it. The great advantages of 5G are the high frequencies and the associated high transmission rates, which ensure an almost latency-free connection and fast data exchange. However, the high frequencies are accompanied by a directional system that usually requires a line-of-sight, or LOS for short: transmitters and receivers must see each other. But the principle of the LOS connection could lead to connection problems, especially in urban and very densely built-up areas.

One of the problems that lead to these connection problems in local 5G networks is the wiping effect. This effect occurs when a signal is transmitted via a line of sight and at the same time copied via reflections. The copy overlay the signal from the line of sight and delete it. The result: the signal does not arrive at the receiver. This multi path propagation via a non-line connection (non-line-of-sight, NLOS for short) remains a problem with 5G, just like with its predecessor 4G. For this reason, one of the main goals of ARIADNE is the development of new concepts that better master these LOS and NLOS scenarios and massively increase the reliability of mobile phone connections.

In the recently launched EU project with the full title “Artificial Intelligence Aided D-band Network for 5G Long Term Evolution”, eleven partners from five countries are researching how the use of high-frequency bands and artificial intelligence can lead to an advanced system architecture for Beyond 5G Let develop.

Greater Efficiency And Reliability of 5G

The aim is to develop energy-efficient and reliable mobile communications based on frequencies in the D band (130-174.8 GHz). Since the D-Band has an aggregate bandwidth of more than 30 GHz, it is ideal for fast data traffic. However, this newly used band is divided into several sub-bands and is therefore not contiguous, which necessitates an adaptation of the radio system architecture used previously and the corresponding network control.

In ARIADNE, the combination of a new high-frequency radio architecture and a new network processing concept based on artificial intelligence is intended to create an intelligent communication system “Beyond 5G”, that is, as a further development of 5G. By 2022, the project consortium wants to implement and demonstrate a radio link with extremely high data rates in the 100 GBit / s range with almost zero latency.

ARIADNE is based on three major research areas: the development of hardware components, the research of meta-surfaces, and the adaptation of network control based on artificial intelligence or machine learning.

Components For A Reliable D-Band Connection

Fraunhofer IAF brings its expertise from the field of high-frequency electronics to the development of hardware components: together with its partners, the Freiburg researchers are developing new radio technologies for communication in the D band (130-174.8 GHz). “Our focus is on the development of new radio modules with the highest spectral efficiency that takes advantage of frequency diversity and offers a control interface for optimization in the network. 

Reflective Surfaces

To avoid network disturbances in NLOS connections, meta surfaces (meta surfaces) and their contribution to an optimization of the radio connection are researched in ARIADNE. Meta surfaces are adjustable reflectors for radio waves and are intended to counteract network control problems in urban areas. If there is no line of sight between base stations on the roofs of the house and the users in the house canyons, meta-surfaces should reflect radio waves and thus ensure the spread outside the line of sight. The control of the meta surfaces should take place via a central network controller.

The concept of metasurfaces is already partially implemented for 5G, but so far only for low frequencies. The higher the frequency of the radio connection, the finer the microstructures on the surface must be, and for frequencies in the D-band, the structures are very complex to manufacture, explains Thomas Merkle. For this reason, the project team is researching the development of metasurfaces that are suitable for both high frequencies and industrial production. At Fraunhofer IAF, researchers are working on the so-called reflectarrays. These are small meta-surfaces on antennas that are used for beam swiveling and focusing.

AI-Based Network Control

To provide a constant and reliable radio connection in all weather conditions, methods of machine learning and artificial intelligence (AI) should be used for network management. So far, mostly classic mathematical methods have been used for mobile radio control. ARIADNE will now use AI-based algorithms to solve radio communication problems. While thorough data analysis is the goal in machine learning, AI is to be used to develop a system for network control that not only recognizes and reacts to problems but can even predict and prevent them.

The final goal of the project partners is to bring the individual project modules together in a test system and to demonstrate the functionality. At the end of the project, they want to present two demonstrators as a result of their research work: The first demonstrator should achieve a connection over 100 meters that is reliable in all weather conditions with a data rate of 100 GBit / s. As a proof-of-concept in the laboratory, the second demonstrator is intended to show how a meta-surface can improve the propagation conditions for radio transmission in the environment. This is how the functionality of meta surfaces at high frequencies is to be proven in the laboratory.

Also Read: How Understanding Your Audience Through Instagram Insights Can Bring More Traffic To Your Account

The post Artificial Intelligence Optimized Mobile Communications appeared first on Trends Tech Blog.