Mohammed Lateef Student Ambassador

147

Currently pursuing TYBSC-IT

BLOCKCHAIN DAY 1 ASSIGNMENT

Q1. What is your understanding of Blockchain?
Ans:- Blockchain is defined as a chain or record stored in the forms of blocks which are controlled by no single authority. It is a combination of distributed database systems and cryptography which creates an immutable ledger. Distributed database systems provide decentralization whereas cryptography provides security in the form of hash algorithms.

Q2. What is the core problem, blockchain trying to solve?
Ans:- (1) Blockchain addresses the problem of data loss due to hardware or connectivity issues.
(2) Blockchain addresses the problem of data corruption due to intermittent hardware or connectivity issues.
(3) Blockchain addresses the problem of data security and trust by making the ledger public.

Q3. Few Features of Blockchain
Ans:- These are various features of blockchain -
1 Decentralization
2 Immutable
3 Validation
4 Enhanced Security
5 Authentication
6 Tamper-proof

Q4. What does a block contain?
Ans:- A block represents the ‘present’ and contains information about its past and future. Each time a block is completed it becomes part of the past and gives way to a new block in the blockchain. The completed block is a permanent record of transactions in the past and the new transactions are recorded in the current one.

Q5. How can verifiability be achieved in a blockchain?
Ans:- The copy of the data which is stored in one block is distributed to all other blocks, if the data is changed in any of the block the data can be made proper from the remaining blocks. So, the verifiability of the blockchain is achieved.

What is a Full Stack Developer?


Full stack developers are jacks-of-all-trades.
The full stack developer. The role was popularized seven years ago by Facebook’s engineering department.
The idea is that a full stack developer can work cross-functionally on the full “stack” of technology, i.e. both the front end and back end.
Full stack developers offer the full package.

“Working on both the server side and client side professionally opens more opportunities” But, of course, full stack development isn’t without its challenges. “To make an analogy with food, you can be good at cooking or good at baking, but mastering both takes time and experience. And I’m not talking about following a recipe, anyone can do that. I’m talking about having the ingredients to prepare something truly good.”

SKILLS AND TOOLS

Full stack developers work, like back-end devs, on the server side of web programming, but they can also fluently speak the front-end languages that control how content looks on a site’s user-facing side. They’re jacks-of-all-trades.

To illustrate the increasing complexity of full stack development, here’s an example of what a full stack might have looked like in recent years, compared to the current moment:

What is a Back-End Developer?

So what makes the front end of a website possible? Where is all that data stored? This is where the back end comes in.
The back end of a website consists of a server, an application, and a database.

A back-end developer builds and maintains the technology that powers those components which, together, enable the user-facing side of the website to even exist in the first place.

SKILLS AND TOOLS

In order to make the server, application, and database communicate with each other, back-end devs use server-side languages like PHP, Ruby, Python, Java, and .Net to build an application, and tools like MySQL, Oracle, and SQL Server to find, save, or change data and serve it back to the user in front-end code.

Back-end devs use these tools to create or contribute to web applications with clean, portable, well-documented code. But before writing that code, they need to collaborate with business stakeholders to understand their particular needs, then translate those into technical requirements and come up with the most effective and efficient solution for architecting the technology.

What Is a Front-End Developer?

Front-end web development, also known as client-side development is the practice of producing HTML, CSS and JavaScript for a website or Web Application so that a user can see and interact with them directly.
The challenge associated with front end development is that the tools and techniques used to create the front end of a website change constantly and so the developer needs to constantly be aware of how the field is developing.

The objective of designing a site is to ensure that when the users open up the site they see the information in a format that is easy to read and relevant. This is further complicated by the fact that users now use a large variety of devices with varying screen sizes and resolutions thus forcing the designer to take into consideration these aspects when designing the site. They need to ensure that their site comes up correctly in different browsers (cross-browser), different operating systems (cross-platform) and different devices (cross-device), which requires careful planning on the side of the developer.


HTML, CSS, & JavaScript:
A front-end developer architects and develops websites and applications using web technologies (i.e., HTML, CSS, DOM, and JavaScript), which run on the Open Web Platform or act as compilation input for non-web platform environments (i.e., React Native).

Web development is the work involved in developing a website for the Internet (World Wide Web) or an intranet (a private network).[1] Web development can range from developing a simple single static page of plain text to complex web-based internet applications (web apps), electronic businesses, and social network services.

A more comprehensive list of tasks to which web development commonly refers, may include web engineering, web design, web content development, client liaison, client-side/server-side scripting, web server and network security configuration, and e-commerce development.

There are three kinds of web developer specialization: 
1. front-end developer
2. back-end developer
3. full-stack developer.
Front-end developers are responsible for behavior and visuals that run in the user browser, while back-end developers deal with the servers.

What type of AI is Jarvis?

Mark Zuckerberg has ended 2016 having completed his personal challenge to build a Jarvis-style AI to run his home.

He announced at the start of the year that he wanted to build a simple AI that could control his home, including his lights, temperature, appliances, music and security. He also wanted it to "learn his tastes and patterns, learn new words and concepts, and even entertain Max" (his daughter.)

"For assistants like Jarvis to be able to control everything in homes for more people, we need more devices to be connected and the industry needs to develop common APIs and standards for the devices to talk to each other," Zuckerberg continued.

From there, he taught Jarvis to respond to text before enabling voice recognition. This began with simple keywords such as "bedroom", "lights", and "on" and evolved to be more specific to each room. He then moved onto vision and facial recognition and later, mobile.

What is Jarvis AI? Do you all know?

• Jarvis is a AI .
• "J.A.R.V.I.S. (Stands for Just A Rather Very Intelligent System), also stylized as JARVIS, or

• Jarvis, is a highly advanced computerized A.I. developed by , and was voiced by actor , to manage almost everything, especially matters related to technology, in Tony's life.

• He was based on hardi who was the Stark family's butler.
• He acts like Tony's best friend when it comes to his personal life and other secret matters, that are enclosed only with Tony and him."

4 Machine Learning examples from day to day life

1. Virtual Personal Assistants 

Siri, Alexa, Google Now are some of the popular examples of virtual personal assistants. As the name suggests, they assist in finding information, when asked over voice. All you need to do is activate them and ask “What is my schedule for today?”, “What are the flights from Germany to London”, or similar questions. For answering, your personal assistant looks out for the information, recalls your related queries, or send a command to other resources (like phone apps) to collect info. You can even instruct assistants for certain tasks like “Set an alarm for 6 AM next morning”, “Remind me to visit Visa Office day after tomorrow”.

Virtual Assistants are integrated to a variety of platforms. For example:

• Smart Speakers: Amazon Echo and Google Home
• Smartphones: Samsung Bixby on Samsung S8
• Mobile Apps: Google Allo

2. Predictions while Commuting

Traffic Predictions: We all have been using GPS navigation services. While we do that, our current locations and velocities are being saved at a central server for managing traffic. This data is then used to build a map of current traffic. While this helps in preventing the traffic and does congestion analysis, the underlying problem is that there are less number of cars that are equipped with GPS. Machine learning in such scenarios helps to estimate the regions where congestion can be found on the basis of daily experiences.

3. Videos Surveillance

Imagine a single person monitoring multiple video cameras! Certainly, a difficult job to do and boring as well. This is why the idea of  training computers to do this job makes sense.

The video surveillance system nowadays are powered by AI that makes it possible to detect crime before they happen. They track unusual behaviour of people like standing motionless for a long time, stumbling, or napping on benches etc. 

4. Social Media Services

From personalizing your news feed to better ads targeting, social media platforms are utilizing machine learning for their own and user benefits. Here are a few examples that you must be noticing, using, and loving in your social media accounts, without realizing that these wonderful features are nothing but the applications of ML.

•People You May Know: Machine learning works on a simple concept: understanding with experiences. Facebook continuously notices the friends that you connect with, the profiles that you visit very often, your interests, workplace, or a group that you share with someone etc. On the basis of continuous learning, a list of Facebook users are suggested that you can become friends with.

•Face Recognition: You upload a picture of you with a friend and Facebook instantly recognizes that friend. Facebook checks  the poses and projections in the picture, notice the unique features, and then match them with the people in your friend list. The entire process at the backend is complicated and takes care of the precision factor but seems to be a simple application of ML at the front end.

•Similar Pins: Machine learning is the core element of Computer Vision, which is a technique to extract useful information from images and videos. Pinterest uses computer vision to identify the objects (or pins) in the images and recommend similar pins accordingly.

HOW CAN AI BE DANGEROUS?
Most researchers agree that a superintelligent AI is unlikely to exhibit human emotions like love or hate, and that there is no reason to expect AI to become intentionally benevolent or malevolent. Instead, when considering how AI might become a risk, experts think two scenarios most likely:

1. The AI is programmed to do something devastating: Autonomous weapons are artificial intelligence systems that are programmed to kill. In the hands of the wrong person, these weapons could easily cause mass casualties. Moreover, an AI arms race could inadvertently lead to an AI war that also results in mass casualties. To avoid being thwarted by the enemy, these weapons would be designed to be extremely difficult to simply “turn off,” so humans could plausibly lose control of such a situation. This risk is one that’s present even with narrow AI, but grows as levels of AI intelligence and autonomy increase.

2. The AI is programmed to do something beneficial, but it develops a destructive method for achieving its goal: This can happen whenever we fail to fully align the AI’s goals with ours, which is strikingly difficult. If you ask an obedient intelligent car to take you to the airport as fast as possible, it might get you there chased by helicopters and covered in vomit, doing not what you wanted but literally what you asked for. If a superintelligent system is tasked with a ambitious geoengineering project, it might wreak havoc with our ecosystem as a side effect, and view human attempts to stop it as a threat to be met.

As these examples illustrate, the concern about advanced AI isn’t malevolence but competence. A super-intelligent AI will be extremely good at accomplishing its goals, and if those goals aren’t aligned with ours, we have a problem. You’re probably not an evil ant-hater who steps on ants out of malice, but if you’re in charge of a hydroelectric green energy project and there’s an anthill in the region to be flooded, too bad for the ants. A key goal of AI safety research is to never place humanity in the position of those ants.

Where is Artificial Intelligence Used Today?

Artificial Intelligence (AI) is brining a drastic changes in technological fields, where it can be implemented to automate the system for more efficiency and performance. AI is now getting used in multiple fields from simply your mobile phone to diagnosing the diseases providing a high-performance and accurate system work with efficiency.
Here we will discuss what are major things and fields AI is used and under process to get fully implemented and launched in up coming years. Here we will discuss mainly about the fields or industries where AI is playing an important role helping humans to work with better performance and efficiency without help of humans.

Currently AI is Used is Following Things/Fields:
■Virtual Assistant or Chatbots
■Agriculture and Farming
■Autonomous Flying
■Retail, Shopping and Fashion
■Security and Surveillance
■Sports Analytics and Activities
■Manufacturing and Production
■Live Stock and Inventory Management
■Self-driving Cars or Autonomous Vehicles
■Healthcare and Medical Imaging Analysis
■Warehousing and Logistic Supply Chain