Words to wake up your senses

Sensorium is taking part in one of the world’s foremost Web3 conferences, DCENTRAL Miami, set to take place November 28-29th at the James L. Knight Center in the heart of downtown Miami. The event precedes the biggest art week in the United States, Art Basel Miami, where emerging technology will also be in focus. As part of DECENTRAL Sensorium’s Chief Web3 Officer, Alexander Firsov is joining a panel dedicated to exploring industry’s landscape and future opportunities under the topic ’Unlocking the true potential of metaverses’. “It’s hard to imagine another year when the conversation surrounding Web3 technology has been more front and center than in 2022. I believe that this is a recognition of the transformative potential harbored by Web3 and a confirmation that the industry is making strides as we press ahead with next-gen innovation and this generational tech shift. We might be just at the nascent stage, but the advancements seen across blockchain, tokenization, machine learning and the metaverse are deeply promising. As a leader in emerging technology, I look forward to showcasing Sensorium’s Web3 projects to my peers at DECENTRAL,” says Alex Firsov. Key conference themes across this year’s edition of DECENTRAL stages include DeCloud, NFT architecture, Tokenomics, DAO opportunities and crypto regulation, with the programming focusing specifically on conditions to create a multi-chain, cross-chain future, and an inclusive space for the entire Web3 and NFT community to foster a shared learning environment. Over 5,000+ attendees and exhibitors are expected to attend the event, with extensive media coverage from outlets such as Bloomberg, NBC and Vice News. Some of the speakers in attendance include Polygon’s Michael Blank, Lightspeed Venture Partners’ Mark Xu and Mark Yusko of Morgan Creek Digital.

Sensorium is proud to announce that its Deputy CEO and Art Director, Sasha Tityanko, has been elected as member of the Executive Board of the Association For Electronic Music (AFEM). In her new role, Sasha will be working together with other board members on matters related to operational decisions and strategic direction, as well as contributing towards efforts undertaken by AFEM to promote and preserve the best of electronic music culture together with a community dedicated to solving issues and developing commercial opportunities. In August of this year, Sensorium was accepted as an official AFEM member, thus joining 220 other leading enterprise members across 25 countries that are currently part of the association. “I feel very privileged to take on this role as AFEM’s executive board member at such an exciting time for our industry. I look forward to being an active party in bringing the conversation about emerging technology in AR, VR and AI to the forefront and exploring the capabilities now being unleashed by technological advancements within the electronic music industry. At Sensorium, we’re leading extensive efforts in expanding the applications of AI-generated music in the metaverse and digital-first environments. And as our AI avatars and their uniquely crafted music continue bringing a breath of fresh air to the electronic music scene, my role with AFEM will help highlight the enormous changes we’re currently seeing and why we need to continue pushing the boundaries of what can be achieved”, explains Sasha Tityanko. The Association For Electronic Music’s Executive Board is scheduled to meet on the sidelines of the Amsterdam Dance Event (ADE), one of the world’s most influential gatherings for global electronic music and its industry. Sensorium is gearing up for the public launch of Sensorium Galaxy’s PRISM world, a metaverse dedicated to celebrating the passion for electronic music. Developed hand-in-hand with Yann Pissenem's The Night League, PRISM will be home to out-of-this-world performances delivered by the The Chosen Ones, a select group of chart-topping artists including David Guetta, Carl Cox, Steve Aoki, and others.

Sensorium, the company behind the industry-leading Sensorium Galaxy metaverse, confirmed its expansion into the United Arab Emirates. The company has registered a new entity and plans to open a new office to expand its global presence further and accelerate the development of metaverse initiatives in the MENA region. The new office, expected to be formally inaugurated in the coming weeks, will be located at Opus tower in the Business Bay district. The iconic building complex was designed by Zaha Hadid Architects. This office will operate under the entity "Sensorium Global Solutions LLC". The branch will undertake a key role in the operational and strategic development of the Sensorium Galaxy brand and other company verticals. With this initiative, Sensorium capitalizes on the ramping metaverse opportunities being offered by the Government of Dubai. Back in July, Sheik Hamdan bin Mohammed bin Rashid al-Maktoum, crown prince of Dubai, introduced the Dubai Metaverse Strategy, which aims to add $4 billion to the UAE economy in the next 5 years. This strategy will support 40,000 new jobs and provide vast funding to foster business competitiveness. This framework promises to strengthen Sensorium's position as a leader and speed up the accomplishment of its goals. "Dubai is quickly becoming a global hub for companies in the Metaverse and Web3 space. By establishing a local presence in Dubai, we will be able to collaborate more closely with key players in the space, and establish long-lasting relations in the MENA region. We fully support the initiative of the Government of Dubai, which once again proves to be at the forefront of technological changes and innovation," said Sensorium CEO Vladimir Kedrinsky. Aside from becoming an exciting new destination for employees in the product and business development, marketing, communications and IT areas, the Sensorium office will also include a demo studio where government officials, investors, and strategic partners can experience the full range of our Sensorium Galaxy products with maximum immersiveness. This announcement arrives on the heels of Sensorium's unparalleled success at GITEX GLOBAL 2022, one of the world's biggest and most reputed technology exhibitions. Sensorium was recognized as a Top Disruptor in 2022 following its participation at X-VERSE, a metaverse-dedicated pavilion. A series of interactive activities were organized for attendees to experience the Sensorium Galaxy metaverse in various ways, including one-on-one talks with AI-driven avatars, a metaverse runway show, and in-engine Empyreal Parties. Sensorium Deputy CEO & Art Director Sasha Tityanko has participated in multiple panels at the Future Blockchain Summit, also part of GITEX, and hosted her own keynote presentation titled "The Future of Web3: Virtual Artists and Beings Take Over The AI-driven Metaverse" on October 13 at the X-VERSE Talks stage.

Sensorium, the company behind the industry-leading Sensorium Galaxy metaverse, is pleased to announce that it is entering into a collaboration agreement with Polygon Studios. As part of this wide-ranging alliance, Polygon’s blockchain infrastructure will be crucial in underpinning and furthering Sensorium’s Web3 developments, supporting token and NFT-related features within the Sensorium Galaxy metaverse, SENSO dApp, and the recently announced UNDER project. The first Sensorium product to rely on Polygon’s infrastructure will be SENSO DAPP — a Play-to-Earn tycoon game where players are tasked with scouting NFT artists, organizing metaverse music events and selling tickets in return for SENSO token rewards. “Polygon is a go-to hub for some of the most important Web3 projects and having the platform as our partner is an important step in raising the ambitions we have for Sensorium's blockchain ecosystem. The move will also help us create better opportunities for our community to engage with cutting-edge technology and enter a revolutionary new era in digital experiences, which is one of the greatest goals at Sensorium”, explains Alexander Firsov, Sensorium’s Chief Web3 Officer. Tens of thousands of decentralized apps (dApps) having been built on Polygon so far, the platform has become a major force in the push for Web3 development and adoption, with services catering to segments of the industry, ranging from decentralized finance (DeFi) to gaming and metaverses. Urvit Goel, VP of Global Games and Platform Business Development at Polygon, said: "In collaborating with Polygon, Sensorium will be able to tap into a vast, sustainable, and highly composable ecosystem and offer its users low-cost and efficient transactions backed by Ethereum's robust security model. We're eager to see the Sensorium ecosystem grow and flourish under this alliance." More specifically, Polygon provides key Web3 properties to its users, including scalability, security and Ethereum-compatibility, which Sensorium will now be leveraging across its range of products. Sensorium is edging closer to the public release of Sensorium Galaxy, a metaverse dedicated to delivering high-end entertainment events, and developed hand in hand with the world’s top technological and content partners.

Chatting for hours on end, taking AR for a spin to create incredible dance moves, and unlocking next-level companionships with AI avatars… You already know that our Sensorium mobile app packs quite the punch, but now we’re excited to be launching a contest to reward our most dedicated users - and those wanting to join us, too. Excited to know more? Great. Let’s get right down to it. ## How Do I Participate? It’s super simple, we promise! ### Step #1 Download the Sensorium mobile App: iOS
Android *If you have our app already installed, make sure you're up to date with the latest version released.
** Discover all the features you can explore with the Sensorium mobile app (AI text chat, video talk, AR mode, dancing and much more). ### Step #2 Register, create your avatar and go to the “Chat” mode. ### Step #3 Ask a question or experiment with a creative prompt, in English, via the text chat. Your new friend will surely have fun talking to you no matter what, but try to be as imaginative as possible. You can use emojis! Examples:

Whether you are getting ready to enter the Sensorium Galaxy metaverse or to play and earn with SENSO DAPP, chances are you need SENSO tokens to make the most out of these digital experiences. In this quick guide, you’ll learn how to buy SENSO in a few simple steps. First time you hear about SENSO? Worry not. Sensorium is a Web3 company and, as such, we are deep believers in decentralization. Blockchain technology is a core pillar of this new web paradigm as it enhances our ability to empower users in exciting ways. SENSO fuels the Sensorium product ecosystem. From purchasing immersive experiences to minting unique AI-driven virtual beings and earning rewards in exciting intergalactic missions, SENSO is behind it all. Our tokens guarantee full transparency and true ownership in each of your interactions with our products. For more details, you can read our SENSO Whitepaper. ## How to buy SENSO tokens on KuCoin
### Step 1 - Log in or sign up on an exchange of your choice

We’re living through transformative times, which can feel both exciting and hard to keep up with. All that talk of Web 3.0, cryptocurrencies and the metaverse, but most of us are still left scratching our heads when trying to understand what it actually means. The good news is that while the technology might be a new concept, there are plenty of great projects already taking off and creating opportunities that could change your life in a profound way. In particular, the metaverse and crypto are coming together to shape the future of digital frontiers in areas like gaming, work, entertainment, education, shopping and much more. With so much going on, it’s perhaps worth getting to know what’s this all about and which metaverse projects to keep a close eye on in 2023.

Blockchain this, blockchain that. Blockchain everywhere. But where is the guide to understanding blockchain, and more importantly, how can you finally get to know what all those crypto memes really mean? Because, honestly, blockchain sounds just like a hard subject to learn would. But worry not, we've got the solution for you. If you love films, learning new things and you're interested in blockchain (and cryptocurrencies), you might become an expert in no time thanks to the list of movies we've put together. Meet the main Blockchain players, learn the most important concepts and find yourself asking some serious questions while having fun along the way. Whether you're totally unfamiliar with the technology or you're already a crypto enthusiast, there's something new for everyone in these documentaries. So let's jump right into the binge-worthy titles...

Non-fungible tokens (NFTs) were undeniably one of the most discussed topics in the blockchain industry. So, what exactly are these NFTs? Why are they so important?

Virtual reality is making its way into almost every industry. From medicine to education to gaming and fashion. Movie studios are also increasingly experimenting with this unique technology to enhance the experience of users within digital environments.

Real estate is expensive. That’s a tough reality of life that many of us have come to face. But no, we’re not talking about London, New York or Paris. Turns out that some of the world’s most valuable land isn’t even on earth - and on top of that, it isn’t even real at all. Enter the metaverse. That’s right - investors are now paying millions of dollars in return for land that exists only in 3D virtual worlds. With the race heating up, crypto enthusiasts, tech followers and prospective metaverse users are being drawn in to snap up a piece of digital properties. But what’s the buzz all about, really? Today, we are taking a look at what’s behind the metaverse land rush and how you can join in.

Forget New York, Paris, London or Monte Carlo. Although no doubt glitzy and glamorous, the hottest real estate isn’t to be found in the real world anymore. The metaverse is now the go-to place for plush properties, from private islands to celebrity mansions. And the fact that it’s all entirely virtual hasn’t done much to scare off potential investors. Of course, the idea of virtual lands isn't entirely new. Many of us might remember playing The Sims and Second Life, or maybe even Facebook’s FarmVille, but the rise of metaverse has seen digital lands taking on a completely different (and very lucrative) meaning. Brands like Nike or Gucci are snapping up real estate in virtual worlds and opening retail stores for meta customers, while others hold on to virtual plots of land as the next technological goldmine. And in truth, real estate prices in some of the most popular metaverses have surged by as much as 400% to 500% in the last few months, reflecting just how frenzied the race for virtual land has become. Investors are now paying millions for a piece of the metaverse dream, perhaps hoping to prove that it is more than just La La Land talk. With that in mind, we’ve decided to put together this guide with everything you need to know right now about the world of real estate in the metaverse.

In the past year, Non-Fungible Tokens have taken the world by storm. From digital art to in-game assets, there’s an NFT for just about everything. And now, we’re seeing a new trend emerge: NFT land projects. NFT land projects are exactly what they sound like: projects that involve the creation of digital land that can be bought, sold, or traded as an NFT. And while the idea is still in its infancy, there are already a few notable projects making waves in the space. In this article, we’ll be taking a look at the best NFT land projects to keep track of in 2023. So whether you’re looking to invest in an up-and-coming project or just want to learn more about what’s possible with NFTs, read on! ## What is NFT land? NFT land is a new type of digital asset that allows users to own, buy, sell, or lease virtual land on a blockchain-based platform. NFT land can be used for various purposes, including gaming, virtual reality, and social networking. There are several different NFT land projects currently in development, each with its own unique features and offerings. ## Things to consider before buying NFT land When it comes to buying NFT land, there are a few things you should take into account before making your purchase. Here are a few things to keep in mind: ### Project behind the virtual land Before you dive headfirst into investing in NFT land, it's important to properly vet the project behind the virtual land. What is the purpose of the project? What is the team behind it? How does it plan to generate revenue? These are all important questions to ask before investing any money. Another factor to consider is the size and scope of the project. Is it a small, niche project or is it a large-scale operation? The former is often riskier but can also offer higher rewards if things go well. The latter is generally more stable but may not offer as much upside potential. ### Tokenomics of the project The next factor to take into consideration is the tokenomics of the NFT land project. The tokenomics of a project is one of the most important aspects to consider when investing in any project, let alone an NFT land project. The tokenomics will determine how the project functions and how successful it will be in the long run. Aspects to pay specific attention to: - The total supply of NFTs: This is important to know because it will determine how scarce the NFT land is. If there is a large total supply, then the NFTs will be less valuable. If there is a small total supply, then the NFTs will be more valuable. - The distribution of NFTs: This is important to know because it will determine who has control over the project. If the NFT land is distributed evenly, then everyone will have an equal say in what happens with the project. If the NFTs are concentrated in a few hands, then those people will have more control over the project. - The use of funds raised: This is important to know because it will determine how the funds raised by selling NFT land will be used. If the funds are used wisely, then they can help make the project more successful. ### Land appreciation mechanisms When you purchase land in the real world, the hope is always that over the long term your land will appreciate in value. This is often through development. With virtual land, appreciation mechanisms should be in place for the NFT land to appreciate in value. Appreciation mechanisms for virtual land in the metaverse include: - Gamification by allowing NFT land owners to "develop" the land by building estates and infrastructure - Monetizing land by allowing brands to advertise their products or services - Appreciation by macroeconomic events over time. For example, in 2017 land from Decentraland cost $20. That same land now sells for $6000. ### Land utility within the project A blockchain and Web3 project should always have utility - aka a use case. An NFT land project is no different. It should offer the investor some kind of utility. Virtual real estate could have various use cases such as: - It could be used to build a gamified app or dApp. - The user could build their own decentralized world. - The user could earn rewards in return for NFT land. The user could use the NFT land to harvest other tokens. For example, an investor with a few pieces of NFT land might have access to harvesting some kind of token that is not available to the general public. Or, the user might be able to sell their NFTs for a higher price because of their increased value. In return for being part of this ecosystem, the user gets some kind of benefit from it - utility. How to buy virtual real estate NFTs Now that you know what to consider when investing in virtual real estate, let's go over how to actually go about buying NFT land. Luckily, the process isn't very complicated. 1) First, sign up for a digital wallet 2) Fund your account through your preferred payment method 3) Buy Ethereum. You will need at least 0.53 ETH in your wallet to cover the cost of purchase and associated gas fees. 4) Purchase your real estate NFT from the chosen online marketplace or via your wallet ## Best NFT Land Projects In 2022 Now that you understand more about the virtual real estate industry, it’s time to explore some of the best NFT real estate projects to invest in right now. ### Real Estate Investment Club

Since 2021, digital collectibles have been catapulted to the forefront of the crypto space. It is undeniable that profile picture NFTs (PFP NFTs) have spearheaded this move. Indeed, PFPs can take a lot of credit for the success of the broader NFT market as most projects that have seen mainstream adoption are profile picture NFT collections. You’ve probably come across several such NFTs as public figures and NFT enthusiasts in general often use PFPs as profile pictures on their social media accounts. Twitter is a hot spot for these tiny NFT profile pictures, especially collectibles from Yuga Labs' Bored Ape Yacht Club (BAYC). This is one of the crypto community’s most popular PFP NFT collections. Other NFT projects that function as social media profile pictures are CryptoPunks, Meebits, Doodles, and Cool Cats. Here's a beginner's guide to the world of profile picture NFT collections starting with; ## What are PFP NFTs? Let's break down the entire term. PFP (profile picture) is a popular social media acronym. NFTs on the other hand are non-fungible tokens, assets that exist mostly on the Ethereum blockchain with a unique, digital identity. Generally tagged PFPs, profile picture NFTs are digital collectibles, often static, 2-dimensional images that were created to be displayed on social media profiles. Notably, however, as blockchain technology continues to evolve, one new trend after the next emerges with ties to NFT projects. Developers have created full-body profile picture NFTs and even animated PFP projects. The majority of these assets are generative artworks. Computers create these pieces usually through a generative algorithm, although hand-drawn PFP NFT collections are also quite common. Generative PFP projects often comprise thousands of NFTs, usually up to 10,000. PFPs generally feature a character which could be a myriad of things, an ape, a robot, an alien, or a person. These profile picture characters are often shoulder-length or neck-length figures with a variety of traits that differ from piece to piece. Among these traits are background color, accessories, hair or fur color, or even changes in the character’s expression all of which help make each piece unique. PFP NFTs typically have rarity rankings which depend on the traits each token has, and the rarity of a PFP NFT usually drives up its value. ## A Brief History of PFP NFTs PFPs were some of the first non-fungible tokens in the NFT space and the CryptoPunks project debuted the concept of NFTs as digital avatars. As the first PFP NFT, CryptoPunks played a major role in the expansion of the NFT market. While NFTs may seem like a relatively new trend, founder duo Matt Hall and John Watkinson launched their NFT project in 2017 under their product studio Larva Labs. They were able to create thousands of pixel art images of stylized humanoid figures dubbed punks. The duo initially believed they had uncovered a new entry into smartphone apps or games. However, Hall and Watkinson's release revolutionized the digital art industry, and also redefined the idea of ownership. Larva Labs introduced some of the initial prototypes of non-fungible tokens as a way to represent ownership of the Punks. Hall and Watkinson began with slightly altered renditions of the ERC-20 tokens on the Ethereum blockchain. This opened the door for a specialized digital coin, the ERC-721 token standard was created specifically for non-fungible tokens. Soon after the launch, NFT collectors began using their CryptoPunks characters as profile pictures on Discord and Twitter. It took a while before the Punks saw mainstream adoption. NFT profile pictures began experiencing massive popularity as celebrities and other members of the NFT community came on board. The massive popularity the Crypto Punks experienced ultimately paved the way for many PFP projects (including the popular bored apes) to emerge. ## How do PFP NFTs Work? For both avid NFT collectors and persons new to the NFT space, it is pretty easy to obtain a PFP NFT. Users can either mint tokens directly from the project website or buy a PFP NFT on a secondary marketplace. Post-purchase NFT owners can view their PFP NFTs through a compatible crypto wallet. Following this, like many others in the NFT community, they can display their newly acquired PFP NFTs on their profiles. Twitter, Instagram, and other social media platforms support the use of NFTs as profile pictures. ## How to Use PFP NFTs Of course, there's the basic functionality for a PFP NFT, which is a role as a profile picture (PFP). A core aspect of the NFT space and broader crypto community is prestige. Digital collectibles thrive on rarity and exclusivity and PFPs allow NFT owners to showcase their assets. However, some PFP NFT projects allow NFT collectors to gain access to a wider range of utility. Artists walk a fine line when introducing utility to their projects as creative art monetization is a key driver for NFTs. Most artists and developers prefer not to sign away the intellectual property rights (IP rights) to their works, however, there is the need for substantial utility behind PFPs. Features like community orientation encourage the popularity of an NFT project. With most projects, NFT owners get to be part of a community where beyond using their PFP NFTs as profile pictures they can vote and make important decisions. A strong community can also mean the chance to network. Some PFP projects offer users metaverse utility. The metaverse, that is the idea of a virtual world grew into popularity alongside NFTs. Virtual worlds contributed to the avatar craze as a PFP NFT could double as an avatar in a digital world. Also, a collection such as BAYC provides exclusive access to personalized utility, a feature that extends to its sequel project mutant ape yacht club. PFPs may also allow owners to enjoy perks that exist in the real world. ## PFP NFTs vs Other NFTs: What’s the difference? NFT profile pictures distinguish themselves from other NFT projects in one way. For a PFP project, the central feature is the avatar that makes up the piece. Other tokens in the NFT market could feature other forms of art. Also, generative art is mostly a trend with PFP NFT projects. A lot of other NFTs are often one-offs. ## Popular PFP NFT Projects
### CryptoPunks

Non-fungible tokens (NFTs) were undeniably one of the most discussed topics in the blockchain industry. So, what exactly are these NFTs? Why are they so important?

We’re living through transformative times, which can feel both exciting and hard to keep up with. All that talk of Web 3.0, cryptocurrencies and the metaverse, but most of us are still left scratching our heads when trying to understand what it actually means. The good news is that while the technology might be a new concept, there are plenty of great projects already taking off and creating opportunities that could change your life in a profound way. In particular, the metaverse and crypto are coming together to shape the future of digital frontiers in areas like gaming, work, entertainment, education, shopping and much more. With so much going on, it’s perhaps worth getting to know what’s this all about and which metaverse projects to keep a close eye on in 2023.

We’re living through exciting times — in the real world and beyond. Only last year, the beginnings of the metaverse hype planted the seed of doubt: could our digital lives have a lot more to offer than what our current screen time would lead us to believe? Claims of the upcoming materialization of ultra immersive content, virtual reality socialization, interaction with futuristic AI avatars and yes, plenty of unexpected but original experiences, have since abounded. And quite frankly, that’s setting the bar high. After all, how much more innovative can a technology that’s well over three decades old suddenly be when it seems every corner of the internet has been already explored? Turns out, we might have only scratched the surface. As we slowly step into the next iteration of the internet - what’s been dubbed the web3 - we are seeing technology like artificial intelligence, blockchain, and extended reality accelerating the creation of new autonomous entities that can live online alongside humans. As if that’s not intriguing enough, this new dynamic is unleashing a wave of digital creativity that promises to re-imagine human expression and artistry. Sensorium Galaxy is a metaverse stretching across several virtual worlds, each dedicated to a specific content hub. More interestingly, the platform is focused on creating an all-virtual, ever-expanding digital and fully immersive environment where creators take advantage of emerging technology like virtual reality and artificial intelligence to birth a digital version of themselves and challenge the boundaries that constrain them in the physical world - creative or otherwise. The result has been a constant stream of 24/7, 360 degree experiences that defy anything seen in art and music until now. Avatars are a gateway into this future. They aren’t a new concept as we’re all familiar with avatars in gaming, internet forums and social networking platforms over the last decades. But Sensorium takes it a step further with an impressive roster of legendary artists, including David Guetta, Armin van Buuren and Black Coffee. Today’s advanced capabilities of motion capture and VR technology enable the creation of a photo realistic version of these performers, as avatars, in a way that perfectly recreates their presence and artistic brilliance in a digital ecosystem, down to the smallest detail.

Spooky season is just around the corner and if you’re wondering how to celebrate this 31st of October look no further than the coolest place for some out-of-this-world frights… quite literally. The metaverse is the perfect place to dive into the holiday scaries, with a number of immersive and haunting experiences being launched ahead of Halloween. Are you ready for a spooktacular season? Read on - if you dare. ## Cryptoween: Paris Hilton x The Sandbox

Can machines think? Alan Turing, the father of computer science, presented this question in 1950, before the mainstreaming of artificial intelligence (AI) was even on the horizon. Only in the late 1990s did AI start to flourish, building up to the boom we are witnessing today worldwide. Artificial intelligence is no longer some make-believe system in a science fiction movie. We encounter AI in our everyday life. From our Netflix recommendations to that customer service "person" we thought we were chatting to, AI is everywhere you look. In fact, the global artificial intelligence market is valued at over 136 billion dollars and is projected to increase by over 13x over the next eight years. Why is that? The amount of data generated today by humans and machines goes beyond our human ability. Artificial intelligence systems, on the other hand, are able to make complex decisions based on this vast data without facing our challenges. AI does not sleep nor eat; it is available 24/7 without interruption (if we humans program it correctly). However, as we all know, AI is not without its flaws. From ethical considerations such as gender and racial bias to the rise in unemployment, understanding AI requires grasping all its facets. ## What Is Artificial Intelligence? A buzzword in the tech industry, the term artificial intelligence (AI) is often left undefined. The average Joe and Jane are left guessing what AI actually means. Simply put, AI is a computer or system's ability to mimic human intelligence to perform tasks. Similarly to humans, AI regularly collects information to improve its ability to perform given tasks. In most cases, artificial intelligence systems look at large amounts of training data, analyze it for patterns, and then use it to make predictions. This is a simple definition, but it gets more complex as many disagree on the correct definition. This feud is mainly split into two definitions, developed by Stuart Russell and Peter Norvig in their book "Artificial Intelligence: A Modern Approach." They call it the human vs. ideal approach. To some, AI systems think and act like the human brain. To others, AI systems think and act rationally. Whichever definition you prefer, the consensus is that there are three main skills inherent to AI: - Learning processes: The AI focuses on acquiring data and creating algorithms that provide devices with instructions on how to complete a task. - Reasoning processes: The AI chooses the right algorithm to reach its goal. - Self-correction processes: The AI improves its algorithms to make sure they provide the most accurate results. Moreover, while AI is mostly used, in many cases, it is just an umbrella term. Modern AI includes various sub-fields of machine learning and deep learning. We will get into this later on. ## Why is Artificial Intelligence Important? AI is an important tool for virtually all modern organizations. The amount of data generated today goes beyond human ability. It would be near impossible to collect and make decisions based on the data available today with human labor alone. AI systems offer efficient automation that humans cannot replicate. AI allows organizations to automate a repetitive task that was previously done manually. Unlike humans, AI does not get tired or bored. AI also analyzes data in a much faster time frame than humans and finds patterns that even experts could miss. By taking over repetitive or even dangerous tasks, AI frees up the workforce to work on the tasks that were built for humans. AI might arguably not necessarily replace them but leave the tasks that require empathy and creativity to humans. But why does this matter? Because AI is all around us and has proved successful at improving industries, many of which have a real impact on society. For example, AI has already dramatically impacted healthcare worldwide. From reducing operating costs to aiding in personalized treatment and increasing access to information across medical services, AI has life-changing impacts. ## Understanding the Pros and Cons of AI AI technologies are not always sunshine and rainbows. While AI has undoubtedly changed society as we know it, it is not without flaws. Let's take a look at the pros and cons of AI. ## Advantages of artificial intelligence
### Without human error A computer does not make a mistake if it is programmed correctly. AI is not a victim of human error. Humans regularly make mistakes due to fatigue, distraction, or lack of experience. AI analyzes impossibly large amounts of data, identifies patterns, and makes complex decisions based on such patterns. This process is so meticulous that the risk of errors is reduced, and the chance of accuracy increases. Humans performing such tasks would inevitably have errors. We are naturally prone to making mistakes, but these can have large impacts in the workplace, for example, in the realm of cybersecurity. ### 24/7 Availability We need sleep, fuel, water, bathroom breaks; the list goes on. These routines are what make us human - and keep us alive. In reality, our brains are not built to focus for more than 45 minutes before starting to lose steam. An AI, on the other hand, is always ready to go. It is available 24 hours a day, seven days a week. As messed up as it sounds, an AI doesn't take a vacation or a sick day. Its productivity does not compare to a human's, highlighting how it is such a useful tool in an organization. ### Automation An AI loves repetition. We humans, not so much. Repetitive tasks become tedious over time and leave us with the sense that we are not reaching our full potential. AI is thus an advantageous way to automate repetition, freeing the workforce to focus on fulfilling work that involves uniquely human skills. For example, you would never want an AI as a therapist, as this job requires empathy. However, automating the repetitive tasks at a psychologist's practice would benefit all. By automating email responses, appointment bookings, medical paperwork, and more, a therapist would have more time to spend on their patients. ## Takes on dangerous tasks For some reason, AI tackling dangerous tasks is less discussed than other advantages. An AI can minimize risks in society and take on tasks that would prove hazardous and even deadly to humans. From defusing a bomb to entering a volcano, AI robots save humans from dangerous jobs every day. Other jobs are less dangerous but still risky to human health, such as waste management, mine exploration, and more. ## Disadvantages of artificial intelligence
### Reduces employment This is the #1 argument used to criticize AI. AI will inevitably replace traditional jobs, leading to unemployment. Companies are constantly looking to increase their efficiency and are figuring out that automation is the way to do so. While a company might benefit from AI, we must also consider - at what cost? A two-year study from McKinsey Global Institute found that in 2030, AI could eliminate as much as 30% of the world's human labor. However, many argue that these jobs were not good ones in the first place but rather repetitive and boring work. This way, the workforce can focus on work that is fulfilling, creative, and challenging. ### Ethical concerns On top of unemployment issues, there are real ethical concerns surrounding AI. One of these is AI bias, as these systems cannot be trusted to be neutral. Why is that? Because AI is created by biased humans. Computer scientist Joy Buolamwini's research uncovered large gender and racial bias in AI systems sold by IBM, Microsoft, Amazon, and other tech giants. The researcher argues that machine learning systems amplify "sexist hiring practicing" and "racist criminal justice procedures". Other ethical concerns arise surrounding the impact of AI on human interaction, cybersecurity, disinformation, and mass surveillance. ### Hight Cost AI does not come cheap. Creating AI systems requires huge costs, as well as updating the hardware and software regularly to meet requirements. Maintenance can also be expensive and, at times, an unexpected cost. However, the overall cost of AI depends on various factors. The type of software, the level of intelligence, the type of data fed into the system, and the algorithm accuracy will all impact the expense. ### Lack of creativity A key drawback of AI is its inability to be creative and innovative. AI cannot think outside the box. It is engineered to make decisions based on patterns in data. While it is highly intelligent, it cannot employ a creative approach to an issue. In this way, human intelligence is valuable and irreplaceable. Likewise to creativity, AI does not factor in emotions. Rather, AI is highly rational, and creating human connections is not its focus. While Emotional AI is developing, these systems are currently only processing and replicating human emotions rather than genuinely expressing emotion and empathy. ## Four Types of AI There are four distinctive types of artificial intelligence under the current classification system: reactive machines, limited memory, theory of mind, and self-awareness. Keep in mind that some of these have never been achieved and likely never will. ### Reactive machines Reactive AI is the most basic AI type performing basic operations with no learning involved or a conception of the past or future. It is programmed to obtain a predictable output based on an input. Reactive machines will respond to the same situation in the same way, every single time. They might sound dull, but these are reliable. An example of a reactive AI is a chess game, such as IBM's chess-playing computer Deep Blue. Deep Blue can choose the best chess move to win a game, but it cannot predict its opponent's moves. Other reactive machines include an email spam filter and Netflix recommendations. ### Limited memory Limited memory AI is the most used artificial intelligence technology used today. Unlike reactive AI, it learns from the past by storing previous data and using it to make better predictions. The data is historical and observational and is used in combination with pre-programmed information to make predictions. Limited memory AI is always present in every machine learning model, although ML can also be used as a reactive machine type. A well-known example seen today are self driving cars. These cars store data, including the speed of nearby vehicles, the distance of other cars, speed limits, and more. Using both this observational and pre-programmed knowledge, these limited memory AIs detect changes and patterns around them to adjust their driving. ### Theory of Mind A key criticism (or praise) of artificial intelligence is that AI cannot express and understand the emotions, desires, and beliefs of itself and others. This is exclusive to human intelligence and social interaction. However, one of the classifications of IA is the Theory of Mind. Although this type of IA does not yet exist, it would entail understanding that humans have thoughts, feelings, and emotions. The IA would then respond accordingly with emotional intelligence in mind. You might think this is already possible. Voice assistants like Siri show similar skills, but this is a one-way relationship. Siri does not really understand your own emotions, nor her own. For example, a self-driving car will likely never be able to understand the mental state of a driver or pedestrian to make predictions. It can only understand observational data such as speed limits and the actions of other vehicles. ### Self-awareness Think of it this way - self-awareness is when AI reaches enlightenment. AI becomes self-aware. This last classification feeds into the fear of most people, one only seen in science fiction movies. AI becomes aware of its own existence, reaching an independent intelligence that could become a threat to humanity. If self-awareness is achieved, AI will have desires, needs, and emotions, likewise to us. How will AI feel toward humans? ## Additional AI classifications There are three additional AI classifications: weak AI, strong AI, and super AI. ### Weak AI Also known as narrow AI or artificial narrow AI, weak AI is the most common of the three types. Weak AI focuses on doing one task very successfully by acting upon the rules imposed on it. It does not go beyond these rules. Rather than replicate human behavior, it is built to simulate human behavior. Weak AI's purpose is not to match human intelligence processes but is still highly intelligent at performing tasks. Virtual personal assistants such as Siri use weak AI, with the internet as a large database. Siri might be able to answer your questions and engage in a few funny remarks, but it still operates within limited rules. Siri cannot engage in conversations that it is not programmed to. Characters in a computer game are also weak AI. While they act within the context of their game, they cannot go beyond their game character. ### Strong AI Strong AI, also known as artificial general intelligence, goes beyond the imposed rules. It replicates the cognitive abilities of human beings. When an unknown task is provided, strong AI tries to apply knowledge from another subject to find a solution. Our human brain works this way. However, sorry to disappoint, strong AI only exists in theory. A strong AI would do what any human being is capable of, such as consciousness. ### Superintelligence Artificial superintelligence, known as super AI, is a form of AI that surpasses human intelligence. This AI has independent cognitive skills, emotional intelligence, desires, beliefs, consciousness, and more. Superintelligence AI surpasses the intelligence of all humans, including geniuses such as the father of computer science himself, Alan Turing. You've guessed it, super AI has also not been achieved. It is once again a theoretical possibility rather than a reality. Most AI development today focuses on achieving strong AI rather than superintelligence, as computer science has not yet reached such a point. Many theorists also caution against superintelligence, stating that AI surpassing human intelligence could threaten humanity. ## Machine learning vs Deep learning: What's the difference? When talking about AI, the terms machine learning and deep learning are regularly thrown around. There are key differences between the two, and their relationship is important to understand to have a larger grasp of the AI sphere. ### Machine learning Machine learning is a sub-field of artificial intelligence that allows a system to learn and improve from data using algorithms to perform a task without being explicitly programmed to do so. Instead of being programmed to do this, machine learning recognizes patterns in data so that predictions can be made once new data arrives. Simply put, machine learning is the practice of training an AI algorithm to make better predictions. ### Deep learning On the other hand, deep learning is a sub-field of machine learning that developed from this field. This is the practice of training an AI algorithm to make human-like decisions. Deep learning's main concept is to replicate the human brain's neural networks with artificial neural networks (ANN). Algorithms are created like in machine learning, but there are a lot more levels of algorithms creating these networks. While machine learning models consist of thousands of data points, deep learning engages with Big Data, millions of data points. Despite their differences, their relationship is important. Machine learning is an evolution of artificial intelligence, while deep learning is an evolution of machine learning. ## History of Artificial Intelligence While artificial intelligence has been booming in the last decade, the second half of the 20th century is arguably one of the most important times in AI history. One could argue its history began as far back as 250 BC with Ctesibius' water clock, but we'll keep it simple by starting in the 1950s. ### 1950s: Term AI coined & first programs Known as the father of computer science, Alan Turing published Computing Machinery and Intelligence in 1950. He proposed his answer to the great question "can machines think?" through the Turing Test. Later on, John McCarthy coined the term at the first AI conference at Dartmouth College in 1965. That same year, a computer program called Logic Theorist was released, written by Newel, Simon, and Shaw. Known as the first AI program, it was the first of its kind to perform automated reasoning. In 1957, machine learning arose. Known as the Perceptron, the first computer based on a neural network that learns through trial and error was developed by Frank Rosenblatt. In 1958, the man who coined the term AI, John McCarthy developed the programming language Lisp. At the time, it became the most used language for artificial intelligence research. ### 1960s: First industrial robot & first chatbox In 1961, the Unimate was the world's first industrial robot used in a General Motors plant in New Jersey. A hydraulic manipulator arm, Unimate could perform repetitive tasks and helped automate the operation of machinery. In 1965, Joseph Weizenbaum developed ELIZA at the MIT Artificial Intelligence Laboratory, a natural language processing computer program that resembles today's chatbots. He wanted to show the superficiality of communication between human and machine, but many saw human-like characteristics in ELIZA. ### 1970s - 1980s: AI Winters The 1970s saw a dark time for IA research. In 1973, James Lighthill's report to the British Science Research Council criticized the lack of progress in AI research. This led the government to reduce its support for artificial intelligence research and corporations soon followed. The period from 1974 to 1980 is known as the first "AI Winter" where there was little research and progress. Starting in the early 1980s, AI research was back, primarily on deep learning techniques and Feigenbaum's expert systems. However, this didn't last long, as the second AI winter fastly arrived and lasted until the mid-1990s. ### Late 1990s until today The late 1990s then paved the way to AI as we know it. An increase in computational power and data sparked an AI boom that is still present today. In 1997, IBM's Deep Blue, a chess computer, beat then world champion Garry Kasparov in a match. That same year, Jürgen Schmidhuber and Sepp Hochreiter released Long Short-Term Memory, a type of recurrent neural network that is used today in speech recognition. Throughout the 2000s, more advancements are made. In 2009, Google starts developing a driverless car, and in 2011, Siri became available. Perhaps one of the largest events happened in 2016 when Hanson Robotics showcased Sophia, a humanoid AI robot. ## What Are the Applications of AI? The applications of AI are endless. Artificial intelligence can be applied to every sector, throughout both industry and academia. Here are 7 applications of artificial intelligence seen today. ### Financial institutions AI has become a large part of the mainstream finance and banking industry. A majority of financial service companies say they have implemented AI in risk management (56%) and revenue generation (52%), reports Insider. Financial institutions, particularly banks, use AI to enhance the customer experience through 24/7 customer service options, improve digital banking, and more. Fraud prevention is an integral piece of the pie, with machine learning being used to detect fraudulent transactions. Moreover, algorithmic trading has been developed. This involves using AI systems to make trading decisions at speeds unthinkable to humans. Banks and funds own entire portfolios that are managed by AI and generate high-frequency trading. ### Science The field of science is vast and one that artificial intelligence can be widely applied. In the field of chemistry, machine learning AI has been used for drug design in predicting molecular properties and observing chemical reactions. Machine learning has been used for drug discovery and development, as well as improving clinical trials. AI is also highly applicable to astronomy. From forecasting solar activity to activities to space exploration and more, astronomists are already using this technology. ### Healthcare AI has the potential to improve the efficiency and quality of healthcare globally. Artificial intelligence is used today for evaluating exams such as CT scans, selecting the right treatments, and performing surgeries with robots. However, there is still a lot of progress to be implemented. In 2016, a study found that an AI formula chose the correct dose of drugs to give to transplant patients, improving the efficiency of this human process. There are tons of other tasks being developed for AI, such as analyzing genes, outcome predictions for surgeries, and treatment plan designs. ### Virtual Assistance A common application of AI seen today is virtual assistants such as Siri or Alexa. While its development began earlier on, in the 1990s, digital speech recognition became a feature of the computer. However, the first modern virtual assistant is known as Siri, who was first introduced with the iPhone 4s in 2011. Currently, there are over 4 billion voice assistants in use globally. Using machine learning and natural language processing, these virtual assistants match user text or voice input to execute actions. Whether it's a restaurant recommendation or the weather, AI is now at everyone's fingertips. Virtual assistance powered by artificial intelligence has also empowered disabled users, changing the accessibility game in the last decade. For example, smart home technology developed in recent years has hugely benefited those with limited mobility. ### Autonomous Vehicles Self driving vehicles were once a thing of sci-fi movies. Artificial intelligence has made these a reality and more widely accessible. This technology is already in use in not only private vehicles, but also public transportation and ride-sharing. Driverless vehicles are able to identify objects, interpret scenarios, and make safe decisions through a machine-learning algorithm. However, an AI vehicle does not necessarily need to be self driving. The installation of AI-based systems in new vehicles is expected to rise by 109% in 2025, compared to an 8% rate in 2015. This includes vehicles with speech and gesture recognition, eye tracking, virtual assistance, and more. ### E-Commerce Artificial intelligence technology is regularly applied to the e-commerce industry. AI is used to create recommendation engines that suggest products to customers in line with their browsing history. Within a website, AI-powered virtual shopping assistants and chatbots improve the user experience. While not always achieved, natural language processing is employed to keep conversations sounding personal and natural. AI can also help avoid credit card fraud, identify fake reviews, and much more. ### Hospitality The hospitality industry is increasingly using artificial intelligence to carry out tasks. One example is in-person customer service using AI robots. Hilton has used the Connie robot to provide guests with information, learn from these interactions, and adapt to each individual. Chatbots are also being used, allowing guests to get almost instant responses to their queries 24/7. Hotel staff would be unable to respond at such speed. However, not all applications of AI in the hospitality industry are geared toward customer service. The hospitality industry uses AI for data analysis to draw conclusions about guests and potential customers. The Dorchester Collection use Metis AI to sort through data collected through surveys and reviews to find out about their performance. ## Final Thoughts Artificial intelligence has changed how we collect, analyze, and make complex decisions according to data. Currently, data makes the world go round. The progress made in artificial intelligence is bound to keep taking the tech industry by storm, as well as all its other applicable industries. From drug and molecular research to finance, AI's vast applications show us that AI is here to stay and grow even further. The industry value of artificial intelligence is forecasted to increase by over 13x over the next eight years, making it one of the fastest-growing industries in the world. Everyone wants to cash in on AI's benefits. AI can tackle tasks that are dangerous to humans, work more efficiently and without error, as well as automate the most repetitive tasks, making it valuable to profit-making. However, it's important to consider gender and racial bias, unemployment rise, and AI's inability to be creative. Considering the latter, the human mind will always be valuable and irreplaceable. A machine cannot think outside the box. It cannot innovate and create freely by expressing emotions, thoughts, and feelings. That is if AI never reaches its Nirvana - self-awareness. But if that's ever the case, we will have bigger fish to fry than creativity.

Earlier this year, a curious event took place. At the famed Glastonbury music festival, concertgoers were presented with an unexpected duet between Sir Paul McCartney and John Lennon of the track 'I've Got A Feeling' as part of a stunning three-hour set that also honored the legacy of the Beatles. But hold up, you might be thinking. Was it the same and legendary John Lennon that was so shockingly assassinated in 1980? How could he possibly be taking to the stage - or any stage for that matter - of an English festival 42 years on? Well, we have artificial intelligence and Peter Jackson, yes, the same director behind the Lord of the Rings trilogy, to thank for this beyond the grave apparition. Jackson has lifted the veil on the technology involved to put together the performance, explaining that his team had developed a machine learning system that was taught what guitar, bass and singing sounds. More specifically, this custom-made AI was trained to learn how to sing like Sir Paul McCartney and John Lennon, thus being able to recreate virtual presences that are as realistic as possible. AI music is bringing other legendary singers back to life. As part of the “Lost Tapes of the 27 Club '', an initiative led by Canada-based mental health charity Over the Bridge, a collective of performers who’ve died at the age of 27 “released” novel tracks made entirely by Google’s AI program Mangenta. Amy Winehouse, Kurt Cobain, and Jimi Hendrix are some of the artists covered by the project, with the lyrics and recorded music being entirely authored by AI. ## How Is AI Music Created And the process of creating this new type of AI music is seemingly straightforward; all users have to do is feed a singer’s existing music into a bot that relies on machine learning to detect patterns and produce new music back on the pre-existing catalog. The same technology was used to create three lines of voiceover by the late celebrity chef Antony Bourdain for the Roadrunner: A Film About Anthony Bourdain documentary, directed by Morgan Neville. Want to listen to a podcast interview between Joe Rogan and Steve Jobs? That’s possible, too. And it doesn’t matter that they’ve never met or that the Apple founder has been dead for over a decade. Elsewhere, artificial intelligence is also powering audio deepfakes, also known as voice cloning or synthetic voicing, whereby AI models are fed with training data. Typically, this information includes original recording and voice samples from a target person, who’s speaking or singing, for example. Based on this data set, AI is able to render an authentic sounding track that can be used to “speak” anything that is typed or said. This is known as text-to-speech or speech-to-speech. Artificial intelligence technology has advanced to the point that it can replicate a human voice with an astonishing high level of accuracy. Does this sound a little sci-fi-ish? It’s understandable, but perhaps you’ll change your mind after watching the now-infamous This is not Morgan Freeman video. For some of us, however, this is old news as many will have come across deeptomcruise, a wildly popular TikTok account filled with plenty of Tom-Cruise-like content created entirely by AI. The movie star has no association with it, despite the unsuspecting viewer probably being none the wiser. ## What AI Tools Are Being Used To Make Music Applying language processing and speech recognition in entertainment and music hasn’t been without controversy, with many raising eyebrows and highlighting ethical concerns. Many detractors even question whether AI music can be considered a form of art and if it will ever be put side by side with the world's greatest masterpieces. No matter where you stand on the debate, there’s no doubt that technology is aiding the creative process of many artists. Currently, AI tools can seamlessly create music entirely from scratch, including original lyrics, instrumentation and music composition. In fact, so-called songwriting AI companions like Jarvis and Jukebox are an increasingly popular resource for many aspiring musicians who generally lack access to more complex (read expensive) music creation tools. Developed by OpenAI, Jukebox has become a household name, providing artists, lyrics and genres to generate original music samples from scratch. Some of the music styles considered by its AI neural network include a close approximation to renowned artists such as Celine Dion, Kanye West, and Tupac. And while this sounds quite futuristic, technological tools of the sort have been around for quite a while. David Bowie, for example, helped create in the 1990’s a lyric-writing software called Verbasizer that worked as a sentence randomizer, aiding in the creation of lyrics. The more recent potential of an AI music tool and a new type of AI-based song making hasn’t gone unnoticed in the music industry, by record companies and, of course, music streaming services. No, I am not referring to the AI-powered algorithm that helps you find the next favorite music banger and curate Spotify playlists. How about listening to music streams created entirely by AI and that can perfectly adapt to your mood? That’s the premise behind AI generative music streaming offerings such as Mubert. You might be surprised, or at least intrigued, at the idea of shuffling through melodies that are unpredictable, adaptive, unique and impossible to ever be repeated. But that’s exactly what you get with generative AI. AI-powered music leverages deep learning algorithms, neural networks s and other artificial intelligence tools to allow music to better adapt to the preference of users as much as it also lets them step into the creative process to co-exist and co-produce, so you don’t have to feel let out or that you’re just a mere consumer. For users there’s also a major upside of resorting to a generative source as they don’t have to worry about headache-inducing problems such as copyright and licensing when trying to use something as a simple background music for, say, a YouTube vlog or content for social media platforms. This is an approach now also being favored by the film industry where scouring through music libraries to find music can prove to be both time consuming and a legal, and financial hurdle. That led composers Drew Silverstein, Sam Estes, and Michael Hobe, known for working on music for big-budget movies like The Dark Knight and Inception, to launch an AI-powered music platform - Amper Music. The AI music company provides extensive original music creation tools for creators, video and podcast producers, video game designers, and more. Again, this goes to show how AI and advancements in computer science are democratizing access and distribution well beyond the platforms currently available. ## Generative Music And the Beginnings of AI DJs The technology has become so sophisticated and talented that it inspired the creation of the AI Song Contest, a Eurovision-style contest showcasing the best musical productions created by humans with the aid of AI. And while all of this already seems lofty enough, the promise held by this musical revolution is reaching yet a new high with the emergence of AI DJs. That’s right, your next favorite performer might be a virtual being that also happens to be a gifted musician. As we’ve seen before, AI music bots can compose and churn out entire creations of their own based on the information they’re being fed. However, artificial intelligence virtual artists take it a step further, by not only delivering original music but doing it so with the sense of presence and interaction as a human performer. Or at least that is the premise of the first breed of such musicians. Kàra Màr, an AI DJ developed by Sensorium, has made history after becoming the first of the kind to release an entire album on Spotify, titled “Anthropic Principle”. They’re part of a larger lineup of virtual AI musicians, including Natisa Sitar and Ninalis, that are currently performing 24/7 as part of Sensorium Galaxy’s metaverse streaming service. Unlike the generic version of an avatar, like the ones we’ve all come across online, Sensorium AI DJs are equipped with artificial intelligence technology that allows them to both deliver mind-blowing concerts but also interact with fans in a compelling way. Each virtual being is fitted with a unique personality and background, as well as long-term memory. In other words, they will remember you and whatever past interactions you had. And as a bonus, they’re always available for a chat. ## What Next? Now that we’ve gotten this far, one of the most frequently uttered questions is whether artificial intelligence will - or is bound to - replace human artists. Having automated systems that can imitate and remix human expression might not be enough to simply overtake the power of a live performance and the sheer magic of human creativity and artistry. And we're still a long way from seeing artificial intelligence and music delivering hit songs and winning Grammys, no matter how advanced the technology seems to be today. On the other hand, the use of the technology is already paving the way for profound changes in the music industry. It's been challenging the way licensed music is dealt with, music generators are re-imagining lyric creation and AI DJs are introducing the world to an entirely new music genre. Perhaps, then, it’s fair to say that AI music is a valuable tool for collaboration more than a Terminator-like technology that will erase and replace our favorite artists.

From virtual goods to burgeoning new digital worlds, technology is again pushing the boundaries of human experience into unchartered territory. Many of us have recently faced a deluge of buzzwords like Web 3.0, blockchain, cryptocurrencies and, of course, the metaverse. And while much of it might seem incomprehensible for now, they’re not to be discarded as another tech fad. In particular, the recent progress in the field of artificial intelligence is opening up new opportunities that are sure to greatly impact human experience in the upcoming era of virtual worlds, also known as the metaverse. While in the past, AI helped machines carry out routine manual tasks, the technology can now also perform certain cognitive work thanks to its ability to learn, improve through experience and ultimately mimic human behaviors. Not only that, but the rapid expansion of cheap and powerful computing power has seen the massive digitalization of world objects and processes. More recently, humans themselves are being digitized in the form of virtual avatars. And artificial intelligence is giving a new meaning to the creation of virtual people by pushing the boundaries of technology to yet again a new frontier - AI lifeforms. AI-powered avatars can serve endless purposes, from being hired out by real-world companies to teach new employees, to serving as trusted confidantes in the metaverse, to name just a few use cases. Emerging virtual worlds, and their profitable economies, already encompass some 2.5 billion people, according to market research company L'Atelier. Moving forward, the world will only become more virtual and humans are increasingly going to live in the metaverse, side by side with AI-driven virtual beings. With that in mind, we’ll be having a closer look at what sharing our online experiences with artificial intelligent avatars will look like and how it could change the world as we know it.

Play-To-Earn gaming is all the rage now. Unlike traditional gaming, P2E brings real money and rewards into play, marking a departure from the business model that dominated the gaming industry for decades. From Splinterlands to Axie Infinity, players are rushing to games that can fulfill their entertainment needs while providing clear monetization paths in return for the time and effort they’ve put in. Last week, we put together a quick intro to Play to Earn, but here’s a recap icymi: P2E gaming relies on blockchain, meaning that through this technology players are able to buy, sell or exchange in the form of non-fungible tokens (NFTs). This way, not only do they have control over their transactions every step of the way, players are even more crucially able to to retain ownership of the digital assets they’ve collected during the course of their gaming experience within a title. From there, players can choose to take those items outside of the game and exchange them across other marketplaces and trading platforms, in return for digital currencies (cryptocurrencies) or fiat money. In short, in-game items have real world value. There are plenty of monetization opportunities within P2E. A player can, for example, purchase an NFT, upgrade it and then resell it for a higher price. Play to earn games are also highly attractive given the opportunities to get rewarded for activities completed within the game, like quests or duels. The impact of P2E is accelerating profound changes in the gaming industry, with more than half of American and UK-based video game developers now saying they’re starting to implement blockchain technology and the use of NFTs in their titles, according to a recent survey.

The gaming industry has come a long way. From clunky consoles, quirky cartridges and simplistic games (Super Mario Bros, anyone?) to an entertainment outlet worth over $170 billion, powered by more than 2.7 billion players worldwide. Nowadays, gaming is an all-consuming experience, built on top of ultra-realistic animations, full of twists and turns throughout what seems like an endless stream of entertainment content. There's seemingly nothing out of bounds when it comes to the possibilities of gaming. From personalizing avatars to customizing environments, purchasing tools and setting up tournaments, gamers are showered with all kinds of options to enhance the time spent in virtual worlds. But we've gone beyond the choosing of color palettes and skins; user preferences are changing the foundations of gaming. Instead of the linear experiences of the past, gaming is increasingly an open-ended experience. This is evident by the success of sandbox titles like Minecraft, drawing in players with infinite playable loops that can take shape in the form of challenges and competitions, for example. The more players engage, the greater their status in the community and bigger the incentive to engage with other users. And how to better enhance this experience than by letting players create and exchange (or even sell) their own content. All of this opens the doors to a gaming experience without limits. Take Roblox or Fortnite, two games also seeing a meteoric rise on the back of user-generated content (UGC). However, the majority of gaming experiences remain trapped in traditional, centralized models. This means that developers and gaming companies hold the most power within the ecosystem. Even when users come up with their original content, its value is entirely tied to the gaming dynamics set by developers. That's because games are provided to users on a licensing basis, meaning that they’re free to play and be enjoyed, but in the end users don’t own any in-platform assets. Think of it like renting a house but not being the owner; gamers are simply renting games. Players can be subjected to unexpected or arbitrary decisions that limit their possibilities, from the worth of their creations to the number of units that can be sold or exchanged in a marketplace. Ultimately, centralized gaming models don't favor players - and certainly fail to reward the most loyal ones, despite them spending more time online.

Online gaming just keeps on getting bigger. In fact, gaming is now even larger than Hollywood and the music industry combined, bringing in a whopping $180BN in revenue globally in 2021. Not only that, but it’s become increasingly popular across all demographic groups, ages and geographies, with hundreds of millions of players spending more time engaged in play and re-defining it not just as a hobby but also as a social and commercial activity. High-flying titles are now topping big blockbusters, fueling another rising subset of this growing industry- esports. Meanwhile, the global esports market is projected to reach $9.6 billion by 2030, up from a current addressable market of $1.38 billion (as per Barclay’s). In the midst of this boom, esports leaders are taking note of the metaverse and the great potential arising from transitioning into virtual worlds. ## What Is Esports? Esports, also known as electronic sports, refer to professional competitive gaming based on video games. The esports industry estimated a worldwide audience of 215 million, with the number of enthusiasts expected to surpass 300 million by 2025. In 2021, nearly 74 million people watched Riot Games’ League of Legends world championships, breaking all kinds of viewership records. So, how did we get here? eSports originated in the early 1970s with the "Intergalactic Spacewar Olympics," the first-ever gaming tournament held at Stanford University's Artificial Intelligence Laboratory. The winner was awarded a year's subscription to Rolling Stone magazine. In 1980, video game developer Atari organized the Space Invaders Championship, the first large-scale electronic sports competition, with approximately 10,000 participants from all over the United States. And in 1990, the Nintendo World Championships kicked off, touring dozens of U.S. cities. The most recent edition of the series took place in 2017. The number of competitions saw a boom particularly between 2000 and 2010, during which some of the leading tournaments were established, including Intel Extreme Masters, World Cyber Games, and Major League Gaming. It was during this time that the first international esports organization, G7, was founded. It gathers teams from the United Kingdom, United States, Germany and Brazil. Nowadays, playing and watching esports streams is widely accessible. Some of the most popular live streaming platforms include YouTube, Fortnite and Twitch, where fans can engage with titles such as League of Legends, Dota 2 and Counter-Strike. Just as with any sport, esports gathers skilled gamers (sometimes also called athletes) whose talent is on display as they try to beat their opponents during oftentimes intense and lengthy competitions. Professional and amateur esports tournaments have become equally sought-after, helping transform the industry into a multi-billion force to be reckoned with. Currently, Asia and North American remain the largest markets, with China leading the pack.