Artificial intelligence or machine intelligence refers to the intelligence that is displayed by the machines, unlike humans and animals.

It is related to the ability of the machine to learn new things and solve problems just like humans. It was initially found back in the year 1956, since then it has seen quite many ups and downs including lack of funding, a pessimistic approach of the people and negative attitude towards AI etc.

But in the recent years (with the onset of 2016) AI industry has seen a boom in their growth and development with the never before advancement of technology, it has now become possible to programme and operate AI without any big glitches or problems.

Many top giants of this industry have already made quite huge investments in this upcoming technology because of its future capabilities and successful predictions. Below listed are the top 25 companies that invested in this technology: -

  1. Google: -

Google has been the major key player in this upcoming industry and has added a ton of value by its entry. In 2014, it invested $400 million in the acquisition of an AI company by the name DeepMind which accounts as the largest acquisition till date.

Moreover, it has further taken some major steps, its machine learning software is free for anyone to use and it has also launched a new project to study in detail and redesign the method the people interact with AI systems by the name of ‘People + AI Research Initiative’.

  1. Spotify: -

Spotify is the new member in this league but has recently taken some big steps to make its presence felt in the industry. It acquired MightyTV in March 2017 which is an AI-based firm using this technology for content recommendations.

The most recent acquisition is Niland, a Paris based company which is a machine-learning start-up. This will help Spotify to filter and present the best-sorted recommendations for its users.

  1. Microsoft: -

Microsoft set aside a whole category of funds from the end of December 2016 to invest in AI-based start-up companies that focus on growth and positive effect on the society with the help of this technology.

Angolo and Bonsai are two firms that are co-led by this fund. Angolo creates summaries of information in real time and Bonsai enables the automatic management of machine learning algorithms. 

  1. Uber: -

Although Uber is a completely unexpected name in this industry, but it has successfully made an acquisition of ‘Geometric Intelligence’ which is an AI-based company aimed at redefining the limits of machine learning. Fifteen of the company’s employees are directed to create an AI lab at the Uber headquarters.

It is destined at rivalling some big tech giants with its heavy investments in autonomous driving technology.

  1. Facebook: -

Facebook has taken the AI to a whole another meaning. With the help of this technology, it aims at making the blind people see the images by narrating it through its application e.g. a blue van with a Labrador on a beach.

It is investing in deep learning AI and aims at finding what matters to its users. It is present in this industry from 2010 and aims at personalizing the experience of the application by displaying content that matters to the users to most.

  1. Apple: -

Apple has been investing quite a bit in AI from the year 2015. It acquired Vocal IQ which is a UK-based company for development of its voice-control feature SIRI after the company produces a programme for General Motors.

In 2016, the company acquired another AI start-up ‘Emotient’ with the aim to develop facial recognition and the customer’s reaction to advertisements.

  1. IBM: -

IBM aims at extracting meaning from photos and videos, text and speech. It has been present in this industry since 2011 when its AI Watson won the US quiz Jeopardy performing faster than its human counterparts.

  1. Skype: -

The Microsoft subsidiary Skype is developing new systems and functions with the help of AI technology.

It is developing new real-time language translations in different languages which can also convert the spoken speech to written-text as the user speaks.

  1. SalesForce.com

SalesForce.com acquired the AI start-up ‘MetaMind’ in April 2016 and aims at developing and opening up new markets and processes with this technology.

As stated in the blog post of SalesForce CEO: this acquisition will offer real AI breakthroughs which can further automate the customer support, marketing and other business processes.

 Shell: -

Although Shell is a completely unusual and unexpected company to invest in such a technology, it aims at developing a helpline which will offer to answer all the customer questions round the clock.

  1. Twitter: -

Twitter has also con=me forward with a few major acquisitions in this industry. Its recent acquisition of an AI company Magic Pony Technology which develops novel learning techniques for visual processing.

Further, it acquired two more such companies’ mad bits and Whet lab.

  1. Jerry Yang: -

Yang is the co-founder of Yahoo and is a major investor in the start-ups irrespective of its stage be it seed or large scale. His AI investments include investment in CrowdAI (focussing on satellite and high-quality images for drone systems and self-driving cars), Zipline (a company focussing on drone delivery system of healthcare essentials like vaccines etc.) and Osaro (a company which aims at increasing the adaptiveness and efficiency of computer systems.)

  1. Jeremy Yap: -

Yap is a Singaporean investor who has investments in over 29 companies. This AI investments list 3 companies, the first one being Twiggle (a language search tech that enables the search engine to mimic a salesperson), Bloomsbury AI (enabling non-programmers to conduct analytics etc.) and the last one being Iris automation.

  1. Scott Banister: -

Banister is very well known for some of his major investments. He is a board member of PayPal and the co-founder of IronPort (which was later acquired by Cisco). He is also a founder of ListBot which was acquired by the tech-giant Microsoft.

His AI investments include Nirvana Systems (a company focussing on powering intelligent applications, this was later acquired by Intel), Osaro and Dill Mil which is a matchmaking application for South Asians.

  1. John Shaw: -

Shaw is an experienced entrepreneur, coder and an active investor with investments in B2B businesses. He is currently developing its own AI start-up by using his experience in the Cloud Computing.

His AI investments include Vic.ai (which focuses on accounting automation) and Kairos AR (which provides facial recognitions). 

  1. Paul Buchheit: -

Paul is best known for creating and developing Gmail and is also a founder of Friend Feed (which was acquired by Facebook in 2009). His investments in AI include investment in Iris Automation (a company that helps prevent industrial drone collisions), lvl5 (a company that focusses on providing accurate maps for self-driving cars) and CloudMex (a company focussing on generating real-time clinic insights).

  1. Ken Hertz: -

Although being a lawyer by profession, Hertz is also a key investor in many AI companies including ObEN which focusses on creating identities of people and celebrities that simulates their voice, personality etc.

  1. Esther Dyson: -

Esther is a key investor in a ton of companies in different sectors like IT, Health, technology etc. Her AI investments include Joany (a company aimed at simplifying the online health insurance buying process and method), Init.ai (a company helping others to create AI applications).

She is also the executive founder of Way to Wellville which aims at coordinating health intervention programmes in cities.

  1. Peter Livingston: -

Peter is an engineer with over five years of experience and is also a Miami-based investor. His major AI investments are: Kairos AR (focused on facial recognition), Numerai (it is a hedge fund which is built by data scientists) and Vayu (which focusses on drone delivering of healthcare supplies to developing cities in developing countries).

  1. Semil Shah: -

Semil Shah is a very big investor in the Silicon Valley with investments in over 70 companies. He also serves on the advisory board of the alpha network and StrictlyVC. Plus, he has been a consultant for many major firms like Trinity Ventures, GGV Capital etc.

His major AI investments are Air Map (a company focussing on providing accurate airspace info for unmanned drones, aircrafts etc.), Iris Automation (a company focussing on prevention of colliding industrial drones) and Sky Safe (providing defence and airspace control solutions).

  1. Wei Guo: -

Wei Guo is the top angel investor in the AI technology and is known to have invested the most in the Silicon Valley with investments in over 120 start-ups.

His AI investments include RoboTerra (specializing in educational robotics), MO Bagel (specializing in internet analytics) and Mashgin (specializing in automated checkout by recognizing retail store items).

  1. AL Brain: -

AL Brain is a US-based AI company that develops and build AI solutions for mobile smartphones and applications. It offers many AI agents and software’s like AICoRE, iRSP which is a robotic software platform.

Further, the focus of their work is to infuse human skills with artificial intelligence and help in matters like problem solving, memory etc.

  1. Amazon: -

Amazon has made big plans to enter the AI industry through both of their services as well as their products. Their programme ‘Amazon Machine Learning’ enables the companies to predict the pattern by analysing data etc.

Further, they have also brought AI into the consumer homes in the form of Alexa.

  1. Cloud Minds: -

Cloud Minds went a step ahead of the industry and is currently developing CI (Cloud Intelligence) instead of AI. They aim at treating robots with humans and not as a separate entity.

In other words, this allows the robot to be controlled by the humans.

  1. ICarbonX: -

ICarbonX is a Chinese biotech company which focuses on providing personalized healthcare and index predictions with the help of AI. It has tied-up with over seven company’s worldwide that specializes in gathering health-care data.

This will enable them to study and use programming to analyse the data and provide personalized results and services.

 Artificial Intelligence is not a thing of the future anymore, it has seen a boom in its development and investment from the last year and is destined to reach new heights in the future with the help of the tech-giants that have already invested tons of funds in this sector.

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AI is gaining popularity,so one must the terms used in AI as well.

Algorithm

A formula or set of rules for performing a task. In AI,

The algorithm tells the machine how to go about finding answers to a question or solutions to a problem.

Analogical Reasoning

Solving problems by using analogies, by comparing to past experiences.

Artificial Intelligence (AI)

A field of computer science dedicated to the study of computer software making intelligent decisions, reasoning, and problem solving.

Artificial Neural Networks (ANN)

Learning models based on the biological neural networks present in the brains of animals.

Based on the activity of neurons, ANNs are used to solve tasks that would be too difficult for traditional methods of programming.

Autonomous

Autonomy is the ability to act independently of a ruling body. In AI, a machine or vehicle is referred to

as autonomous if it doesn't require input from a human operator to function properly.

Backpropagation

Short for "backward propagation of errors," backpropagation is a way of training neural networks based on a known,

desired output for specific sample case.

Backward chaining

A method in which machines work backward from the desired goal, or output, to determine if there is any data or evidence to support those goals or outputs.

Case-Based Reasoning (CBR)

An approach to knowledge-based problem solving that uses the solutions of a past, similar problem (case) to solve an existing problem.

Chatbots: A chat robot (chatbot for short) that is designed to simulate a conversation with human users by communicating through text chats,

voice commands, or both. They are a commonly used interface for computer programs that include AI capabilities.

Classification: Classification algorithms let machines assign a category to a data point based on training data.

Cluster analysis: A type of unsupervised learning used for exploratory data analysis to find hidden patterns or grouping in data

clusters are modeled with a measure of similarity defined by metrics such as Euclidean or probabilistic distance.

Clustering: Clustering algorithms let machines group data points or items into groups with similar characteristics.

Cognitive computing: A computerized model that mimics the way the human brain thinks. It involves self-learning through the use of data mining, natural language processing, and pattern recognition.

Convolutional neural network (CNN): A type of neural networks that identifies and makes sense of images.

Data mining

The process by which patterns are discovered within large sets of data with the goal of extracting useful information from it.

Deep learning

A subset of machine learning that uses specialized algorithms to model and understand complex structures and relationships among data and datasets.

Data science: An interdisciplinary field that combines scientific methods, systems, and processes from statistics, information science, and computer science to provide insight into phenomenon via either structured or unstructured data.

Decision tree: A tree and branch-based model used to map decisions and their possible consequences, similar to a flow chart.

Forward chaining

A situation where an AI system must work "forward" from a problem to find a solution. Using a rule-based system, the AI would determine which "if" rules it would apply to the problem.

Game AI: A form of AI specific to gaming that uses an algorithm to replace randomness. It is a computational behavior used in non-player characters to generate human-like intelligence and reaction-based actions taken by the player.

Genetic algorithm: An evolutionary algorithm based on principles of genetics and natural selection that is used to find optimal or near-optimal solutions to difficult problems that would otherwise take decades to solve.

Heuristics Search Techniques

These are rules drawn from experience used to solve a problem more quickly than traditional problem-solving methods in AI. While faster, a heuristic approach typically is less optimal than the classic methods it replaces.

Inductive reasoning

In AI, inductive reasoning uses evidence and data to create statements and rules.

Knowledge engineering: Focuses on building knowledge-based systems, including all of the scientific, technical, and social aspects of it.

Logic programming: A type of programming paradigm in which computation is carried out based on the knowledge repository of facts and rules; LISP and Prolog are two logic programming languages used for AI programming.

Machine learning

A field of AI focused on getting machines to act without being programmed to do so. Machines "learn" from patterns they recognize and adjust their behavior accordingly.

Machine intelligence: An umbrella term that encompasses machine learning, deep learning, and classical learning algorithms.

Machine perception: The ability for a system to receive and interpret data from the outside world similarly to how humans use our senses. This is typically done with attached hardware, though software is also usable.

Natural language processing (NLP)

The ability of computers to understand, or process natural human languages and derive meaning from them. NLP typically involves machine interpretation of text or speech recognition.

Recurrent neural network (RNN): A type of neural network that makes sense of sequential information and recognizes patterns, and creates outputs based on those calculations.

Planning

A branch of AI dealing with planned sequences or strategies to be performed by an AI-powered machine. Things such as actions to take, variable to account for, and duration of performance are accounted for.

Pruning

The use of a search algorithm to cut off undesirable solutions to a problem in an AI system. It reduces the number of decisions that can be made by the AI system.

Recurrent neural network (RNN): A type of neural network that makes sense of sequential information and recognizes patterns, and creates outputs based on those calculations.

Strong AI

An area of AI development that is working toward the goal of making AI systems that are as useful and skilled as the human mind.

Supervised learning: A type of machine learning in which output datasets train the machine to generate the desired algorithms, like a teacher supervising a student; more common than unsupervised learning.

Swarm behavior: From the perspective of the mathematical modeler, it is an emergent behavior arising from simple rules that are followed by individuals and does not involve any central coordination.

Turing test

A test developed by Alan Turing that tests the ability of a machine to mimic human behavior. The test involves a human evaluator who undertakes natural language conversations with another human and a machine and rates the conversations.

Unsupervised learning: A type of machine learning algorithm used to draw inferences from datasets consisting of input data without labeled responses. The most common unsupervised learning method is cluster analysis.

Weak AI

Also known as narrow AI, weak AI refers to a non-sentient computer system that operates within a predetermined range of skills and usually focuses on a singular task or small set of tasks. Most AI in use today is weak AI.

Weights

The connection strength between units, or nodes, in a neural network. These weights can be adjusted in a process called learning

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Chatbots have been used in the customer service sector for a long time now, but never have they been given big responsibilities and duties it helps the people single-handily. Earlier they were used for weather updates, ordering tickets, food etc.

But with the evolution of time chatbots have gained much more importance and have literally taken over this market as a whole with minimal to no use of people to be physically present to supervise them with their entry in social care, business helplines, law and many more they have definitely proved themselves as a positive investment for the public.

  1. Legal Advice bot: -

Gone are the days when the people need to physically visit a lawyer’s office to get legal advice and pay him tons of money to do that. With the entry of the first robot lawyer ‘DoNotPay’, this market changed forever.

DoNotPay started as a small platform to get the drivers out of parking tickets. This platform gained attention when it opposed over a lakh of such tickets. People from all over the world started contacting Joshua (the mastermind) regarding their other legal issues as well, this was when Joshua expanded his business and converted it into a bot lawyer helping with each and every legal issue.

This not only saves a lot of time but also a lot of paperwork and heavy fees that the lawyers charge.

  1. Therapy bot: -

As the name suggests, woebot is a 24x7 therapist chatbot that is friendly and has a comic nature, it really helps you lift up your mood and makes you cheer up. The user can chat with it by sending it messages on the website or application and the bot responds accordingly after analysing the problem the user is going through.

Coming to the price, the first fourteen sessions with this bot is completely free and then a charge of $6 - $12 is charged per week depending upon the plan that you choose from the available options.

  1. U-report bot: -

Developed by UNICEF, u-report is a polling bot with the help of which its followers (known as the u-reporters) who are usually young can present their opinion on a particular topic about which the poll was. E.g. Climate change etc. Then all these 3 million+ opinion are sorted by the bot and is used to influence the public policy.

U-report has gained a lot of attention over the time and has gathered 3.4 million+ followers who do not hesitate to present their opinion. The questions are based on your demographics which are taken when you sign up.

  1. Quit smoking bot: -

Developed by Dr.Amelie G. Ramirez of the University of Texas, Quitxt is a platform that helps its users to quit smoking by sending them text messages several times a day encouraging them to quit and not look back.

The addicted person can mark their quit day and go on an 8-10 week programme in which they will receive 5-7 messages a day which will be reduced over time as they continue to resist their addiction to smoke. Apart from positive messages, this platform also helps the puffers manage stress and live a peaceful life.

  1. Meditation bot: -

As the name indicates, MeditateBot is a Facebook messenger based chatbot that helps the people to meditate by enlisting the benefits and positives of meditating. Further, as a beginner, you do not have to fill lengthy forms and disclose too much private information, moreover, this bot lets you choose your meditation time as well as the duration.

Over 500 thousand people have joined the bot in a short period of time to remain calm and composed throughout the day.

  1. Voting bot: -

Digital Marketing firm MSSG has really come forward with a Facebook messenger based platform to use chatbots for the use of democracy as well. The MSSG voting bot tells you the location of your voting booth with other necessary details as well.

You simply need to type in your name and address in the message and send it. The bot will send you your voting location along with the address and a pinned map position as well.

  1. E-commerce bot: -

Operator is an application based chatbot that helps people find gifts and items to purchase according to their choice. If you would like to buy as small as a tie you can simply type in your requirement or select from the application options and it will show you the best option by checking all the e-commerce websites.

With the product, the bot will even present you with the best offers and sales going through different websites.

  1. Education bot: -

The whole idea of learning from a bot sounds weird at first, but a company has actually managed to do so and create tons of users and fan base. Duo lingo is an application based chatbot that helps you learn a new language or languages in the most easy and efficient manner.

The language, time and the level are decided by the user and you can also test your skills by opting for tests present in the application itself.

  1. Medical bot: -

Babylon Health aims at asking the doctors available at everybody’s palm, and for this, they developed a healthcare application ‘Babylon Health’. Unlike other such applications which present you with a general result or solution, Babylon presents tailored and precise solutions for your problem along with a message on how to use, dosage and other important vitals etc.

It is considered best for small non-fatal issues like cold, headaches, small wounds, scratches etc.

  1. Reservation bot: -

Reserve is a hospitality bot that enables its users to search and book tables in restaurants and other eateries listed with them. The results are displayed according to your location, food preference, restaurant type etc. If the application is unable to process your request, it will simply transfer your request to a member of their support team who will take care of your request.

The application gives a friendly feel and acts and chats with a friend who happens to know each and every restaurant.

  1. Finance bot: -

‘Chip’ is a smart finance management application based chatbot that provides useful insights to its users into their spending, savings and the real savings that they could be done by minimizing the unnecessary expenditures.

You can send funds directly to your bank account with the help of this application. Every time there’s a change, the application sends informal messages to the user filled with GIF’s and emoticons making a really close feeling as chatting with a friend.

  1. Credit score bot: -

Launched in February 2017, Clear Score is a credit-score checking and managing application based chatbot.

The application helps the people in three major segments. The first known as ‘build’ for the people who do not have any credit history. ‘Repair’, for the people who have poor credit score and prove a coaching in order to improve it and last ‘Shape up’ for the people having a healthy score and ways on how to manage it.

The application has proved to be really helpful and has tons of users worldwide.

  1. Accounting bot: -

Accounting can be tiresome and a monotonous task, with mechanical entries every now and then, it can prove to be quite boring and demanding job. But bot anymore. A business software firm ‘Sage’ has come up with a new accounting assistant by the name ‘PEGG’.

Pegg helps the entrepreneur manage and track all the expenditure and finances of the firm by simply conversing or chatting with this virtual assistant.

  1. Fashion bot: -

Chatbots of many different famous companies like H&M, Sephora etc. has come up with their own chatbots that help their clients find the best look and design possible.

H&M Chatbot helps the people find the best clothes that suit them by looking and analysing their style and fashion from photos of the past. Sephora bot helps its clients save money and time and book their appointment in a very easy 3 way step process.

  1. Love bots: -

Swiping left and right on applications is a thing of the past now. With the entrance of bots in this industry, there has been some major technological advancements.

Foxsy is a love finding bot which will provide you the best match by comparing and analysing a ton of things like interests, favourites, music etc. that will be taken at the time of registration.

Google’s AI-building AI actually went ahead and built a fully-functional AI child that, as it turns out, is more capable than any AI built by human hands. Historians will look back at this moment, from their ruined cities and hideouts from their robot masters, as the time where the downfall of humanity began.

Of course,  it’s not actually all that doom and gloom, the child AI is really only capable of a specific task – image recognition. Using its AutoML AI, Google’s AI-building AI created its child AI using a technique called reinforcement learning.

This works just like machine learning, except it’s entirely automated where AutoML acts as the neural network for its task-driven AI child.

Known as NASNet, the child AI was tasked with recognising objects in a video, in real time. AutoML would then evaluate how good NASNet was at its task and then improve its algorithms using the data to create a superior version of NASNet.

This endless automated tweaking paid off though when tested on the ImageNet image classification and COCO object detection datasets – both known for being “two of the most respected large-scale academic data sets in computer vision” – NASNet outperformed all other systems.

NASNet was 82.7% accurate at predicting images on ImageNet’s validation set. Going by previously published results, this is 1.2% higher than any other system. It’s also listed as being 4% more efficient than man-made devices and has a mean Average Precision (mAP) of 43.1%. Interestingly, a less-demanding version of NASNet outperforms mobile platforms by 3.1%.

Obviously, in its current guise, NASNet isn’t going to be the downfall of humanity.

It is, however, the key to how we build better AI systems in the future. With self-learning AI and AI’s that can also moderate and alter other AIs, we could create AI that is better for autonomous vehicles or automated factories.

"We hope that the larger machine learning community will be able to build on these models to address multitudes of computer vision problems we have not yet imagined," they wrote in their blog post.

The trouble is, such advances in AI could have dangerous implications. Beyond simply building in a way that’s hard to regulate or intervene in, it’s possible an AI system like the shuttered Microsoft Tay, could pass on its learned biases, hard-coding them into its next-generation AI.

Thankfully, there are regulatory bodies out there trying to ensure this future doesn’t come to pass. We already know that Elon Musk and Stephen Hawking are very much against AI advancement, but the world’s biggest tech companies are also pushing a joint partnership on AI.

This partnership on AI is all about bringing together these megaliths of tech to ensure the future of AI isn’t going to cause the breakdown of society.

Source:Alphr

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