Our team has done some research and curated below top 20 Artificial Intelligence (AI ) and Machine Learning (ML) startups in India.

If you know any new AI startups,Kindly reach us we will review and update our list. Thank you.

  1. Alndra System: -

Set-up in Bengaluru, Alndra systems focusses on creating smart AI-based products that help the public like Smart Attendance Campus, where a student can simply mark his presence online, Smart Verify Health etc.

  1. Fluid AI: -

Fluid AI is based on the idea to solve some of the major issues in different segments of the web (internet), the government sector, marketing and finance which includes a high accuracy facial and image recognition.

  1. Arya.ai: -

Headquartered in Mumbai Arya.ai is one of the best AI companies that helps other companies build intellectual systems and solve complex problems in a very short period of time.

  1. Locus.sh: -

As the name suggests, Locus.sh provides intellectual services to improve and ease the logistics process like real-time tracking, dispatch processes etc. Its dashboard provides a hawk eye view of your package and its exact location on the map.

  1. Haptik.ai: -

Haptik.ai is a combination of both AI and humans that are transforming the way humans perform their day-to-day functions such as setting an alarm, ordering stuff, booking a taxi, paying utility bills etc.

  1. Morph.ai: -

Morph.ai is a Chabot based AI company that focusses on generating personalized conversations for the purpose of marketing which leads to increased conversion rates and more sales. It spreads the brand awareness and understands customer needs.

  1. Super Text: -

Based in Bengaluru, Super Text specializes in designing Chabot’s that can be further integrated with services like messengers, line, slack and many more.

  1. Xurmo: -

Being a self-service platform, Xurmo connects all the data and provides it analysis which is completely automated. Publishing applications, workflow management, data investigation are some other features of the company.

 

  1. Sig Tuple: -

Developed for the medical industry, Sig Tuple provides analysis for visual medical data used to aid diagnosis. Their platform is able to provide aid for five major segments in the medicine world namely chest x-ray, semen, urine microscopy, OCT and blood smears.

  1. Tricog Health Services Pvt. Ltd.: -

Tricog health services is a revolutionary company that provides its services in the medical world and helps diagnose heart attacks in moments the patient arrives at the hospital which enables early care and treatment leading to potentially saving lives.

  1. Mad Street Den: -

Headquartered in Chennai, Mad street den creates and develops new applications with the help of artificial intelligence technology. Veu.ai is a brilliant example of their work directed towards the retail industry.

  1. Embibe: -

Embibe helps the students score good marks and improve their skills by providing them with a detailed and personalized analysis of their tests and mistakes and how to improve them. This helps in building confidence among the students.

  1. Niki.ai: -

Niki.ai is an application based platform which provides the users with over twenty services like booking a cab, order food, pay bills and many others. The best feature is that if you are rude to the app, the app can even block you.

  1. Zenatix Solutions Pvt. Ltd.: -

Zenatix solutions provide a really unique business service to its clients. For eg. If one of its clients has 500 stores and pays rs.30-80 crores in electricity charges annually, zenatix will help the business save 10 to 30% of the bill by providing solutions and methods to do so.

  1. Active.ai: -

If you have ever sent a balance request to your bank account to your bank on Facebook messenger, you just used the service of active.ai. This company provides Chabot services to many institutions like banks, big brands etc.

  1. Boxx.ai: -

Boxx.ai is a software-based company that provides companies with products that helps businesses solve their complex analytics processes. They have a good product feedback and a pay-per-use policy which makes them the first choice in this sector.

  

  1. Netradyne: -

Netradyne focusses on the driver’s security and has launched their product ‘Driveri’ which is a driving monitoring and assistance product. It mounts on the windshield and records the performance of the driver with features like GPS, accelerometer, gyro meter etc. Any unsafe driving event gets recorded on videotape and gets automatically uploaded to the company’s cloud.

  1. Innefu Labs: -

Innefu Labs is a Delhi based start-up which specializes in cybersecurity solutions especially biometric authentication. Its patented product AuthSheild uses both images as well as speech recognition to authenticate a user. The registering process is very simple, the user needs to click a selfie from his phone and speak a few words, and both of them are recorded and used as an authentication password.

  1. Uncanny Vision: -

Uncanny vision uses AI and ML to create and run cost-effective surveillance security on a large scale for cities and industry clients. In addition, it also provides real-time updates and analytics to its clients through its application.

  1. Staqu: -

Established in Gurgaon, Staqu is an AI research firm which focusses on understanding the image recognition technology and provides services to many e-commerce sites for tasks such as image search, generation of tags as well as product recommendations.

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Education is an industry which has seen little to no growth in its methods and technology from its origin.  With artificial intelligence exploring each and every industry, education can prove to be a really good development sector.

In other words, with the help of artificial intelligence in education, there can be a ton of improvements that the teachers and the institutions were not able to undertake because of many physical constraints etc.

Some examples how AI can help this sector is: -

  1. As a complement to the teacher

As we all know, that institution relies on the age-old method of one-class-fits-all that is they pack too many children into a single class and allot a single teacher to them. This is hampering the all-round development of the children as each student learns at his own pace. With the help of AI, this gap can be filled. It can help the teacher by providing suggestions on their teaching methods and style to enable an improved learning experience.

Third Space Learning is one such company in this industry. It tracks the teaching patterns of the teachers and provides them valuable feedback.

  1. Grading

The use of artificial intelligence can help the teachers and the institutes to analyse, interpret and grade the answer sheets of the students. This will not only save the time of the teachers and professors but will also make this process really fast and errorless.

  1. Tutoring

Tutoring is the next biggest sector that has seen drastic improvements with the onset of this technology. Many platforms like Brainly, Chegg etc. who provide services that answering questions to the doubts of the students have now opted artificial intelligence in their operations in order to filter out spam messages and questions, low-quality content or controversial content etc. which was earlier done by hundreds and thousands of moderators online.

Furthermore, these sites also now provide a more user-friendly approach where the users get personalized suggestions about the topics that may be doubtful.

  1. Customized Content

Textbooks, notes and other course materials are designed by the teachers according to an average child which are then printed and distributed to a large number of students who may or may not be average.

An AI start-up by the name Content Technologies. Inc. (CTI) is changing the face of this issue. Now, the university or the institute can directly upload the course material on their website where it is customized according to the student with the help of deep learning patterns etc. and distributed to the students accordingly.

Many prestigious websites like Course era, Khan Academy etc. have already adopted this technology and is using it to improve their operations in terms of productivity and efficiency.

With the development and advancements of artificial intelligence in the education world, students are now being able to learn in a better and quicker manner from any part of the world. This has not only helped them to have a better understanding of the subjects but has also helped them improve their grades.

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Artificial intelligence is an upcoming technology which has rapidly spread in the market and has already covered innumerable industries. Business, manufacturing industries, brands, celebrities, healthcare, education, government, household etc. are some examples of its spread.

The involvement of various big giants has enabled this technology to enter the lives of the people at the personal level through various devices that are used on a day-to-day basis by the public.

Some of the devices are listed below: -

  1. Virtual Personal Assistants (VPA): -

Siri, Cortana and Google Now are some examples of virtual personal assistants which help you in a number of things like maintaining your schedule, finding a location and many more. The use of AI in these applications helps the user to get a personalized experience as the app continuously learns about its user.

  1. Smart Cars

The automobile industry is witnessing a growth in the use of AI, Google’s self-driving car and Tesla’s autopilot being some examples, the industry will soon witness a major turnover where most of the new companies opt for this technology at an increasing rate due to its ease of use and user-friendliness.

  1. Video Games

Video Games has been the industry who have been using this technology from the start, although there has been massive developments in the recent years which has improved the user experience and has improved the game as a whole. The game Middle Earth: Shadow of Mordor launched in 2014 is the best example. The game is designed to memorize the patterns and characters for the user which helps them while playing it.

  1. Fraud

Fraud Detection is the biggest industry that has seen a reduction in the number and instances of crime and fraud with the help of this technology. The use of OTP’s, confirmation emails and messages are some of the common ways that are opted by banks and financial companies to reduce and eventually stop these crimes.

  1. Shopping

Targeted advertisements, purchase item prediction, special discounts and coupons are some of the ways the companies use AI in your shopping patterns. Haven’t you seen an advertisement on a page of the product that you were exploring some time ago with special discounts? This is the most effective use of this technology which enables the companies to offer special discounts to individuals who the AI anticipates will require a discount to convert.

  1. News

A large proportion of the news stories that you see on the internet are generated by AI solely. Including facts, researching the net for the correct information, images etc. are various steps that are taken by the AI programmes in order to produce a verifiable and true news article for the public to read.

  1. Customer Support

Many brands, celebrates and websites are adopting this technology at an increasing rate to offer their services to the customers. Gone are the days when a representative would have to chat with the customer in order to solve their issues, nowadays this is done with the help of AI programmes and chatbots. They not only solve issues of the people but also make them feel that the company is present 24x7 which improves their loyalty.

  1. Security

A single person monitoring a lot of security cameras is physically impossible, this increases the chances of crimes in the neighbourhood. AI can prove to be really helpful in such a case. It can monitor a lot of cameras at the same time and alert the authorities when it sees something suspicious.

  1. Smart Home Devices

Home devices industry has also adopted this technology in order to stay up-to-date and devices in-demand. Smart home lighting devices controlled by an application is an example of this new technology.

The use of smart AI devices in the home is only limited by your imagination.

  1. Recommendation services

 Services like movie recommendations on Netflix, amazon prime, music recommendations on Spotify, Hungama etc. are some examples of use of the AI for recommendation purpose. This program learns your patterns of watching and gives you similar content based on the past analysis.

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One might assume Canada to be a chilled out country with not much to do rather than ice hockey, beer etc. Away from the mainland, Canada would not be expected to have the leading research on the latest technology developments. But, that is false. Canada is one of the leading countries in artificial intelligence research. The country has seen numerous start-ups in two locations of Toronto and Montreal specializing in the developments and use of artificial intelligence.

Some of the start-ups are listed below: -

  1. Element AI

Founded in 2016, Element AI has over $102 million in investments by many big giants such as Microsoft, NVidia, and Intel etc. The company plans on bringing this technology to the masses by introducing it in day-to-day businesses. The company helps the businessman who wants to incorporate this technology into their business but are not aware of how to do it.

Furthermore, Element AI also acts as an incubator for other AI start-up companies by helping them in the process and propose joint-ventures too with their client companies.

  1. Automat.ai

Based in Montreal, Canada, Automat.ai is an AI specific company which brings communication to famous celebrities, brands and influencer with the help of artificial intelligence.

With the help of this, now the famous people and brands are able to interact with the fans and the public using basic communication tools like messaging, chatbots etc. This enables to give a personalized feel to the customers, helping the brands to serve them better.

  1. Fluent.ai

As fascinating as the name sounds, Fluent.ai is an artificial intelligence based company that focusses on the acoustic-only technology of speech recognition capable enough to run without a cloud connection. This will associate speech with content without the use of speech-to-text translation.

The system is very accurate and learns about the users from its operations. Plus, it can also be customized by the users.

  1. Imagia

Setup in Montreal, Canada, Imagia is a company that focusses on providing a more personalized healthcare system to the users. With the help of scientists, Imagia develops and distributes healthcare solutions relating to image analysis.

Cancer detection, segmentation etc. are a few focus groups of the company. Its main motto is to recognize the disease and treat the patients as quickly and accurately as possible. 

  1. Sportlogiq

Sportlogiq is a sports analysis AI based company operating out of Montreal, Canada. It helps the sports teams by analysing the player movements, body activities, fitness level etc. and enables them to be the best to win the game.

Further, it also helps the broadcasters and the media groups by using this technology in order to help them get more viewers and views on their channels and shows.

Conclusion: -

With major investments by many big giants in the countries upcoming AI-based technology companies, Canada is all set to give a boost to this sector and cover up all the lagging sectors where its operations have not been as promising. At the current rate of growth, it may be seen that one day Canada may lead the market in the artificial intelligence sector.

This artcile owned and written by @AIMLMarketPlace Team.

FOR ALL THE hype about killer robots, 2017 saw some notable strides in artificial intelligence. A bot called Libratus out-bluffed poker kingpins, for example. Out in the real world, machine learning is being put to use improving farming and widening access to healthcare.

But have you talked to Siri or Alexa recently? Then you’ll know that despite the hype, and worried billionaires, there are many things that artificial intelligence still can’t do or understand. Here are five thorny problems that experts will be bending their brains against next year

The meaning of our words

Machines are better than ever at working with text and language. Facebook can read out a description of images for visually impaired people. Google does a decent job of suggesting terse replies to emails. Yet software still can’t really understand the meaning of our words and the ideas we share with them. “We’re able to take concepts we’ve learned and combine them in different ways, and apply them in new situations,” says Melanie Mitchell, a professor at Portland State University. “These AI and machine learning systems are not.”

Mitchell describes today’s software as stuck behind what mathematician Gian Carlo-Rota called “the barrier of meaning.” Some leading AI research teams are trying to figure out how to clamber over it.

One strand of that work aims to give machines the kind of grounding in common sense and the physical world that underpins our own thinking. Facebook researchers are trying to teach software to understand reality by watching video, for example. Others are working on mimicking what we can do with that knowledge about the world. Google has been tinkering with software that tries to learn metaphors. Mitchell has experimented with systems that interpret what’s happening in photos using analogies and a store of concepts about the world.

The reality gap impeding the robot revolution

Robot hardware has gotten pretty good. You can buy a palm-sized drone with HD camera for $500. Machines that haul boxes and walk on two legs have improved also. Why are we not all surrounded by bustling mechanical helpers? Today’s robots lack the brains to match their sophisticated brawn.

Getting a robot to do anything requires specific programming for a particular task. They can learn operations like grasping objects from repeated trials (and errors). But the process is relatively slow. One promising shortcut is to have robots train in virtual, simulated worlds, and then download that hard-won knowledge into physical robot bodies. Yet that approach is afflicted by the reality gap—a phrase describing how skills a robot learned in simulation do not always work when transferred to a machine in the physical world.

 

The reality gap is narrowing. In October, Google reported promising results in experiments where simulated and real robot arms learned to pick up diverse objects including tape dispensers, toys, and combs. 

Further progress is important to the hopes of people working on autonomous vehicles. Companies in the race to roboticize driving deploy virtual cars on simulated streets to reduce the time and money spent testing in real traffic and road conditions. Chris Urmson, CEO of autonomous-driving startup Aurora, says making virtual testing more applicable to real vehicles is one of his team’s priorities. “It’ll be neat to see over the next year or so how we can leverage that to accelerate learning,” says Urmson, who previously led Google parent Alphabet’s autonomous-car project.

Guarding against AI hacking

The software that runs our electrical gridssecurity cameras, and cellphones is plagued by security flaws. We shouldn’t expect software for self-driving cars and domestic robots to be any different. It may in fact be worse: There’s evidence that the complexity of machine-learning software introduces new avenues of attack.

Researchers showed this year that you can hide a secret trigger inside a machine-learning system that causes it to flip into evil mode at the sight of a particular signal. The team at NYU devised a street-sign recognition system that functioned normally—unless it saw a yellow Post-It. Attaching one of the sticky notes to a stop sign in Brooklyn caused the system to report the sign as a speed limit. The potential for such tricks might pose problems for self-driving cars.

The threat is considered serious enough that researchers at the world’s most prominent machine-learning conference convened a one-day workshopon the threat of machine deception earlier this month. Researchers discussed fiendish tricks like how to generate handwritten digits that look normal to humans, but appear as something different to software. What you see as a 2, for example, a machine vision system would see as a 3. Researchers also discussed possible defenses against such attacks—and worried about AI being used to fool humans. 

Tim Hwang, who organized the workshop, predicted using the technology to manipulate people is inevitable as machine learning becomes easier to deploy, and more powerful. “You no longer need a room full of PhDs to do machine learning,” he said. Hwang pointed to the Russian disinformation campaign during the 2016 presidential election as a potential forerunner of AI-enhanced information war. “Why wouldn’t you see techniques from the machine learning space in these campaigns?” he said. One trick Hwang predicts could be particularly effective is using machine learning to generate fake video and audio.

Graduating beyond boardgames

Alphabet’s champion Go-playing software evolved rapidly in 2017. In May, a more powerful version beat Go champions in China. Its creators, research unit DeepMind, subsequently built a version, AlphaGo Zero, that learned the game without studying human play. In December, another upgrade effort birthed AlphaZero, which can learn to play chess and Japanese board game Shogi (although not at the same time).

That avalanche of notable results is impressive—but also a reminder of AI software’s limitations. Chess, shogi, and Go are complex but all have relatively simple rules and gameplay visible to both opponents. They are a good match for computers’ ability to rapidly spool through many possible future positions. But most situations and problems in life are not so neatly structured.

That’s why DeepMind and Facebook both started working on the multiplayer videogame StarCraft in 2017. Neither have yet gotten very far. Right now, the best bots—built by amateurs—are no match for even moderately-skilled players. DeepMind researcher Oriol Vinyals told WIREDearlier this year that his software now lacks the planning and memory capabilities needed to carefully assemble and command an army while anticipating and reacting to moves by opponents. Not coincidentally, those skills would also make software much better at helping with real-world tasks such as office work or real military operations. Big progress on StarCraft or similar games in 2018 might presage some powerful new applications for AI.

 

Teaching AI to distinguish right from wrong

Even without new progress in the areas listed above, many aspects of the economy and society could change greatly if existing AI technology is widely adopted. As companies and governments rush to do just that, some people are worried about accidental and intentional harms caused by AI and machine learning.

How to keep the technology within safe and ethical boundswas a prominent thread of discussion at the NIPS machine-learning conference this month. Researchers have found that machine learning systems can pick up unsavory or unwanted behaviors, such as perpetuating gender stereotypes, when trained on data from our far-from-perfect world. Now some people are working on techniques that can be used to audit the internal workings of AI systems, and ensure they make fair decisions when put to work in industries such as finance or healthcare.

The next year should see tech companies put forward ideas for how to keep AI on the right side of humanity. Google, Facebook, Microsoft, and others have begun talking about the issue, and are members of a new nonprofit called Partnership on AI that will research and try to shape the societal implications of AI. Pressure is also coming from more independent quarters. A philanthropic project called the Ethics and Governance of Artificial Intelligence Fund is supporting MIT, Harvard, and others to research AI and the public interest. A new research institute at NYU, AI Now, has a similar mission. In a recent report it called for governments to swear off using “black box” algorithms not open to public inspection in areas such as criminal justice or welfare.

Written by Tim Simonite to wired.com

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