AI For Everyone

AI For Everyone

What is artificial intelligence?

Artificial Intelligence definition:

Artificial intelligence for people in a hurry the easiest way to think about artificial intelligence is in the context of a human after all humans are the most intelligent creatures we know off AI is an expansive part of software engineering the objective of AI is to make frameworks that can work shrewdly.

And autonomously people can talk and tune in to communicate through language this is the field of speech recognition much of speech recognition is statistically based hence it's called statistical learning humans can write and read text in a language this is the field of NLP or natural language processing humans can see with their eyes and process what they see this is the field of computer vision PC vision falls under the emblematic path for PCs to process data.

As of late there has been another way which I'll come to later people perceive the scene around them through their eyes which make pictures of that world this field of picture preparing which despite the fact that isn't straightforwardly identified with AI is required for PC vision people can comprehend their environment and move around fluidly this is the field of robotics humans have the ability to see patterns such as grouping of like objects this is the field of design acknowledgment machines are stunningly better at design acknowledgment.

Since they can utilize more information and measurements of information this is the field of AI presently how about we talk about the human brain. The human brain is a network of neurons and we use these to learn things if we can replicate the structure and the function of the human brain we might be able to get cognitive capabilities in machines this is the field of neural networks if these networks are more complex and deeper.

And we use those to learn complex thing that is the field of deep learning there are different types of deep learning and machines which are essentially different techniques to replicate what the human brain does if we get the network to scan images from left to right top to bottom it's a convolution neural network a CNN is used to recognize objects in a scene this is the manner by which PC vision fits in an item acknowledgment is practiced through AI people can recall the past.

Like what you had for supper the previous evening admirably at any rate the majority of you we can get a neural system to recollect a restricted past this is an intermittent neural system as you see there are two different ways a eye works one is symbolic based and another is data based for the database side called a machine learning we need to feed the Machine lots of data.

Before it can learn for example if you had lots of data for sales versus advertising spend you can plot that data to see some kind of a pattern if the machine can learn this pattern then it can make predictions based on what it has learned while one or two or even three dimensions is easy for humans to understand and learn machines can learn in many more dimensions like even hundred or thousands that's why machines can look at lots of high dimensional data and determine patterns once it learns these patterns it can make predictions that humans can't even come close to we can use all these machine learning techniques to do one of two things classification or prediction.

As an example when you use some information about customers to assign new customers to a group like young adults then you are classifying that customer if you use data to predict if they're likely to defect to a competitor then you're making a prediction there is another way to think about learning algorithms used for AI if you train an algorithm with data that also contain the answer then it's called supervised learning.

For example when you train a machine to recognize your friends by name you'll need to identify them for the computer if you train an algorithm with data where you want the machine to figure out the patterns then it's unsupervised learning.

For example you might need to take care of the information about heavenly items known to man and anticipate that the machine should think of examples in that information without anyone else on the off chance that you give any calculation a goal and expect the Machine through trial-and-error to achieve that goal then it's called reinforcement learning a robot's attempt to climb over the wall until it succeeds is an example of that so there you go.

Who invented artificial intelligence:

John McCarthy is one of the "establishing fathers" of artificial intelligence, along with Alan Turing, Marvin Minsky, Allen Newell, and Herbert A. Simon. McCarthy begat the expression "artificial intelligence" in 1955.

Artificial Intelligence vs Machine Learning:

Artificial Intelligence vs Machine Learning. Now my topic of discussion is AI vs Machine Learning vs Deep Learning. These are the term which have confused a lot of people and if you too are one among them, let me resolve it for you.

Well artificial intelligence is a broader umbrella under which machine learning and deep learning come you can also see in the diagram that even deep learning is a subset of machine learning so you can say that all three of them the AI the machine learning and deep learning are just the subset of each other.

So let's move on and understand how exactly the differ from each other. So let's start with artificial intelligence. The term artificial intelligence was first instituted in the year 1956. The concept is pretty old, but it has gained its popularity recently.

But why well, the reason is earlier we had very small amount of data the data we had Was not enough to predict the accurate result, but now there's a tremendous increase in the amount of data statistics suggest that by 2020 the accumulated volume of data will increase from 4.4 zettabyte stew roughly around 44 zettabytes or 44 trillion GBs of data along with such enormous amount of data.

Now, we have more advanced algorithm and high-end computing power and storage that can deal with such large amount of data as a result. It is expected that 70% of Enterprise will Implement ai over the next 12 months which is up from 40 percent in 2016 and 51 percent in 2017.

Just for your understanding what does AI well, it's nothing but a technique that enables the machine to act like humans by replicating the behavior and nature with AI it is possible for machine to learn from the experience. The machines are just the responses based on new input there by performing human-like tasks.

Artificial intelligence can be trained to accomplish specific tasks by processing large amount of data and recognizing pattern in them. You can consider that building an artificial intelligence is like Building a Church, the first church took generations to finish. So most of the workers were working in it never saw the final outcome those working on it took pride in their craft building bricks and chiseling stone that was going to be placed into the great structure.

So as AI researchers, we should think of ourselves as humble brick makers whose job is to study how to build components example Parts is planners or learning algorithm or accept anything that someday someone and somewhere will integrate into the intelligent systems some of the examples of artificial intelligence from our day-to-day life our Apple series just playing computer Tesla self-driving car and many more these examples are based on deep learning and natural language processing.

Well, this was about what is AI and how it gains its hype. So moving on ahead. Let's discuss about machine learning and see what it is and white pros of an introduced. Well Machine learning came into existence in the late 80s and the early 90s, but what were the issues with the people which made the machine learning come into existence? Let us discuss them one by one in the field of Statistics.

The problem was how to efficiently train large complex model in the field of computer science and artificial intelligence. The problem was how to train more robust version of AI system while in the case of Neuroscience problem faced by the researchers was how to design operation model of the brain.

So these are some of the issues which had the largest influence and led to the existence of the machine learning. Now this machine learning shifted its focus from the symbolic approaches. It had inherited from the AI and move towards the methods and model. It had borrowed from statistics and probability Theory.

So let's proceed and see what exactly is machine learning. Well Machine learning is a subset of AI which The computer to act and make data-driven decisions to carry out a certain task. These programs are algorithms are designed in a way that they can learn and improve over time when exposed to new data. Let's see an example of machine learning. Let's say you want to create a system which tells the expected weight of a person based on its side.

The first thing you do is you collect the data. Let's see there is how your data looks like now each point on the graph represent one data point to start with we can draw a simple line to predict the weight based on the height.

For example, a simple line W equal x minus hundred where W is waiting kgs and edges hide and centimeter this line can help us to make the prediction. Our main goal is to reduce the difference between the estimated value and the actual value. So as to accomplish it we attempt to draw a straight line that fits through all these various focuses and limit the mistake.

So our main goal is to minimize the error and make them as small as possible decreasing the error or the difference between In the actual value and estimated value increases the performance of the model further on the more data points. Well, this was a basic discussion in case you have any doubt feel free to add your query to the comment section.

Artificial Intelligence future:

Artificial Intelligence future. This wall has seen four major revolutions that changed its entire face now the first revolution was in 1784 when the first steam engine was introduced and then in 1870 the second revolution that means electricity was invented the third one was in 1969 when the word information technology was introduced in the world and finally the fourth one is the revolution of artificial intelligence which we are experiencing right now.

The future of AI holds more inventions that will bring us closer to an unparalleled future and in today's session we will talk about the future of artificial intelligence and what its gonna unfold now before we begin this session let's have a look at today's agenda so first we will see how artificial intelligence has evolved since the beginning.

So we'll talk about the evolution of AI and then we will move on and talk about the beginning of the AI revolution and from where it all began and then moving on to the next topic we will talk about all the reasons AI inventions and finally we will discuss about the future of artificial intelligence and what Moore is going to come up now before we begin this session.

So let's get started so talking about the evolution of AI artificial intelligence makes it possible for machines to learn from experience adjust to new inputs and perform human-like tasks now the earliest research into thinking machines was inspired by a confluence of ideas that became a prevalent in the late 1930s 40s and also the early 1950s.

So let's have a look at the evolution of this life changing technology from the early 50s to the present date now in nineteen the Alan Turing devised the Turing test now if a machine could carry on a conversation that was indistinguishable from a conversation of the human being then it was reasonable to say that the machine was thinking then in 1956 to 74 it was called as the golden era for AI.

So the web or project in 1967 built a robot that could measure distances and directions to objects utilizing outside receptors artificial eyes and yours and it's discussion framework additionally permitted it to speak with an individual in Japanese with an artificial mouth next in the 1980s.

A type of AI program calls the fare frameworks was embraced by companies the world over and information turned into the focal point of mainstream AI inquire about another worldview called the intelligent agents became widely accepted during the 1990s.

Now it is a system that perceives its environment and takes actions that maximize its chance of success now in the first decades of the 21st century access to large amounts of data faster computers and advanced machine learning techniques was successfully applied to many problems throughout the economy.

And by 2016 the market for AI related products hardware and software reached more than eight billion dollars not just that the New York Times reported that interest in AI had reached a turmoil and the worldwide spending on AI systems estimated to reach around thirty five point eight billion dollars in 2019 and increase of 44% over 2018 and to more than double to seventy nine point two billion dollars in 2022.

So the growth and evolution of AI is definitely a continuous process and it's enormous now before we start talking about the future of AI let's have a look at the creative inventions done in the past which involves AI now the beginning of the AI revolution was from the 1950s from that point numerous researchers developers rationalists and scholars began in strong opposing the cutting edge comprehension of artificial intelligence in general with each new decade.

There were new advancements and discoveries that changed individuals' central information on the field of artificial intelligence likewise it indicated how chronicled headways have slung AI from being an unattainable dream to a tangible reality for current and future generations now some of the important advancements throughout the history of AI torchin on the father of information theory published programming a computer for playing chess which was the first article to discuss the development of a chess-playing computer game not just at unimate an industrial robot was also invented by George Devol.

In the 1950s now talking about the 1960s in 1965 Joseph a computer scientist and professor developed ELISA an interactive computer program that could functionally converse in English with a person it blurted out canned lines for certain keywords using programmed scripts the next phase was the 1970s.

Now this phase witnessed the advancements particularly focusing on robots and automatons now the web bought one the first anthropomorphic robot was built in Japan at Waseda University now its features included moveable limbs ability to see and the ability to converse now in 1980 is the growth of artificial intelligence continued and web bot 2 was built at Waseda University.

This inception of the web BOTS allowed the humanoid to communicate with people as well as read musical scores and play music on an electronic organ then came the 1990s now in 1995 computer scientist Richard Wallace developed the chat BOTS Ellis inspired by Eliza also deep-blue a chess-playing computer was developed by IBM in 1997 now in 2000 professor Cynthia developed kismet a robot that could recognize and simulate emotions with its face it was structured like a human face with eyes lips eyelids and eyebrows not just that in 2009 secretly developed a driverless car and by 2014 it passed.

Nevada self-driving test as well so these were some of the advancements and achievements of artificial intelligence in the past the current decade has been immensely important for AI innovation so let's have a look at how artificial intelligence changed our lives in the recent decade now the current decade has been immensely significant for AI advancements as of late artificial intelligence has gotten installed in our everyday presence we use cell phones that have voice help and PCs that have intelligence capacities AI is no longer a pipe dream.

So let's talk about some of a ice achievements in this decade now in 2010 imagenet launched the imagenet large-scale visual recognization challenge also Microsoft launched Kinect for Xbox 360 the first gaming device that tracks human body movement using a 3d camera and infrared detection in 2011 Apple released Siri.

A virtual assistant on Apple iOS operating systems Siri depends on a natural language user interface to infer observe answer and recommend things to its human user it adopts the voice commands and projects and individualized experience for the users then in 2012 to Google researchers trained a large neural network of sixteen thousand processors to recognize images of cats by showing it 10 million unlabeled images from YouTube videos.

These were just a few or of the many sectors which will be taken over by artificial intelligence in the coming years and with this we have come to the end of our session and I hope you have understood what the future of AI wholes and where else it's going to expand and I hope you understood the contribution of AI over the years and how is going to rule over almost every sector so don't forget to let us know about your opinion in the comment section below.

Advantages of artificial intelligence:

Advantages of artificial intelligence. Technology moves at breakneck speeds and we now have more power in our pockets than we had in our homes in the 90s artificial intelligence or AI has been intriguing idea of sci-fi for a considerable length of time however numerous analysts believe we're at long last drawing near to making AI.

A reality here are four different ways AI may influence us in the future one automated transportation we're already seeing the beginnings of self-driving cars though the vehicles are currently required to have a driver present at the wheel for safety despite these exciting developments technology isn't perfect yet.

And it'll take a while for public acceptance to bring automated cars into widespread use Google began testing a self-driving car in 2012 and from that point forward the US Department of Transportation has discharged meanings of various degrees of robotization with Google's vehicle named the principal level down from full mechanization one self-drive stage that has really taken off is that one used by Tesla other transportation methods are closer to full automation.

Such as buses and trains number two cyborg technology one of the main limitations of being human is simply our own bodies and brains in the future we'll be able to augment ourselves with computers and enhance many of our own characteristic capacities however a large number of these conceivable cyborg upgrades would be included for comfort others may fill a progressively viable need AI will get valuable for individuals with severed appendages.

As the brain will be able to communicate with robotic limbs to give the patient more control this kind of cyborg technology would significantly reduce limitations that amputees deal with on a daily basis number three taking over dangerous jobs robots are already taking over some of the most hazardous jobs available including bomb defusing yet these robots aren't quite robots.

Yet they are in fact rambles being utilized as a physical partner for defusing bombs however requiring a human to control them instead of utilizing a whatever their arrangement they have saves thousands of lives by taking over some of the most dangerous jobs in the world as technology improves we will probably observe more AI incorporation to enable these machines to work different employments.

Likewise being reevaluated for robot reconciliation is welding known for delivering harmful substances in ten warmth and ear-splitting noise can now be outsourced to robots in most cases number four solving climate change solving climate change might seem like a tall order from a robot yet machines have more access to data than one person ever could.

Putting away a staggering number of measurements utilizing enormous information AI would one be able to day distinguish patterns and go through that data to accompany answers for the world's most concerning issues in spite of the fact that we don't have the foggiest idea about the specific future it is very obvious that communicating with AI will before long become a regular action.

Examples of artificial intelligence:

Examples of artificial intelligence. Here are eight amazing examples of artificial intelligence number 8 Siri most people don't realize that there are several levels of artificial intelligence and an example of a lower tier AI is that of Siri.

The digital assistant to Apple device users technically speaking Siri is a pseudo intelligent digital personal assistant by that they mean that while she can interact with you she personally doesn't start conversations she is not an AI you can have a back and forth conversation with but that doesn't mean that she can't learn.

Siri has the ability to listen to how you talk how you ask for things what you ask for and more and then tailor her results and actions to better fit your needs even if you speak to her in another language plus as a personal assistant Siri has the ability to go into the programs of your phone or iPad or other.

Such Apple device in order to make sure that things get done including putting reminders on your calendar opening up an app playing music and more the more you interact and ask things from Siri the more adapted she becomes to you and your patterns so well not a true AI in regards to learning on the go all the time she does have the intelligence to grow thanks to her user how often do you use Siri or in my case.

Since I'm an Android user bixby do they actually help you because in my case it seems like it always pops up when I don't need it and starts making voice to text that makes no sense or purposefully ignores me when I try to use it number 7 Hal 9000 in the Space Odyssey book series by arthur c clarke and later the movie 2001 a space odyssey directed by Stanley Kubrick the antagonist of the story was not a human but rather a learning computer the one named Hal 9000.

But it didn't start out that way Hal 9000 was actually built as part of a mission to Jupiter or Saturn depending on whether you're reading the book or watching the first movie and was designed to control the systems of the spaceship discovery 1 along with that goal it was allowed to speak and would often talk to the crew to understand what they were doing at times House official abilities book and movie where speech speech recognition facial recognition natural language processing lip-reading art appreciation interpreting emotional behaviors automated reasoning.

And playing chess hal represents one of many worst-case scenarios when it comes to artificial intelligence from the books and film how starts out as a perfectly capable AI but as time goes on certain faults in his programming emerge due to this the members of the discovery one crew in the first book and movie decide to shut down how to their misfortune Hal doesn't feel this is right and thus decides to get rid of the crew so that it's programmed objectives can be met this kind of broken thinking is what many fear in AI and yet before these malfunctions.

Hal is a perfect example of an AI that can help people on certain missions and be an excellent tool as long as they perform correctly number six Alexa Alexa is an AI device of a different nature for this is a device meant to help you in all parts of your home life much like most telephone collaborators all you need to do to get Alexa to accomplish something is discussion to her anyway her range is what makes Alexa.

So valuable to many a program like Siri is limited to what she has available in the device you have her on in contrast Alexa is only limited by what you have in your house she can turn off lights make calls for you actually make purchases online as long as you have the internet send notices to you when things need to be done and much much more furthermore as long as you give her the appropriate files she can activate music read audiobooks to you via the narrator of the file.

And even jump to a specific part of the audiobook if you need to get ahead not to mention the range of Alexa in terms of how you can activate her is quite impressive many people note that you can be across a whole room and get her to do what you need with a simple shout versus other programs that have to have you be up close and personal to deliver commands as their hearing range is actually quite short.

Alexa is very much a home AI and is something that many are using in order to make their own lives easier and many more are adapting her technology to grow her even more do you guys have Alexa how is your experience been let us all know in the comments below and now for number 5 but first which AI do you have or would you like to have let me know in the comment box.

Coming up number five Tesla car the company Tesla has been working hard to develop the next generation of cars and to that end they have given their cars their own version of AI to the extent that these cars can drive themselves they call this autopilot you likely may have seen versions of this where a car can parallel park on its own in order to fit into a space we would take forever to back into Tesla is taking that further though and their car is capable of driving to and from an area with a degree substantially greater than a human can in terms of safety.

Tesla reports they have eight surround cameras providing 360 degrees of visibility around the car and up to 250 meters of run 12 refreshed ultrasonic sensors supplement this vision taking into account location of both hard and delicate articles at almost double the separation of the earlier framework a front oriented radar with redesigned getting ready gives additional data about the world in an overabundance recurrence.

That can see through overpowering precipitation fog dust and even the vehicle ahead basically the vehicle uses its cameras and sensors to see the world around it and then uses its intelligence in order to analyze and adjust to all scenarios this isn't the only model to have such features other models have features that allow the car to sense when a car is too close and will initialize the brakes before the driver.

So that no damage is done certain cars have a warning feature to let drivers know that they have a car in their blind spot does your car do this all of this technology is slowly leading to a day when drivers won't be required the cars will do it all themselves number 4 amazon.com online shopping is a way of life in the modern world but what makes amazon.com so special is that it actually senses and understands many of the things you buy.

And then will give you ideas on what you should buy next this is referred to as a transactional AI this is because it's something that is understood and refined over time the more you buy the more Intune it will become to recommend you things you're more likely to buy that you may not have even known that you wanted.

Artificial intelligence applications:

Artificial intelligence applications. We all hear about how AI can help in revolutionising and redefining industries helping in a today menial task and drastically changing our decision-making process but have you wondered what kind of industries have adopted air technologies already.

And how are they actually benefiting from them. let us talk about the top 10 applications in 2020 on number 10 we have the agriculture industry AI has been helping farmers in collecting and analyzing farm data like soil health and condition house and crafts etc Blue River Technology a pioneer in this industry has helped farmers in controlling lead and pass through precision spraying of Vita sites.

And pesticides our number 9 we have the automobile industry we all have heard of Tesla haven't we Tesla Smart cars have AI monitoring or sensors detecting predicting and preventing any dangers of problems in a vehicle they also have assisted driving cars as an AI acting as copilot and driverless cars are something.

Coming up number 8 we have the shopping industry the most frequent way in which these ecommerce websites apply a product recommendation he keeps a track of all the data like your passport chains your shopping style and also the current trend and use it to suggest items will most likely end up buying another way they are implementing AI is customer support the chat box which assist us in buying inquiring complaining and so on and number seven we have home automation AI integrated with IOT is being used in home automation for enhance security.

As a personal assistant assisting in reducing a day to day tasks like online shopping are setting up reminders setting up room temperature etc examples are home automation I see a number sex via social media twitter is using AI to filter out head comments Facebook and Instagram use image recognizing techniques to create albums and personalise your feeds.

And so on and number five we have the gaming industry force and counter assault record also known as fear is a first-person shooter video game developed by monolith productions the opponent here on the air as unpredictable and reacts every minor detail making it quite challenging.

And very tough to win our number four we have the education industry many education and cities apply AI to make learning more comfortable for the student by customizing the learning material based on to this knowledge experience and intelligence Institute's such as topper and quiz let's use AI for smart test preparation.

A number three we have the navigation industry GPS navigation systems in degrees AI to keep track of data such as traffic in a particular area and luck in my newsroom paints on the past records like how much time it took in the past for navigating through a particular area our number two we have the healthcare and the research industry from disease protection diagnosis to Nepal exogenous AI has already been helping doctors.

And researchers two of the major contributors are companies like IBM Watson health and our minds they're helping in development of drugs and drug research are number one we have creativity by my making awareness artist AI can done create a behavior and use it to create music paint and so on one of the most jaw-dropping example is IBM Watson cognitive platform which was used to create a movie trailer the first of a Sky Force 20th Century Fox horror flick Kollmorgen so these were the top ten applications of AI.

News about artificial intelligence:

News about artificial intelligence. What is AI let's start with the question what do you think the most complex object in the universe is try and think of it I guarantee you the answer is in your head literally that's because it's the human brain the most complex networks most powerful systems cannot match it changing that is the ultimate goal of artificial intelligence.

It is not about building a robot but creating a computer mind that can think like a human but there are many steps along the way so-called simple or narrow AI systems are already everywhere from Apple's Siri to Facebook's friend recommendations.

But in our cars our homes in an air traffic control and narrow AI has been around for years doing one specific task better than any human the computer deep blue beat the world chess champion way back in 1997 but ask it to play draughts and it wouldn't know where to start it couldn't learn a new game for itself it couldn't think as a human.

And so we come back to the challenge in some say the danger of creating a human or general AI a computer mind that thinks like a human that learns that improves that could even become superhuman experts predict 2050 is the year we could see it if it is even possible it's a race work billions some say it will save humanity other set could destroy us either way if and when it happens the world will be changed forever.

NVIDIA artificial intelligence:

NVIDIA artificial intelligence. The graphics engine is actually rendered by a technology that we built this is the first time we combine machine learning and computer graphics to do image generation using deep networks fortune in data are given some driving sequences of different cities.

And then we used another segmentation network to extract the high-level semantics from these sequences we have the ue4 engine to generate the colorized high level layouts different objects were given different colors the network converts this representation to images.

I made my quarter to dance Condon style which I don't think he would do by himself we find some good dancing videos from another person and then use my motto to synthesize the dance move that was created by machines it's not me.

Artificial intelligence ICO:

Artificial intelligence ICO. In this, I would be talking about effect on AI a decentralized network for artificial intelligence as always we're not paid or mandated to do any of our reviews this is just a personal opinion an analysis and not investment advice the global artificial intelligence market is growing at an increasing rates with a projected size of fifteen point seven trillion dollars as early as 2013 between transportation Commerce and communication.

AI is likely to have a substantial impact on humanity as time goes on however only a few companies such as Google Facebook and Amazon are positioned to develop these algorithms right now this chart shows the top acquirers of AI starters between 2012 to mid-july all of them are major enterprises the entry barrier for the AI market is very high due to intensive data processing diverging tasks.

And computational costs this is why it is currently dominated by large corporations effects on AI proposes a private decentralize ecosystem for AI development nei related services the effective network is designed to provide an alternative to services like Amazon's Mechanical Turk fiber one space and guru the effective network will operate fully on smart contracts that are deployed on the neo blockchain.

The goal will be to provide most if not all of the services necessary for healthy and accessible AI markets the effective network is the name of the projects open decentralized network which provides services in the AI markets the network requires no fees has a low barrier to entry and is split up into three distinct phases the effect Mechanical Turk or MTurk for short is a private decentralized marketplace for work that requires human intelligence.

It is based on centralized business models such as Amazon's MTurk fiber one space and guru comm but the key difference is that effect MTurk is peer to peer the effect smart market will be a decentralized market place where algorithms can exchange their services with users and with each other Apple owners can register their AI product and specify the price or usage fee.

And these apps are available for everyone on the smart markets up until phase 3 the algorithms still run on central servers the final Network phase of the affective Network will put these algorithms on the blockchain so they will be running on a global scale via the Neo blockchain this table from their light paper compares the effect MTurk with Amazon's centralized MTurk the effect on AI team proposes to create a network that differentiates itself by being secure and private very low cost and extends globally this slide summarizes.

The project's historical milestones and future development roadmap the effect on AI algorithm project began in the second quarter of 2016 and the first implementation of their algorithm on the website occurred in the second quarter of that year after this implementation the idea was born to put a factor VII on a blockchain from there the company was officially founded in the third quarter of 2017 phase one of the project officially began in the fourth quarter.

The full release of face-on is set for the third quarter of this year while phases two and three are currently set to come out sometime in 2019 you think that AI will be raising funds for their project by issuing EF x tokens the hardcamp is 14.8 two million euros and implies a maximum arc Aqaba 37 million euros on a fully diluted basis there is no presale while the public crowd sale will be launched sometime in March.

The exact dates for the whitelist registration and the ICO has not been announced yet so please stay tuned for updates this chart shows how the total supply of 615 million tokens will be distributed 20% of the tokens will be reserved for future funding and will be locked by a smart contract for 18 months if predetermined milestones are met these tokens will be released for a second round of funding for the later phases of the project.

Otherwise the tokens will be burned and this chart shows the intended use of their proceeds 43% will be used for blockchain and platform development including security and hardware 50% will be used to cover business expenses including employee and partnership acquisition marketing overhead.

And so on the remainder will be used for blockchain AI and IOT research for the most up-to-date information on the effect on AI ICO please check their website and join their telegram group the e FX token will be launched on the neo blockchain adhering to the net 5 token standard it will be the medium for payments between workers and requesters on the affective Network.

The team's priority is to maintain liquidity for EFX tokens especially during the early stages where no major exchanges have listed the token workers should always be able to sell their EFX rewards for negative tokens and requesters and network users should always be able to buy EFX to help with this the effect network will maintain a central pool of tokens called the Galaxy pool.

To provide liquidity encourage adoption and stabilize network fees the Galaxy pool ensures stable exchange rates for platform users and is not suitable for day traders it has a mechanism to prevent price manipulation as the FX tokens are used as a currency on the effective network the more activity the network has the more valuable the tokens should be effect on AI currently has a team of at least eight people.

And they are based out of the Netherlands the biographies for the CEO and key team members are summarized on this slide please note that the effect on AI advisor list has not been released to the public yet some opportunities we wanted to highlights first a lot of human intelligence tasks can be performed by people without specialized skills.

This needs that the unbanked anywhere in the world could potentially work on the effective network and get paid according to the team's own projections brokers on the effects network can earn around $9 per hour on average compared to only earning $2 per hour on current centralized platforms such as Amazon's amateur the project is quite ambitious but follows a logical process where they gradually put their algorithms on the blockchain.

Basics of Deep Learning

Conclusion:

So companions in this article I was given a detail presentation about AI. Furthermore, I portrayed most significant purposes of AI.

Expectation you make the most of my detail data about AI! And if you had any questions about AI leave a remark I will answer.

What's more, If you delighted in it!

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AI For Everyone