8 Revolutionary Artificial Intelligence Technologies Of The Modern Era

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Starting with something we use in our daily lives on a consistent basis and something quite obvious but nevertheless extremely impactful in modern-day society are Smartphones.

Smartphones are a symbolic representation of the words “Revolutionary Technologies” in every aspect. These inventions have solidified the groundwork and are a major benchmark to what the upcoming technologies of the world would need to compete against.

These phones, which fit in the palm of your hand, are able to do a multitude of tasks, including Global Positioning System (GPS) locations, messaging, phone calls, tracking selective devices, online transactions, activating Bluetooth systems, accessing social media, web browsing, and tons more applications.

But, what actually makes these smartphones even better than what they initially offer?

The integration of Artificial Intelligence into these devices takes them to a whole different level. The performance of these devices amplifies to produce more desirable results and solutions to common tasks and problems that are to be addressed in everyday life.

The AI technologies in smartphones include the Face Recognition based face lock systems, which prevent any unauthorized user from accessing your Smartphone without your permission. Only the registered users face is recognized and granted access. It uses the concepts of computer vision, deep learning, and artificial neural networks to perform the complex face recognition locking system.

If you are interested in building a similar face recognition model from scratch using deep learning and computer vision, I would recommend all of you to check out the following article.

The other Artificial Intelligence activities in Smartphones also include some natural language processing and machine learning innovations like the features of autocorrect and autocomplete. Both these technologies significantly help in introducing uniqueness, efficiency, and comfort to the users using these devices.

The features of autocorrect and autocomplete are based on deep learning topics and principles of concepts such as Long-Short Term Memory (LSMTs), transformers, sequence to sequence models with attention, and most importantly, the core aspects of natural language processing.

Finally, to mention another fabulous feature of Smartphones is the integration of virtual AI assailants like Google AI and Siri. We will discuss this topic further in one of the other sections of this article.

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Self-driving AI cars or autonomous vehicles are a future trend developing at a fast pace. Many companies and tech giants are investing their valuable resources into the development of modernized self-driving cars.

As the name suggests, these cars are completely autonomous and work to coordinate their movements without the interference of a human user or any additional assistance. You can put these cars on autopilot and set the respective location while you lay back and take a nap or chill.

These autonomous vehicles will drive through the traffic, passing through checkpoints, and covering the full distance to accomplish the targeted and desired goal. To understand some of the principle methodologies of how these autonomous vehicles work, they make use of several additional components.

These components include Light Detection and Ranging (LIDAR) for 360 degrees regulation, multiple cameras, safety wheels, high-quality advanced systems, and so much more. However, we will focus strictly on the Artificial Intelligence aspect of these vehicles.

AI plays a major role in the development of these advanced cars. One of the main concepts of working of an autonomous vehicle during the training stage is the use of convoluted neural networks. Deep convolutional neural networks can be used with a large set of trainable parameters can be used with a large training dataset to train these self-driving AI cars.

For additional training, even concepts of image segmentation and masking, alongside data manipulation techniques, like specific image data augmentation methods, can be used for teaching these autonomous AI cars. After multiple loops and epochs of training, these models will start to perform at decently good ratios and improve their levels proportionately. They can detect obstacles and drive at a pretty smooth rate.

A great example for the development of modern autonomous vehicles can be credited to Tesla Inc. This company, led by CEO Elon Musk, aims to provide electric cars with the installation of Artificial Intelligence technologies. These cars are highly beneficial for the future to prevent multiple cases of accidents which humans are error-prone to commit. They also help to reduce pollution.

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Gaming is a phenomenon where hardcore gamers, casual players, and hobbyists fantasize about in-game details, explore the virtual world, and enjoy playing video games. I love gaming from when I was a child. I am a nerd when it comes to gaming because I am an immense fan of it. Personally, it excites me to a high degree to see how immensely the Gaming World is changing.

With various gaming consoles such as the Playstation, Nintendo, and Xbox, gaming is on a meteoric rise and doesn’t show any signs of slowing down. NVIDIA recently released the RTX 3080 graphics card, which has an incredible performance increase and adds an erotic beauty to games like never before.

Oh, Wait! Talking about Graphics Processing Units (GPUs) ignites my interest in two things I love the most, Gaming and Artificial Intelligence. The constant and continuous evolution of gaming with advancements in Artificial Intelligence is significant.

Some of the first games developed in the world of gaming used certain hardcoded sequences for performing specific sets of sequences. Also, hit scan technologies were used to determine the effect of a shot landing as a guaranteed hit in some first-person shooter (FPS) games.

With increasing developments in AI, more realistic changes are continuously made for making the NPC (Non-playable characters) characters and other game characters react more realistically to various situations. Note that the term “realistic” is quite a relative term in this context.

Going down the memory lane reminds me of the profoundness of playing video games. The technological evolution of a game like Doom in 1993 to Doom Eternal in 2020 is meteoric. I went from playing this:


To now playing this


The technology has evolved from pixilated characters to more graphical oriented approaches. In the field of AI, the concept of reinforcement role plays a crucial role in learning a certain aspect of gaming. You can train your own AI with repeated hit and trial method to play games and allow the network to develop critical thinking along the way.

An example of AI and reinforcement learning through continuous failures through various generations is the flappy bird game. The AI neural network built for this feature fails for a number of generations. However, after training for millions of epochs, it gains a better understanding and performs at a level exceeding the precedence of humans.

Other examples of the gaming industry evolution can be contributed to Neural Networks in Chess engines, which are performing at a strong level and helping Grandmasters prepare new innovative lines.

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One of the most awaited and groundbreaking creations of the year 2020 was the GPT-3 model created by the OpenAI team. The GPT-3 model trained on 175 billion machine learning parameters is a revolutionary AI technology of the modern generation. Its features and computing aspects leave it currently unmatched in the field of natural language processing.

Generative Pre-trained Transformer 3 is an autoregressive language model that uses deep learning to produce human-like text. It is the third-generation language prediction model in the GPT-n series created by OpenAI, a San Francisco-based artificial intelligence research laboratory. (Check reference [4] for more information from Wiki)

The GPT-3 developed by OpenAI can be considered as a language generating algorithm that can generate text like no other AI algorithm. It can be used for the prediction of various words and sentences, answering questions like a chatbot, or generating unique text from scratch. The GPT-3 model can generate entire articles from scratch, including news, magazines, and so much more. The surprise factor though, is that these articles produced are nearly impossible to differentiate from human work to machine work.

I would highly recommend checking out one of my previous articles on the topic of prediction of next words. It is not as advanced as the fabulous GPT-3 architecture, but it should give you a brief idea of how concepts of natural language process, deep learning, and neural networks can be used to create spectacular things.

Some have criticized GPT-3 for being so good that it bypasses the human-level intellect and stands shoulder to shoulder competing in humans. This power of computing and producing new results every single time can lead to fraudulent activities. However, this discussion is not the scope of this article as we will focus only on the positives. The creation of the GPT-3 model by the OpenAI team will remain a revolutionary step in technological advancements for the years to come.

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The concept of humanoid robots taking over the entire universe has been a keen topic of interest in sci-fi (science fiction movies). However, this view is far from reality as we are still a long way from reaching the super ceding level of General AI.

Robotics and robots have several definitions. But, we will focus on the general description of robots. According to the International Standards Organisation (ISO), an industrial robot is defined to be

An automatically controlled, re-programmable, multipurpose manipulator, programmable in three or more axes, which can be either fixed in place or mobile for use in industrial automation applications.

The above definition is just one out of many possible ways to think about robots. Any electromechanical object which can perform locomotion and automate a certain task and help benefit our society is another way I like to term the word “robot.” Robots and Artificial Intelligence have a long historical correlation thanks to movies and books.

GIF From Giphy

Even though some of these aspects may be coined as unrealistic expectations for the day today, there are objectively many use cases of Artificial Intelligence and Robotics today. Robotic arms are programmed with AI for the automation of tasks.

To mention some of the tasks that Robots and AI combined together (smart robots) can perform are precise assembly applications for assembling parts, cross-checking and packaging of products in industries, service robots for gauging customer satisfaction, and open-source robots for performing a wide variety of applications.

In the not too distant too future, we will witness the growth of more realistic humanoid robots integrated with Artificial Intelligence to create a more productive and efficient world. I am hyped in the anticipation of what the future holds for artificial intelligence and robotics.

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Virtual Assistants, in simple terms, are devices that help in providing guidance and assistance to humans for performing various tasks like playing music, making phone calls, messaging, and so much more. Virtual Assistants like Google AI, Siri, Alexa, Cortana, and many other similar virtual assistants from various companies are rising in popularity due to their capability and overall convenience they provide to humans.

These AI virtual assistants have the potential to automate any realistic task. The scope of these virtual assistants is on the increase, and there is currently a high demand for these products. You can additionally use your Artificial Intelligence skills to develop a complete home automation system programmed in your house using these virtual assistants, which can monitor, control, and regulate various operations.

I would highly recommend checking out one of my previous articles on creating unique and innovative chatbots from scratch using natural language processing, neural networks, and deep learning. I have used the concept of one-dimensional convolutional layers to solve this task.

This model you develop should help in gaining a better understanding of how chatbots work and also enable you to gain a better view of Virtual Assistants as well as the working of the GPT-3 model. You can view this from the link provided below.

The role of virtual assistants in the modern world keeps increasing with the rapid development of technologies. In the near future, the quantity and demand of these virtual assistants will continuously increase. Hence, it is a great time to learn and experience the virtual assistant technologies with Artificial Intelligence.

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Augmented Reality is an experience to viewers that helps to create an interactive experience of the world and surroundings all around us to produce realistic interactiveness. These visuals are often times generated through computers or software but help in enabling the natural world to look more enhanced with these generated images and models.

There are many types of realities that are becoming increasingly popular with each passing day. To discuss a few of these are the technologies of augmented reality, virtual reality, and mixed reality. We have already seen what augmented reality is. An example of the augmented reality is a popular game like Pokemon Go.

While augmented reality only creates an enhancing effect with an interactive environment, virtual reality serves to immerse and dwell the user into a complete experience. You are taken into a completely immersive experience often times with the help of VR devices. Mixed Reality is a combination of both augmented and virtual reality. (Refer reference [6] for more information on this topic)

Virtual Technology and Artificial are a heavenly combination. These two features combined together can create dynamic features and expectations from the virtual world, which was once considered impossible. To state an example of the Virtual realities with artificial intelligence, I would like to go back to the topic of gaming.

In 2020 (the previous year to the date this article was published), the popular game company Valve produced a game called Half-Life Alyx, which is groundbreaking in every way possible. The GIF below is a simple representation of virtual reality combined with the power of Artificial Intelligence.


With the help of augmented reality and artificial intelligence, you can be taken to an entire virtual universe, which is so realistic that you can have a fantastic experience. The features of AI, such as the enemy bots or the non-playable characters (NPCs), only add more substance and content to the virtual generated world.

Augmented Reality and Artificial Intelligence when integrated together have endless possibilities. It is exciting to speculate and think about the multiple, unique permutations and combinations we can experiment with these technologies to create mind-blowing products that will prove to be feature of beauty in the upcoming years.

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Internet of Things, as the name suggests, is the art of controlling all the interactive elements in the surrounding with the help of the Internet. The popularity of AI has blown out of proportion in recent times due to the large quantities of quality products that can be produced with them.

With the help of embedded devices like Arduino, Raspberry Pi, Nvidia Jetson Nano, and many others, and the combination of sensors, motors, and other physical components that can be controlled with a Bluetooth module or Wi-Fi (basically the internet), you can create magnificent products.

We have already determined that IoT is a brilliant and groundbreaking technology that is capable of achieving high success rates with its products. However, with the integration of Artificial Intelligence into IoT (also referred to as AIoT sometimes), these technologies will create a new revolution in the development of the world.

The AI technologies with IoT allows you to create multiple products and technologies. Some of these even include the technologies previously mentioned, like Self-driving cars (or autonomous vehicles), task-specific robots, and so much more.

The Internet of Things combined with AI can create many wonderful inventions that will lead to the entire landscape of the future changing for the greater good. Tensorflow even has versions such as Tensorflow-lite versions to support embedded systems.

Companies like Google are investing heavily to make smaller chips and install the technology of Artificial Intelligence in these components, which are barely the size of a few nanometers (The chips to clarify this statement). AI and IoT will mark a new revolution to transpire the future of humanity.

I would highly recommend checking out the following article from the link provided below to gain a deeper understanding of the topic of the Internet of Things and AI in further detail.