Virtual Reality on blockchain
Virtual Reality has been around for quite some time now. When I was a kid people spoke about this virtual world. Virtual games. Virtual lives. Early internet portals like Compuserve, Prodigy and AOL made you believe in this future. Even BBS boards and text driven games with monochrome screens made you feel like you were in a different world. Open up your creative Imagination. It was cool and the future. At least we hoped.
The Early games on Commodore 64 and other cloned PC 8088 computers and 300 baud modems were exciting. You were also called a geek and dork by most folks. But Hey when we got a 1200 baud modem, yeah that was awesome.
Playing games and programming in BASIC and turbo Pasal made me dream of being in and buildings worlds like Gauntlet , Ultima III , eye of the beholder , star control 2, wing commander earl weavers baseball , and Pete rose baseball.
Imagine tying to upload and download a large game like Wing commander on dial up back in the day? My friend Dan and I tried to do that. Often. Those were the days.
So what’s any of this have to do with Virtual Reality ?
Creative Imagination to expand the human experience is what power VR and AR holds. Interactive experiences open up an infinite number of imaginary worlds where you are part of the living story. And doing this while never having to leave your own home.
Communicate, collaborate and interact with your long-distance friends and family in ways that were never possible before. We see early successes and awesome possibilities with headsets like oculus and htc vive and Microsoft hololens.
Today, designers , creators and developers can alter a VR or AR experience as per their own interests. It is also important that the developer and players control a huge amount of personal information provided by players. Decentralized Systems and blockchain will be huge for many things going forward , including virtual and augmented reality.
The combination of virtual reality and blockchain can decentralize the future platforms and applications. It changes the dynamic by giving control of the virtual online world back to the players and visitors.
Taking a step back. Virtual reality is more players , visitors and participants. Current and legacy coin terms more like users , watchers , and viewers. An interactive virtual world where Creative Imagination Experiences rule the day is all about visitors, players and participants.
Where are we now ?
There is a second life and Minecraft like virtual world on blockchain now called Decentraland. Visitors and players can buy a plot of virtual land with the platform’s cryptocurrency called ‘MANA’. They can then build anything as per their liking such as a building, house or a virtual neighborhood and then populate it with unique virtual objects.
They can host social events and even turn it into a profitable business if they are forward thinking. The virtual landowners in Decentraland can even monetize their worlds by selling or renting ad space in exchange for MANA.
It’s Early stages now and only works on desktops / laptops and the latency is poor. But it’s still a sign of the ready player One and the matrix future to come.
Taking decentraland virtual world powered by blockchain into consideration, the future value of VR might be more decentralized and open. This might help people understand how crypto actually holds value and can function better in the real world as well. In the virtual world, bitcoin or some other crypto token is governed by incorruptible intelligent smart contracts. As these things improve, many are suspecting a surge of people demanding the exact reality in the real world. People do not want corrupt governments and archaic governance anymore. Coronavirus can further boost this concept because of its social distancing and less contacting measures.
By creating a virtual world that entirely runs on the blockchain, it can help provide a template for ways blockchain functions in the real world. And it just works. Behind the scene. The creative imaginary interactive virtual mixed reality worlds will change the world. For real this time.
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Data is the lifeblood of many organizations, but it can be hard to get your hands on when data protection protocols are in place. With synthetic data you needn’t worry about access time-consuming roadblocks because this new technology bypasses them entirely!
Consider one financial institution with rich streams containing strategic information for decision makers–it was so highly protected that gaining internal use rights was practically impossible without outside help from specialists who knew how break through these security measures
Synthetic data is the answer to all of your problems. It can protect you from a myriad security threats and vulnerabilities by eliminating any chance that hackers might have at accessing company or customer information without consent, while also maintaining privacy for everyone involved in its creation!
What is synthetic data ?
AI-based synthetic data has been used to bring statistical properties and patterns of real world events into a different context.
The goal is reproduce the probability distribution or sampling theorem, but this time with new variables that weren’t present in any previous datasets
Now you can train machine learning and computer vision models faster than ever! With synthetic data, companies are able to quickly create large sets of training examples. This is a huge advantage for those who need access and time on their hands – it’s like having your own personal data set ready at any moment.
The power to analyze large datasets with speed and accuracy, without the need for third party data sets that are prohibitively expensive.
Synthetic data gives companies access to mimicked real world synthetic datasets and images made from high-quality analyzed real world sources at a low cost – enabling them not only see how their business would perform but also make informed decisions about where it needs improvement or success!
Why is it so hard ?
While the benefits of synthetic data are compelling, realizing them can be difficult. Generating synthetic files requires an organization to do more than just plug in AI tools that analyze their own datasets; this complex process needs people with specialized skill sets and understanding about machine learning and deep learning algorithms who have advanced knowledge on how these technologies work together as well specific frameworks tailored for each task at hand.
What’s next ?
Synthetic data is a complex and often tricky area to work in. Organizations should be sure that the value will outweigh any drawbacks before getting involved with it, which can include pitfalls from doing so wrong or having incorrect assumptions when creating synthetic datasets for use within your company’s operations.
Data-driven leaders who want their organization to be successful should make it a priority and never abandon the idea of using data and analytics as an integral part in decision making.
Engineers at the University of Waterloo combined two existing deep-learning AI techniques to identify players by their sweater numbers with 90-per-cent accuracy.
“That is significant because the only major cue you have to identify a particular player in a hockey video is jersey number,” said Kanav Vats, a Ph.D. student in systems design engineering who led the project. “Players on a team otherwise appear very similar because of their helmets and uniforms.”
Player identification is one aspect of a complicated challenge as members of the Vision and Image Processing (VIP) Lab at Waterloo work with industry partner Stathletes Inc. on AI software to analyze player performance and produce other data-driven insights.
The researchers built a data set of more than 54,000 images from National Hockey League games—the largest data set of its kind—and used it to train AI algorithms to recognize sweater numbers in new images.
Accuracy was boosted by representing the number 12, for instance, as both a two-digit number and two single digits, 1 and 2, put together, an approach known in the field of AI as multi-task learning.
“Using different representations to teach the same thing can improve performance,” Vats said. “We combined a wholistic representation and a digit-wise representation with great results.”
The research team is also developing AI to track players in video, locate them on the ice and recognize what they are doing, such as taking a shot or checking an opposing player, for integration in a single system.
Check out some cool artificial intelligence companies in San Diego, including Pagarba Solutions.