Our metaverse will provide a unique 3D virtual reality learning and therapuetic experience that is fully immersive. The following will establish our unique program as the best and to be emulated by using:
artificial intelligence ("AI"),
proprietary 3D VR Robots ("Robots"),
multiple interactive and creative 3D virtual reality ("VR") environments,
automatic language translation software,
HIPAA compliant blockchain data protection,
with Web 3.0 optimization.
Spectruth because truth is special.
Why Virtual Reality?
Virtual Reality offers a unique, multi-sensory and fully immersive learning experience for children throughout all key stages.
We retain 10% of what we read, yet 90% of what we experience. Bringing personal experience into a classroom, and engaging children in new activities not normally possible, holds the potential to truly transform knowledge retention.
What is Artificial Intelligence?
Artificial Intelligence (AI) involves using computers to do things that traditionally require human intelligence. This means creating algorithms to classify, analyze, and draw predictions from data. It also involves acting on data, learning from new data, and improving over time. Just like a tiny human child growing up into a (sometimes) smarter human adult. And like humans, AI is not perfect, yet…
The difference between AI and regular programing? Regular programs define all possible scenarios and only operate within those defined scenarios. AI ‘trains’ a program for a specific task and allows it to explore and improve on its own. A good AI ‘figures out’ what to do when met with unfamiliar situations. Microsoft Word cannot improve on its own, but facial recognition software can get better at recognizing faces the longer it runs.
To apply AI, you need data. Lots of it. AI algorithms are trained using large datasets so that they can identify patterns, make predictions and recommend actions, much like a human would, just faster and better.
We interact with AI every day in our professional and personal lives:
Task automation: repetitive back-office tasks such as clerical work, invoicing, and management reporting can be automated to save time and improve accuracy. Factory and warehouse work can also be automated using AI-powered robots.
Customer support: remember the online text chat you had with your bank’s customer support? That may have been a chatbot instead of an actual human.
Social media: Facebook uses AI to recognize faces. When you upload photos to Facebook, it puts a box around the faces in the photo and suggests friends’ names to tag.
Self-driving cars: Onboard cameras and computers identify objects and people on the road, follow traffic signs, and drive the car. Early models are already safer than human drivers.
Still, even the best AI today cannot match up to the human brain in some respects. While some AI is designed to mimic the human brain, AI today is only good at a relatively narrow range of tasks. AI can apply massive computing power to a narrow set of data and methods. The brain, on the other hand, applies medium computing power to a much wider set of data and methods.
Put differently, we can apply our brains to almost anything, while AI specializes in certain things.
Real-world Applications of Artificial Intelligence: Machine Learning, Deep Learning, Neural Networks, Evolutionary Algorithms
Let’s briefly look at machine learning, deep learning, neural networks, evolutionary algorithms, and some real-world applications. Keep in mind that many real-world applications use more than one AI technology.
Machine learning algorithms identify patterns and/or predict outcomes. Many organizations sit on huge data sets related to customers, business operations, or financials. Human analysts have limited time and brainpower to process and analyze this data. Therefore, machine learning can be used to:
Predict outcomes given input data, like regression analysis but on much larger scales and with multiple variables. A perfect example is algorithmic trading, where the trading model must analyze vast amounts of input data and recommend profitable trades. As the model keeps working with real-world data, it can even ‘improve’ itself and adapt its trading strategies to market conditions.
Find insights or patterns in large data sets that human eyes sometimes miss. For example, a company can study how its customer purchase patterns are evolving and use the findings to modify their product lines.
Do a lot more in less time. Goodbye grunt work.
Many AI methodologies including neural networks, deep learning, and evolutionary algorithms, are related to machine learning.
Neural Networks and Deep Learning
A neural network tries to replicate the human brain’s approach to analyzing data. They can identify, classify and analyze diverse data, deal with many variables, and find patterns that are too complex for human brains to see.
Deep learning is a subset of machine learning. When applied to a neural network, it allows the network to learn without human supervision from unstructured data (data that isn’t classified or labeled). This is perfect for analyzing ‘big data’ that organizations collect. These big data sets include different data formats such as text, images, video and sound.
Neural networks are frequently combined with machine learning, deep learning, and computer vision (training computers to derive meaning from pictures). That’s why people talk about ‘deep neural networks,’ which is basically a neural network with more than 2 layers. More layers = more analytical power.
Deep neural networks can be trained to identify and classify objects. A cool use is facial recognition — identifying unique faces in photos and videos. Neural networks also learn over time. For instance, they get better at classifying objects and identifying faces as they are fed more data.
A subset of machine learning, evolutionary algorithms self-improve over time. They create a population of algorithms and preserve the ones most successful at predicting outcomes. Applying the ‘survival of the fittest’ principle, the best algorithms are kept alive and the losers are discarded. Sections of code from the winning algorithms are used to create a new population of algorithms, and the selection process repeats.
Evolutionary algorithms are well suited to optimization tasks where there are a lot of variables and a dynamic environment. Basically: find a way to the best possible result.
AI and Spectruth’s metaverse
The Learning Center will host the Academy and the Clinic. Both will rely heavily on AI with human oversight.
The Academy will use an AI virtual Robot to tutor and provide learning games to help students assimilate quickly. Professional educators will create chatbots that answer almost all questions virtually. By using chatbots to eliminate the majority of time-consuming and common questions, the human educators can focus their attention on one-on-one precision teaching so ensure no child is left behind in the curriculum.
The Clinic will use AI to help diagnostic testing, therapy recommendations, training recommendations, and chatbots. Professional Board Certified Behavior Analysts (“BCBA”) will develop and oversee online testing to help users quickly identify if they are likely to have any behavioral disorders like autism. If yes, then the therapists will arrange for one-on-one virtual meetings to discuss results, further testing, and therapy treatments. The BCBAs will establish common treatment programs will be established and administered by our AI with common questions answered with chatbots. Using scientific methods and AI with experienced therapists will allow Spectruth to provide the best scientifically therapy efficiently.
Every user becomes oriented with their personal artificial intelligent virtual robot (“Robot”) during their first login. It plays three vital roles within our metaverse: it orients our users to the metaverse’s features, it befriends them, and it provides valuable indirect data for our AI analysis.
The Robot will guide the user on mini quests to introduce key features of the metaverse. It is personalized and upgraded at the Town Hall and designed to befriend our user as it learns the user’s preferences with every interaction.
The data collected indirectly is vital to our metaverse’s ability to help our users.
Every age group will be helped by the Robot:
An person has a guide that never gets frustrated when the they need to repeat quests to become 100% orientated.
A typical teenager will customize their Robot, bring them to their VR classroom, explore the metaverse together, and challenge the Robot to VR games.
Most morally important to Spectruth is the Robot’s potential to provide social enrichment through specific dialogue, quest recommendations, and positive reinforcements. The designers of the Robot have extensive experience working with ABA (Applied Behavior Analysts) professionals.
How to Blockchain Storage Works
Blockchain Date Storage
Once the data is collected, it is customized for effective storage in the blockchain. The data that is stored on the blockchain becomes a time-stamped network of secure logs of data. This is why the blockchain data stored is usually immutable and very safe.
Decentralized Cloud Storage in the Blockchain Age
Decentralized cloud storage has been experiencing remarkable waves in the current blockchain age. To a significant extent, a number of blockchain experts have been developing better techniques for providing cloud and hosting services in the blockchain technology industry.
Advantages of Blockchain Storage
One of the foremost benefits that are associated with the use of blockchain storage is that it is relatively cost-effective when compared to some centralized cloud storage platforms. For instance, common centralized cloud storage platforms like Amazon S3, Google One, and Dropbox offer 1 GB worth of storage space for the price of $0.023, $0.02, and $0.005 per month, respectively.
However, the prices for companies that offer secure storage services through blockchain storage, go for as low as $0.002. This is a significant gap when compared to the amount charged by the centralized cloud storage platforms.
In another sense, the use of blockchain storage nullifies the payment of extra costs for third-parties and intermediaries that are involved in transaction processes of other payment systems outside of the blockchain system.
Another of the advantages of blockchain storage is that it involves zero purchase of any equipment in order for it to function. What’s more, is that no installation of any additional software is needed for it to function effectively.
Since blockchain data is usually stored in a plethora of devices on a distributed chain of nodes, it very resistant to technical malfunction as well as intrusions. Hence, the users do not necessarily have to provide extensive admin resources that will cost extra money.
The effect of this advantage of blockchain storage is because each network node can be duplicated and stored as a copy in the database. This is why there can be no event of a malfunction. In the event of any node going offline or failing, the security and operation of the network will not be affected.
Furthermore, blockchain storage has been developed to be more transparent than other cloud providers. This is because, in traditional payment systems, the transactions that occur in the network are not dependent on only the parties involved, but also include an intermediary.
The intermediary there could be a credit card company, a bank, or any payment provider. However, this is not the case in blockchain technology. Transparency is ensured through the distributed network of nodes that carry out the verification of transactions through “mining”.
This is regarded as one of the most essential and indispensable advantages of blockchain storage. First of all, the transactions that take place in the blockchain system are immutable because thanks to the absence of a single central authority, no individual or group can take away or corrupt your files.
In addition, this also means you cannot be restricted to access your files, and no authority can make adjustments to your transactions or files in the name of censorship. The verification of your files is made possible since your file’s hashes are stored in the electronic ledger.
Transactions in the blockchain storage are tamper-free, because verified transactions are almost impossible to be altered. The implication of this is that the moment a data log has been stored into the blockchain, it becomes largely impossible to make amendments.
In fact, every alteration in the blockchain transactions is tracked and recorded on a distributed and public ledger and this makes blockchain storage a perfect option for keeping records of any form of financial transactions that requires audit management.
When compared to other forms of traditional cloud storage platforms such as Amazon or Google Drive, one of the advantages of blockchain storage is that it is more available to users and features the least fault tolerance.
Security is, without a doubt, the basis of blockchain storage. The retention and transmission of data are more secure with blockchain-based decentralized cloud storage. This is because the encryption of files is done with private keys.
Therefore, anyone without the key would be unable to access the file. The files are segmented into bits and stored on numerous nodes so that a single point of malfunction does not render the system susceptible to infiltration.
The benefit of blockchain storage in terms of securing your files, is that you are able to recover your files, even if a particular node should malfunction. This is the opposite in centralized storage where you would most likely lose your files, if a failure in the system occurs.
What is Web 3.0?
There has not been a consensus for the definition of web 3.0; however, the vision is clear. Developers are marketing Web 3.0 as if it will be a complete reinvention of the web. Web 3.0 can be likened to an artificial intelligence assistant that understands its users and personalizes everything.
Web 1.0 was when the internet could have been compared to a library of information stored as vast walls of texts that were read only. (Wikipedia as an example)
Web 2.0 is the natural evolution of Web 1.0 by allowing user interaction with dynamic websites that act more as applications than simple pages of information. (Amazong as an example)
Our contribution to Web 3.0 occurs when our AI engine provides search results using our user's natural language combined with data acquired through cookies and analyzed using our artificial intelligent software.
For example, a grandmother of a low-functioning, six-year-old boy diagnosed on the autism spectrum would be able to type "teach tying shoes" and our AI would analyze her search result history and add the tags "boy", "low-functioning", "ASD", "English" to ensure she recieves the best recommended program and treatments.