Top Virtual Reality (VR) games:

Technology has grown leaps and bounds during the last couple of decades. Developers are pushing the boundaries to create tech solutions that are innovative and unique. One such technology that has gained popularity in recent times is Virtual Reality. It is an artificial environment created with software and presented to the user in a way that the user suspends belief and accepts it as a real environment. It includes three-dimensional images that appear to be life-sized from the user’s perspective. It also has the ability to track a user’s motions and eye movements, and correspondingly adjust images on the user’s display to reflect the change in perspective.

The virtual reality world must be large and detailed enough for users to explore and get immersed into. With PlayStation VR, HTC Vive, and Oculus Rift out alongside less expensive headsets like the Samsung Gear VR, Google’s Daydream View and Cardboard, users have a huge selection of Virtual Reality games to choose from.

Here are some of the most popular VR games among users.

Fallout 4 VR: With detailed environments and engaging gunplay, Fallout 4 VR was one of the biggest VR titles in 2017. There are several weapons that players can choose to blow away the inhabitants of the virtual world. This first person shooter game is currently exclusive to the HTC Vive headset but can be played on Oculus Rift with a bit of adjustment.

Arizona Sunshine: This first-person shooter immerses the player in a post-apocalyptic desert town. There is an arsenal of guns and other weapons that players can use to kill blood thirsty zombies. This game is available on PSVR, Oculus Rift and HTC Vive headsets.

Resident Evil 7: Based on the popular survival horror series Resident Evil 7 offers a completely different way for players to see everything in the realm of VR. With creatures lurking around every corner to attack players in the virtual world, this game manages to provide an incredibly intense experience for users. Resident Evil 7 is currently available on PSVR, Oculus Rift and HTC Vive headsets.

Lucky’s Tale: This VR game is available on Oculus Rift and translates the classic 3D platform into virtual reality. It makes use of the player’s ability to manipulate perspectives hiding secrets behind trees and under obstacles. The levels in this game are short to maintain the comfort level of the player in virtual reality.

Keep Talking and Nobody Explodes: It is a multiplayer game where the user wearing the VR headset acts as a bomb disposal agent. Each level has an explosive device with a series of batteries, widgets and nodes to work with. The person wearing the headset has to describe the bomb and work as a team to disarm it. This game offers the player an adrenaline rush that is not seen in many others. It is available on Oculus Rift, HTC Vive and PSVR headsets.

Stay tuned for information on other upcoming and popular VR games.

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Applications of Augmented Reality:

Augmented reality has been around for many years, but it wasn’t until the emergence of smartphones equipped with GPS, camera and AR capability that AR came into its own among the public. Augmented reality technology combines the digital world with the real world in the form of live video imagery that is enhanced with computer-generated graphics. AR can be experienced through headsets and displays on mobile devices. The number of AR apps available for the android and iOS devices has expanded dramatically, and are not limited to just games. Retailers are showing tremendous interest in the possibilities of using AR for their business.

Handheld AR Equipment: There is a list of AR software development kits available for Android smartphones and Apple’s mobile devices. These kits give developers the tools needed to add AR elements to their apps.

AR Headsets: Although devices like Microsoft’s HoloLens or Facebook’s Oculus headset are quite expensive. Other companies have started offering headsets at a third of the price the high end headsets like the HoloLens. Most AR headsets operate while tethered to a PC, but it won’t be too long before untethered headsets will be available in the market.

AR Applications:

Early PC, smartphone and tablet applications for augmented reality focused on games, but AR has much broader uses in the real world. The possible commercial and educational applications are unlimited.

Augmented Reality in 3D viewers:

This allows users to put life-size 3D models in their environment with or without the use of trackers. Trackers are the simple images that 3D models can be linked to in Augmented Reality. Popular 3D viewers include AUGMENT and Sun Seeker.

Augmented Reality in Browsers:

The AR browsers can enhance users’ camera display with contextual information. For example, when you point your smartphone at a building, you can see its history or estimated value. Examples of these type of browsers include Argon4, AR Browser SDK and more.

Augmented Reality Games:

AR Gaming software is probably the most common type of App. These apps create mesmeric gaming experiences that use your actual surroundings. Some of the popular AR games include Pokémon Go, Parallel Kingdom, Temple Treasure Hunt, Real Strike, Zombie Go, etc.

Augmented Reality GPS:

AR applications in smartphones generally include Global Positioning System (GPS) to spot the user’s location and its compass to detect device orientation. Examples: AR GPS Compass Map 3D, AR GPS Drive/Walk Navigation.

Augmented Reality is a technology that has changed the face of smartphone apps and gaming. AR adds digital images and data to amplify views of the real world, giving users more information about their environments.

Want to develop your Augmented Reality app? With 7 years of experience in developing mobile apps, we at BMS Innolabs are ready to take any challenge to make the best use of our expertise for your business.

An introduction to Chatbots.

Chatbots are computer programs that can have the ability to mimic human conversations in their natural format including text or spoken language. This is accomplished by using artificial intelligence techniques that includes Natural Language Processing (NLP), image & video processing, and audio analysis. Their most interesting feature is that they can learn from past interactions and become smarter over the time. Chatbots work in two ways:

  • Rule Based: They provide predefined responses from a data base, based on the keywords in the search.
  • Smart Machine Based: They inherit capabilities from AI and adjust their behavior based on customer interactions.

The arrival of this technology is has given rise to new realms of engaging customers and ways of doing business. With instantaneous and personalized customer response that meets customer expectations, chatbots have revolutionized the customer service industry. Powered by Artificial Intelligence (AI), Chatbot intelligence will increase with better use of conversational interfaces, and in future it will be used not only for customer support and retention, but acquisition as well. The objective of using chatbots is not to replace humans, but to bridge the gap between brands and consumers. Although the implementation of chatbots in the call center industry will have huge implications with potentially disruptive technology. Generally, chatbots can be trained with four major types of data projects.

  • Utterance collection: Here, the bot is trained to identify instances where people come up with different ways to ask the same thing.
  • Relevance: Using this, the bot is trained to give relevant responses to real user questions.
  • Intent: Here, the bot learns to judge the user’s intent while they are engaged with them.
  • Entity recognition: This type of data project is used to help the bot understand nuance and context of the conversation.

Currently, front-end chatbots are used in several domains, but are still in the primitive stage. Compared to humans, these front-end chatbots lack empathy and the ability for problem solving. For businesses, chatbots can be used to manage customer queries round the clock without any delay. There are many other advantages of incorporating this technology in business.

  • Interactions are possible through familiar platforms like Facebook chat through API.
  • Easy to interact using a simpler interface.
  • Capability to outperform humans in terms of speed in handling customer queries.
  • Easy to build, cost efficient and improved efficiency.

Chatbots can currently be seen on websites and social platforms to assist customers in their interactions with the brand. Chatbots not only communicates through voice or text, users can now interact with them via graphical interfaces and widgets as well. This technology gives businesses a new way to interact and deliver their messages to customers on chat platforms.

What is Machine Learning?

Machine learning (ML) is an application of Artificial Intelligence (AI). It provides systems the ability to learn and improve from experience without being explicitly programmed. The learning process begins with observations and data such as examples provided by us, direct experience or instructions, in order to look for patterns in data and make better decisions in the future. The primary objective of ML is to enable computers to learn automatically, without any human intervention.

The processes involved in machine learning are similar to that of data mining and predictive modeling, which require searching through data to look for patterns, based on which program actions are adjusted accordingly. Social Media giant Facebook uses machine learning to personalize each members news feed. The software uses statistical analysis and predictive analytics to recognize patterns in user data and use them to populate the News Feed. Search and recommendation engines use also use this technology to personalize online ad delivery in near real time. There are many other use cases in machine learning that includes building news feeds, fraud detection, spam filtering, network security threat detection and maintenance.

Machine Learning methods:

Here are the categories of Machine Learning algorithms.

Supervised Machine Learning Algorithms: These algorithms can add what has been learned in the past to new data to predict future events. By analyzing a known dataset, the algorithm produces a function that is used to predict output values. It can also compare outputs, find errors and make modifications accordingly.

Unsupervised machine learning algorithms: These algorithms are used for unlabeled training data-sets and learn how a function can be inferred to describe its structure.

Semi-supervised machine learning algorithms: These algorithms use both labeled and unlabeled data for training. Systems using this method are able to significantly improve learning accuracy. This method of learning is chosen is the given data requires skilled resources to train it.

Reinforcement machine learning algorithms: This learning method enables the system to interact with its environment by producing actions and discovering errors and rewards. In order to maximize performance, these algorithms allow machines and software to ascertain the ideal behavior to determine which action is best in a specific context.

Combining machine learning with AI can make it even more effective in processing large amounts of data. Machine learning enables analysis of this data to accurately identify profit making opportunities and potential risks.

The role of Artificial Intelligence:

In the age of digital transformation, Artificial Intelligence (AI) will have a huge impact on businesses and on society as well. Humans have reached a point where biological evolution can’t keep up with the pace of change. The world has become far complex than our brains can handle.
Nowadays, aspects like economics, politics, culture, outcome of wars that change history and much more are all driven by technology. The human brain can’t help but misconstrue about every possible stimulus in our daily lives. This is where AI comes in and brings about a paradigm shift in the way we perceive the world and everything that happens in it. AI will bring about one of the biggest technological revolutions in history.
As technology and our understanding of how our minds work has progressed over time, our concept of what constitutes AI has changed too. AI devices are classified into two fundamental groups. Systems such as those designed to trade stocks, navigate autonomous vehicles and other similar applications fall under the Applied AI category. Systems that have led to the development of concepts like Machine Learning belong to the Generalized AI category.
One of the ways to create Artificial Intelligence is through Machine Learning (ML). It is dynamic and does not require human intervention to make changes, making it less susceptible to human errors. Neural networks, which is designed to classify information the same way the human brain does has been key to teaching computers to think like we do. Based on the data fed to it, these networks will be able to take decisions and make predictions with a degree of certainty.
Natural Language Processing (NLP) is another field of AI that is heavily reliant on Machine Learning. It helps machines understand the vast complexity of human language and respond in a way that is comprehensible by the audience. Industries in all sectors, right from healthcare to banking and manufacturing can use AI to automate a number of tasks.
Much of the progress we have seen in the recent years is thanks to changes in how we perceive AI working, which has been brought about by Machine Learning. Deep Learning (DI) is another field that is a subset of Machine Learning. It refers to the number of layers in a neural network.
Something that has been treated by technologists as an inevitability is the fact that we will eventually develop a human-like AI that will play a major part in shaping the future.