What Is Artificial Intelligence (AI)?

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.

The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal.

When most people hear the term artificial intelligence, the first thing they usually think of is robots. That’s because big-budget films and novels weave stories about human-like machines that wreak havoc on Earth. But nothing could be further from the truth.

As technology advances, previous benchmarks that defined artificial intelligence become outdated. For example, machines that calculate basic functions or recognize text through optimal character recognition are no longer considered to embody artificial intelligence, since this function is now taken for granted as an inherent computer function.

AI is continuously evolving to benefit many different industries. Machines are wired using a cross-disciplinary approach based in mathematics, computer science, linguistics, psychology and many more.

What is machine learning?

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.

The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.

But, using the classic algorithms of machine learning, text is considered as a sequence of keywords; instead, an approach based on semantic analysis mimics the human ability to understand the meaning of a text.

Current statistics of ai in use today

Today, Artificial Intelligence is a very popular subject that is widely discussed in the technology and business circles. Many experts and industry analysts argue that AI or machine learning is the future — but if we look around, we are convinced that it’s not the future — it is the present.

With the advancement in technology, we are already connected to AI in one way or the other — whether it is Siri, Watson or Alexa. Yes, the technology is in its initial phase and more and more companies are investing resources in machine learning, indicating a robust growth in AI products and apps in the near future.

The following statistics will give you an idea of growth!

– In 2014, more than $300 million was invested in AI startups, showing an increase of 300%, compared to the previous year (Bloomberg)

– By 2018, 6 billion connected devices will proactively ask for support. (Gartner)

– By the end of 2018, “customer digital assistants” will recognize customers by face and voice across channels and partners (Gartner)

– Artificial intelligence will replace 16% of American jobs by the end of the decade (Forrester)

– 15% of Apple phone owners’ users use Siri’s voice recognition capabilities. (BGR)

Unlike general perception, artificial intelligence is not limited to just IT or technology industry; instead, it is being extensively used in other areas such as medical, business, education, law, and manufacturing.

How Does Google Use Machine Learning?

In modern times, Google is everywhere!!! So much so that you are most probably reading this article using Google Search. And while Machine Learning has long been a part of Google, now it seems that ML is everywhere! From Google Search to Google Photos to even Google Translate, everything uses Machine Learning.

And these are only the more common items! In fact, Google and its parent company Alphabet are heavily invested in Machine Learning Research in almost all imaginable fields like Ethical Principles, Quantum Computing, Healthcare, Robotics, Perception, etc. Sundar Pichai, the CEO of Google commented that “Machine learning is a core, transformative way by which we’re rethinking how we’re doing everything. We are thoughtfully applying it across all our products, be it search, ads, YouTube, or Play. And we’re in early days, but you will see us apply machine learning in all these areas.”

So it is obvious that Google eventually plans on fully integrating Machine Learning in all its operations. But that futuristic world is still a little far away! For now, let’s see some of the ways in which Google currently uses Machine Learning so that we can understand the full scope of its applications in the future.

1. Google Translate

Want to translate a text from English to Hindi but don’t know Hindi? Well, Google Translate is the tool for you! While it’s not exactly 100% accurate, it is still a great tool to convert text, images, or even real-time video from one language to another. And in case you wonder how it translates more or less accurately, well Google Translate uses Machine Learning of course!
It uses Statistical machine translation (SMT) which is a fancy way of saying that it analyses millions of documents that are already translated from one language to another (English to Hindi in this case) and then looks for the common patterns and basic vocabulary of the language. After that, it picks the most accurate translation possible based on educated guesses that mostly turn out to be correct. For Example: Let’s see how Google Translate translates “Machine Learning is cool” into Hindi!!!

2. Google Photos

In case you are a millennial, I am sure you are a selfie addict! And of course, you use Google Photos a lot if you are an Android user as well. And it’s no shock that you do! Google Photos allows you to back up all your photos in a single location even if they were shot from multiple devices and it also offers lots of other cool effects using Machine Learning.
For Example, Google Photos also automatically creates albums of photos taken during a specific period without any input from you. And that’s not all, it can also select the “best photos”. And in case you haven’t sorted all your pictures into albums, you can also search for them by typing in names. Suppose you want to find a picture with your dog, type in “Dog” and you will get all the dog pictures! This is done using Image Recognition, wherein Deep Learning is used to sort millions of images on the internet in order to classify them more accurately. So using Deep Learning, the images that are classified as “Dog” in your Google Photos are displayed.

3. RankBrain

Suppose you want to know who is the CEO of Google? And then you want to know who is his wife? But how do you search this on Google? You cannot exactly write the name of Sundar Pichai or his wife since you don’t know it! In this case, you can simply search “CEO of google wife” on Google and you will get the required results. This is achieved using RankBrain in Google Search.

4. Google Assistant

Want a little help in organizing your calendar? Want to know the best Italian restaurants near your home? Want to book movie tickets on the go? Well, never fear!!! Google Assistant is here to make your life easier! It is basically a personal assistant that is enabled using a combination of Google Knowledge Graph, Image Recognition, and Natural Language Processing.

The Google Assistant is envisioned as a chatbot by Google which can be connected to your phones, TVs, speakers, etc. with the ability to actually have a conversation with you. Here the Google Knowledge Graph provides information gathered from various sources while Natural Language Processing allows the Google Assistant to interact with you and formulate its answers according to your questions.

5. DeepDream

We all know that humans dream? Well, what if computers dream as well?!! This is the premise of Google DeepDream that used convolutional neural networks to find random patterns in various images and amplifies them in different ways. These images can be tweaked in any possible manner using the input data and various parameters so that the results obtained can be funny, weird or even trippy!!!

Other Powerful examples of ai in use today

1. Siri

Siri is one of the most popular personal assistant offered by Apple in iPhone and iPad. The friendly female voice-activated assistant interacts with the user on a daily routine. She assists us to find information, get directions, send messages, make voice calls, open applications and add events to the calendar.

Siri uses machine-learning technology in order to get smarter and capable-to-understand natural language questions and requests. It is surely one of the most iconic examples of machine learning abilities of gadgets.

2. Tesla

Not only smartphones but automobiles are also shifting towards Artificial Intelligence. Tesla is something you are missing if you are a car geek. This is one of the best automobiles available until now. The car has not only been able to achieve many accolades but also features like self-driving, predictive capabilities, and absolute technological innovation.

If you are a technology geek and dreamt of owning a car like shown in Hollywood movies, Tesla is one you need in your garage. The car is getting smarter day by day through over the air updates.

3. Cogito

Cogito originally co-founded by Dr. Sandy and Joshua is one of the best examples of the behavioral version to improve the intelligence of customer support representatives, currently on the market. The company is a synthesis of machine learning and behavioral science to enhance customer collaboration for phone professionals.

Cogito is applicable on millions of voice calls that take place on a daily basis. The AI solution analyzes the human voice and provides real-time guidance to enhance behavior.

4. Netflix

Netflix needs no introduction — it is a widely popular content-on-demand service that uses predictive technology to offer recommendations on the basis of consumers’ reaction, interests, choices, and behavior. The technology examines from a number of records to recommend movies based on your previous liking and reactions.

It is turning more intelligent with each passing year. The only the drawback of this technology is that small movie go unnoticed while big films grow and propagate on the platform. But as I wrote earlier, it is still improving and learning to be more intelligent.

6. Flying Drones

The flying drones are already shipping products to customers home — though on a test mode. They indicate a powerful machine learning system that can translate the environment into a 3D model through sensors and video cameras.

The sensors and cameras are able to notice the position of the drones in the room by attaching them to the ceiling. Trajectory generation algorithm guides the drone on how and where to move. Using a Wi-Fi system, we can control the drones and use them for specific purposes — product delivery, video-making, or news reporting.

Conclusion

Artificial Intelligence is gaining popularity at a quicker pace; influencing the way we live, interact, and improve customer experience. There is much more to come in the coming years with more improvements, development, and governance.The applications for artificial intelligence are endless. The technology can be applied to many different sectors and industries.