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A detailed look through the fascinating world of AI

It was back in the 1950s when Marvin Minsky and John McCarthy, who are considered the fathers of the field, described artificial intelligence (AI) as any task performed by a machine that previously required human intelligence to complete. This can be described as a simple explanation of a complicated term, am sure even Minsky and McCarthy would not have been able to predict what AI would be perceived as in the modern world. Sometimes an evil force out to extinct humanity, other times a helping tool to evolve humans, AI has been depicted and perceived in various ways around the world in the 21st century. Now, the discussion is not about machines completing tasks on behalf of humans, but about machines replacing humans altogether! I won’t be jumping onto the pessimist viewpoint of AI (we’ve reserved that for later) but, in our AI edition, we wanted to get our readers acquainted with the technology and its integration into the real world.

Minsky and McCarthy define AI in a broad and general sense. Thus it sparks arguments about whether just a machine doing mundane tasks is truly AI or not. However, the modern definitions of technology are more specific. Francois Chollet, an AI researcher at Google and the creator of Keras, a machine learning library software, has stated that intelligence is directly tied to a machine or software’s ability to adapt and improvise in a new environment. The AI machine is capable of generalizing its knowledge to apply it to unfamiliar situations, just like humans (or better?)

Modern AI-powered systems such as your virtual assistants operate under this rule. Though your virtual assistant is capable of a limited set of tasks, they can only use their training to give an apt output. The Siri on your iPhone surely has some witty answers for your entertainment whenever you ask her a question but there are other times when she is just clueless. This is characterized as ‘Narrow AI. We’ll discuss the types of AI further in detail.

Typically, AI systems demonstrate or replicate some human behavioral patterns. Some of these patterns include learning, planning, problem-solving, reasoning, motion, and manipulation. To a lesser extent, AI is capable of creativity and social intelligence. If we lean towards science fiction, AI is also capable of feeling emotions and diving deep into philosophy trying to find the purpose of their existence. Let’s not get too ahead of ourselves as even humans haven’t been able to find the answer to that question yet!

Firstly, let’s learn about the types of AI. Looking at the technology from a stratospheric viewpoint, AI can be broadly divided into three parts. These parts include both the actual and hypothetical implementation of the technology.

Artificial Narrow Intelligence (ANI)
Artificial General Intelligence (AGI)
Artificial Superintelligence (ASI)

Artificial Narrow Intelligence (ANI)

Artificial Narrow Intelligence (ANI) which is also known as weak AI or narrow AI is perhaps the only type of AI0 that humanity has successfully mastered. Narrow AI is tied to a goal, designed to only perform a singular task. This could include the fingerprint reader or face unlock on your mobile device, voice assistants, driving a car, or searching things on the internet. The AI is simply programmed to follow specific tasks and it does the same without a hiccup. Well, most of the time.

These machines are undoubtedly super intelligent, but only in the fields they have been programmed in. It operates under a narrow set of tasks with limitations and constraints, thus it is typically referred to as weak or narrow AI. This type of Ai is not designed to replicate human patterns, behaviors, and thinking but is simply designed to simulate human behavior based on a limited set of parameters and context. In simple terms, your Siri assistant is incapable of having human-like conversations with you as it is not designed to do so and operates under limitations. Wouldn’t it be fun if Siri could one day just start talking to you like JARVIS from the Iron Man films?

While Siri is one example of Narrow AI, other examples include Tesla’s self-driving cars that use visual recognition and recommendation engines to suggest products based on your purchase history. These systems can simply only learn and be taught to process specific tasks. While Narrow AI is a straightforward concept to understand, it is furthermore classified into two possibilities. These include Reactive AI and Limited memory AI.

Reactive AI – It can be defined as the ‘Basic’ version of AI. It comes with no memory and data storing capabilities. It simply emulates human behaviour and responds to different inputs without relying on any past information.

Limited Memory AI – This is a more advanced version of Narrow AI. It has great memory and storage capabilities which allows machines to interpret the output based on statistical data. Most of the AI being used now in the mainstream is limited memory AI. It enables machines to dive into a large amount of data in the realms of deep learning to bring out the most accurate results.

Examples of Narrow AI

Virtual assistants like Cortana by Microsoft, Siri by Apple, and Alexa by Amazon
Rankbrain: The algorithm used by Google to sort the search result
Self-Driving Cars
Facial recognition and interpretation software
Social media marketing tools to check platform violations and content recommendation
Also used as a medication and prediction tool to diagnose diseases like cancer and other health-related issues with accuracy

Artificial General Intelligence (AGI)

So, we’ve coursed our way through the real-life implementation of the technology with Narrow AI. Now, it’s time to jump into hypothesis and what something could be regarded as fiction by many. Artificial General Intelligence (AGI) is referred to as ‘Strong’ AI as it is able to carry out cognitive processes. AGI in theory is capable of demonstrating intelligence equal to humans. AGI machines are able to perform any task that a human can do, but unlike humans, they are unlimited in the ability to solve multiple problems at the same time.

Let’s reflect upon human intelligence to understand the territory AGI charters. When compared to human intelligence, AGI demonstrates intelligence similar to it. Think about it, human beings are unique and complex beings that possess a wide array of abilities. Humans possess the senses of hearing, taste, sound, and touch. We can think about making a move and then extend our physical selves to complete the said movement with ease.

The human brain is undoubtedly an impressive wonder of our existence. Not only is it capable of critical thinking, but it also is a complex algorithm that hasn’t been studied yet completely. This makes it difficult to replicate the human brain in the form of artificial intelligence. The complex algorithm that is our brain is trained right from birth till our death. Learning from trial and error and continuously learning and unlearning to store information and develop as a human being.

The complexity of the human brain is established. Now, imagine decoding this complex nature of human existence and programming it into artificial intelligence. Sounds… impossible? It just might be!

These are some of the reasons which make it nearly impossible to make AGI equal to human nature. The limitless powers of the human brain cannot be simply translated into a machine. Hence, the creation of AGI is still a far-off dream. While AGI is years away from coming to fruition, pop culture has depicted it for years. Some examples of AGI in films are

Iron Man’s Personal Virtual Assistant JARVIS
HAL from 2001: A Space Odyssey
Programs from The Matrix
The Terminator
Voice Assistant from the film Her

Fun Fact: What humanity knows about the human brain is that it is a neural network, capable of processing 86 billion neurons of sensory information. However, one of the world’s fastest computers, K, built by Fujitsu took 40 minutes to simulate a single second of neural activity. So, it won’t be an overstatement to say that we’re far away from AGI becoming a reality!

Artificial Superintelligence (ASI)

Beyond the simple narrow AI and maybe an attainable general AI lies the realms of futuristic yet dystopian artificial superintelligence (ASI) Machines with superintelligence are self-aware, that’s more than some humans can say for themselves. These self-aware machines can think of abstractions and interpretations of the world that humans cannot. Human beings are capable of operating under the set limit of a few billion neutrons. ASI, on the other hand, does not have any such limitations as its intelligence surpasses the unfathomable!

ASI is not just capable of understanding human emotions but can have its own desires and beliefs. It finds its application in all domains of human interest ranging from maths, science, and arts, basically, whatever you can think, ASI can excel in!

ASI has long been a muse around the world as a dystopian science fiction entity. Films depicting AI overpowering humanity portray ASI, now you know!

Challenges with AI – Long Way to Go!

Deep learning, machine learning, and artificial intelligence are some fancy terms that people throw around casually while talking about the future of technology. A majority of humanity is convinced that AI and machine learning is the future and that it will be taking over the world sooner than expected. While AI as a technology has revolutionalized several sectors like the manufacturing industry, healthcare, and space exploration, it is not where you think it is. Yes, AI has been growing at a steady rate gaining popularity and growing smarter with each passing day. But that does not mean that it is flawless!

It is surely important to note that AI right now is facing a number of challenges but that doesn’t stop it from upscaling year by year. Reportedly, AI can boost business productivity by up to 40%, whereas, the number of AI-related startups around the world has grown 14 times since 2000. Since the application of this technology spreads wide and its exploration is still limited, there are a number of obstacles currently present in the field which is to be conquered. Let’s have a look at all the challenges currently with AI –

Human-level

This is perhaps one of the biggest challenges currently with AI which has kept researchers and developers scratching their heads. While AI currently is smart and some companies boast over 90% accuracy in their daily AI tasks, humans are simply smarter. Humans are sharper and more accurate than AI as of now, which is contrary to the popular belief that the technology is smarter than us.

Let’s take a simple example here, whenever you’re asked to ‘Confirm if you’re not a robot’ before entering a website, you can simply point out all the pictures consisting of a bus or a traffic signal, or dogs. AI, on the other hand, just cannot do so effectively. Sounds strange right? Why cannot a smart algorithm figure out which photos feature dogs? For a deep learning algorithm to perform a similar task will require a large amount of finetuning. It would require a large dataset, hyperparameter optimization, strong computing power, and uninterrupted training and testing of data. Sounds exhausting!

Data

The most crucial aspect of deep/machine learning models is their basis on the availability of data and the resources to train them. Humans have a lot of data. This data is generated from billions of users from around the world. However, there are chances of this data being used for bad purposes. Plus, data security is another important aspect that looms upon us as a possible threat. It was only back in 2021 when 533 million Facebook users had their data leaked from over 100 countries. What would happen if an AI algorithm is fed data of that magnitude? It’s scary to even think about! Plus, the data leaks can also make their way to the dark web which can later be used for nefarious activities. Some companies are currently working towards tackling this issue by training the data on smart devices which do not send data back to the servers, but only the trained model.

Knowledge Barrier

There are a number of implementations of AI in the market right now. AI can replace the traditional systems currently in use effectively. But the problem here lies in the actual knowledge of AI around the world. Sure, AI can be used by tech enthusiasts, students, and researchers on a global scale. But right now, there are only a number of people who are aware of the potential of AI. The technology still only reigns in the territory of science fiction amongst people due to its representation in pop culture. The adaptation of AI into the mainstream with the use of it to upscale production, manage resources and understand consumer behavior is still a far-off dream.

Computing power

Machine Learning and Deep Learning are the baby steps required to develop artificial intelligence. But, the amount of computing prowess these power-hungry algorithms require is one of the top reasons why AI is not where it should be right now. These algorithms demand a high number of cores and GPUs to work efficiently. Right now, humanity has already figured out a number of domains where we can implement AI deep learning frameworks. Be it tracking the cosmos or asteroids, and human health care, AI can be implemented to an extent that can be life-changing but the lack of computing power keeps us at bay. These algorithms require supercomputing powers and they do not come cheap. Not everyone can afford a supercomputer to build an AI including some of our smartest brains.

Global Landscape – Countries Leading the AI Race

The adoption of AI has been growing across the globe at a rapid scale. Right now, many countries have a stake in the AI revolution. The current exciting developments in the AI field are sweeping the globe off its feet and influencing all businesses around the world. AI enables face recognition, corporate development, self-driving vehicles, and better online outcomes that influence the decision of many if not every business out there.

Reportedly, the global AI market will be valued at a staggering $360bn by 2028, growing at an annual rate of 33.6%. The use of AI can be seen across a number of industries be it the transportation, manufacturing, finance, and even education sectors. Due to this extensive influence of AI on multiple sectors, many countries have now jumped in to invest heavily in AI research and development. The reason behind this heavy investment is to sustain long-term growth and the protection of national security. There is simply no denying that AI will develop to the point in the future where it will directly influence our lives (Hopefully not like an episode from Black Mirror!) AI will play a huge role in the corporate environment in the near future thus it is not a surprise that many countries are now deeply invested in the technology. It is time to have a look at all the countries currently making a big splash in the AI race –

China

I am sure you’re not surprised to see China on this list to any degree! China has long been an aspirational world leader in artificial intelligence. According to China’s own State Council, it will become the global leader in AI by 2030 having a reported market capitalization of $150 billion. Another thing to note here is that the country has published more deep-learning research papers than any other country from around the world. But, China’s high population is also a factor responsible for its growth in the AI sector. The most significant factor for AI’s growth in China is its internet-using population which amounts up to a massive 75 million which generates a gigantic amount of digital data to handle and for AI algorithms to learn from (Data Privacy is a myth, my friends!) Another factor here for China’s lead in the AI sector is its government’s transparent ambitions and objectives with the technology. Baidu, Tencent, and Alibaba are only some of the Chinese AI companies that are leading the AI sector.

USA

When it comes to conquering AI technology, the United States has been one of the leaders. The country has a well-established tech culture with some of the prominent tech giants based out of it. Whereas, the country has also profited from $10 billion in complete venture financing which is directed toward artificial intelligence. The USA has been a well-known player when it comes to offering technological advancements in manufacturing robots to the world. It also plays a crucial role in the manufacturing and industrial industries. Be it Amazon, Google, Microsoft, Facebook, and IBM, these are all big parts of the development of the AI industry and are based out of the USA. The United States currently has all the components required to dominate the field of AI and robotics thus it makes number two on our list.

Canada

With some of the world’s most talented brains and creators of AI technology, Canada has paved its way to becoming an AI leader. The Canadian government is heavily invested in AI and plates a significant role in its advancement in the country. It was back in march 2017 when the Canadian government announced a total investment of $125 million in the field of AI. Canada mainly focuses on two AI components like Machine Learning which is based out of Montreal and Toronto and Reinforcement learning which is based out of Alberta. Waterloo is Canada’s big AI hub having over 90 firms dedicated to AI development.

Germany

Germany ranks number sixth globally when it comes to the number of AI research articles published. The country is known for its precision and technological advancements. Be it self-driving cars, quantum computing, or robots, Germany has placed itself as a leader in AI development. Germany, similar to China has the ambition to become the global leader in AI. For this reason, two of its top technology universities and its top exporting state are currently collaborating with corporations like Porsche, Bosch, and Daimler to develop rich artificial intelligence.

India

Yes, India is also a pioneer when it comes to artificial intelligence. Our rapidly growing nation is currently going through a massive digital transformation thanks to the cost-effective internet provided here. This digital revolution has a direct impact on the growth of AI in the country. The government of India may not have granted any funding or allocation to the AI sector but the country is still covering a massive ground in AI thanks to various initiatives taken by individual companies.

Race to the Top! – Companies Leading AI Research

Artificial Intelligence has surely become a growing force in the business industry today. Be it cloud computing or edge computing, AI is being used as a mix and match of technologies to exceed in several aspects of a business. AI-enabled solutions have become popular thanks to businesses now transforming digitally. The number of businesses now using AI services reportedly grew by 270% from 2015 to 2019, it is still rising as 2022 comes to a close and will only continue to grow more in the coming years. As of 2022, the AI services market is reportedly forecast to grow to US $62.5bn which is a considerable growth from US $19.4bn back in 2020.

While machine learning leads the pack in the AI revolution, businesses are expanding their technological reach with the help of other technologies like predictive analysis, business intelligence, data warehouse tools, and deep learning. These technologies enable big business giants to alleviate several industrial obstructions with ease. Surely, entire industries are being reshaped with AI right now. Robotic Process Automation (RPA) companies have now swiftly changed their platforms to AI, whereas AI in healthcare has also proven to be a boon in patient healthcare.

Several companies have showcased a great interest in AI during the pandemic to better the customer experience in a variety of areas. In our AI special we wanted to have a look at all the companies currently leading the race of AI and Machine Learning through the integration of their technologies into apps and systems. Check them out right now –

Amazon Web Services (AWS)

AWS clearly takes the cake when it comes to being the leader in cloud computing. The company offers both consumer and business-related AI products and services. A number of its AI services build into end-consumer products. Let’s take Amazon Echo as an example, this little speaker brings AI right into your home through your personal voice assistant, Alexa. While Alexa is known as Amazon’s AI, its primary AI service is called ‘Lex’. It is an Alexa variant that is exclusive to businesses. There is also Polly which turns text into speech and Rekognition which is an image recognition service. Besides AWS, Amazon has a number of products based on AI.

There’s the SageMaker Data Wrangler, a new service that is meant to accelerate the data preparation for machine learning and AI applications. Amazon Codeguru is another service by Amazon which allows coders to enhance their code quality with the help of Ai-powered code suggestions. Finally, Amazon also has Kendra which is an AI and machine learning-powered search tool meant for corporate purposes.

Google

I am sure you’re not surprised to Google on this list as it is among the top AI companies right now. While there are several ways Google integrates AI in its business, one notable AI innovation by the company is the Multitask Unified Model famously known as MUM. This technology is aimed to enhance the Google search experience amongst users. MUM is used to better link the information that a web searcher is looking for with precise accuracy. Google has been on a massive AI acquisition binge as it is deeply invested in the integration of AI into our daily lives. Google Cloud itself sells a number of AI and machine learning services to companies around the world. The industry-leading TensorFlow software project and its very own Tensor AI chip project are known around the world.

Microsoft

Microsoft is a juggernaut when it comes to the betterment of AI technology. The company not only provides technology but also funds and experiences to organizations working on AI to tackle global issues. Microsoft AI has the potential to enable anyone be it an individual or an organization to study, develop, and innovate in the field. Back in 2020, Microsoft unveiled Project Bonsai, a platform for designing industrial control systems. The company had also launched Project Moab which was an experimental platform designed to introduce engineers and developers to Bonsai. Microsoft also build the Specktacom which was geared toward cricketers. Speckatacom was a technology dedicated to collecting data on speed, quality, twists, and the swing of a cricket bat using a tiny sensor attached to the bat. It used wireless technology and cloud analytics to collect the data.

Alibaba Cloud

Alibaba Cloud is the leading cloud platform in Asia. It offers its clients a top-notch machine-learning platform for AI. The company has managed to make AI easy for users with the help of a visually pleasing interface. Companies using Alibaba Cloud’s platform can simply drag and drop data components into a canvas in order to assemble their AI functionality. On the platform, users can also find the scores of algorithm components that can handle a number of different tasks. This enables businesses to use pre-built solutions for their tasks without the hassle of building one which can be time consuming. One can surely expect Alibaba to show significant improvement and growth in the AI sector in the coming years.

Qualcomm launches Snapdragon AR2 Gen 1 and S5/S3 Gen 2 sound platforms

Qualcomm came all guns blazing during its Snapdragon Summit 2022 which was held in Hawaii. While the first day of the summit was dedicated to the flagship Snapdragon 8 Gen 2 processor, the second day showcases a number of new technological advancements by Qualcomm in the fields of AR, sound, and AI. Let’s have a detailed look at everything announced on the Day 2 of the Snapdragon Summit 2022 –

Snapdragon AR2 Gen 1

Qualcomm has revealed the Snapdragon AR2 Gen 1 which will be the company’s dedicated chip for augmented reality. The chip packs a number of features as a dedicated solution for AR headsets. The new AR platform has been built up from the ground in order to unlock a new generation of highly capable AR glasses.

Qualcomm has unveiled that the chip is ‘purpose build for AR’. The company has built a multi-chip distributed processing architecture coupled with customized IP blocks. The main processor has been shrunk down by 40% but there is no compromise on processing as it delivers 2.5x better AI performance while also consuming 50% less power. Another key feature of the AR2 Gen 1 is that it is based on a multi-chip architecture. The multi-chip architecture includes an AR processor, AR co-processor, and connectivity platform. However, Snapdragon has also revealed that the AR2 won’t be a standalone solution as it will require a Snapdragon-compatible host device like an SD phone or a laptop in order to carry out complex AR tasks. With the advancement of immersive technology and the growing curiosity amongst users to explore the world of VR and AR, Snapdragon is certainly moving in the right direction. One can expect that with the introduction of the AR2 Gen 1, users will finally be able to see slimmer AR glasses that are straight out of Sci-Fi films!

Qualcomm S5 and S3 Gen 2 sound platform

While the Snapdragon 8 Gen 2 improves on a number of performance features for Qualcomm’s mobile platform, the cherry on top is the company’s new Snapdragon S3 and S5 Gen 2 Sound platforms. The new platforms are designed to work along with the latest 8 gen 2 chipset and bring a number of audio features including spatial audio support. The S5 and S3 Gen 2 audio chips come with Snapdragon Sound Technology for an improved audio experience for users. The chip sports features like low latency, improved connectivity, lossless audio via Bluetooth, and much more.

Qualcomm revealed that the new sound platform comes with the support of spatial audio with dynamic head tracking and lossless music streaming. Have you ever experienced your music lagging on Bluetooth earbuds while running? Qualcomm’s new audio solution will surely cut that issue down marginally if not entirely! The sound platforms also feature Qualcomm Adaptive Active Noise Cancellation. This feature adapts to the fit of the earbuds and your surroundings in order to avoid ambient noises. Features like Adaptive Transparency mode and automatic speech detection are also present here.

Sci-Fi Bonanza! – Best Artificial Intelligence Films

Beyond the noise of blockbusters and celluloid spectacles, movies are capable of changing people and expanding a viewer’s perception of reality by injecting notions into their heads. Artificial intelligence, machine learning, and data science are some of the popular terms in today’s world and it is only natural that mainstream films around the globe have depicted them on a massive scale. Be it the nuanced take of Joaquin Phoenix’s Her or the action commercial take of Shankar’s Robot, there is more than just one way artificial intelligence has been showcased on the silver screen.

I am sure that a big chunk of humanity has been introduced to the concept of artificial intelligence via sci-fi films. Thus, it was made imperative for me to discuss all the sci-fi films depicting AI in our AI special edition. I’ve made it clear that movies are far more than just a medium of entertainment and amusement, they play a vital role in shaping our consciousness and worldview. In simple words, movies educate us and spread vivid ideas more efficiently than a book.

The prominent reason why films are effective is due to them being a visual medium. The engaging medium binds people to their seats and immerses them in an experience like no other, of course, if done well. The content displayed on the screen is far more interesting than words printed on a book at least in my opinion. This explains why people now jump on YouTube and other visual stimulants like social media during their free time rather than reading a book. Films also allow people to attach concrete graphics to an idea like the Infinity Stones from the Marvel Cinematic Universe, Lightsabers from Star Wars, and so on. Being a film buff, there’s no other way for me to explore the complexities of AI and machine learning but movies.

AI in films

Mainstream popular films have a love-hate relationship with AI. Sci-Fi films tend to exaggerate the evil of AI by presenting them as an extinction-inducing entity. Marvel fans surely know about Ultron from the second Avengers movie. Iron Man builds an AI to protect the world but it instead becomes hell-bent on wiping out humanity off the face of the Earth. On the other hand, AI is depicted as a helping hand to aching souls with its portrayal in the film Her, where Theodore Twombly ends up developing a relationship with an artificially intelligent virtual assistant similar to Apple’s Siri. This leaves us questioning the actual nature of AI when it comes close to its portrayal in films. In the future, will AI control and dethrone us to become the apex predator? It’s too soon to make that judgment now. But what I can do for the time being is to list down the best films with the portrayal of AI for your amusement and understanding of the concept in a rather fictitious take. Please note that the films mentioned below are discussed in detail including spoilers for the same. Read on:

2001: A Space Odyssey (1968)

Putting the best first! Everyone reading this article should mark this one as essential viewing. If you’re a film buff, am sure you have experienced or at least heard about this Stanley Kubrick directorial. Portraying the evolution of humankind and its journey beyond earth, 2001: A Space Odyssey efficiently depicts the complexities of AI with the H.A.L 9000 (short for Heuristically Programmed Algorithmic Computer) which is an AI character on the film’s spaceship. The supercomputer in this film is basically in charge of most operations on a spacecraft heading to Jupiter. This leads to jaw-dropping events when the computer goes corrupt and decides to destroy the world as we know it. HAL kills off the crew members in the spaceship one by one thus reminding the audience that letting AI take control of operations could go wrong in a horrific manner. The film surely is a starting point for mainstream cinema to depict AI in a negative light as it set a course for mainstream films in recent times. The cult classic film dives deep into the reliance of humanity on technology and what happens when the said technology decides to go rogue. 2001: A Space Odyssey for me is a subtle commentary on humanity’s foolishness or let’s just call it innocence to depend upon technology without understanding its potential harm.

Metropolis (1927)

The silent German film Metropolis is surely one of the first portrayals of AI in cinema. The 1927 film is not for everyone as the film is nearing a century since it was released but can make for compelling viewing for film enthusiasts. Watching Metropolis can allow people to understand what people back then thought of Artificial Intelligence and sentient robots. This film too paints the technology in a negative light as a robot decides to take over a city. The dystopian depiction of AI in this film has inspired everything from Blade Runner to modern iterations of superhero films. Besides AI and technology, the film also portrays a class divide between the working class and city planners. The film’s ‘False Maria’ robot was the first robot to be depicted on film and it also inspired the look of the beloved C-3PO from Star Wars.

I, Robot (2004)

Before Will Smith slapped his way to his downfall, he was one of the prominent ‘Movie Stars’ in Hollywood. The man worked in all types of films ranging from sci-fi and romance where he charmed the audience with his acting chops and personality. One of the films from the peak Will Smith era was I, Robot. The film sets itself in 2035 where humanoid robots powered by AI are now a part of everyday life. Detective Spooner played by Will Smith hates robots cause he was in a car accident where the robot decided to let a 12-year-old girl die only cause she had lower chances of survival compared to him. The film revolves around a humanoid robot Sonny who has gone rogue after pushing his owner to death from the 50th-floor window. The AI humanoid robot goes against the three rules designed by humans to protect them which include – that robots shall not harm any human, shall obey any instruction given to them by a human, and that robots must avoid any and all actions or situations that could cause harm to themselves. The film starts off as a murder mystery but soon becomes a conspiracy flick revolving around enslaving the human race.

The Matrix series

Long before Keanu Reeves featured in the Cyberpunk 2077 game, he was a part of the cyberpunk classic action flick, The Matrix. The first Matrix film is arguably one of the best sci-fi films ever made. The Matrix tells the story of a man named Thomas A. Anderson who spends his mundane life in New York working as a computer programmer. However, he spends his nights as a computer hacker known as his pseudonym Neo who tends to run into trouble due to his illegal activities. Neo grows suspicious of the superficial reality he is living in which leads him to meet Morpheus who makes him realize the truth about this world. And what is this truth about this world you may ask? Well, that nothing is real! I am sure you are aware of all the ‘We are in a simulation’ memes and conspiracy theories. The Matrix film series is one of the biggest reasons why this idea is so mainstream. There’s also The Matrix Revolutions and The Matrix Reloaded which followed the original film, completing the trilogy. However, the fourth film is what made it a perfect film series for me. The Matrix Resurrections which hit theatres in 2021 featured a plot that is eerily meta. The film actually takes a hit at the studios pushing for a fourth installment in the franchise by mentioning that Warner Bros (The studios actually behind the film trilogy) will move forward with the project with or without the original talent involved in it!

Avengers: Age of Ultron (2015)

I did not feel like missing out on Avengers: Age of Ultron while talking about films that feature AI. The Marvel Cinematic Universe and Iron Man’s personal AI assistant JARVIS actually inspired Mark Zuckerberg to build his own AI assistant, so it’s only natural that one film from the MCU makes it to the list. In the film, Tony Stark aka Iron Man and Bruce Banner aka Hulk join hands to build artificial intelligence that can act as a ‘suit of armor around the world.’ However, things quickly south when the AI becomes sentient and hacks his way into JARVIS and corrupts him. The evil AI then binds itself with one of Iron Man’s prototype robots to mobilize himself and eventually builds a strong alloy suit to take over the world and end the Avengers. Ultron also manages to get his hand on one of the infinity stones to build a vibranium-based android body for himself, but ultimately fails to do so. To the unversed, Vibranium is the strongest metal in the fictional Marvel universe across the films and comic books. The film can be easily discredited as ‘kids entertainment’ actually shares a profound narration on AI and its relationship with humans. Ultron, just two minutes after its creation connects itself to the internet and goes through the entire human history to quickly come to a conclusion that we need to go extinct. Now, that’s scary!

The Terminator (1984)

Another bleak take by humans on AI and how it can suddenly turn evil and start killing everyone. If AI ever becomes as intelligent as portrayed in films and ends up watching the films mentioned in the list then am not sure what will be its reaction, interesting to say the least. The Terminator illustrates the possibility of AI becoming an existential threat to humans. In the film, Skynet, an AI system sends a cyborg assassin back in time to prevent the birth of John Connor who in the future will lead a rebel group against Skynet. This film is a warning to humanity about creating an AI which could potentially end us all! Terminator 2 is definitely one of the best sequels made by Hollywood, however, the rest of the Terminator films can be skipped as they tend to stretch a simple plot into multiple stories which just don’t work as effectively as they should.

So here we are at the end of the line, having seen some of the best AI films you can ever imagine. Some honorary mentions of this list include – WALL-E, Chappie, Tron: Legacy, The Iron Giant, The Day the Earth Stood Still, and Superintelligence. Diving into these films to get entertained and amused is just fine, in fact, that is what films are primarily meant for. However, they also share a deep commentary on human beings and our dependence on technology. Whether AI takes over the world or ends up becoming the tool that allows humanity to grow into its next chapter is yet to be seen. But these films unquestionably put forward perspectives and asks questions about the future of the human condition.

Depths of ML – What is Machine Learning?

There is no debate about the fact that humans and computers are different entities. One of the main differentiating factors between humans and computers is that the former is capable of learning from past experiences. Well, to some extent. At the same time, computers need to be told what to do specifically. Computers are code-based strictly logic machines that do not possess common sense. This means that if we want them to do something, we have to tell them what to do precisely. This is done by providing them with step-by-step instructions on what to do exactly. Humans write scripts and program computers to follow instructions. This is where Machine Learning comes in! In simple terms, Machine Learning (ML) is a concept that consists of teaching computers to learn from experiences beyond data.

What is Machine Learning?

Machine Learning (ML) is a form of Artificial Intelligence (AI) that allows the software to predict more accurate outcomes without being programmed to do so exclusively. ML algorithms draw from historical data as input in order to predict new output values. Some of the ways ML is used are through recommendation engines, fraud detection, spam filtering, malware threat detection, and much more. So, what’s the big deal? Why is ML being used around as a trendy keyword in the world of AI?

ML is important as it allows enterprises to observe the changing trends in customer behavior. Business operational patterns can also be observed through ML, whereas the technology also helps in the development of new products. Tech giants around the world like Google, Facebook, Uber, and many others use ML as a central part of their operations. Similar to AI, ML also has different categories. While classical ML is usually classified by how an algorithm learns to output accurate predictions, there are four different approaches to how it is done. The approaches to ML are listed below –

Supervised Learning

In this type of ML, data scientists supply algorithms with specifically labeled training data. The variables of the data here are defined to the minutest details and both the input and output of the algorithm are specified. Supervised learning algorithms are good at binary classification, multi-class classification, regression modeling, and ensembling.

Unsupervised Learning

Unsupervised ML algorithms do not require the data to be labeled. Most types of deep learning used are unsupervised algorithms. These algorithms discover hidden patterns and groupings without the need for human input. Due to its ability to discover similarities and differences in information, unsupervised learning is the best solution for customer segmentation, image recognition, exploratory data analysis, and more.

Semi-supervised learning

As one would expect, this is the middle ground between Supervised and unsupervised learning. While training this type of algorithm, data scientists use smaller labeled data sets to guide classification. A small amount of labeled training data is fed to an algorithm which allows it to learn the dimensions of the data set.

Reinforcement learning

This type of learning is used to teach a machine to complete a multi-step process for which the rules are clearly defined. An algorithm is programmed with a distinct goal and a prescribed set of rules to accomplish that goal. One of the main implementations of reinforcement learning is robotics. Robots can learn to perform physical tasks with the help of reinforcement learning. Whereas, reinforcement learning can also be used to teach bots to play a number of different video games. Resource management is another way where RL can be used as finite resources and a defined goal can allow enterprises to plan how to allocate resources.

There are a lot of ways where machine learning is being used in a wide range of applications today. One of the best examples here is your Facebook news feed. The news feed uses ML to personalize every member’s feed. If you as a user frequently go on Kim Kardashian’s Facebook page then your News Feed is likely to show you more of her activity on the feed. We often start seeing advertisements for a certain product right after we search for it on Google or Amazon, that is due to the machine learning algorithm working in the background. Behind the scenes, the software is simply using statistical analysis and predictive analysis in order to identify patterns in your user data and use the same data to populate your news feed.

Top AI Things You’ve Probably Never Realized

AI is often touted as the technology that has the potential to change our lives. Thanks to its depiction in mainstream media, AI is also frowned upon by many as a technology that will take over the world. However, many are not aware of the extent to which AI is already being used in society and in everyday life. It is important to recognize that AI currently in use is mostly narrow. While superintelligent AI is still years away from fruition, there have been gradual changes in the field of Ai that could easily go unnoticed to people who do not actively seek out information about the AI field. To explore just how much AI affects our daily lives, we have listed down all the applications and platforms that use AI which could have gone under your radar.

According to a survey conducted by HubSpot, 63% of people are not actually aware that they use AI technologies. AI’s purpose in the current technological framework is to enhance the human experience, and humans being unaware that they’re using AI beats the purpose of the technology to some extent. Here are the top AI things you’ve probably never realized –

Amazon

Amazon’s artificial intelligence has been around for a long time now. Primarily, Amazon’s AI has been used in its site predictions and suggestions which aided in its sales increase massively. Amazon is undoubtedly one of the largest E-commerce players in the world right now with its owner Jeff Bezos seldom playing catch and release with the world’s richest man position. Reportedly, a third of the company’s sales come from their AI recommendations to end customers. With gradual progress, Amazon’s AI has become accurate and useful. Amazon’s AI is capable of predicting users’ shopping behavior and preferences to accurate precision. There’s also Amazon Alexa that uses audio input from users to give almost-accurate results when it comes to playing music and controlling your smart home devices.

Siri

Apple’s very own voice assistant is one of the most popularly used AI around the world. It is perhaps also the best example of speech recognition software. The program is as close as humans can get right now to Iron Man’s JARVIS voice assistant. The program connects to all your information ranging from messages, calendars, music, contacts, notes, etc. to create a personalized experience for you and also become smarter in the process. Using all the information at its disposal, Siri can understand your commands and requests with much ease. All of us enjoy asking Siri to give us beatbox beats but the voice assistant used for your amusement is far smarter than you think it is. There might come a day in the future when Siri never says ‘I do not understand that as it will be programmed to understand everything you have to ask her.

Netflix

Netflix needs no introduction. Netflix has brought about a revolution in the entertainment industry changing the way people consume content. Earlier, traditional cable television and theatres were the only way people could consume entertainment. It won’t be an overstatement to say that Netflix revolutionalized and also personalized the entertainment industry. The entire catalog of films, series, documentaries, and reality TV is ranked and customized to a personal level per user using Machine Learning. Through the use of AI, Netflix studies viewer engagement to find similarities and differences in your viewing pattern. The AI also studies which genres of content you usually watch and recommends similar content. The end goal of this AI is to retain viewers for the maximum amount of time, so, the next time you cannot stop watching a series or binge-watch film after film on Netflix, an AI could be responsible for it!

Gmail

Similar to Siri, Google’s email platform also uses machine learning to stop unwanted emails and spam mail from entering your inbox. This AI works by analyzing and learning patterns from previous emails in order to make the most accurate decisions it can. This AI is meant to protect users from malware and prevents users from being subjected to deceitful and harmful emails. Google has also recently announced the introduction of Smart Reply. This service replies to emails as users do. The things interesting around here as this feature analyzes all of a user’s previous conversations with attention to how they reply. The predictive algorithm then produces short replies for the emails, it is also capable of producing some complex replies. In the future, I am sure you won’t have to write replies to boring emails as an algorithm will take care of it.

Tesla

Tesla is currently one of the leaders when it comes to car manufacturers. The electric vehicle company, while manufacturing gorgeous-looking cars, has also worked on vehicles with predictive powers. One of the most renowned features of Tesla cars is self-driving hardware. With the help of these features, the car can drive itself while the driver can rest his hands away from the steering wheel. The car can detect when there is a pedestrian or an obstacle in front of it and come to a stop. One can expect this feature to only get smarter with the passing of time. However, when Tesla vehicles can operate the self-driving feature on Indian roads is when I’ll be completely impressed with it!

Depths of ML – What is Machine Learning?

What is Machine Learning?

Supervised Learning

Unsupervised Learning

Semi-supervised learning

Reinforcement learning

Top 6 sports sectors where Artificial Intelligence is paving the way

To err is human!

1st Test of Aus vs Ind, Dec 2003

India was at 62/2, trailing Australia’s 323 all out

Sachin Tendulkar steps out to the playing arena and the crowd cheers for the cricketing maestro. He faces the first two balls of his innings against Aussie speedster Jason Gillespie and is set to face the last delivery of the over. Gillespie releases the ball towards Sachin, which bounces high on a high-bouncy surface at Gabba.

The ball raps Sachin on the pads, and within a second, Gillespie appeals for the LBW to the umpire Steve Bucknor, known as ‘Slow Death’ due to his style of taking a big pause for a moment before raising a finger. Everyone knows the ball was offside and much above the stumps, but Sachin was given out LBW shouldering arms by Bucknor.

Sachin looks shocked by the decision, but he turns back and heads to the pavilion without any questions. Now, what happened in the Gabba test was completely a human error, and back then, in2003, players didn’t have any options to review the decision, unlike today, where we can get 100% accurate results with the help of AI.

How?

Have you seen Bennett Miller’s biographical sports drama film, Moneyball? The movie gives us a brief idea of how Billy Beane (played by Brad Pitt), a general manager of the baseball team and Peter Brand (played by Jonah Hill), an economics graduate, forms a competitive sports team by integrating computer-based methods.

Artificial Intelligence has been playing a prominent role in several industries already, and in the last few years, it has been introduced into the world of sports. Artificial Intelligence has a positive impact on the sports industry, and it has evolved the way we view and consumes sports content with real-time statistics and analytics.

Top 6 sectors where Artificial Intelligence is paving the way

AI Augmented Coaching

You must have seen coaches noting down something on a paper while the match was going on, haven’t you? The points they note down on paper can further be used to improve sports performance by understanding different metrics such as shot selection, spin, speed, and movement of players.

Along with the post-match observation and analytics, we can measure a forward pass or a penalty kick in football, LBW and run out in cricket and a lot of similar actions in various sports with the help of Artificial Intelligence. The data helps coaches to develop better training programs for the players and team.

AI can deliver real-time analytics for sports which helps coaches develop counter strategies and have a more immersive experience beforehand. The performance metrics of the athletes calculated through AI help coaches understand the areas where they have maximum potential to sweeten and where they need to focus more.

AI-based Advertising

We have over 7 billion people spread over 7 continents, and every place has its taste when it comes to sports. Whatever the game is, in the end, what matters is – how you get the audience’s attention. With the help of Artificial Intelligence, we can understand and showcase the most relevant ads according to the audience’s demographics.

Within a short span, AI has become the future of advertising, and if you’re not employing AI for digital advertising, you’re at a disadvantage. Artificial Intelligence allows companies to estimate the efficacy of their advertising campaigns in real-time. With AI-powered tools, advertising teams can automate specific cognitive tasks.

AI in Streaming & Broadcasting

Artificial Intelligence is the “science of making machines smart”, and it has the ability to create an impact on the way the audience experiences sports. With the help of Artificial Intelligence, we can choose the accurate camera angle to display on viewers’ screens, and broadcasters can pick out highlights they wish to distribute post-live matches.

Player Selection with the help of AI

When franchises or teams are about to select players, they need to go through a whole lot of workload, from their past performances to what they are really good at. Earlier, it was a painful journey, but with the arrival of AI, they can keep track of the performances of different players and analyse players’ records before selecting them for a team.

AI in Decision Making

We have already discussed how a wrong umpiring decision can significantly impact the game. To avoid such instances and keep the game fair, AI is introduced into many sports, which helps them come to an accurate conclusion. In cricket, we have hawk-eye technology to point out whether the batsman is out or not in cases of LBW.

AI in Health & Fitness

Wearable technology has become a part of day-to-day life in the last couple of years, but besides normal usage, we can use wearable technology to put players through physical tests that use AI to track the movements and physical metrics of the players. With that, we can detect early signs of musculoskeletal or cardiovascular issues or even stress-related injuries.