What did I learn from 4.0 Tech Online Bootcamp?
AI
" A.I. is more important than fire or electricity " - Sundar Pichai (CEO, Alphabet)
# AI in Diverse Domains
Lifestyle
Healthcare & Medicine
Food & Agriculture
Banking & Finance
Transportation & Automobiles
E-Commerce
Robotics
Education
Entertainment .....
# AI - Global Economic Impact
AI is estimated to create an additional $13 Trillion of value annually by the year 2030
# AI - New Jobs
Artificial Intelligence To Create 58 Million New Jobs By 2022
# Tech Giants have AI at their Core
Google - Targeted Advertisements (Major source of revenue)
Amazon - Product Recommendations
Neftlix - Content Recommendations
Facebook - Friend Suggestions Targeted Ads
Tesla - Self Driving Cars
Uber - Connecting Drivers to People
Targeted Advertisements (Personalized ads) - When u search for smth on the internet, u will see the product on the page. There will be links such as from Amazon, Alibaba and etc. They will pay Google to make their products available while sea
Why Targeted: U will search for notebook and you might be interested in buying the notebook. They will show u the products instead of their full specifications
* Google Tracks your data. It knows what is your search history
# What is AI? (Branch of CS)
- Creation of Intelligent Machines
- Programming machines to exhibit intelligence
- Machine identifying patterns and learning by itself
# Types of AI
< Search-based AI >
* Puzzles(Games): They program machines to solve more difficult puzzles in a fraction of seconds.
* Google Maps: When u search for a location, Google will not give u a random route, but the best possible route based on: time, distance and etc.
- Machines will be programmed to behave more intelligently and smarter than u and us.
< Knowledge-based AI >
* Aarogya Setu app (famous while covid)- It will ask u a questions, based on the answers u are giving, it will ask questions. In the end it will give u recommendations. It will act as the part job of doctor. It is not replacing doctor. Behaving intelligently.
* How we do these app: We call out well-educated & experienced doctors and professionals. And we will program according to the instructions guidance that they will give.
* We are emberring certain knowledge and Machine is interacting with u intelligently
* We also have to program the machine to draw the process and conclusions out of the knowledge
If Jack wasn't sick, he would've gone to school
Jack would've gone to school or hospital today, but not both
Jack went to hospital today.
Jack did not go to school today
Jack is sick today
< Uncertainty-based AI >
" AI in Uncertain Environments "
- We use some applications such as weather to show the predictions. The rate of predictions indicates how likely it is going to occur.
- We don't have perfect knowledge. We have certain parameters like humidity. Based on parameters we will try to figure it out. We program the machines how to behave intelligently in these uncertain conditions and make conclusions/inferences. (Probability-based Artificial Intelligence)
- A store assistant suggesting clothes based on your interests and preferences.
Ordinary life Example: when u are the first time visitor, he will observe you based what u are looking for. If u are the frequent visitor, he knows what types of product u like or dislike.
- Apps like Amazon: They will show the recommended products for you. Because you might have visited the website previously, searched for certain products, added to your wishlist, liked few of them. These apps will track all of your data, observe certain patterns and behave intelligently.
Machine Learning
- A subfield of AI that gives computers the ability to learn without being explicitly programmed.
* Amazon app which is behaving according to certain patterns is an example of Machine learning.
* We are not writing the program, it is identifying the patterns according to the data that u provided and browsing history & behaving intelligently
* Machine Learning is a part of Artificial Intelligence
How do babies learn? - Through Patterns
They identify the patterns while someone is speaking such as dad, mam, and learn accordingly.
" Observations - Sense Organs "
How do Humans observe Patterns?
- Get Information through Sense Organs
Process it in the Brain
" Observations - Data " (Machines way of learning)
- Similarly, computers are also capable of identify patterns
They identify patterns from the DATA we provide
- Any information that is stored electronically: Image, Text File, Video, Emails, Messages, etc.
" Patterns > Programs (Intelligent) "
Data > ML Software > Program (Intelligent)
Example: Face Recognition built upon Machine Learning Technology
- It will ask u to register your face
- While registering your face, it will ask you return your face & take your picture with different multiple triangles.
# You are giving the date to the software (data - your face)
- It knows that it is you. There are pictures of others too. It holds a massive base of pictures & recognizes u based on the data that u provided.
- When we feed this data into machine learning software, it will give us an intelligent program which is a Face Recognition Program based on these patterns.
- Every time you open your phone, if it is you, it will unlock your phone. If another person puts his face, it will not unlock. Says, face is not matching, this is not you.
- It will work all the time, even certain changes are made such as hair cut done, washing your hair, shave. Among all photos on the database, it will identify and recognize you according to the patterns.
What is exactly happening here: " Prediction Function "
Data > ML Software > Program (Intelligent)
New Inputs > Prediction Function > Predicted Output
Difference: Traditional Programs vs ML Software
Input > Traditional Program > Output
Seeds - Algorithms
Nutrients - Data
Gardener - You
Plants - Programs
< Speech To Text > (Voice Recognition & Assistants)
Underlying Patterns: Sounds, Modulations, etc
Why Now?
" Computing Power "
- Exponential Growth in Computing Power
- Specialized processors (GPUs)
Historically, data was stored in:
Clay Tablets
Manuscript Stories
Paintings
Computers
Cloud
" Cloud Storage " - Storing large amounts of data digitally enables computers to identify patterns in the data
- Total number of Websites from 1991 to 2019 > 1.72 billion websites
- Over 2.5 Quintillion (10)18 Bytes of Data is Created Each Day!
Instagram - 277,777 stories
Neftlix - 694,444 Hours of video
YouTube - 4,500,500 Videos
Twitter - 511,200 Tweets
Ride - 9,772 Rides
Deep Learning
- part of Machine Learning. Similar to how ML is a part of AI.
- certain types of techniques in which we identify patterns in huge volumes of data
< Artificial Intelligence Networks > (ML algorithms)
- Artificial Neural Networks are based on the ideas of how the human brain works
- Gets Inputs from Sense Organs
- Processes the Inputs
- Send Signals to other Neurons
- Gets Inputs from the Data Provided
- Processes the Inputs
- Send Signals to other Nodes
Face > Processing (Neuron & Nodes) > Identifies whether it is you or Not you
Data > ML Software > Program (Intelligent) 10
New Inputs > Prediction Function > Predicted Output
* The more data you give, the better predictions you will get
The quality & quantity of data is more important
Practice: https://teachablemachine.withgoogle.com/train
Data Science
- the science of extracting knowledge and insights from data
Example: It takes the data of a huge amount of orders and instead of presenting the output, it will make intelligent business decisions.
ML - is a field of study that gives computers the ability to learn
Data Scientist
ML engineer
Data Analyst
ML Researcher
Data Acquisition - Logging & Manual Labeling & User generated
Data Engineering - Move/Store Data & Build Infrastructure & Reliable Data Flow
Data Wrangling - Cleaning & Anomaly Detection & Data Transformation
Modeling - ML Algorithms & Training & Evaluation
Deployment - Interpreting Results & Packaging & Shipping
Business Analytics - Visualisations & Insights
Introduction to Cyber Security
- 30,000 Websites are hacked worldwide every day
- 280 Days - Average time to identify and contain a data breach
" Cyber Security is the greatest threat to every company in the world " - Ginni Rometty (Former CEO, IBM)
* Malicious Software / Malware - any software created to cause damage
< Social Engineering >
- an art of Tricking people into doing things YOU want.
" Phishing " (Online forms of Social Engineering)
- Leading cause for 90% data breaches
- 92% malware delivered via email
# Phishing - spam messages & emails
# Phishing desks are set by companies to their employees to understand how suspectible they are to phishing attacks.
< Ramsomware > Digital Kidnapping
- you will click the link, download the malicious file, and thereby it loads your information & data
- and tells you unless u pay certain amount of money, your information will be locked.
Global Impacts while Covid situation: 2020
- Online Classes / Remote Working
- Attacks on Academic Institutions and Business Organizations
- 36% of victims paid the ransom
- 17% of victims who paid a ransom never recovered their data
< Technology Hacks >
" Telecom Infrastructure " - Making international calls freely by finding flaws in the existing telecom infrastructure during the late '60s and early '70s.
" The Two Steves of Apple " (Unconventional thinking) - Built a blue box for $100 worth of parts that can control hundreds of billions of dollars of infrastructure in the entire Telephone network in the whole world.
< Cameras >
"I'm in your baby's room:" A hacker took over a baby monitor and broadcast threats, parents say
< Wearables >
- Your daily step count isn't the only information hackers can steal from wearables. Hackers can exploit smartwatches, fitness trackers to steal your ATM PIN. Kids' Smartwatches are a Security Nightmare Despite Years of Warnings.
< Medical Devices >
< 1.4 Million Jeeps recalled > (Cars)
- Hackers will control cars, cars will drive under the control of hackers and cause accidents + issues.
< Smart Rifles >
- Took control over the Rifle and able to change the Target
< Drones >
- DJI Drone Hack Opens Up Flight and Video Records to Threat Actors
- Drones are quickly becoming a cybersecurity nightmare
< Aeroplanes >
- Computer expert hacked into the plane and made it briefly fly sideways
< Satellites >
- NASA Computers Hacked By Intruders
< Critical Infrastructure > Nation state-sponsored Attacks
Rise of Threats = Rise of Opportunities
- More Cyber Security Job Openings in 2021
- Skill Gap: Fewer than 1 in 4 applicants are qualified for cyber security positions
- Mandatory Cyber Security Knowhow: Every IT position is also a cybersecurity position now and needs to be involved with protecting and defending apps, data devices, infrastructure, and people.
- 0% unemployment rate in cybersecurity / Endless opportunities in this field
< Frameworks > - To Counter The Current State of Cyber Threats
S - Spoofing
T - Tampering
R - Repudiation
I - Info Disclosure
D - Denial of Service
E - Elevation of Privlege
" Spoofing " - Impersonating something or someone else (Social Engineering)
" Tampering " - Modifying data or code without authorization/permission (Ransomware)
" Repudiation " - Denying that an action or an event has occurred
" Information Disclosure " - Exposing information to someone not authorized to see it
" Denial of Service " - Deny or degrade service to authorized users
" Elevation of Privileges " - Gain capabilities without prop authorization
< Approaches > { Offense informs Defense }
- Threat Modeling - Analyzing and identifying attacks before they happen
- Penetration Testing - Evaluating the security by safely performing attacks
- MITRE ATT& CK - Knowledge base of adversary tactics and techniques based on real-world Cyber attacks
< Responsibly Reporting Threats >
" Vulnerability Disclosure Policies " - Find and report vulnerabilities responsibly and get rewarded.
< Bug Bounties > India has been leading the world in the number of hackers every year constantly since the last 5 years.
In 2016, a total of 205 Indian security researchers have participated in such programs and received ...$ as bounties.
hackers - Steven Levy
Hackers Internet's Immune System - Keren Elazari
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