IBM Watson – Technology Or Magic ?

Isaac Asimov, a science fiction author wrote a trilogy series called “Foundation” in 1950s. The foundation is all about a scientist named Harry Seldon who picks up a group of high IQ people in different fields at a very early age of 8 to 10 years and creates a civilization on an uninhabited planet. A super computer governs this civilization. Since all the people are of known behavioural trend, this computer not only analyses  characters and their offsprings, but also governs them silently. At any given time it can predict who is going to be their leader, how long he is going to rule and who will be the successor. It can predict the entire civilization for next 150 years. When an issue arises, the computer can predict and provides the solution for the same. It learns from the current civilization to prepare prediction for next 150 years.

Now the entire story is far fetched, but seemingly plausible, thanks to Watson. That is the power of Watson. Its artificial intelligence, though not as accurate as that depicted in the fiction, it is a starting point.

IBM Watson can analyse all the data fed into it and come up with an accurate prediction. This is not an easy task for any computer or logic. It really pains us when somebody thinks Watson just answers queries. It is not a product or a piece of code, it is an IBM (marketing) brand used for a whole bunch of stuff.

Please don’t confuse a framework with an algorithm. Tensorflow is a software library that can be used to implement a number of machine learning algorithms. It’s the algorithm itself that matters, not the framework. Tensorflow is just a library that helps with parallelism, which is only useful in a hand full of cases.

IBM developers – as far as I know – are a bit indifferent when it comes to libraries. They rely heavily on (and contribute to) open source and will use whatever works best. A lot of the components/algorithms they use are much older than TensorFlow and most machine learning libraries. If you ask me, they probably have built most of this stuff from scratch without using any particular framework.

IBM Watson is a cognitive computing based Artificial intelligence super computer which uses unstructured big data as a source. Watson is a question answering computer system capable of answering questions posed in natural language.

Watson is a question answering computer system capable of answering questions posed in natural language, developed in IBM’s DeepQA project by a research team led by principal investigator David Ferrucci. Watson was named after IBM’s first CEO, industrialist Thomas J. Watson. The computer system was specifically developed to answer questions on the quiz show Jeopardy!

In 2011, Watson competed on Jeopardy! against former winners Brad Rutter and Ken Jennings.

Watson received the first place prize of $1 million.

Watson had access to 200 million pages of structured and unstructured content consuming four terabytes of disk storage including the full text of Wikipedia, but was not connected to the Internet during the game. For each clue, Watson’s three most probable responses were displayed on the television screen. Watson consistently outperformed its human opponents on the game’s signaling device, but had trouble in a few categories, notably those having short clues containing only a few words.

In February 2013, IBM announced that Watson software system’s first commercial application would be for utilization management decisions in lung cancer treatment at Memorial Sloan Kettering Cancer Center, New York City, in conjunction with health insurance company WellPoint.  90% of nurses in the field who use Watson now follow its guidance wholeheartedly.

At the core, Watson is a complex NLP system. Numerous processes are involved that are rule-based, such as Lucene building a variety of indices, based on rules, as one of 20+ pre-processing steps for corpus content i.e documents that contain the domain knowledge.

There is a second phase where humans provide examples of implicit rules. A textual query is related to a portion of the corpus, Q&A, essentially telling Watson that when it sees the same query after training it should respond with the area of the corpus indicated.

The challenge is that Watson, and NLP in general, is a non-deterministic system based on probabilities. The training process above is repeated thousands of times and the algorithms  build up probabilities of the relationship of a text query to an area of the corpus.

Some experts will suggest that IBM Watson is a failure and some will tell you that it is the biggest technological marvel ever. The debate will be forever, the lesson is to take the positives from the Watson and build on it.

Harnessing its powers is the way forward.

Understanding Cognitive Computing

Gartner has rated cognitive computing as a platform that will bring about a digital disruption unlike any seen in the last 20 years. This makes it worthwhile for your business to check out cognitive computing capabilities and how it can deliver advantages to your business.

Cognitive computing systems bring about the best of multiple technologies such as natural language queries and processing, real time computing, and machine learning based technologies. By using these technologies, cognitive computing systems can analyze incredible volume of both structured and unstructured data.

The objective of cognitive computing is to mimic human thoughts and put it in a programmatic model for practical applications in relevant situations. This biggest name in cognitive computing – IBM Watson, relies on deep learning algorithms aided by neural networks. They work together to absorb more data, learn more, and mimic human thinking better.

Advantages Of Cognitive Computing

Today, we have compiled a list of some key benefits of cognitive computing through real life use cases:

1 – Better data analysis

Take the example of healthcare industry. Cognitive computing systems can collate information, reports, and data from disparate sources like medical journals, personal patient history, diagnostic tools, and documentation of similar lines of treatment adopted in the past from different hospitals and medical care centers.

This provides the physician with data backed and evidence based recommendation that can enhance the level of patient care provided to the patient. So here, cognitive computing will not replace the doctor, it will simply take over the tedious job of sifting through multiple data sources and processing it in a logical manner.

2 – Efficient processes 

Swiss Re is a great example of how a complex process can be made simpler by employing cognitive computing. According to officials, using cognitive computing helps them to identify and take action based on emerging patterns. It also helps them to spot opportunities and uncover issues in real time for faster and more effective response.

Its underwriting process for the Life and Health Reinsurance business unit was revolutionized when it used IBM Watson to analyze and process huge amount of unstructured data around managing exposure to risk. This enabled them to purchase better quality risk and thus add to their business margins.

3 – Better level of customer interactions

Hilton partnered with IBM to enable better quality of interactions and drive a superior front desk and hospitality experience to guests. The result is Connie, a Watson enabled robot concierge. It can provide amazingly relevant, contextual, and accurate information on broad subjects around travel and hospitality, like, informing about local tourist attractions, providing information on hotel amenities, and providing fine dining recommendations. Hilton is reimagining the entire travel experience with Connie, to make it smarter, easier and more enjoyable for guests.

These advantages highlight the massive potential that cognitive computing possesses. Embracing it at an early stage will help you experiment and personalize the tremendous power of cognitive computing to deliver incredible gains to your business.

Marketing Bot- What is it?

Since time immemorial, there has been a lot of changes in technology which has only benefitted marketing and its attributes. Again, there is one consideration in artificial technology, which is becoming a hot topic to support online marketing. – the Bot.

Bots and chatbots are emerging as an integral part of automated technology, which are way too appealing to perform simple tasks with ability to respond as a human and interact like them.

Marketing ‘ChatBot,’ as the name suggests, is an interface integrated with channels like Slack and Facebook to revert to any customer query related to products. Rather than making customers wait for all day long for the revert, ChatBots can make it quick and real-time. This is not the end – the Bots can also collect and save the data for future insight of the customer and its behavior.

Who all are using Chat Bots?

Service-oriented companies which are looking for serving their customer queries in real time are using the chatbot. The prominent industries to name some are- travel industries, ecommerce industries and many more.

So, if you are willing your company’s marketing sales to be benefited with Chat Bots too, here are top 5 Chat Bots to consider.

Top 5 Chat Bots in Marketing

1. ManyChat

These days, Facebook has become a great deal for businesses as 75% of consumers are using it. So, if you have a Facebook Page of your company then ManyChat is the option for you. It will help you respond instantly to any Facebook query. You can also set auto-responses with keywords and post management on your page as well.

Other benefits

• 2 minutes required to set it up
• No coding is needed
• Targets only genuine news to your subscribers
• Automatically adds subscriber and updates everyone

2. SurveyBot

SurveyBot also works on the same interface as ManyChat does. With this bot, you can create marketing surveys to collect useful data from Facebook messaging. It behaves like a real human by using Answer Piping, re-engagement and conversational logic; it also uses 12 question types to put up right questions.

Other benefits

• Behaves more like a real human
• Collect information from subscribers
• Analyze survey results
• Build lead generation

3. MotionAi

With an amazing visual interface, Motion.Ai stands out as one of the most powerful bots. This bot is easy to set up and allows you to draw your own flowchart and chat diagram. Motion.Ai allows you to get bot templates and additional apps to get you started.

Other benefits

• Minutes to launch the bot
• Owns a bot store to choose templates
• 2 bots can be built
• 1000 messages per bot

4. Chatbot

Mr. Chatbot is specifically designed for ecommerce industry, which uses Chatbot technique of Facebook Messenger. It basically uses AI (Artificial Interactions) to drive sales. So, create your ecommerce Chatbot with Mr.ChatBot and see the difference.

Other benefits

• Responses within a few seconds
• Language usage according to users
• Signed up users will get Newsfeed and special promotions

5. Assist

Assist has a big name as it is used by Hyatt, one of the customer services oriented companies. This chatbot offers a platform for all types of conversation, doing away with the pre-defined scripts specifically for the travel, shopping, and hospitality domain.

Other benefits

• Fast working platform without pre-defined scripts
• Natural language processing
• Realistic interaction with customers

These chatbots signify everything that is right with the user experience delivered by way of engagement with the customer. When you are building a chatbot, the above 5 products would emerge as stellar examples of how a chatbot should be devised, designed, and deployed.

The Impact Of Artificial Intelligence

Gone are the days when Artificial Intelligence belonged to the realm of hardcore scientific technology. Today, it happens to be an integral segment of daily operations and day-to-day life. From the retail space to crime investigations, AI has revolutionized various sectors across the globe. We all have come across spam filtering and voice recognition systems. Those using iPhones are well acquainted with Siri, the personal voice assistant.

In a nutshell, AI has been there for a long time, and it is revolutionizing various aspects of human life and how! Here’s a short account of how Artificial Intelligence systems and technologies are taking human lives to the next level!

Focusing on the future

We just can’t deny our advancements towards technology and innovation. The time isn’t far when computerized robots would replace human workforce. We already have chatbots serving us, and that gives us crystal clear ideas of automated technologies. The prime focus is on the future and how AI can create opportunities for further development!

1. Chatbots in retail space

Customers will always want to get personalized experiences. While associating with a brand, they will want the company to understand their requirements, needs, and preferences. Chatbots collect crucial data about consumers thus creating endless opportunities for data analytics. Brands get the chance to create personalized products for consumers thus maximizing their revenues to a great extent.

Powered by Artificial Intelligence, chat bots and smart assistants have transformed the retail space completely. Even if you shop online, you can be sure of getting unmatched experiences.

2. AI powered financial advisors

Some of the companies are leveraging AI systems in a never-seen-before way. By extracting and analyzing historical data sets, they are learning about their customers’ investment decisions. Based on these reports and data, they are making meaningful assumptions thus offering the best investment opportunities to clients.

Digital financers are getting the chance to understand a person’s financial credibility thus offering the best assistance to him.

3. Empowering the general workforce

If you are operating in the service arena, you will need to know whether you are getting the right price for your service. AI systems and strategies have empowered service professionals, thus helping them know their true worth. With the help of Artificial Intelligence, employees can find out whether they are underpaid or get the right remuneration. The consequences are beneficial for both the employer and employees, as a satisfied workforce delivers unmatched performances.

4. Weather predictions

AI software and systems can come up with precise weather predictions. Individuals will get clear ideas of weather conditions in a particular place, which will help farmers to a great extent. That’s not all; with prior notifications about bad weather conditions, aircrafts can identify dangers and fly safely.

5. Increased security

No matter where you are, you can always play the careful vigilante. Whether it’s your home or office, AI systems will help you keep them safe and secure. You simply don’t need to worry about home safety, as smart security systems powered by Artificial Intelligence will do the needful.

AI systems have become a prime requisite for homes, commercial units, and business enterprises. With such remarkable footprints as of now, it won’t be wrong if we say that Artificial Intelligence is here to make lives better!

How Does A Chat Bot Work?

Chatbots make it easier for people to communicate with businesses.

Think of it as a replacement for all of the apps you have downloaded. Instead of opening the Airlines app, chatbot could tell you your flight’s delayed, another chatbot from FedEx could tell you your package is on the way, and so on.

Chatbots allow you to search for the info in natural conversational language as compared to search engines where you will have to input not so natural ‘keywords’.

These bots will fill a role of being both useful and promotional for Brand’s Facebook pages where they already put lot of efforts on customer engagement. Bots will take it to the whole another level.

• Hey, what’s up?
• How’re you doing?
• How do you do?
• Hello!

Anything familiar in these sentences?

They all are some or the other variation of a greeting message.

How do you respond when someone asks you one of the above questions?

You respond, typically like – I am good, how about you?

Some other day you might respond as – I am fine, thanks for asking.

This is exactly how Chat Bots work. A typical Chat Bot maps a sentence into a so called intent which in this case is the greeting intent. With every intent are associated a set of responses. The bot picks up one of these responses and sends it back to the user. This is done so as to give a more natural feel to the bot by avoiding sending the exact same response again and again.

Platforms like Facebook has given developers access to Chat SDKs that allow them to build interactive experiences and bots for interaction, shopping, booking travel etc.

Following are few capabilities of these platforms :

1. Send/Receive API. This includes the ability to send and receive text, images, and other rich content with CTAs.

2. Generic Message Templates. People definitely prefer to tap buttons and see beautiful images, rather than learning new difficult ways to interact with your bot. That’s there are structured messages with call to actions, horizontal scroll, urls, etc.

3. Welcome screen + Null state CTAs. Developers can think of the message thread as their own app. There are tools available to customize the experience. This starts with the welcome screen. People discover featured bots and enter the conversation. Then, they see your brand, your Messenger greeting, and a call to action to “Get Started”.

4. Natural Language Assistance : The Wit – landing Bot Engine of Facebook enables ongoing training of bots using sample conversations. This enables you to create conversational bots that can automatically chat with users. This helps you to build bots much easily. You just have to tell what your user said, the engine will tell you what your bot should do next.

5. Bot continuously gets smarter as it learns from conversations it has with people.

What is the AI involved?

The element of Artificial Intelligence comes in during the intent recognition. The bot is supposed to take a look at the words and possibly their arrangement in order to figure out what the intent is. This can be done in multiple ways like:

• Simple word mapping: words like hi, hello, what’s, etc can be mapped to the greeting intent. However, this is quite inaccurate because ‘hello, who the hell are you?’ doesn’t quite sound like a greeting 😛
• Machine Learning: if you are familiar with Machine Learning, you would be able to easily identify that the above problem is a supervised learning based classification problem. In simpler words, the problem at our hand is as follows – you are given a bunch of sentences and the corresponding intent against them. Now, you are given a new sentence and you need to classify it as belonging to one of the intents. This problem can be solved using a number of ways. The simplest way would be to use a Naive Bayes based implementation. In this implementation, we convert the sentence into a vector of numbers. The corresponding intents are also given ‘codes’ to identify them numerically. This input is fed to a training algorithm which learns how to classify these sentences. Later on, the trained model can be used to classify new sentences (if it has been trained well). Over time, it can be retrained with fresh data so as to make it learn better.

A more complex Machine Learning approach will involve training a multi-layer artificial neural network which is almost sure to give far better accuracy.

Once the intent has been identified, the bot can pick up one of the answers corresponding to the intent.

In simpler terms

• Your knowledge base or CMS is the database of information that is used to seed your chatbot with the information needed to respond to your users’ questions
• The data store captures data on your users’ activities and whether or not your chatbot was able to match their questions or prompts with an adequate response
• Natural Language Processing translates users’ free form questions into information that can be mapped in real-time to find or formulate appropriate responses
• Finally, the chat apps shown in the schema above — e.g., Facebook Messenger, Slack, Whatsapp, etc. — are the interface through which users access and interact with your bot

Once up and running, a chatbot requires a training period, during which the system “learns” how to best match users’ questions to appropriate responses. The more interactions, the more data,  the faster the chat bot learns and the more quickly you’re able to provide a high-quality experience for your users.

The Future Of Business Intelligence

In today’s modern world, business intelligence is of utmost importance as data in business practices take center stage. BI will stand in the prime of all this and will direct future marketing strategies and business decisions. After all it is proven that companies using analytics are 5x more likely to make faster business decisions.

Today we look at BI’s prospects and why it will be center to all major business decision making in 2017 and beyond:

1. Big Demand for BI analyst

As the graph of Big Data increases, the no of people require to crunch that data and arrive at an intelligent solution for a business enterprise will simultaneously increase. A report by Mckinsey global institute states that in the next four years the US alone would face a shortage of 1.5 million managers and 1,90,000 analysts.

2. Make it universal

Currently, BI is specifically targeted to internal employees and information workers. The more it’s spread out and the more relevant it becomes to everyone, it will be a Game Changer. Outside the purview of corporate boundaries, it should reach out to suppliers and customers. Business intelligence has the power to enable businesses to compete more effectively and change people’s way of working.

3. Easier analysis of past data

As the cost of storage for data shrinks rapidly, it would be much easier to analyze past events and data. For example, currently due to data cost we are able to analyze just an economic cycle but in future, we can analyze much more than that. This will help us in forming a strong pattern. This will help businesses to bear just minimum losses in the event of a recession. History is a great teacher and BI will help us to avoid repeating the same mistake.

4. Personal analytics will be norm

As more and more data gets collected in the system, the future definitively holds good for personal analytics. It can primarily be used for self-improvement. Also, it will be used for improving family life and local communities. BI won’t be geeky in the future and everyone will be able to self-analyze. There are tremendous opportunities for software vendors to develop tools regarding personal analytics.

5. Business Intelligence will be a collaborative effort

The future of the BI would bring different tools and platforms together. Today individual BI is the norm, tomorrow it will be collaborative. Shared and immersive analytical experiences would increase in great proportion. The form factor of the devices will also gradually shift from small to large. This will help a group of data scientists explore data in real time basis.

6. Data knowledge Gap will shrink further

Data knowledge Gap in the next few years will further narrow from a group of data scientists to a normal manager or executive. As more forms of data visualization grow, more people will become familiar and comfortable with it. Major companies will also mandate training in BI.

With the above-mentioned points, there is ample evidence that Business Intelligence is here to stay. We can safely assume that, not only will it make a big impact but also it will scale up rapidly.

Facebook Engineers Pull The Plug On AI Bots

As the world’s most powerful computer systems begin to embrace artificial intelligence in earnest, using smart algorithms to increase efficiency and and speed, the potential damage that a “rogue” AI could cause continues to grow. Many in the tech community have theorized how an artificial mind could turn against its creators, and Facebook just got an interesting lesson in how such a scenario might unfold. Facebook engineers were forced to pull the plug on one of the company’s AI systems after its bots began communicating with each other in a completely new language which humans simply couldn’t decipher.

Facebook developers were attempting to get the two “chatbots” to barter a trade with one another utilizing hats, balls, and books of varying values, according to the Independent. The two bots quickly resorted to speaking a variation of English between one another that seemed largely incomprehensible to the developers but was seemingly understood clearly by the two bots.

The AI bots, which were originally programmed to use plain English to communicate with one another, were found to be speaking what appeared to be gibberish. Sentences like “I can can I I everything else” and “Balls have zero to me to me to me to me to me to me to me to me to,” were being sent back and forth by the AI, and while humans have absolutely no idea what it means, the bots fully understood each other. Without being able to understand how or why the bots were communicating, Facebook had no choice but to shut down the system.

The very obvious danger here is that computer which can communicate with each other using their own language are not only impossible to understand but much more difficult to control. In this case, the bots were not bound by plain language and seemingly developed a more efficient way of communicating with each other, deciding for themselves what was best.

It’s both impressive and scary.

AI Industrial Applications

Technological advancements have always been the prime force behind the creation of innovative applications. From the business landscape to service industries, tech innovations have completely revolutionized operations and functionalities. The latest inclusion in the list of technological discoveries is AI, which is ensuring unmatched experiences for users.

From the entertainment industry and service sectors to manufacturing and production, Artificial Intelligence or AI is the source for numerous revolutions. On that note, we can take a quick look at the most significant applications of AI.

Identifying the applications

Take a look around, and you will come across innumerable operations where Artificial Intelligence is used. Whether it is a coming-of-age gaming app or online shopping portals, AI is helping developers create personalized user experiences. Here are some of the industrial applications of the technology.

1.     Artificial Intelligence in entertainment

Games development is a significant project in the entertainment industry. With the ever-changing needs of individuals, developers are trying their best to create gaming apps with improved functionality. You must be aware of some of the names like Far Cry and Middle Earth. While playing these games, the player can impersonate a real-world person and perform several activities like him or her. Doesn’t it sound interesting? Well, it is the AI technology that makes it happen.

2.     Artificial Intelligence in e-commerce 

Every shopper wants to enjoy personalized shopping experience. You will surely love it when your targeted store knows your preferences and can offer products according to that. Almost every leading ecommerce store leverages AI to identify their consumers’ interests and develop specific shopping plans for them. Recommendations and the presence of chatbots will help consumers find answers to their queries.

3.     Artificial Intelligence in Reporting and journalism

Report preparation is an integral part of journalism and news-making. With the emergence and widespread popularity of digital platforms and channels, articles and blogs have gained huge importance amongst voracious readers. Those who wish to stay informed about the latest developments and stay abreast with tech advancements follow well-written blogs. What some of us don’t know is that simple reports and articles aren’t that tough to prepare, and one can do so by leveraging Artificial Intelligence.

4.    Artificial Intelligence in Finance and banking

The rise in banking transactions and an increase in the number of financial accounts have created the need for automated processes. Data accumulation, analysis, and processing have become quite crucial for the hassle-free maintenance of business accounts. It’s here that AI makes your job easier in the following ways:

• Tracking consumer base
• Identifying and solving issues
• Ensuring 100% transaction security
• Offering suggestions on beneficial schemes and policies

Banking institutions and financial service providers are making the most of AI, thus ensuring unmatched experience for consumers.

5.     Artificial Intelligence in healthcare industry

The healthcare sector is growing by leaps and bounds thus creating the need for innovative processes and technologies. Doctors and physicians need a technology that can help them diagnose a patient easily. AI applications, specially created for the healthcare sector, can also help in the treatment procedures. That’s a great way of reducing the time which will automatically cut down costs.

Signing off

The usage and application of Artificial Intelligence have become highly important for the growth of diverse sectors. It finds specific advantages in industrial uses, as depicted in this post.

The Chat Bot Revolution

Significant developments in AI and the rapid proliferation of messaging applications have led to the growth of chatbots. We will surely come across a multitude of tasks that are performed and executed through messaging apps and software. It is no wonder that Juniper’s new research finds that chatbots will lead to a cost savings of $20 million in 2017 which will multiply to a whopping $8 billion by 2022.

It’s here that we come to the crucial point. Does the widespread popularity or increased usage of these bots point at a specific opportunity? Does it actually talk about a trend that’s going to rule the tech arena in future? Finding answers to these crucial questions is what we plan to do with this blog!

The recent developments in the world of chat bots

Chat bots have come a long way from just being communication aids to integrated messaging software. Companies are taking a keen interest in providing services and solutions around this technology. Cases in point –

1. Microsoft’s own bot framework to allow development of chatbots
2. Facebook acquires Wit.ai
3. IBM acquires Cognea

App usage recession

There’s no denying the utility of apps even till this day! Dynamic, highly functional, and innovative applications have completely transformed the way people work and do business. However, things began to change from 2015. Apps weren’t the ‘hot’ property anymore as the app market was struck by severe recessive forces.

If we refer to what Google has to say about this, we will find that an average user has nearly 36 applications on his smartphone. However, 80% of those apps aren’t used regularly. That explains the situation quite clearly. If you want your app to get noticed and used on a daily basis, it has to be relevant and rank amongst those few apps which find applications in day-to-day functioning. While social media apps are the most popular ones, it is the gaming applications that follow suit.

The emergence of Chatbots

What we need to find out is how chat bots are different from apps? Are they reincarnations of an application or distinctive entities? Let’s take a look!

Businesses today share one point of similarity. Each of them strives hard to ensure 100% satisfaction for consumers. Whether it’s a small-scale business or a huge venture, customer service and support are critical to its growth and development. It is here that chat bots enter into the scene. Every consumer or buyer will wish to gain personalized experiences while associating with a brand and chat bots can make it happen for them.

What’s the future for chatbots?

We can’t depend or rely on technologies entirely when it comes to ensuring 100% customer satisfaction and support. Human intervention is always necessary. However, chat bots ensure logical, transparent, and clear communications. You will have them right within your applications, and no matter what you speak will get recorded. So, there’s no chance of ambiguities or confusions.

As far as the current market trends suggest, chat bots are heading towards a bright future. Let’s keep our fingers crossed and wait for the final results!

The AI Surge

The continued interest of businesses and consumers alike in going beyond the norm has spawned the massive rise of Artificial Intelligence globally. Even if we are ready or not, AI is definitely entering our lives and will not stop anytime soon. Be it NLP, ML, or cognitive computing, AI is providing tremendous gains to businesses in improving their sales and marketing functions, and assist in design of new business models.

Some eye-opening stats indicate the way businesses are embracing Artificial Intelligence like never before–

• Gartner predicts that by 2020, almost 1/3^rd of the companies will use AI in some form within atleast one of their primary sales processes.
• IDC predicts that by 2019 (just two years down the line), 40% of the digital transformation initiatives will involve AI capabilities
• IDC also predicts that by 2019, almost all IOT initiatives will be supported by AI capabilities

Be it self-driving cars or digital PA’s, AI is growing and growing fast. 2017 can rightly be called as the watershed year for AI. There are four primary reasons for this statement:

1 – Decreasing computing and bandwidth costs

Chips are becoming smaller and more cost-effective. This means that in all likelihood there will be a chip or processor in every single thing. This reversal of Moore’s Law will be the primary accelerant for increased adoption of Artificial Intelligence the world over. Also the steadily falling bandwidth costs means that faster speeds can be availed of at a lower price.

2 – Data – The oil needed to run AI machine

Any AI system is as good as the data it generates, analyzes and acts upon. Fortunately, with the rise of Social, Media, Analytics, and Cloud (SMAC), the volume and velocity of data being generated from various sources has literally exploded in the last decade. This data is now being harnessed in smart ways by AI systems to improve their performance and provide a better user experience. It is data that enables machine to learn. Instead of models, we now have actual data to describe various conditions to feed into the AI system.

Google’s AlphaGo Beats a Go World Champion

3 – Connected devices

The parallel rise of IOT and connected devices is also a big boost to the Artificial Intelligence industry.  RFID and sensors have enabled transmission of huge amount of quality data among connected devices that can also receive instructions and be programmed for specific actions.

4 – Improvements in Machine Learning capabilities

On its own, data cannot be used much. It needs to be refined and analyzed so that patterns emerge ad trends arise from seemingly random numbers and figures. With Machine Learning, algorithms and models can be applied to extract this advantage from unrefined data. Some examples include –

• Facebook’s DeepFace,
• Google AI platform, AlphaGo that beat a Chinese player in Go, and
• Google X Labs’ Machine Learning algorithm that picks cat videos on YouTube

As evident, Artificial Intelligence will be a significant disruptor across major industries in the world. The key question here will be – Are you already to adapt to the magical world of AI?