Impact of Artificial Intelligence in Different Technologies

Artificial intelligence is a science friction for over years in the technology world and it is taking its real form as machine learning or deep learning. The neurons and the neural networks help to process the information and perform the complex functions. Technology is changing the lifestyle and the business in a variety of ways. Artificial intelligence is bringing in changes in the form of automated transportation, anticipating the climatic changes, improved support from the robot, changes in the job industry, and changes in the software industry. Let me discuss in detail about the impact of Artificial intelligence in different technologies.

Software Industry

Netflix is the famous application which uses the machine learning technique to satisfy the customers. The content in the Netflix app is divided with some logic like the genre, actors, reviews, length and more. The machine learning algorithms at Netflix analyze the user’s actions. The personalized content made Netflix the best streaming company. Netflix transformed into a global streaming service from a DVD rental website. Linear regression, logistic regression, and other machine learning algorithms are some of the machine learning algorithms used in Netflix Company.

Google maps use the Artificial Intelligence for providing information to their viewers. If the customers want the details of the parking location then the standard logistic regression model is used to collect the information. In the directions card, the find parking tab shows the parking spots near the destination where we search.

Let me see some of the benefits of Artificial intelligence in the software development process

  1. AI is used as the natural language or visual interfaces to improve the rapid prototyping.
  2. The documentation and the debugging code become easy with the help of the machine learning. The smart programming assistant provides the relevant document, best practices and example of the code with the examples.
  3. Error handling part in the coding becomes easy as it analysis the past experiences automatically and flag them automatically.
  4. Long-term maintenance and team collaboration are possible only with the help of clean code. The code refactoring helps to improve the performance.
  5. Better project management is possible with the help of the machine learning. Machine learning provides the precise estimates of the cost and time for the project.
  6. Help for the decision making in a challenging environment. To decide about the project and the business the past records are analyzed and better decisions are arrived at.
  7. Provides smart search results through the internet. Many big companies like Apple, Google and Microsoft use the machine learning techniques to provide the search results.

Business analysis and machine learning

E-commerce mobile app with machine learning, sports forecast app with machine learning, healthcare apps with machine learning, finance apps with machine learning, restaurants app with machine learning, transportations app with machine learning, time management apps with machine learning, travel apps with machine learning, weather forecast apps with machine learning are some of the interesting mobile apps which makes the machine learning still more interesting to the business world. Machine learning is enlarging the business and improves the analysis in multiple domains.

Transport Industry

The self-driving cars are already into the circulation and initializing more changes in the form of automated transportation. In the year 2012, Google initialized a test car and following that the US Department of transportation has the plan to release different types of cars with automation.

Artificial intelligence for the weather predictions

Using the big data and AI one can identify the trends and provide a solution to the world’s biggest problems. The better predictions for the bad or good weather report help majority of losses in times of emergencies.

A robot with human emotions

Artificial intelligence trains the robots about the human brain and the robots with the human emotions undertakes many activities which humans can only do. “Pepper” is the first robot invented by Japan. In the year 2015 within a minute, the “pepper” robot reached the highest selling units of 1000 units.

Artificial intelligence and the job industry

Robots are taking over so many jobs like the welding, producing toxic substances, intense heat, and noisy works are integrated with robots for efficient work. One research says that around 47 percent of the US department is at risk because of the automation.

Conclusion

The algorithmic bias is the flaws that happen without the human control in the process are the risk factor in using the artificial intelligence in all the domains. Some of the benefits of using the machine learning are it is easy to manage, backed with hardware support, the memory and the running time is constant, and a high degree of the portability. Recently companies with the security threats used the machine learning technology like logistic regression to identify the malicious website and to make the security process consistent multiple machine learning algorithms can be used.

Skills Required for IT Jobs

The first question which cracks the mind of the college students after completing the engineering is how to enter into the software industry? Does the qualification with high marks is enough? Obviously, the first screening is with qualification but to travel till the end and get selected in the interview some specialized skills are needed. IT jobs are the highest paid jobs in the local job market and the global job market. To help the IT graduates to enter into the IT industry we virtually provide you an outlook of the top level jobs and the Skills Required for IT Jobs. Let us analyze the skills of the software profession in alignment with the experience. For the experienced professionals and fresher skills and the respective salary differ.

Software Architect skills

In the United Kingdom, the software architects are paid high whereas in the USA they are paid with a median income. The skills required for a software architect are understanding the application logic to know about the software development process, analyzing dependencies of the technologies, review the requirements, provide the estimates, provide the design, good communication skills, good management skills, and analytical skills. Software architects are the team coordinators and the technical leaders.

Data scientist skills

The job of the Data Scientist is to analyze the data, test the data, experiment the processes, formulas, solutions to the different business challenges. Data scientists are among the top five paying jobs and the large enterprises hire a data scientist to identify the problems and solutions. The subjects to be prepared before attending the data scientists interview are statistics, common metrics, cost functions, machine learning, and tool knowledge {R, python, mathematics, and weka}, a mathematical concept like eigenvectors, singular values, PCA, LDA, Gibs sampling, and information bottleneck etc.

DevOps Engineer skills

DevOps Engineer should have an understanding about the operating systems like Windows or Linux OS, fluency in web languages, continuous integration tools, and the problem-solving skills. The agile process and the tool for the software delivery give the in-depth knowledge of the DevOps.

Database administrator’s skills

The database administrators are responsible for the design, security, policies, and implementation of system processes for the database management. As per a report, the salary of a database administrator is $68,363 and there are many big companies with the vacancy of the database administrator like L and T and HCL technologies.

Java developer skills

The skills required for the Java developer is in-depth programming skills. The responsibilities of the Java programmer are the deployment, designing prototypes, testing prototypes, taking part in the software development and architecture. The knowledge of different programming languages like Perl, Python, and Java XML is an added advantage of the Java developer. To gain in-depth knowledge into the Java language it’s good to join the Java Training.  The renowned training institutes provide practical oriented training with the industry experts.

Android developer skills

Java knowledge, understanding of XML, Android SDK skills, android studio, APIS knowledge, database knowledge, and material design are the skills required for an Android developer.  Android development is the best option for those with programming skills and interested in mobile phones.

Skills required for the front-end developers

Web designers know the PHP programming and the front-end developers know the web designing and the customization of the themes available for the front end technologies. The knowledge of the HTML, CSS, javascript, and jquery are important for a front-end developer.

Dot net developer skills

The skills required for a dot net developer are the HTML, CSS, Jquery, Bootstrap, and javascript. The certification from MCSD is an added advantage for the dot net professional.

Quality analyst skills

There are so many testing tools in the market like selenium, katalon studio, UFT, test complete and Watir. The skills required for a quality analyst are Active listening, reading comprehension, monitoring, complex problem solving and critical thinking. Testing tools are differentiated as web application testing and desktop testing. Selenium is the popular tool used for the web application whereas RPA is about the web application and desktop application testing. Selenium Training provides in-depth knowledge into the web application testing.

Skills required for the system architect

System Architect is responsible for the functionality and security of the systems. The architectural alternatives available for the system architects are client or server or web model, operational or informational, flexibility and performance. The skills required for a system architect are the design of the system, assign quotas, think scalability, prototype heavy loads, and focus on the key components.

Tech jobs are the fascinating jobs with a large number of opportunities and high salary. Some of the designations where the salary is high in the software industry tend to be a software architect, DevOps engineers, java developer, mobile developer, front-end developer, dot net developer, and systems architect. The number of rounds in the interview determines how screwed your hiring process is. Technical skills can be listed as programming skills, project management skills, business intelligence or business analysis skills, security intelligence, designing skills, marketing skills, and writing skills. Software jobs demand both the soft skills and the hard skills. The suitable jobs for the experienced professional are a software architect, data scientist skills, DevOps engineer and database administrator. The suitable jobs for the fresher are Java development, Android development, front-end development, dot net developer, quality analyst, and system architect.

Tips before attending the interview

  1. Gain the knowledge about the company and the number of rounds in the interview. Motivate yourself with the expected questions and provide a clear answer to all the questions.
  2. Utilize the online resources available to explore the latest concept in the desired technology.
  3. Check the linked in profiles of the engineering team members and understand the different profiles in the company with the help of the linked in profiles.
  4. Know the different problem-solving approaches and work out them practically.
  5. Practice with mock interviews with the help of your friends or trainers.
  6. Practice the soft skills and the non-technical part also.

Mere knowledge or high mark will not make the interview process easy. The effort and constant practice shape the knowledge with the required skills. Knowledge is gained through the academic studies whereas the application of knowledge is gained only by regular practice or experience.

Technologies which aid for the Cyber-security and Data security

The devices, websites, and databases are increasing in numbers in recent days which emphasize on security and enhanced user experience. Technologies like Android development, cloud technology, big data and IOT support for the security enhancements. As of Nokia MbIT 2018 report, the mobile data usage in India has risen to 144 percent to 2360 petabytes and it is said that 11-gigabyte usage per month per user for the 4G broadband. Let me discuss in detail about the Technologies which aid for the Cyber-security and Data security.

Internet usage and the mobile usage improve the global presence of the business and initiate the threats for the security of the data which has to be handled with the high-end technologies. Computer security, internet security, and the information security are equally focused to improve the security in multiple areas of the business world.

Android development and security measures

In Android P the crypto provider is removed to improve the security. The BC provider is duplicated by the AndroidOpenSSL and this will explicitly affect the applications with BC provider. The duplication of functionality pays way to the risks. So, the crypto provider is removed in the Android P.

The older OS version is the risk factor which exploits the hardware of the Android phones. The AVB in the Android oreo has cool features like the common footer format and rollback protection. The verified boot in the Android already prevents the devices and this is a reference to the verified boot. If the device works at older version then the rollback protection prevents the OS. Android Training provides the in-depth coverage about the latest concepts in the Android Development. The Pixel2 and Pixel 2XL protect the device and this new protection is recommended by the Google for all the Android device manufacturers.

The OEM Lock Hardware Abstraction Layer (HAL) protects the device if the device is stolen. The lock and unlock pattern of the phone are saved in the Replay protected memory block {RPMB}. The pixel devices from Android are upgraded with key attestation which strongly attests the IDs such as hardware identifiers. For the enterprise-managed devices, the encryption keys are now ejected from RAM which improves the security of the data. Protection of Android phones in various scenarios like when the device is boot-up, locked or unlocked, and when the OS is of the old version is inevitable for the business and personal usage.

Cloud technology and security measures

The question of security brings down the difference between the public cloud and the virtual private network. Data encryption in the cloud technology supports the data loss both at the rest and in transit. The roll based access control which is designed for the role assignment; role authorization and transaction authorization reinforce the security measures in a cloud-based environment.

It is the general opinion that the public clouds are designed for the volume and not for the security. The multiple deployment models in the private, public and hybrid cloud enhance the security. The data migration and data restoration services are important for the data security in a cloud environment. Virtualized intrusion detection, prevention systems, virtualized firewalls and virtualized systems security are the components which improve the security in the cloud technologies. The private and public cloud both are doubled up with the data centre security with the use of IAAS to improve the security measures.

Big Data and security measures

The information security or the data security is a vibrant topic for the online services. Encryption data is useless to the outsiders or hackers as it is understood only by the owner of the data. Encrypted data provides end to end security for the input and output of the information. The strong firewall is another big data security tool for the protection of a big volume of data. The strong filters also help to avoid the third parties or unknown data sources breaking the security. Controlling the data through the BI tools and the analytics tools also protect the data. Big Data Training helps the students to understand the practical usage of the big data technology.

IOT and security measures

The revolution of network-connected devices and the hacking tools demand the best security systems. Internet of things is applied to the small and big devices.

The challenges for the IoT devices

  1. The critical functionalities and easy to interrupt through cyber-attack
  2. There are thousands of identical devices and if one device is hacked then it replicates in other devices also,
  3. Any changes in the devices are deployed only within the embedded devices and can’t control through remote software.
  4. If the embedded devices are connected to the internet then it is important that it is protected by the security checks.
  5. Purchase the device from a reputed vendor because the security comes from the production of the devices.
  6. Use the devices in the private network and keep your password of the network safely.
  7. The IOT sensor detects the security and improves the security of the devices.

Why security intelligence is important for the future technologies?

Security intelligence systems use a mix of advanced technologies to tackle the security threats. The security intelligence should take in to account the log management, network visibility, SIEM analysis capabilities, data collection tools, and advanced threat detection tools. As hackers are inventing the next generation techniques to break the network it is important to improve the security measures. The old tools like DLP, SIEM are lacking in terms of visibility and scalability of the security measures in a challenging environment.

So, security intelligence is very much important for the future technologies to have a risk free environment. The evolution of technology brings so many changes which have to be measured with the security measures. The three levels of the cyber threat intelligence are tactical, operational and strategic. In relation to the brand and the technology different methods can be applied to obtain the threat intelligence. Effective security understands the infrastructure and the functionalities of the devices. IOT automation and business analytics are the emerging technologies which contribute to the security intelligence of the multiple devices and the businesses.