Understanding Artificial Intelligence, Machine Learning and Deep Learning

Artificial Intelligence (AI) and its subsets Machine Learning (ML) and Deep Learning (DL) are playing a major role in Data Science. Data Science is a comprehensive process that involves pre-processing, analysis, visualization and prediction. Lets deep dive into AI and its subsets.

Artificial Intelligence (AI) is a branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is mainly divided into three categories as below

  • Artificial Narrow Intelligence (ANI)
  • Artificial General Intelligence (AGI)
  • Artificial Super Intelligence (ASI).

Narrow AI sometimes referred as ‘Weak AI’, performs a single task in a particular way at its best. For example, an automated coffee machine robs which performs a well-defined sequence of actions to make coffee. Whereas AGI, which is also referred as ‘Strong AI’ performs a wide range of tasks that involve thinking and reasoning like a human. Some example is Google Assist, Alexa, Chatbots which uses Natural Language Processing (NPL). Artificial Super Intelligence (ASI) is the advanced version which out performs human capabilities. It can perform creative activities like art, decision making and emotional relationships.

Now let’s look at Machine Learning (ML). It is a subset of AI that involves modeling of algorithms which helps to make predictions based on the recognition of complex data patterns and sets. Machine learning focuses on enabling algorithms to learn from the data provided, gather insights and make predictions on previously unanalyzed data using the information gathered. Different methods of machine learning are

  • supervised learning (Weak AI – Task driven)
  • non-supervised learning (Strong AI – Data Driven)
  • semi-supervised learning (Strong AI -cost effective)
  • reinforced machine learning. (Strong AI – learn from mistakes)

Supervised machine learning uses historical data to understand behavior and formulate future forecasts. Here the system consists of a designated dataset. It is labeled with parameters for the input and the output. And as the new data comes the ML algorithm analysis the new data and gives the exact output on the basis of the fixed parameters. Supervised learning can perform classification or regression tasks. Examples of classification tasks are image classification, face recognition, email spam classification, identify fraud detection, etc. and for regression tasks are weather forecasting, population growth prediction, etc.

Unsupervised machine learning does not use any classified or labelled parameters. It focuses on discovering hidden structures from unlabeled data to help systems infer a function properly. They use techniques such as clustering or dimensionality reduction. Clustering involves grouping data points with similar metric. It is data driven and some examples for clustering are movie recommendation for user in Netflix, customer segmentation, buying habits, etc. Some of dimensionality reduction examples are feature elicitation, big data visualization.

Semi-supervised machine learning works by using both labelled and unlabeled data to improve learning accuracy. Semi-supervised learning can be a cost-effective solution when labelling data turns out to be expensive.

Reinforcement learning is fairly different when compared to supervised and unsupervised learning. It can be defined as a process of trial and error finally delivering results. t is achieved by the principle of iterative improvement cycle (to learn by past mistakes). Reinforcement learning has also been used to teach agents autonomous driving within simulated environments. Q-learning is an example of reinforcement learning algorithms.

Moving ahead to Deep Learning (DL), it is a subset of machine learning where you build algorithms that follow a layered architecture. DL uses multiple layers to progressively extract higher level features from the raw input. For example, in image processing, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits or letters or faces. DL is generally referred to a deep artificial neural network and these are the algorithm sets which are extremely accurate for the problems like sound recognition, image recognition, natural language processing, etc.

To summarize Data Science covers AI, which includes machine learning. However, machine learning itself covers another sub-technology, which is deep learning. Thanks to AI as it is capable of solving harder and harder problems (like detecting cancer better than oncologists) better than humans can.

Death Of The DVD – Are Video Rentals A Thing Of The Past?

Don’t we all have fond memories of renting movies at Blockbuster? Our family would schedule movie night, pop in some buttery microwave popcorn, and rent the latest DVD of choice. My sister and I would fight over who gets to pick the movie, and end up renting a chick flick that my dad has to sit through. But those memories seem to be a thing of the past. With the steady decline of Blockbuster Video sales in the past few months, reports have shown that they are finally filing for bankruptcy this September. Is this finally the death of the DVD?

This was not the first scare in the past years. In the late 1980s and the uprise of cable channels like HBO and Cinemax, the chitchat among tech experts and publicists were predictions about the end of the video retail world. People were going to prefer getting cable television than go out and rent a movie, but that didn’t really materialize.

And then came the Internet. It first started with the decline of CD sales due to the Napster era, when online music downloads posed an imminent threat to the largest music stores. It trickled over to the video retail scene in the late 90s by means of DivX, an online compression technology that allowed users to download their favorite movies in high quality. Discussion forums and threads were bustling with predictions about the decline in sales for the movie rental businesses, but the retail industry crept back up and people were enjoying their much needed Blockbuster fix.

But here comes another threat: Netflix and Gamefly, online service offerings that provide flat rate DVD through rent-by-mail and streaming capabilities. Just recently, Netflix celebrated their 2 millionth user. This is even discounting RedBox, a kiosk-based DVD rental business that lets anyone rent movies for a dollar overnight. Blockbuster strived to compete against these emerging businesses by launching Blockbuster On Demand and select kiosks, but looks like their feeble attempts have not been very successful.

Blockbuster’s claim is that the announced bankruptcy will last for only a couple of months, but technology experts state otherwise. The former number one video retail store has already closed out hundreds of stores and launched thousands of kiosks across the country.

Not that we have seen a decline in the movie industry. In fact, millions of people have started to watch more movies than they’ve ever had for the past few years. Returns from films show that it is up by a couple hundred millions this year, and people still enjoy watching the latest films in movie houses. The movie industry is booming, but we don’t know for certain if the next few months will predict the conclusion of the hope that was given to video retail stores nationwide.

Major film studios such as Universal, Sony, Walt Disney, Fox, Paramount and Warner Brothers have agreed to discuss this with Blockbuster’s CEO Jim Keyes, but we don’t know what the future holds for them. If Blockbuster can act quickly and provide competitive advantage to a world of music downloads, video streaming and kiosk convenience, then the impending death of the DVD may not be realized soon.

Top VR Games for Your Android Phone

VR or virtual reality is the new innovation by the tech world that has become an integral part of almost all sorts of games online. Virtual reality is a three dimensional environment that would render live and interactive experience to the gamer. There games are being designed to enhance the quality of the games and to give an awesome gaming experience to the gamer. The more innovative and user-friendly versions of these VR games are coming up in these days that are compatible enough even on smart phones.

Latest VR games would allow you to play the game on multiple devices with a single gamer name. You can play while commuting also by using your android phones. The latest versions of VR games are designed in such a way that they would render the same experience as a pc, laptop or a play station. Now as we know what is a VR game is all about let’s look at few latest VR games designed for android phones,

• Mekorama VR – A puzzle game where you have to guide a small robot through various levels. At the beginning it’s quite simple because there will be few stones to be moved but the difficulty increases from one level to the next. In this game you use the controller to move the stones and show the robot the way to move up.

• Hunters Gate: A game for action lovers – You will become a savior of the world when the world has been attacked by demons and you have to keep them back. This is a fun-filled and graphically impressive game. This is a famous rolling game whose elements make you stronger over time and will teach you new skills. For playing this game you must use daydream controllers, and these controllers help you in keeping track of what’s happening from above, which reduces your too much interaction with the virtual movement.

• Need for Speed: A VR game for admirers of speed, the game enhances the sensation of speed by Virtual Reality and is probably the best racing game for Daydream-capable smart phones. An exciting ride is guaranteed because of its impeccable graphics and breakneck-pace. Besides that the choice of customization and car tuning made this game more enchanting and exciting.

• Gun jack 2: End of Shift – A game where you will be sitting on cannon on our solar system and fend off the attackers who are desperate to steal the minerals from our planet. You will be having immense arsenal weapons and can control everything with your gaze.