For a quick overview of a subject or a breakdown of concepts, SlideShare serves as a go-to platform for many. The recapitulations found in many of the presentations are both concise and informative.
The most popular presentations are the ones that have received the most number of likes and have been viewed more than the other presentations in a particular category.
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AIM brings you the 14 most popular presentations on Artificial Intelligence, Machine Learning. Deep Learning and everything else in between.
1) Artificial Intelligence and Law Overview
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People who are not aware of what artificial intelligence is will find the topic presented in a very simple manner here.
Along with the explanation of what AI is, the two major approaches towards AI are discussed– logic and rules-based approach, and machine learning approach. Special emphasis on the machine learning approach can be seen in the slides devoted to its detailed examination. The examination goes beyond the rudimentary explanation of what machine learning is and presents examples of proxies that seem like machine learning but are not.
The presentation lists examples of AI in the field of law and identifies some of the limitations of AI technology.
2)What is Artificial Intelligence – Artificial Intelligence Tutorial For Beginners
For the uninitiated, this presentation offers an ideal rundown of AI. The question of AI being a threat is raised at the very beginning. However, as the presentation progresses, it discusses the basics necessary for understanding AI. The most basic question of what is artificial intelligence is answered.
A brief history of AI and the discussion on recent advances in the field of AI is also found. The various areas where AI currently sees practical application have been listed. Fascinating uses that AI can be put to in the future are also found in the presentation. The two approaches of achieving AI, machine learning and deep learning, is touched upon.
All in all, this presentation serves as a simple introduction to AI.
3) Why Social Media Chat Bots Are the Future of Communication
An exciting application of AI can be found in chatbots. Here, the limitless scope of chatbots is explored. The various milestones reached by leading players in bot technology such as Facebook, Skype and KIK are enumerated.
The evolution of chatbots and its absorption of more AI in the future is also looked into. E-Commerce is touted as the biggest beneficiary of the advancement in chatbots and that bot technology will owe its rise to services and commerce.
Two tech giants, Facebook and Google, have been pitted against each other based on their ongoing developments in this area and the question of who will emerge as the best is raised.
4) AI and the future of work
This presentation talksabout the far-fetching applicability of AI and ML,and the perils of that applicability. In order to derive a better understanding of this presentation, it is advisable to first watch the original talk.
During the course of the presentation, many examples of how machines can learn and perform any human task that is repetitive in nature are cited.
Other possibilities suggested include the creation of new unheard jobs for human beings as a result of aggressive use of AI and other allied technologies. Qualities that are characteristic only of human beings, may be the basis on which these jobs will be created is also suggested.
It concludes with a message- Ride the train, don’t jump in front of it.
5) AI and Machine Learning Demystified
In this presentation, Carol Smith establishes that AI cannot replace humans. Smith conveys that AI can serve the purpose of enabling human beings in making better decisions.
The slides talk about how the actions of AI are the result of the human inputs going into its programming. An AI’s bias is not its own, but the human bias with which it has been programmed, is emphasised on.
Other issues such as the need for regulations and other considerations within it that require deliberation are also touched upon. The presentation leaves you with a message – Don’t fear AI, Explore it.
6) Study: The Future of VR, AR and Self-Driving Car
Though no descriptive breakdown of topics related to AI is found, the presentation offers interesting numerical insights into many questions. Statistics on three main subjects – artificial intelligence, virtual reality and wearable technology, is provided here.
A variety of questions and the numerical representations of their responses are found under four main categories:
- Will you purchase a self-driving car when they become available?
- Are you concerned with the rise of Artificial Intelligence?
- Is wearable technology part of your daily life?
- Do you own or intend to purchase a Virtual Reality headset in the next twelve months?
From consumer opinions to overall consensus of countries, the numbers show current trends and the possible trends in the future based on increasing development in the mentioned technologies.
7) Artificial Intelligence
There are many who have been introduced to AI only recently due to the buzz surrounding it and may not be aware of the early developments that led to its current status.
This presentation from 2009 offers a simple yet informative introduction to the rudiments of AI. AI’s history and a timeline of all the significant milestones in AI up to 2009 can be found. The presentation also provides an introduction to AI programming languages such as LISP and PROLOG.
For those who would like to have a crash course on the basics of AI in order to catch up with it current trends, this presentation serves the purpose.
8) Solve for X with AI: a VC view of the Machine Learning & AI landscape
While the concepts of AI or ML are not spoken about, light is shed on other important aspects of it. The presentation discusses about how many known tech giants such as Google are bolstering their AI capabilities through mergers and acquisitions.
The role of venture capital(VC) in the landscape of AI and machine learning,and the involvement of VC in the firms that were acquired are mentioned.
Another point highlighted is how large companies are moving towards ML and re-configuring themselves around ML, and how it is not a US-centric phenomenon. Key points have been expressed in the form of self-explanatory graphical representations. Rounding off the presentation is the possible direction that ML can take and a few pointers on achieving success in ML.
9) Deep Learning – The Past, Present and Future of Artificial Intelligence
This presentation provides a comprehensive insight into deep learning. Beginning with a brief history of AI and introduction to basics of machine learning such as its classification, the focus shifts towards deep learning entirely.
Various kinds of networks such as recurrent neural nets and generative adversarial networks have been discussed at length. Emphasis has been given to important aspects of these networks and other mechanisms such as natural language processing (NLP).
Detailed examples of practical applications and the scope of deep learning are found throughout the presentation. However, this presentation may prove difficult for first time learner’s of AI to comprehend.
10)The Future Of Work & The Work Of The Future
The subject of self-learning of robots and machines is explored here.Talking about the fictional Babel fish, it is suggested that the advancements in technology leading to improved learning and translations by machines made the Babel fish a near-real entity.
New ‘power’ values such as speed, networked governance, collaboration and transparency, among others, have been put forth and juxtaposed against older ones that are not fully technology driven.
Going against the popular assumption that robots and machines will replace human beings, the presentation proposes that we are on the brink of the largest job creation period in humanity.
11) Asia’s Artificial Intelligence Agenda
This presentation is a briefing paper by the MIT Technological Review and talks about how the global adoption of AI is being sped up by Asian countries. It suggests that Asia will not only benefit greatly from the rise in AI technology, but will also define it.
The data collected for the review has been summarized in the form of simple info-graphics. They are a numerical reflection of the mood surrounding the adoption of AI across different industries and how it could possibly impact human capital. The review also suggests that while there is awareness about AI in Asia, only a small percentage of companies are investing in it.
Pointers for business leaders in Asia to capitalize on AI is offered in the end along presentation with an info-graphic timeline of the history of AI.
12)10 Lessons Learned from Building Machine Learning Systems- Netflix and10 more lessons learned from building Machine Learning systems-Quora
While they are two separate presentations, they talk about the same subject- machine learning. The presentations are a summary of the analysis of machine learning adopted by two platforms, Netflix and Quora.
In case of Netflix, emphasis has been given to the choice of the right metric and the type of data used for testing and training. It also emphasises the need to understand the dependence between the data used and the models employed. The advice to optimize only areas that matter is offered.
The second presentation on Quora, talks about teaching machines only what is necessary. It stresses on the need the to focus on feature engineering and being thoughtful about the ML infrastructure. Another point it highlights is the combination of supervised and unsupervised being the key in ML application.
13) Design Ethics for Artificial Intelligence
With 135 slides, this presentation provides an exhaustive insight into the creation of an ethically sound AI. An introduction to the subject of User Experience(UX) design is followed by the rules that have to be considered during the designing process.
The chronological progression of UX, beginning with experience design and ending with intelligence design, and the direction in which this process is headed is also discussed.
Supported by powerful visuals, the presentation touches upon many essential considerations such as nature of intelligence, purpose of existence, awareness of self and the need for which the AI is created.
It raises a pertinent point that while creating AI,human beings are creating something that embodies qualities that they lack.
14) Artificial Intelligence
Made for a school competition in 2009, it provides many examples of cutting-edge applications of AI at the time.
Many of the examples, such as mind controlled prosthetic limbs, Ultra Hal Assistant and Dexter- the robot provide a trip down the AI memory lane where the applications of AI seemed like a page out of a sci-fi novel. It presents a list of areas where AI can assist human beings.
It concludes with a series of questions, some of which, are still being debated. Such as machines replacing human beings’ and human unemployment due to the use of machines.
Artificial Intelligence : Artificial Intelligence (AI) is the simulation of human intelligence by machines. 1) The ability to solve problems. 2) The ability to act rationally. 3) The ability to act like humans.What are the 4 techniques based on artificial intelligence and machine learning? ›
In this post, we will go through the top most AI techniques: Heuristics, Natural Language Processing, Artificial Neural Networks, Machine Learning, Support Vector Machines, and Markov Decision Process.What are the 7 types of AI? ›
- Reactive Machines.
- Limited Memory.
- Theory of Mind.
- Artificial Narrow Intelligence (ANI)
- Artificial General Intelligence.
- Artificial Super Intelligence (ASI)
There are a lot of ongoing discoveries and developments, most of which are divided into four categories: reactive machines, limited memory, theory of mind, and self-aware AI.What are the 5 big ideas of AI? ›
In this fun one-hour class, students will learn about the Five Big Ideas in AI (Perception, Representation & Reasoning, Learning, Human-AI Interaction, and Societal Impact) through discussions and games.What are the 7 steps of machine learning? ›
- Data Collection. → The quantity & quality of your data dictate how accurate our model is. ...
- Data Preparation. → Wrangle data and prepare it for training. ...
- Choose a Model. ...
- Train the Model. ...
- Evaluate the Model. ...
- Parameter Tuning. ...
- Make Predictions.
According to the current system of classification, there are four primary AI types: reactive, limited memory, theory of mind, and self-aware. Let's take a look at each type in a little more depth.What is the most common type of AI used today? ›
Limited memory AI learns from the past and builds experiential knowledge by observing actions or data. This type of AI uses historical, observational data in combination with pre-programmed information to make predictions and perform complex classification tasks. It is the most widely-used kind of AI today.What is artificial intelligence give 10 examples? ›
Perhaps the most popular use of A.I. comes in the form of digital smart assistants, such as Siri, Alexa and Google Assistant. These A.I. -powered personal assistants are able to take in your voice commands and translate them into actions, such as adding items to your shopping list or calling a friend.What are 10 ways AI is used today? ›
- Voice Assistants. ...
- Entertainment Streaming Apps. ...
- Personalized Marketing. ...
- Smart Input Keyboards. ...
- Navigation and Travel. ...
- Gamified Therapy. ...
- Self-driving Vehicles. ...
- Facial Recognition Technologies.
Abstract: If John McCarthy, the father of AI, were to coin a new phrase for "artificial intelligence" today, he would probably use "computational intelligence." McCarthy is not just the father of AI, he is also the inventor of the Lisp (list processing) language.What are the 2 types of learning in AI? ›
AI Learning Models: Knowledge-Based Classification
Factoring its representation of knowledge, AI learning models can be classified in two main types: inductive and deductive.
Artificial intelligence is generally divided into two types – narrow (or weak) AI and general AI, also known as AGI or strong AI.What are the benefits of artificial intelligence? ›
- Reduction in Human Error. ...
- Zero Risks. ...
- 24x7 Availability. ...
- Digital Assistance. ...
- New Inventions. ...
- Unbiased Decisions. ...
- Perform Repetitive Jobs. ...
- Daily Applications.
To understand some of the deeper concepts, such as data mining, natural language processing, and driving software, you need to know the three basic AI concepts: machine learning, deep learning, and neural networks.What is AI used for? ›
Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Most AI examples that you hear about today – from chess-playing computers to self-driving cars – rely heavily on deep learning and natural language processing.What are the 17 goals of AI? ›
The 17 Sustainable Development Goals
- No Poverty. ...
- Zero Hunger. ...
- Good Health & Wellbeing. ...
- Quality Education. ...
- Gender Equality. ...
- Clean Water & Sanitation. ...
- Affordable & Clean Energy.
- Find trends, patterns, and associations.
- Discover inefficiencies.
- Execute plans.
- Learn and become better.
- Predict future outcomes based on historical trends.
- Inform fact-based decisions.
- Text AI.
- Visual AI.
- Interactive AI.
- Analytic AI.
- Functional AI.
Currently AI is Used is Following Things/Fields:
Virtual Assistant or Chatbots. Agriculture and Farming. Autonomous Flying. Retail, Shopping and Fashion.
There are three main elements to every machine learning algorithm, and they include: Representation: what the model looks like; how knowledge is represented. Evaluation: how good models are differentiated; how programs are evaluated. Optimization: the process for finding good models; how programs are generated.What are 2 main types of machine learning tasks? ›
Machine Learning is complex, which is why it has been divided into two primary areas, supervised learning and unsupervised learning. Each one has a specific purpose and action, yielding results and utilizing various forms of data.What are the 4 AI process stages? ›
AI is going to evolve in 4 phases: toy, servant, caregiver and parent. We are currently in the late AI toy phase. This can be characterized as automating simple tasks. The Roomba carpet vacuum is a great example.What are the 4 types of data that machine learning can use? ›
Data can come in many forms, but machine learning models rely on four primary data types. These include numerical data, categorical data, time series data, and text data.What are the advantages of machine learning? ›
It is a type of data mining that allows computers to “learn” on their own by analyzing data sets and using pattern recognition. Machine learning has many benefits, including improved accuracy, efficiency, and decision-making.What type of AI is Google? ›
Google Search is a form of narrow AI, as is predictive analytics, or virtual assistants. Artificial general intelligence (AGI) would be the ability for a machine to “sense, think, and act” just like a human.What are the 6 branches of AI? ›
The Major Branches of Artificial Intelligence
Machine Learning. Neural Network. Fuzzy Logic. Natural Language Processing.
Siri is Apple's personal assistant for iOS, macOS, tvOS and watchOS devices that uses voice recognition and is powered by artificial intelligence (AI).Why artificial intelligence is important in modern world? ›
Today, the amount of data that is generated, by both humans and machines, far outpaces humans' ability to absorb, interpret, and make complex decisions based on that data. Artificial intelligence forms the basis for all computer learning and is the future of all complex decision making.How AI is used in education? ›
AI enhances the personalization of student learning programs and courses, promotes tutoring by helping students improve their weak spots and sharpen their skills, ensures quick responses between teachers and students, and enhances universal 24/7 learning access.
Netflix uses artificial intelligence and machine learning to predict which images best engage which viewers as they scroll through the company's many thousands of titles. It is one of the best ways Netflix is utilizing Artificial Intelligence effectively in 2022.What is artificial intelligence with examples PDF? ›
What is Artificial Intelligence? Artificial Intelligence is the development of computer systems that are able to perform tasks that would require human intelligence. Examples of these tasks are visual perception, speech recognition, decision-making, and translation between languages. ❏ Many More!Which device is used for AI? ›
Smart assistants are defined as the devices that are loaded with software and help you to access information, control other devices and perform tasks. These AI based smart assistants use voice commands to deliver the tasks. Examples of a few such smart assistants are Alexa, Siri, Google Assistant and Cortana.How AI can help society? ›
AI can offer accessibility for people with disabilities.
Virtual assistants, including Siri, Alexa, and Cortana, can perform innumerable tasks from making a phone call to navigating…
Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.How do you define artificial intelligence? ›
Artificial intelligence leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind.What is artificial intelligence definition simple? ›
Artificial intelligence (AI) is the ability of a computer or a robot controlled by a computer to do tasks that are usually done by humans because they require human intelligence and discernment.What is artificial intelligence definition PDF? ›
Artificial intelligence (AI) is a branch of computer science. It involves developing computer. programs to complete tasks which would otherwise require human intelligence. AI algorithms can. tackle learning, perception, problem-solving, language-understanding and/or logical reasoning.What is the main aim of artificial intelligence? ›
The objective of general AI is to design a system capable of thinking for itself just like humans do. Currently, general AI is still under research, and efforts are being made to develop machines that have enhanced cognitive capabilities.
Stanford's John McCarthy, seminal figure of artificial intelligence, dies at 84. McCarthy created the term "artificial intelligence" and was a towering figure in computer science at Stanford most of his professional life.
Artificial intelligence is generally divided into two types – narrow (or weak) AI and general AI, also known as AGI or strong AI. More recently a third type has been introduced – conscious AI.What are the advantages and disadvantages of artificial intelligence? ›
Advantages and Disadvantage of Artificial Intelligence.
|Advantages of artificial intelligence||Disadvantages of artificial intelligence|
|1. It defines a more powerful and more useful computers||1. The implementation cost of AI is very high.|
Artificial intelligence (AI) is intelligence - perceiving, synthesizing and infering information - demonstrated by machines, as opposed to intelligence displayed by animals and humans.What are the 5 types of AI? ›
- Text AI.
- Visual AI.
- Interactive AI.
- Analytic AI.
- Functional AI.
Artificial intelligence is shaping the future of humanity across nearly every industry. It is already the main driver of emerging technologies like big data, robotics and IoT, and it will continue to act as a technological innovator for the foreseeable future.