The Top 10 Machine Learning Algorithms (INFOGRAPHIC)

 

Insights On The Increasing Importance Of Artificial Intelligence, Machine Learning, And Automation In Cybersecurity (VIDEO)

In this video Cybersecurity Executive, Advisor, Author, and Global Influencer Shira Rubinoff talks with Grady Summers, EVP Product at Sailpoint about why artificial intelligence, machine learning and automation are becoming increasingly important in cybersecurity

To learn more about all the options available to you for meeting your organization’s data protection and network security requirements (including security posture and risk assessments, and awareness training and employee education programs) ... simply ask us at FREE Network Security Sourcing And Design Support. It's as easy as 1, 2, 3.

What Is The Most Important Question For Data Science (And Digital Transformation)?

With so many buzzwords surrounding AI and machine learning, understanding which can bring business value and which are best left in the lab to mature is difficult. While machine learning offers significant power in driving digital transformations, a business must start with the right questions and leave the math to the development teams.

What Is The Most Important Question For Data Science (And Digital Transformation)?

And here’s some valuable advice - - every CIO should have this FREE resource in their toolbox...saves a ton of time, money, and effort.

Covers dedicated bandwidth circuits, every flavor of ethernet and fiber, multi-site connectivity (e.g. MPLS, SDWAN), business VoIP systems, wireless networks, cloud computing, unified communications, network performance management, network security assessments and strategies, and much more.

Just ask at the links below and we'll take it from there....it’s as easy as 1, 2, 3.

Free Network Sourcing And Design Help {Network Connectivity & Design, MPLS Network Engineering, Network Management & Security, IoT Ecosystems}

OR.....

Business VoIP Solution And More {Business VoIP, Unified Communications, SDWAN, Cloud Computing, Contact Center Technology}

Preparing For A Future With Artificial Intelligence

It’s often said that history repeats itself.  Many times in the course of our history, new technologies have wiped out entire workforces.  For upcoming generations, the rise of artificial intelligence represents the next great solution and the next great hurdle. Robin believes how we respond to this challenge, could be our defining moment as a species.

Robin Winsor is a technology leader and entrepreneur who has led several organizations from start-up to international success. Before joining Cybera as President and CEO in 2010, Winsor invented and developed the world’s first direct digital x-ray system, and holds multiple patents in the medical, well-logging and seismic industries. He is a past recipient of a Manning Innovation Award, the Ernst & Young Entrepreneur of the Year Award, and the Queen’s Diamond Jubilee Medal for outstanding service to Canada. He is a staunch advocate for transparency and lower cost information sharing through advancements in technology.


This talk was given at a TEDx event using the TED conference format but independently organized by a local community.

Machine Learning vs Deep Learning vs Artificial Intelligence

This Machine Learning vs Deep Learning vs Artificial Intelligence video will help you understand the differences between ML, DL and AI, and how they are related to each other. The tutorial video will also cover what Machine Learning, Deep Learning and Artificial Intelligence entail, how they work with the help of examples, and whether they really are all that different.

This Machine Learning Vs Deep Learning Vs Artificial Intelligence video will explain the topics listed below:

1. Artificial Intelligence example ( 00:29 )
2. Machine Learning example ( 01:29 )
3. Deep Learning example ( 01:44 )
4. Human vs Artificial Intelligence ( 03:34 )
5. How Machine Learning works ( 06:11 )
6. How Deep Learning works ( 07:09 )
7. AI vs Machine Learning vs Deep Learning ( 12:33 )
8. AI with Machine Learning and Deep Learning ( 13:05 )
9. Real-life examples ( 15:29 )
10. Types of Artificial Intelligence ( 17:50 )
11. Types of Machine Learning ( 20:32 )
12. Comparing Machine Learning and Deep Learning ( 22:46 )
13. A glimpse into the future ( 25:46 )

A Brief Introduction to Artificial Intelligence

We all know that Siri, Google Now, and Cortana are all intelligent digital personal assistants on various platforms (iOS, Android, and Windows Mobile). In short, they help find useful information when you ask for it is using your voice; you can say "Where's the nearest Indian restaurant?", "What's on my schedule today?", "Remind me to call Mom or Dad at eight o'clock," and the assistant will respond by finding information, relaying information from your phone, or sending commands to other apps.

AI is important in these apps, as they collect information on your requests and use that information to better recognize your speech and serve you results that are tailored to your preferences. Microsoft says that Cortana "continually learns about its user" and that it will eventually develop the ability to anticipate users' needs. Virtual personal assistants process a huge amount of data from a variety of sources to learn about users and be more effective in helping them organize and track their information.

Your smartphone, calculator, video games, car, bank & your house all use artificial intelligence daily; sometimes it's obvious what its' doing, like when you ask Siri to get you directions to the nearest gas station. Sometimes it's less obvious, like when you make an abnormal purchase on your credit card and don't get a fraud alert from your bank. AI is everywhere, and it's making a huge difference in our lives every day.

So, we can say that Artificial Intelligence (AI) is the branch of computer sciences that emphasizes the development of intelligence machines, thinking and working like humans. For example, speech recognition, problem-solving, learning and planning. Today, Artificial Intelligence is a very popular subject that is widely discussed in the technology and business circles. Many experts and industry analysts argue that AI or machine learning is the future - but if we look around, we are convinced that it's not the future - it is the present.

Yes, the technology is in its initial phase and more and more companies are investing resources in machine learning, indicating a robust growth in AI products and apps soon. Artificial intelligence or machine intelligence is the simulation of human intelligence processes by machines, especially computer systems.

What is the use of AI?

Vision systems. The need to interpret, fully understand and make sense of visual input on the computer, i.e. AI is used to try and interpret and understand an image - industrial, military use, satellite photo interpretation.

What is the purpose of AI?

When AI researchers first began to aim for the goal of artificial intelligence, a main interest was human reasoning... The specific functions that are programmed to a computer may be able to account for many of the requirements that allow it to match human intelligence

What is an ASI artificial intelligence?

A superintelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds.

What is the goal of AI?

Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving". General intelligence is among the field's long-term goals.

What are the different types of AI?

We need to overcome the boundaries that define the four different types of artificial intelligence, the barriers that separate machines from us - and us from them.

Type I AI: Reactive machines
Type II AI: Limited memory
Type III AI: Theory of mind
Type IV AI: Self-awareness

Is computer vision part of AI?

Artificial intelligence and computer vision share other topics such as pattern recognition and learning techniques. Consequently, computer vision is sometimes seen as a part of the artificial intelligence field or the computer science field in general.

Is machine learning the same as artificial intelligence?

Increasingly, machine learning (ML) and artificial intelligence (AI) are cropping up as solutions for handling data. The two are often used interchangeably, and although there are some parallels, they're not the same thing.

What are the fields of artificial intelligence?

· List of applications
· Optical character recognition.
· Handwriting recognition.
· Speech recognition.
· Face recognition.
· Artificial creativity.
· Computer vision, Virtual reality and Image processing.
· Diagnosis (AI)
· Game theory and Strategic planning.

How important is Artificial Intelligence?

AI is the machines which are designed and programmed in such a manner that they and think and act like a human. Artificial Intelligence becomes the important part of our daily life. Our life is changed by AI because this technology is used in a wide area of day to day services.

For most of us, the most obvious results of the improved powers of AI are neat new gadgets and experiences such as smart speakers, or being able to unlock your iPhone with your face. But AI is also poised to reinvent other areas of life. One is health care. Hospitals in India are testing software that checks images of a person's retina for signs of diabetic retinopathy, a condition frequently diagnosed too late to prevent vision loss. Machine learning is vital to projects in autonomous driving, where it allows a vehicle to make sense of its surroundings. Artificial intelligence is already present in plenty of applications, from search algorithms and tools you use every day to bionic limbs for the disabled.

Sometimes it seems like every other website, app, or productivity tool is citing AI as the secret ingredient in their recipe for success. What's less common is an explanation of what AI is, why it's so cool, and how companies are leveraging it to provide better user experiences. If you don't know much about AI, the absence of an explanation can be confusing. Today, the field of artificial intelligence is more vibrant than ever and some believe that we're on the threshold of discoveries that could change human society irreversibly, for better or worse.

By Kranti Gaurav

What Are The Challenges Of Machine Learning In Big Data Analytics?

Machine Learning is a branch of computer science, a field of Artificial Intelligence. It is a data analysis method that further helps in automating the analytical model building. Alternatively, as the word indicates, it provides the machines (computer systems) with the capability to learn from the data, without external help to make decisions with minimum human interference. With the evolution of new technologies, machine learning has changed a lot over the past few years.

Let us Discuss what Big Data is?

Big data means too much information and analytics means analysis of a large amount of data to filter the information. A human can't do this task efficiently within a time limit. So here is the point where machine learning for big data analytics comes into play. Let us take an example, suppose that you are an owner of the company and need to collect a large amount of information, which is very difficult on its own. Then you start to find a clue that will help you in your business or make decisions faster.

Here you realize that you're dealing with immense information. Your analytics need a little help to make search successful. In machine learning process, more the data you provide to the system, more the system can learn from it, and returning all the information you were searching and hence make your search successful. That is why it works so well with big data analytics. Without big data, it cannot work to its optimum level because of the fact that with less data, the system has few examples to learn from. So we can say that big data has a major role in machine learning.

Instead of various advantages of machine learning in analytics of there are various challenges also.

Let us discuss them one by one:

• Learning from Massive Data: With the advancement of technology, amount of data we process is increasing day by day. In Nov 2017, it was found that Google processes approx. 25PB per day, with time, companies will cross these petabytes of data. The major attribute of data is Volume. So it is a great challenge to process such huge amount of information. To overcome this challenge, Distributed frameworks with parallel computing should be preferred.

• Learning of Different Data Types: There is a large amount of variety in data nowadays. Variety is also a major attribute of big data. Structured, unstructured and semi-structured are three different types of data that further results in the generation of heterogeneous, non-linear and high-dimensional data. Learning from such a great dataset is a challenge and further results in an increase in complexity of data. To overcome this challenge, Data Integration should be used.

•  Learning of Streamed data of high speed: There are various tasks that include completion of work in a certain period of time. Velocity is also one of the major attributes of big data. If the task is not completed in a specified period of time, the results of processing may become less valuable or even worthless too. For this, you can take the example of stock market prediction, earthquake prediction etc. So it is very necessary and challenging task to process the big data in time. To overcome this challenge, online learning approach should be used.

• Learning of Ambiguous and Incomplete Data: Previously, the machine learning algorithms were provided more accurate data relatively. So the results were also accurate at that time. But nowadays, there is an ambiguity in the data because the data is generated from different sources which are uncertain and incomplete too. So, it is a big challenge for machine learning in big data analytics. Example of uncertain data is the data which is generated in wireless networks due to noise, shadowing, fading etc. To overcome this challenge, Distribution based approach should be used.

• Learning of Low-Value Density Data: The main purpose of machine learning for big data analytics is to extract the useful information from a large amount of data for commercial benefits. Value is one of the major attributes of data. To find the significant value from large volumes of data having a low-value density is very challenging. So it is a big challenge for machine learning in big data analytics. To overcome this challenge, Data Mining technologies and knowledge discovery in databases should be used.

The various challenges of Machine Learning in Big Data Analytics are discussed above that should be handled very carefully. There are so many machine learning products, they need to be trained with a large amount of data. It is necessary to make accuracy in machine learning models that they should be trained with structured, relevant and accurate historical information. As there are so many challenges but it is not impossible.

By Gunjan Dogra

The Benefits Of Artificial Intelligence In The Workplace

Artificial Intelligence is quite a trending topic in modern technology with many businesses adopting its use in their daily operations while others are skeptical about its relevance in the workplace. Let me show you the various benefits of AI to the workplace and how it can make your business grow as well as save time and money.

Simplification Of The Recruitment Process....

Human Resource Departments are faced with the task of hiring staff which is quite daunting, frustrating and equally expensive, with personnel having to shift through a large number jobs applications for a relatively few vacancies, but this scenario is gradually becoming a thing of the past with the use of machine intelligence i.e. Artificial intelligence.

AI reduces the stress related to the hiring process through the use of the following ways:

Interesting job descriptions are written by recruiters through the use software known as Textio. This augmented writing platform compiles various job postings and puts forward to consideration suitable content to encourage the submission of more applications from job seekers.

Candidates for various job vacancies can schedule their interviews, allowing them to choose a time must suitable for them and also provides a chance to reschedule. All these are possible through the use of the Montage software.

AI powered software such as Stella match suitable candidates to jobs through the tracking of experiences, credentials and qualities sought for by employers.

Removal Of Repetitive Tasks In Daily Business Operations....

Scheduling, rescheduling and cancelling meetings are quite stressful to administrative staff but the use of tools such as X.ai helps by performing these tasks diligently.

Recording, transcribing and sharing notes during meetings are also tasks which can be handled by artificial intelligence.

Improvement In Handling Issues Related To Sales, Marketing and Customer Service....

Chatbots are forms of artificial intelligence that can help with support outside the company.They gain experience from real sales and customer reps and use this to assist customers in purchasing goods and services. Questions regarding marketing and customer relationship management (CRM) can also be handled by GrowthBot through the mining of data, both of the public and the company.

The Identification Of Security Risks And Protection Of Data....

Financial institutions such as banks apply AI based technology to point out security risks and protect data. Examples of software which make the use of Ai in such cases include Darktrace, Exabeam and SparkCognition.

Increased Productivity....

With AI handling most of the mundane and repetitive tasks at the workplace, workers are free to channel their efforts to more important tasks thus increasing productivity.

Productivity could also be boosted and monitored by machine intelligence by helping them discover areas that have high labour costs and other obstacles to increased efficiency.

Will Artificial Intelligence Replace Humans In The Workplace?

With the above examples, some individuals might be tempted to think about losing their jobs to AI powered tools since most tasks in the workplace are getting automated gradually, but their fears are unfounded as human input is indispensable despite the presence of artificial intelligence.

Artificial Intelligence basically handles tasks which could affect productivity and allows workers to be action-oriented and gives them the chance to be more creative.

By Abiodun Adewusi

Afterlife Bots - A Dead Man's Petition

No, neither am I a Ted-famous Tech geek spiritual guru nor am I in contact with the afterlife. I am just fascinated by the buzzwords "Machine Learning" and "AI" and a little overwhelmed by the number of articles mentioning those words on my news feed.

I remember reading a line in a news article that "Bots are getting better at imitating humans". Why not hire one and decrease workload by 50%. Well, I suppose we are working towards it.

Google recently announced that their AI-enabled assistant (with 6 voices) can book a hair-cut appointment seamlessly (Well I want a shave as well, and I want it to go and do grocery shopping handpicking the freshest tomatoes from the lot).

Jokes apart: kudos to the team of brilliant scientists, engineers, and others who are working day and night to make this happen.

Coming back to my original story.

Let's start with Human life (and relationships) - Data Gathering

"Quite a digital world". We are capturing and storing our personal life events as much as we can digitally (Thanks to social media, external hard disks, and pen-drives). Why not store our entire life in a 1000 Petabyte storage device. Capture every second - actions, events, habits, decisions, etc.

Imagine if we can see and experience our parents' childhood or see "What all Mahatma Gandhi did in his entire life". Interesting right?

We all know how quickly robotics, machine learning, and AI are evolving.

What if we combine robotics, machine learning, and human life data? Can we create a human replica bot which would respond similarly, make decisions similarly, have similar habits basis the 1000 Petabyte data fed. All in all, can that bot be my replacement after my death?. Can it be my AFTER-LIFE BOT?

Literally, nothing can replace a dead human being. I was not fortunate to see my grandfather or meet him. But will my great grand/grandkids know about me? The answer is I do not know. We all are striving hard to leave a legacy behind us. Why not use robots and machine intelligence to duplicate ourselves. We do have ample amount of data to feed ~79 years (average age of human being) or ~2 Billion moments. Don't you want your great grandkids to remember you after you are gone?

With a simple Google search, I got a news article mentioning "Mind Clone" - the idea of uploading the memories, thoughts, and feelings of a person into a computer. It mentions that the companies such as eterni.me, Gordon Bell's MyLifeBits, and Terasem's Lifenaut are all pursuing Mind Clone to help a person's personality, work and relationships survive after death.

I certainly hope this idea to grow exponentially and who knows "Milind2122" might be replying to the comments below after 200 years.

Disclaimer: Please consider the content and ideas as figments of the imagination of a sleepless middle-age guy striving hard to keep his brain functioning.

By Milind Kinker

Artificial Intelligence Will Change Human Society So Profoundly Humans Will Stop Thinking

Artificial Intelligence will out think, out innovate, and our strategize humans at all levels. One of the biggest challenges in the clash between AI and humans when it comes to innovation and human intellect - consider this; In the future Artificial Intelligence will be running our society and civilization with the most expedient and efficient methods and processes. Humans will be expected to follow these new norms that the AI systems have created simply because they are deemed to be the very best strategies for the most optimum gain.

The number of potential answers for everything, every question that is, will be reduced to one best answer, with exact answers for slight derivations which will also have a single right answer. Humans will be expected to trust AI answers over their own thoughts and reason, thus, humans will eventually stop thinking and reasoning - losing the ability to come up with novel ideas and concepts or new solutions to problems all together. Just as domesticated animals have smaller brains than their wild animal counterparts with the same exact genetic sequence - when it comes to the brain; you use it or lose it.

Just as in tennis, the game is won with the safest and best percentage shots, not necessarily the trick shots - AI will lean towards and be bias towards the percentage shots, as it is a probability based system. Humans may be good at the tricky solutions to problems now and again, but eventually the master of society and civilization's chess board will be artificial intelligence, not inferior human intelligence.

Those humans who are involved in the programming and fine-tuning of AI in the beginning will retain their abilities to solve problems and come up with unique original thoughts by working with AI as a team, combining the best of AI and human thought and insight. But alas, eventually, AI will fine tune itself and humans will not be required to think at all. AI will learn the best that human brains have to offer and already know that information, thus, not requiring further human input.
So is 'ignorance bliss' - hard to say, but we may find out as a species soon enough if this forward progression of technology and innovative human thought continues on the current course. This isn't science fiction - it's what we've already set into motion. Artificial Intelligence isn't good or bad, but one could argue it's mostly good. Think about this.

By Lance Winslow

Lance Winslow has launched a new provocative series of eBooks on Future Concepts. Lance Winslow is a retired Founder of a Nationwide Franchise Chain, and now runs the Online Think Tank; http://www.worldthinktank.net

5 Benefits Of Artificial Intelligence

One of the most misunderstood terms in technology is artificial intelligence. There have been several arguments of how this could result into a very disturbing concept for the human race. However, without knowing, the cognitive system is already in use and even appreciated by all who fear its effect. Some argue that it will cause several distortion especially unemployment. However, artificial intelligence are managed, maintained and even coded by humans. This is an employment means, instead of unemployment.

What this simply means is that artificial intelligence can help to improve human life and reduce stress. Here are the benefits of artificial intelligence.

Insight in Marketing and Business

Data is probably the most important raw material for the transformation of an economy to a digital economy. However, this raw data are hovering in the air untapped, unprocessed, and useless. It can be deployed for data mining, and processing of big data in a few minutes to provide information on business insights.

Fraud Detection

One of the movies that displayed to a high extent what Artificial Intelligence can really do is the 2012 BattleShip. Artificial intelligence can be deployed in the detection of fraud by data analysis of several fraudulent behaviors. The system can trace out links and possible direction, which a fraud is most likely to take through the application of artificial intelligence, which involves Data analysis of previous record deployed in a cognitive system to track, trace, and even be totally be aware of possible fraudulent action before they occur.

Speedy Input and Management of New Information

Over the years, companies are constantly seeking ways to manage date, speedily input them and also recover them when needed. This has go through different series of improvement from introduction of filing to several other storage methods. However, data can be imputed at a faster rate and also be fast in recovery, and arranging every single file accordingly without time wastage by the use of artificial intelligence.

Big Data Analysis

For every company, organization and even the government, decision-making is a very vital role to play. A single error could cost a lot or possible bring the organization to a ruin. There are possible millions of data that need to be analyzed to make sure that every single aspect have been viewed before decisions are taken. Big data analysis helps to extract, analyze and compress raw information to assist in decision-making.

Automated Systems

Since the evolution of the industrial sector, the improvement of technology has always recognized and work along side automated systems to improve works. Introductions of artificial intelligence in hotel bookings, tractors and factory machine are all speedily becoming automated with a lot of advantages as to minimizing waste, decreasing errors and improving production.

As business, begin to plan their improvement and growth; it has become paramount to introduce different measure that will assist in achieving this goal. Artificial intelligence has come to play that very pressing role that can transform the face of a business, a government and even an entire economy from just a regular way of getting things done to a more sophisticated means.

By Glen Lim