How Companies Can Set Up Their IT Infrastructure To Be Future-Proof

October 2, 2021

In times of increasing data traffic and increased business-critical applications, companies should prepare for digital transformation. Many are still a long way from a future-oriented, cloud-compatible IT infrastructure. For them, converged infrastructure systems can be a quickly implementable alternative to conventional solutions.

It sounds like a relic of the old days, but servers based on RISC and Unix systems are still common practice in some companies; they continue to prevail, particularly in the financial and health sectors. This does not mean that the companies are modern and future-proof. A particular obstacle is that the systems are not suitable for integrating cloud environments due to their proprietary system software. At the same time, new applications and the know-how among IT professionals for the old platforms are increasingly dying out.

Companies that continue to operate such an outdated IT infrastructure despite everything quickly lag behind the competition. Because the advancing digitization “forces” companies to set up their IT environments in an agile, flexible, and decisive manner. A healthy thought-out IT infrastructure solution that ideally supports all cloud variants can be the solution here.

Rethink The Foundations Of The IT Infrastructure In The Company

The new cloud-based IT environment should support existing applications and processes and design agile development and deployment models. Because a future-proof IT infrastructure acts as a strategic partner for a company, automating and simplifying (existing) business processes. An alternative to the outdated solutions is cloud-compatible converged infrastructure systems that meet all the criteria of sustainable corporate IT. They include selected and validated server, storage, and network components. These are combined in an optimized IT system – including management and virtualization software.

Converged Infrastructure:

Where Does It Make Sense?

While a Hyper-Converged Infrastructure (HCI) primarily appeals to companies that want to set up a standardized platform for exclusively virtualized workloads and microservices with little effort, a Converged Infrastructure (CI) is particularly suitable for companies with more than 500 employees. These have high demands on their IT infrastructure regarding scalability, performance, availability, and reliability.

The advantages of a CI solution: Thanks to the integrated architecture, it can be used in virtualized and non-virtualized customer environments and hybrid cloud scenarios. Furthermore, it easily adapts to different requirements. On the one hand, this minimizes the business risk and, on the other hand, increases the efficiency of the data centers.

Datacenter Architecture: Modern And Custom-Made

The FlexPod-CI is designed to increase IT responsiveness while reducing computing costs. It consists of four main components: Unified Computing System (UCS), Unified Management software, storage components, and data center switches – all coordinated with one another. Therefore, the implementation effort is deficient; ideally, it takes less than a day to get the CI up and running.

Since the UCS systems have a programmable infrastructure, users can centrally manage the server resources using unified management software and flexibly assign workloads. Different automation functions simplify operation. Users also can centrally manage FlexPods working in different data centers and automating the entire stack. Further advantages for companies with demanding business applications: Fast flash memory for applications that require short response times, central storage management, automated data management, and high performance of the data center switches with data rates of up to 400 Gbit / s.

IT Infrastructure In The Company: FlexPod In Practice

In practice, this can mean: Increase reliability, create data backups. The IT service provider Logicalis implemented a FlexPod system with a NetApp Metro cluster with 30 terabytes for the medium-sized office manufacturer. Thus, Palmberg can save CIFS (Common Internet File System) data and secure virtual machines ten times faster. Thanks to the deduplication of the CIFS data, the company could save about 40 percent of the storage volume.

Reason for the implementation: a complete renovation of the data center. In collaboration with Logicalis, the university’s IT department developed a concept based on the FlexPod CI. It ensures that the IT infrastructure in the company is flexible and expandable as required. The higher reliability, especially of the SAP systems, is another advantage of the solution.

IT Infrastructure In The Company: Little Effort, Significant Effect

With competent support for implementing a converged infrastructure, companies can quickly set up their IT infrastructure for the future. Such a solution, which can be flexibly adapted to the respective requirements, relieves the IT department. This can again concentrate on its core business and easily control demanding business applications.

ALSO READ: Hyperscale: How Companies Get The Most Out Of The Hybrid Cloud

Hyperscale: How Companies Get The Most Out Of The Hybrid Cloud

Techno Rumours

October 2, 2021

Hyperscale How Companies Get The Most Out Of The Hybrid Cloud

If companies know the differences between the standard hyperscale and the customizable solutions from local cloud providers, they can place workloads where they are best-taken care of. This gives users complete flexibility.

AWS, Google, Azure, and, more recently, Alibaba’s hyperscale’ offerings are all very similar. They offer scalable computing power in a multi-tenant environment that is paid for according to consumption. The offer of the Hyperscale is mainly based on three pillars: flexibility, additional services, and scalability. However, customers pay a surcharge for a high level of flexibility. This is mainly due to the size necessary to cover peaks to provide almost any computing power.

This flexible basis of storage and computing power is used to offer additional PaaS (Platform as a Service) services. These services can be booked quickly without having to develop them yourself, such as scalable databases or payment services. Again, the costs are usually higher than if you were to develop these services yourself.

Hyperscale: Impact Of Data Protection Regulations

Hyperscale are globally present and have data centers in many countries under the umbrella of a global parent company. In the case of US hyperscale, the parent company’s business location is sometimes an issue. The possibility of access by US authorities is possible in the case of US hyperscale. Even a subsidiary owned by a US company is required to allow US authorities access following the parent company’s legislation.

High Entry Price Without An Exit Strategy

Due to the standardization based on the size of the hyperscale, special requests or adjustments are usually not possible. Customers have to adhere to the standards, the way they work, and the solutions that the hyperscale provide. Using these proprietary standards, the use of the offers of hyperscale often leads to unwanted manufacturer loyalty. These define how to do business with them and how to use their infrastructure. For example, AWS S3 has almost become the industry standard, and it isn’t easy to find a way to work outside of AWS when that standard needs to be used.

Smaller Cloud Providers Have A Different Business Model

Compared to the hyperscale, the cooperation with smaller providers, who can undoubtedly operate globally, offers many advantages. These providers do not have to provide a massively scaled overhead to cover short-term high-demand peaks. They are not interested in use cases that would increase their highest peak demand but would result in idle hardware in the remaining time.

In fact, in practice, only a tiny percentage of workloads have high peaks. Most workloads are reasonably stable and predictable. This is a central factor in the business model of smaller cloud providers: this overhead does not exist and therefore does not have to be factored into their pricing. Smaller providers have a completely different business model compared to hyperscale! Their offerings for predictable workloads are therefore much cheaper – in reality, 30 to 50 percent savings than hyperscale – and in some cases even more.

ALSO READ: Internet Fraud: How New Technology Secures Online Banking

Hyperscale: Paid Support In The Public Cloud

In addition to the higher costs, the offers of hyperscale have other disadvantages. For example, support is chargeable and not included. Customers must purchase a support package that specifies what type of support they will receive. For smaller providers, essential support is usually included in the price. The hurdle for support is much lower, and customers can speak personally to the people who operate their platform. You can get advice, review business models together, or decide what would work best. These things are impossible with the anonymous hyper-scale approach.

Hyperscale: Consider Differences In Cloud Portfolios

Compared to the hyperscale, smaller providers lack the amount of PaaS services. For example, AWS currently offers more than 150 different PaaS services on its platform. If you look at the portfolios, the smaller providers offer everything below the PaaS line. That is, bare metal and dedicated compute, which hyper scalers only offer to a minimal extent. For example, AWS only has a handful of different server models in its portfolio that can be used as bare metal.

In comparison, smaller vendors potentially have hundreds of different models and specifications tailored to the optimal performance. Small cloud providers are also able to add a customizable cloud layer to this infrastructure layer. This enables customers to use a generic service and build their services in a better way.

Smaller providers will most likely not offer a highly scalable database. But they will offer a platform that is cost-effective, stable, and customizable. This allows a company to run its database much better, and customers are not tied to a particular provider and their specifications for how a database should work. Of course, there is a threshold to the use of any service, after which it is much easier and better to build your service than to give a hyperscale a ton of money for a generic solution. But how do you correctly decide where a workload should ideally run?

Hybrid Cloud: Complete Flexibility At Manageable Costs

Hybrid cloud computing has been around for more than 20 years and has become the standard for most cloud infrastructures. Hyperscale and smaller vendors alike have noticed that customers need both pieces and have established connections for the two clouds. The ideal is to combine everything with everything that should be the basis for every portfolio of smaller providers. This is vastly different from hyperscale, who are not interested in letting their customers choose what any competitor has to offer.

Put Workloads Where They’re Best-Taken Care Of

The decision-making process of choosing and setting up the right provider starts with the required workload. Workloads that are volatile and require a lot of flexibility will likely require the performance of a hyperscale. Anything predictable can be run much more efficiently in a smaller vendor data center, tailored precisely to needs. In this way, companies get the best of both worlds and generally do not choose one of the two alternatives.

Public Cloud Of Hyperscale – A One-Way Street

The “cloud-first” approach is generally not a good idea. It is more efficient to look closely at workloads and then find out what the best solution is. There are hardly any customization options with a hyperscale and rarely make economic sense. There’s no going back with cloud-first, while it’s easy to go the opposite path from bare metal to a different cloud environment that can be customized for any specific purpose. Companies should keep their options open by choosing a hybrid cloud model. This gives you the same flexibility at manageable costs and a good price/performance ratio.

ALSO READ: Mobile Robots: How AI And Edge Computing Are Accelerating Their Use

Mobile Robots: How AI And Edge Computing Are Accelerating Their Use

Techno Rumours

October 2, 2021

Autonomous things are changing many industries in which processes based on artificial intelligence and edge computing were so far more of a marginal phenomenon. Intelligent devices such as mobile robots are advancing into fields of application that require physical interaction with people and the environment.

Companies that want to benefit from the great potential in automating tasks should closely follow the current trends in robotics and edge computing. Mobile robots, for example, offer a multitude of potential applications that are no longer a dream of the future. But what determines the new autonomy of things? Autonomous things interact with each other and with people in an extended ecosystem without human supervision.

The use of autonomous devices is made possible primarily by advances in artificial intelligence, network technology, and cloud and edge computing. They are used in a wide variety of areas: from household appliances to driverless transport systems and drones in warehouses to the maintenance and monitoring of systems and buildings and self-driving automobiles.

Mobile Robots In Use During The Vehicle Inspection

A concrete example from practice is the mobile robot “Spot” from Boston Dynamics. He can climb stairs, take high-resolution photos with the help of machine image processing and collect valuable data for preventive maintenance. Among other things, it is used for vehicle inspections. Equipped with computer vision technology and the necessary computing power onboard, Spot can independently walk around a vehicle and register its condition. With additional dashboards, employees can see the overall status at a glance via the app.

Further future-oriented application scenarios already exist, for example, Reply projects in building information management and system monitoring showed. With the help of predictive maintenance models and deep learning algorithms, potential threats to health, safety, or the environment can be identified. The mobility and autonomy of the robot enable precise visual and acoustic measurements or gas detection in areas that are difficult to access.

Data Collection Through Wireless Connectivity And Edge Computing

Thanks to object and pattern recognition, mobile robots can navigate and continuously record data with various sensors – from cameras to microphones and GPS to temperature, humidity, gas, or radiation detectors. Wireless connectivity with intelligent system architecture and cloud edge computing makes it possible to use the captured data with AI and machine learning algorithms that give the mobile robot autonomy to decide how it best performs a task.

The AI is divided over several levels in an intelligent network, from a central cloud to an edge cloud to the individual robots. This means: As edge devices, mobile robots analyze the data directly before it is sent to the cloud. This preprocessing can, among other things, drastically reduce the data volume and save energy when transferring data to the cloud. This method is particularly suitable for tasks that would overwhelm the device’s storage capacity. This approach can also be followed to protect sensitive data from being accessed in the best possible way.

Mobile Robots: Adapting Artificial Intelligence To The Required Performance

The demands on computing power and energy consumption are pretty considerable for autonomous things. In principle, such devices can be equipped with exactly the degree of intelligence that they need for the performance they require. So-called “weak AI” is sufficient for a robot that does simple tasks. For more demanding activities, on the other hand, more robust variants are required. Implementing the AI in the right place is imperative so that the corresponding robot is not overloaded and the high speed of decision-making is maintained.

Smooth Communication Between Man And Machine

When using autonomously moving robots, communication between humans and machines must run smoothly. Voice interfaces are increasingly gaining acceptance here as a medium of interaction. Machine learning models for speech recognition and technologies such as sentiment analysis, semantic networks, ontologies, and self-learning chatbots help applications understand natural language as well as possible.

The world of new autonomous things opens up many new perspectives. It is now a matter of setting the technical parameters correctly for each application. In case of doubt, a competent partner familiar with the many individual aspects is constructive. In addition, the partner can optimally configure the equipment of the desired solution.

ALSO READ: Transformation In A Crisis: Automation And AI Are Changing World Of Work

Transformation In A Crisis: Automation And AI Are Changing World Of Work

Techno Rumours

October 1, 2021

Automation and AI are changing the world of work. The Covid-19 pandemic and the resulting uncertainty are causing loss to companies, to convert their work even faster. In this situation, managers focus in particular on their employees and their further development. How artificial intelligence and automation will change the world of work in the future.

Every third employee does not have enough time for training and education in their working life.
The use of predictive analytics in companies has increased fivefold.

Even before the Corona crisis and its effects, 99 percent of companies were transforming. According to Mercer’s new study “Global Talent Trends 2020”, 42 per cent of employees assume that their job will be replaced by artificial intelligence and automation within the next three years. Seventy-one percent believe that their employers prepare them well for the future of work, and 77 per cent trust that their company will train them accordingly if their job changes due to increasing automation.

Automation And AI Transformation: Bringing Profitability And Empathy Together

Automation and AI are changing the world of work. The study offers comprehensive insights into nine industries and 16 regions of the world; 450 people were interviewed.

“It is important to reconcile economic efficiency and empathy, especially in uncertain times like these. Companies need both a financial model and a cultural mindset that allows them to prepare for the future and position themselves accordingly,”. “Rethinking the purpose and priorities – that is important for the entire company, but especially for HR managers. This year’s study results clarify that the HR function plays a key role in building a sustainable organization. “

Trend 1 In The Automation And AI Transformation: Focus On Futures

Ninety-six per cent of company managers believe that the purpose of an organization, i.e. its purpose, should go beyond the requirements of the shareholders. However, only 28 percent of companies meet this requirement today. According to the study, every third employee would prefer to work for an employer responsible to all stakeholders, not just to shareholders and investors.

The design of a sustainable business model is a topic that is definitely on the agenda of many executives – 80 per cent want to focus more on sustainability in the areas of the environment, social affairs and corporate governance. While 71 percent of employees trust that their employer will prepare them for the future of work, 69 per cent feel threatened by a burnout risk.

The way we look at career paths is also changing: 84 per cent of the employees surveyed state that they can imagine working beyond retirement age. On the other hand, 73 percent of companies do not have active programs for dealing with employees shortly before the statutory retirement age. “Dealing with older employees and personnel planning that does justice to all generations are becoming more important,” .

ALSO READ: AI Systems: How New Technology Is Changing IT Professions

Trend 2 In The Transformation: Race To Reskill

Ninety-nine per cent of the companies surveyed are currently transforming and at the same time report significant skills gaps. But even though 75 percent of employees say they are ready to learn new skills, 33 percent say they don’t have enough time for training.

Additionally, only 37 per cent of HR leaders invest in reskilling employees as part of their strategy to prepare for the future of work. In addition, 41 per cent do not know what skills their workforce has today. “When it comes to transformation, the question is not whether, but how. To stay at the top, companies have to train their employees on a large scale, quickly and across all generations,”.

But which skills will be most in-demand over the next twelve months? When asked about the top 3 skills, HR managers named entrepreneurship and a global mindset in second and third place. Employees, on the other hand, named innovation and problem-solving skills as the top two. At the top for both groups is digital marketing.

Trend 3: Sense With Science

Machine learning is constantly evolving and permeating more and more industries and lifestyles. The use of predictive analytics, i.e. predicting future developments by evaluating data, has increased almost fivefold in five years . Still, only 51 percent of organizations use metrics to identify employees who are likely to quit.

Automation and AI are changing the world of work. After all, 49 per cent have an eye on when key employees are likely to retire, 18 per cent know the effects of salary strategies on employee performance, and 14 per cent use analyses to correct and prevent inequality. 13 per cent can determine whether it is better to hire employees externally, build them up internally or use freelancers. Other forms of data collection on employee engagement are also increasing: 61 per cent of companies are already using tools for pulse checks or regular feedback, and 33 per cent are planning to invest in them this year.

While machines outperform humans in tasks that focus on speed and scalability, humans are still superior when it comes to verifying meaningfulness and judgment – both central elements of ethical decision-making. Sixty per cent of HR managers are confident that they can ensure that Artificial Intelligence is free from bias and that no prejudices are institutionalized. However, codes of ethics on the collection, application and impact of staff reviews are still in their infancy.

In talent assessment, in particular, it is important to combine digital methods and human intuition. Today, only about every second employee has had positive experiences with assessments and found them useful. “Companies today know more about human behaviour and cognition than ever before. How they collect this information and react to it requires serious consideration of moral and ethical aspects,”.

Trend 4: Energize The Experience

Automation and AI are changing the world of work. The topic of employee experience, i.e. the experiences that employees have in their job, has found its way into the HR function. Seventy-four per cent of companies are redesigning their work to focus more on their employees. Yet only 28 percent of C-suite executives believe that investing in employee experience in the company will pay off. And while 67 percent of employees trust their employer to take care of their wellbeing, only 26 percent of HR leaders have a health and wellbeing strategy in place. Only three per cent say that they offer an outstanding employee experience.

The topic plays a role here. Employees whose businesses are focused on health and wellbeing are twice as likely to be motivated. And motivated employees are essential to realizing a company’s transformation plan: They are more likely to stay with the company, are more resilient, and are more willing to learn accordingly.

ALSO READ: Cloud Strategy: 3 Tips On How Cloud Security Becomes Business Enabler

Cloud Strategy: 3 Tips On How Cloud Security Becomes Business Enabler

Techno Rumours

October 1, 2021

The term security encompasses more than just protecting a company. A holistic security strategy supports all business processes up to DevOps projects instead of restricting them. To implement a holistic cloud strategy, suitable security tools must be integrated and responsibilities assigned to avoid misunderstandings, and to be able to defend the complex cloud environments against cyberattacks. Complexity is increasing as more and more companies realize that a single cloud environment is not the right approach in the long run. Whether private or public, every cloud service offers different tools and options, from advanced machine learning tools to low prices for storage space.

For most companies, this means that sooner or later, they will pursue a cloud strategy that takes a multi-cloud environment into account. This requires a uniform security platform that performs security controls and compliance for hosts and containers in an automated form, regardless of the cloud provider or the deployment model used, to meet the requirements of DevOps and the various clouds. For cloud security to succeed, companies should consider three key components: unification, automation, and integration.

Cloud Strategy: Standardization Of Security Solutions

If you look at today’s security situation, you see that the threat actors are the same, but the environment that needs to be protected has changed significantly. Traditional security tools cannot save a cloud because they were not developed for dynamic cloud environments and have gaps in visibility and security. And even if they have been retrofitted, they have become unusable for the types of attacks targeting cloud environments. Overcoming these current cybersecurity challenges is untenable for security teams who want to keep up with the realities of a cloud-native world with selective solutions.

When the limitations of these stand-alone products become obvious, this often leads to ad hoc approaches aimed at fixing blind spots and a lack of integration. The solution is simple: Protect the cloud by using the cloud. A cloud-native security platform is the best way to eliminate the gaps in invisibility and scale it to the needs of a company, from containers to microservices.

Armed with full visibility and continuous workload detection, these platforms support vulnerability identification efforts and ultimately help DevOps teams weave security into CI / CD workflows so that issues can be resolved before they reach production. IT security needs to keep pace with DevOps and work across all clouds to maintain security and visibility as workloads are moved to be truly effective.

Automation Is Critical To Any Cloud Strategy

Another characteristic of a multi-cloud environment is its fast pace. A good example of the dynamics of a cloud environment is microservices, which can be set up quickly and are often very short-lived. Therefore, companies need to know which processes are being carried out where and who is carrying them out. This is where automated detection and monitoring of assets come into play. Companies can use it to get an overview of everything without slowing down a business process.

By interlinking security with CI / CD, the guarantee can be increased by enabling a “shift left” approach. Thanks to automation, the security system can be orchestrated more effectively to remedy weaknesses and security risks early in the development life cycle. However, care must ensure that security gaps are not introduced using Infrastructure-as-Code (IaC) templates. Automation prevents security from being an obstacle for developers. Instead, it reduces complexity and enables rapid deployment, providing organizations with the visibility and security orchestration needed.

Integrated Security Solutions Are Scalable

When a company renews its security strategy, it is important to consider that it cannot work in isolation, especially when working with DevOps. Its integration enables the security department to work seamlessly with applications, cloud instances and cloud workloads. Only the integration turns an average security strategy into an effective one. When examining non-cloud-native tools, it becomes clear that they are not designed to protect dynamic cloud environments.

The latter are often not optimized for cloud-native applications and make monitoring more difficult. They also require additional manual intervention. In contrast, cloud-native solutions offer consistency across the entire cloud environment and maintain the level of security and compliance without incurring as much overhead as on-premise tools that were previously relied on.

Cloud Strategy: More Transparency And Control Through A Security Platform

Only the interaction of the three components described above results in a cloud strategy, including a security platform that can support companies in their growth. Cloud-native security platforms offer visibility and control across public, private, hybrid and multi-cloud environments. Complemented by automation, this enables security teams to focus on more important tasks instead of identifying cloud misconfigurations that can be used for cyberattacks. Many problems are avoided much earlier, and success for the company is achieved more quickly.

ALSO READ: AI In Mechanical Engineering: This Is How Companies Get Started

AI In Mechanical Engineering: This Is How Companies Get Started

Techno Rumours

October 1, 2021

Fraunhofer spin-off plus10 works with mechanical engineering companies to develop industry-specific use cases for artificial intelligence, making it easier to get started with AI. The workshop provides systematic road maps for machine manufacturers. The workshop format has already been successfully implemented at the plant manufacturer Hosokawa Alpine.

Some machine manufacturers have already tackled the integration of Artificial Intelligence (AI) in their machines and systems and in-house processes. Due to the novelty and versatility of these approaches, appropriate expert knowledge is usually not available or only partially available in the company. Therefore, mechanical engineers look for and find the missing AI expertise externally. So it happens that many system manufacturers enter into cooperation with start-ups.

As a current study by the VDMA Startup-Machine shows, there is often a lack of a systematic approach to such collaborations, although this can be decisive for success. That is why the Fraunhofer spin-off has a plus10an offer specially developed for mechanical engineering companies. This makes it easier for companies to take the first steps towards AI in mechanical engineering. As a provider of AI software for machine and production optimization, the experts at plus10 know the potential that arises from using artificial intelligence. They are also informed about what is technically possible and where problems lurk.

Integrative Workshop To Get Started With AI, Especially For Mechanical Engineering Companies

As the study by VDMA Startup-Machine shows, more than 50% of the manufacturers of machines and systems have already entered into cooperation with various start-ups. For 84% of the surveyed plant manufacturers, the motives are to develop new products or improve existing ones. To remain competitive, companies get external input. But for cooperation to be a success, it is essential that it is strategic and aligned with a previously defined target. It is precisely for this reason that plus10 has developed an integrative workshop format, especially for machine and system manufacturers. This workshop systematically develops the introduction to AI that is individually tailored to the company.

It shows that there is a willingness and openness for new technologies in mechanical engineering. Often the only thing missing is the knowledge or experience of what would be technically possible with AI and what prerequisites are necessary for this. Identifying these points of contact and potential use cases in the company is the goal of plus10’s AI introductory package. This is not a piece of one-sided advice. The use cases are developed together: Employees from the company bring valuable business knowledge from different perspectives to the workshop.

The Necessary Expertise For AI Applications In Mechanical Engineering Companies

At the same time, AI and automation technology specialists from plus10 provide the necessary expertise on AI basics, existing solutions and best practices in mechanical engineering. After the organized and systematic derivation of use cases, these are technically assessed with the AI experts. In this way, the company develops AI use cases that are individually suitable for them with the associated requirements, benefits and challenges. As a result of the workshop, machine builders receive a specific use case preselection, including a technical assessment, so that they can move on to implementation promptly.

The joint development of possible applications in the company has further advantages: On the one hand, it creates an understanding of new technologies among employees and thus supports the development of knowledge and skills in this area. On the other hand, the acceptance of digital projects in the workforce is decisive for whether the deployment is successful. The VDMA Startup Machine Study also confirms this: Projects involving employees as supporters are more successful . It is therefore worth promoting the support of internal experts by integrating them into digital measures.

AI In Mechanical Engineering: Workshop At The Plant Manufacturer Hosokawa Alpine

The collaboration between mechanical engineering companies and AI start-ups also showed successes at the plus10 workshop and the plant manufacturer Hosokawa Alpine. Christian Riendl, Head of Electrical Engineering of the Film Extrusion Division of Hosokawa Alpine AG, reports on the joint seminar: “Together with plus10, within two days we worked out specific applications of how artificial intelligence can be integrated into our systems in a way that adds value and at the same time is technically realistic. With its concrete examples for implementation in mechanical and plant engineering, plus10 made the topic very tangible. That helped us extensively to identify AI applications for our systems. “

ALSO READ: Cybersecurity In Companies- To Protect Themselves When Introducing 5G

Cybersecurity In Companies- To Protect Themselves When Introducing 5G

Techno Rumours

September 30, 2021

_How Companies Protect Themselves When Introducing 5G

Cybersecurity is becoming more critical than ever with the introduction of the new 5G standard. This is how companies prepare themselves, against the dangers of the Internet. Cybersecurity is not infallible. Companies should therefore do everything in their power to prioritize security when implementing 5G in their operations.

Cybersecurity In The Age Of 5G

Introducing the new high Cybersecurity speed standard for mobile data transmission is taking longer in neighboring countries . But one thing is sure: sooner or later 5G will also arrive with us. The fifth generation of mobile communications allows data transmission rates of up to ten times the speed of its predecessor, 4G. Many are expecting a revolution in corporate communication, the world of work, and, last but not least, video streaming. Despite all the euphoria, it should not be overlooked that cybercriminals will also take advantage of the new possibilities to run broader attack campaigns on more and more end devices.

5G will expand the available bandwidth and, at the same time, reduce the size of the individual data packets. This makes it easier to attack mobile devices with very small and complex to detect malware. These are usually hidden in the code of applications. The file size of malware combined with limited bandwidth in mobile data transmission has hindered large-scale campaigns against mobile devices. However, with the introduction of 5G at the latest, these hurdles will disappear. Therefore, smartphone users will have to prepare for a wave of highly specialized and increasingly sophisticated malware attacks in the future.

Companies should start implementing a cybersecurity strategy now to contain the new risks in advance. 5G is in the starting blocks, and 6G is already in the planning phase.

IoT Devices Are Vulnerable

In addition to mobile devices, IoT devices are at the top of the list of cybercriminals who aim to paralyze or exploit companies deliberately. Many things in our everyday life are continuously connected to the Internet and use it to exchange data. From baby cameras to cars, a large part of the world we live in has now become hackable. And every day, more IoT devices are adding to the attack surface for cybercriminals.

Unfortunately, many of these valuable objects are still poorly secured. Quite a few have a predefined access password such as “admin” or “password” – not a genuine hurdle for hackers, who thereby gain access to a host of IoT devices that are often misused for DDoS attacks when necessary.

The probability that a hacker will find a particular IoT device on the Internet is very high – the higher connection speed will make it even easier for them in the future. The hackers bundle thousands of these recruited devices in botnets and abuse their willies followers for large-scale cyber attacks. With the help of 5G, hackers will be able to extract information faster than ever before. That is why the protection of the personal data of employees and customers has the highest priority.

External Work As A Weak Point In Cybersecurity

With targeted attacks, cybercriminals are usually out to steal the most sensitive and valuable information. For this reason, companies in the banking, logistics, and transport sectors, alongside legal companies, are at the top of the attacker’s priority list. After all, sensitive information is the core of the business in all of these sectors.

Protecting sensitive data is already a major headache for many of these companies – the arrival of 5G is likely to exacerbate this pain. More and more companies are promoting the benefits of working away from home, and this has increased since the arrival of Corona. Often, however, employees are negligent in meticulous compliance with all the necessary safety precautions that must be taken into account when working outside the office. In this way, they open up an additional and, above all, avoidable gateway for cybercriminals.

And then there is the careless employee in the inner circle to consider. The higher this is in the company hierarchy, the more authorizations and insights are linked to his account. The greater the risk if this employee does not adhere to all of the company’s security and compliance regulations.

The Focus Is On A Lack Of Cyber Education

A recently published report gave a shockingly high number of employees poor testimony: According to this, one in four employees has no idea of the cyber threats that their company is confronted with on a day-to-day basis. Every fourth employee is not familiar with the words phishing, social engineering, or ransomware.

These numbers highlight the need for organizations to educate their employees about internet fraud and cybersecurity before 5G is implemented across the organization. Because a careless, untrained employee can destroy all good resolutions and safety measures of his company.

Another finding of the report is that 69 percent of employees use their company devices for private purposes. This results in several problems for IT departments regarding prevention: the more permissive an employee is with his company device when using it for private purposes, the more difficult it becomes for supervisors and IT security officers, the extent and to overlook the possible consequences of this use.

Cybersecurity Best Practice

Below are some practical employee training tips that can give companies fresh ideas on how best to protect themselves against the dangers of the Internet:

Don’t let up: There is anyone solution to all problems. Above all, you should get rid of the habit of practicing an often outdated and therefore useless course once a year. It would make more sense to present the current dangers to your employees in shorter cycles and train them on identifying harmful websites and messages. Therefore, it is advisable to regularly convey current knowledge to employees in short learning units that do not take longer than a few minutes. This means that you can react promptly to new threats.

Training is compulsory: to be effective, training must take place every month. By keeping your employees entirely up to date without exception, you make it easier for the IT department and all those responsible to guarantee the security of data and digital infrastructure.

It has to be a bit of fun: A creative approach has proven highly effective for consolidating teaching content. People find it easier to memorize information when it is conveyed with the help of recurring characters and a little humor. A little story makes things less dry and provides more than bland, monotonous, and ultimately inconclusive training.

ALSO READ: Data Security In The Cloud: Why Banks Shouldn’t Miss Their Opportunities

Data Security In The Cloud: Why Banks Shouldn’t Miss Their Opportunities

Techno Rumours

September 30, 2021

Many banks do not dare to outsource critical data to the cloud because the geopolitical and regulatory uncertainties are significant. But Europe has already taken the initiative to become more independent as an economic area. Banks should, therefore, not miss their opportunities in the cloud.

Tok-Tok? Forbidden. Huawei? Locked. Microsoft Teams? Declared inadmissible for banks by the Data Protection Commission. These are just a few examples of the potential impacts of geopolitical tensions that the financial industry has grappled with over the past year. Because not only the Corona crisis has massively changed the global framework. Financial institutions today are also constantly exposed to new global dynamics to which they must react.

These uncertainties make the path to the public cloud difficult for many. Their use would be urgently needed for banks because with comprehensive offers from cloud service providers, higher availability, greater flexibility, and scalability, and a higher level of security can be achieved than in their own data center. Resilience, or rather “operational resilience,” is strengthened. Therefore, the financial sector would have to take the next step into the cloud and outsource essential applications and data. But how is that supposed to work?

Data Security In The Cloud – Get Out Of The Dilemma

The dilemma can only be resolved if Europe succeeds in becoming more independent as an economic area. The EU has already recognized this. The European cloud initiative “Digital Operational Resilience Act” (DORA) launched an initiative that subjects cloud service providers such as Microsoft, Google, or Amazon to the same regulations that apply to banks. This also clarifies the question of how data can be stored, shared, and used. With the European cloud initiative “Gaia-X,” a pioneering project has also been launched. EU states will have a standardized set of rules and a marketplace for cloud services following European values. And thus an alternative to purely US and Chinese offers.

Off To The Cloud – They Are Making The Proper Use Of Opportunities

But how can the path to the cloud succeed safely? Before starting, banks should first get an overview of the risks associated with using the cloud. The institutes evaluate aspects such as the dependency on the service provider, data security, availability, or political upheavals. Ideally, they follow a structured decision-making process. In the end, independent third parties can also freely assess risks. This is also in the interests of the board of directors and the management, which under no circumstances wants to be accused of negligence due to the current board liability.

Financial institutions should take a holistic view of the risk position compared to the status quo. Many houses could even improve their risk profile if they swap weaknesses in their own data center for professional and resilient operation at the cloud providers. The institutes often overlook the opportunities in risk assessment, and ultimately business strategy factors. What tools can I use to analyze my database deeply and quickly? How can I fully understand my customers and support them across all channels? What will my employees need in their future workplace?

Data Security Within The Cloud: The Exemplary Architecture

Data is technically secured in the cloud. If there are weaknesses, they are often not due to the cloud provider but rather to the financial service provider himself: In practice, cloud architectures are sometimes poorly designed and thus open gateways for hackers. Since the responsibility for data security within the cloud lies with the banks, it is their sole responsibility to establish an appropriate (security) architecture. Cloud providers cannot be held responsible here.

It is essential to plan the architecture of cloud solutions stringently, taking into account data protection requirements and associated measures: It is essential to choose wisely in which countries or regions the data may be stored and processed. The selective choice of cloud services as the architecture is also decisive since processing the USA’s data cannot be ruled out for some.

Finally, there is the question of who holds the key used to process and store the data in the cloud. The supervisors demand that banks themselves are responsible – especially for accounting-related systems. In an emergency, the institutes could remove the key to make the data in the cloud unusable. However, this is equivalent to an IT blackout. It should therefore be considered whether the key management is not left with the cloud provider. Services are then integrated that ensure practicability and usability.

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AI Systems: How New Technology Is Changing IT Professions

Techno Rumours

September 29, 2021

AI Systems How New Technology Is Changing IT Professions

AI systems will change the professional world and the fields of activity of the IT specialists themselves. AI will take over routine activities and even the programming of algorithms. Industry knowledge and consulting skills will be in demand in the future. This also has an impact on the training and further education of young professionals.

Artificial intelligence, or AI for short, is gaining greater public awareness in the corona pandemic. Not only did an artificial intelligence system, the Canadian health platform BlueDot, warn of viruses of unknown origin in the Wuhan area before the WHO was officially informed. Evaluations of lung recordings, tracking processes for the spread, or monitoring distances in the logistics area are just a few possible uses. The ideas and possible applications are incredibly diverse. Several research projects are currently ongoing in the area of drug discovery alone.

AI Systems: Moving Into Everyday Life

The corona crisis can therefore prove to be a motor for the further development of artificial intelligence. The subject is, of course, not new. Learning algorithms have long since found their way into everyday life – in the form of navigation systems, voice assistants, or vacuum robots. Comfortable in daily life, they are much discussed, linked to the highest expectations, and feared as job killers. In any case, the time is ripe for applications of artificial intelligence. Because, unlike in the past, the storage and computing power required for this is now available. Enabling scalable storage capacities through cloud platforms and high processing speeds also makes AI economical for companies.

“Many potential users first think of process optimization, here the boundaries are often fluid between digitization and the use of artificial intelligence,”. Automation alone can replace many routine processes, repetitive and tiring activities for humans. However, AI can do much more: Through machine learning, the generation of knowledge from experience, the algorithms can deal with unknown data, find patterns, and independently derive actions. Chatbots, for example, which are increasingly used in customer service, get better and better over time with supported learning.

Deep Learning Enables Forecasts Based On Complex Relationships

Deep learning based on neural networks enables forecasts based on very complex relationships. Well-known applications can be found in the area of predictive maintenance or in predicting customer behavior. A crucial aspect of AI comes into play: Uncovering previously unknown relationships lead to new insights and thus promises real added value.

But how can companies use artificial intelligence systems to add value? To recognize and use their potential, IT users need development and implementation services and comprehensive advice. Because the use of AI elements is not comparable to the introduction of new software, for example. Instead, very different technologies and approaches are summarized under the term artificial or artificial intelligence, also AI. The best known include speech and image recognition or data analysis. A Bitkom project on the periodic table of AI offers detailed information and an overview, But it also illustrates how complex this topic is.

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Knowledge Of AI Systems And Industry Knowledge Is Becoming More Critical

This results in a comprehensive spectrum of specializations and specialist knowledge for the developers and programmers of AI models. “IT consultants and business analysts will also need an appropriate background to familiarize potential users with the possibilities of artificial intelligence.

The next step is to jointly find specific use cases in the company and design a suitable model for them. Companies need support in analyzing the options and estimating the costs: What amounts of data are required, and is it available in sufficient quality? If not, how much effort would it take to prepare the data? How much time should be planned for “training” the chatbot?

AI Systems: IT Knowledge Alone Is Not Enough

The AI model must also fit the application. Sub-symbolic processes such as neural networks are compelling, they are suitable for image recognition, for example, but their decisions are not understandable for people. So when it comes to traceability and documentation, they would not be suitable. IT know-how alone is not enough, who has worked in the banking sector for many years, explains: “To provide competent advice and to be able to speak to users on an equal footing, IT specialists also need knowledge of the specifics Processes, the business environment and the legal requirements in the respective industry.”

At the same time, rule-based routine activities in the IT area will also be taken over by AI algorithms in the future. Google Brain reported a corresponding success in 2017 with the development of speech recognition software using an AI system. IT experts will be best able to support companies on the subject of AI if they acquire background knowledge of the possibilities and AI systems, have consulting and problem-solving skills, and specific industry knowledge.

IT Young Talent Promotion: Future-Oriented Education And Training

However, specialists with this profile are likely to be rare. Companies are, therefore, primarily dependent on external support. Promoting young talent would often be the better alternative in the long term. Still, many companies lack the resources to train IT career starters or internal trainee programs.

The Digital Workforce Group has developed a holistic model to bring young professionals and companies together. Tailor-made support concepts and mentoring, project assignments, and internalization are the cornerstones. The personalized training is supplemented by offers of expert lectures and regular TechTalks. Workshops together with companies offer platforms for discussion and the exchange of experiences.

“AI is one of our main topics. With special project labs, we allow young IT talents to implement their developments, for example, with humanoid robots, and thus further develop their skills in the field of AI,”. After all, independent learning drives people and moves them forward – the template on which AI was developed in the first place.

ALSO READ: Internet Fraud: How New Technology Secures Online Banking

Internet Fraud: How New Technology Secures Online Banking

Techno Rumours

September 29, 2021

Internet Fraud How New Technology Secures Online Banking

The advancing digitization of services, which is being driven both by the corona pandemic and the development of new technologies, offers users significant advantages and great dangers. One of the most important uses for this is online banking.

Today almost all banks have stepped into the Internet and offer a whole range of different services via digital channels and mobile devices with online banking. The digitization of account management and the further development of open banking options are expected and used by users. Many fintech and neo-banks are just one example of the trend towards digitization, which is very popular among customers. But with the rise of online banking and digital services, so too do the dangers of Internet fraud, where hackers use complex technologies to capitalize on the development.

Internet Fraud Damage Is Increasing Sharply

Internet fraud in the banking sector is a significant challenge that can be viewed from two angles:

Ensuring the safety of users and their assets
Regulatory pressure and compliance

Both of these lead to further hurdles, including the cost of infrastructure, additional staff, the time required to comply with new regulations, and increasing the digital competence of users. The main reason why this challenge is so demanding is that it is invisible and should be: fast and without any significant impact on the user experience and banking operations. Therefore, it requires the use of specialized, AI-supported technology.

Prevent Internet Fraud From New Technologies

To meet security and regulatory challenges, organizations can employ technology that processes a wide range of usage data to continuously verify the identity and intentions of users, thereby protecting personal assets.

It does this by evaluating specific digital usage details, including transactions, sessions, devices, and behavioral data, to create a trusted digital profile. Based on this profile, it is possible to identify subtle differences in the details of use. Once such a digital fingerprint is created, any associated anomalies or changes in known and trustworthy behavior are used to optimize the profile to provide valuable insights to the banks.

The assessment can be carried out continuously throughout the entire digital use (onboarding, authentication, account management, transactions, etc.) and thus offers trust and security for both end-users and companies. This approach ensures that there are no unnecessary authentication hurdles in online banking.

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The Same User Experience – But Safe

Everything starts with registering for online banking. As soon as a user downloads the content of a page, a function is loaded, which begins to transmit data to the analysis server. This can be done on websites via a JavaScript snippet, on mobile devices via an SDK integrated into the mobile banking app.

The collected data is examined on the analysis servers, after which the risk assessment is linked to the current user, the session, the device, and the behavior. An authentication hurdle can be inserted if the user profile is new and the AI engine is not trained on it. If the user profile is known, an uninterrupted experience can ensue during the entire usage. As soon as a user logs in, the AI evaluates the behavior pattern, for example, typing behavior and mouse movements, to confirm the identity.

Behavioral Biometrics As An Additional Signature

This behavioral biometric data is unique for each user, similar to a fingerprint or the iris pattern. The EU directive PSD2 (Payment Service Directive 2) regards behavioral biometrics as a component of identity and allows the method of identity confirmation. While users write their e-mails or enter their passwords, the digital profile can be updated with the digital behavior, and the risk assessment can be adjusted if necessary. If a user typically sends money from their safe home location but is suddenly 500 kilometers away, this is a signal to increase the risk assessment.

If the user navigates the online banking app differently, this is also a signal to increase the risk assessment. Suppose the user uses a seemingly fake and static mobile device on which the accelerometer does not move for an extended period. In that case, this is a signal to increase the risk assessment. Anything that represents an anomaly can be measured and assessed to determine how it will affect the final risk assessment. Today’s technology can evaluate hundreds of these signals and adjust the risk assessment accordingly.

Verification Of The Process In Less Than 150 Milliseconds

The most important task of modern anti-fraud technologies is to continuously evaluate the details of users and their behavior in digital banking. The system adjusts the risk assessment accordingly. As soon as a critical event occurs in online banking, for example, access to PII (Personally Identifiable Information), applying for a loan, or making a payment, the bank can use APIs to ask the analysis server how high the risk is for the active user.

As the system continuously updates the risk value, the information is immediately available and accessed in less than 150 milliseconds. The bank can then use this information at its discretion. In addition, modern fraud prevention solutions usually offer a graphical user interface (GUI). With this, fraud analysts or other banking specialists can evaluate the risk assessment details, such as meetings, devices, or warnings.

Powerful Internet Fraud Prevention Solution

Sophisticated technology offers a robust fraud prevention solution by creating a trustworthy digital profile from details of user behavior. It’s like a unique fingerprint. The standard information database can offer both companies and users additional digital experience security and trust. The system decides within 150 milliseconds whether a process is classified as trustworthy or fraudulent. This enables secure online banking in a fraction of a second, and, in case of doubt, additional authentication hurdles are interposed to prevent attempted fraud.

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