Qubik

About Qubik

Our Mission, Our Goals, and Niches:

Our Mission:

Is built into Qubik, that is the power of Intelligent Solutions. Intelligent Solutions are the exact/perfect answers to problem/puzzles. Qubik strives to apply its technologies across various domains by mapping one puzzle and its solution to another (like AI training/machine learning using Qubik Intelligent Solutions). We believe Qubik Technologies can tackle/map critical challenges like: Efficient Route Planning, Advanced Battery/Power Technologies, Faster Protein Folding, Faster DNA Sequencing, Cancer Cures, Lifesaving Drugs, and Better/Longer Lives.

Our Goals:

Is enabling our customers to solve real-world problems using Qubik.

Niches:

Qubik uses Intelligent Solutions with 100% accuracy built in, it uses Qubik technologies to quickly and efficiently access and utilize Huge Data, that is it uses much more puzzles (data) than the number of bits on every data storage device in the world added together. Qubik datasets contain exact ordered solutions to complete spectrums of puzzles, based on the minimum number of moves to solve them. Replicating the quality and quantity of the data at any cost using other technologies is currently impossible. AI (Artificial Intelligence) benefit from both Huge Data and knowing the corresponding best solutions. Qubik Technologies can accelerate guided or autonomous Machine Learning (ML) with perfect and unbiased data. AI (Artificial Intelligence) may find errors/flaws in its algorithms that may have been impossible to find using smaller or more nuanced data. Ultimately using Qubik should result in better more accurate/safer AI (Artificial Intelligence) that can apply the logic it has learned across different domains and situations. We also strive to make the world a better place by creating a framework to solve puzzles/problems better, faster and more efficiently than any existing technologies, including AI (Artificial Intelligence), Supercomputers, and Quantum Computers while using a very small fraction of the resources, processing power, disk-space, and energy.

Frequently Asked Questions

Please reach out and contact us, if you cannot find the answers to all of your questions.

What is the expertise of Qubik?

Qubik has a diverse range of expertise in fields such as AI (Artificial Intelligence) including AGI (Artificial General Intelligence) and ASI (Artificial Super Intelligence) Testing, Benchmarking and Training using Puzzle Technologies (PATENT PENDING: 18/676,001) Similar to the Rubik's Cube but with a new spin and other new technologies found nowhere else. Qubik can also boast of Exact Perfect Unbiased Data, the Fastest Search Algorithm, Huge Data Technologies, the Largest Databases in the world, Extreme Efficiency and solving problems that AI (Artificial Intelligence), Supercomputers and Quantum Computers Can't.

What can Qubik do that Improves AI Testing?

Qubik Can Test, Train and Benchmark your AI (Artificial Intelligence), Including AGI (Artificial General Intelligence) and ASI (Artificial Superintelligence) with perfect, bountiful and unbiased training data and perfect solutions. With Qubik you can know in real time when your AI makes less than a perfect move. Benefits include accelerated training, and the ability to measure and track any improvement or degradation in performance.

What can Qubik do that Improves AI?

Having the luxury of vast amounts of perfect data (puzzle patterns and perfect solutions) with the ability to easily measure and increase the difficulty of the puzzles, not only makes it much easier to measure how well an AI is improving (or degrading), but it may also be used to more easily find possible gaps/problems in AI Algorithms; Qubik technology allows problems to be identified that likely would not be possible using any other types of datasets or technologies, ultimately fixing these issues lead to better and more reliable/safer AI while using a small fraction of the energy and resources used with other technologies and finally, an AI that can solve advanced puzzles is more likely to solve advanced problems including finding and creating novel scientific discoveries and solutions.

What are recommended guidelines/strategies to Train/Test with Qubik for better and more accurate/safer AI?

1. Clear Objectives and Strategies:

Qubik puzzles/tests are designed with objective, measurable goals, and correct answers built-in from the start; answers can quickly be checked/verified. Complexity can be scaled from solving simple one-move puzzles to predicting intricate patterns, for example asking for the pattern for the Puzzle Number 10,303,738 within the 38 Move Spectrum (Note: this question would be much easier, if it had just solved the prior puzzle number from the same move spectrum). Ideally you can structure and restructure different test and different combinations of test/puzzles to learn how your AI algorithm learns/performs best while being able to identify gaps in learning that may have been much harder to find with nonstructured, much more nuanced, or a far smaller domain of testing data. Know your AI limitations, remember that many questions that can easily be answered by Qubik may even be very hard or impossible for quantum computers or supercomputers to answer with other currently known technologies.

2. Safety First:

Introduce AI to complex real-world problems only after it has proven its learning and problem-solving abilities in structured safe environments. Struggles in structured settings likely indicate greater challenges with real-world variables.

3. Incremental Difficulty:

Start with simple problems to establish a baseline for AI capabilities, then progressively introduce more complex tasks to expand its problem-solving skills.

4. Transfer Learning:

Structure tests to encourage AI to apply knowledge from one task to related tasks, demonstrating adaptability and learning efficiency.

5. Transparent Evaluation Metrics:

Employ objective benchmarks for accuracy and speed to consistently measure AI performance across various builds.

6. Continuous Learning Monitoring:

Track AI performance over time to ensure ongoing learning and improvement from new data and experiences.

7. Reproducibility:

Maintain training and testing conditions that can be replicated for result verification and peer review.

8. Ethical Considerations:

Prioritize issues like privacy, fairness, and consent in data collection for AI training/testing. Qubik only uses its own proprietary perfect unbiased data for both training and testing, making it ideal for ethical AI training and testing.

9. Efficiency:

Qubik’s real-time feedback is available at every move, and solutions to puzzles during any stage of the game can be made available in real-time to facilitate even faster AI training, also a very fast database algorithm can retrieve any puzzle/pattern in less than 1/100th of a second from greater than 32 Decillion (32 X10^33) puzzle patterns, while only using the energy and resources of one server.

10. Sufficient Training and Testing Data:

Qubik Datasets not only have more data than all the data on all the HDDs (Hard Disk Drives) in every datacenter, but it has more data than what is on all HDDs in the world combined.

Question From Perplexity.AI: "How does Qubik's technology handle real-time processing of extremely large datasets?" (And it's Summary of it's reason for the question and my answer)

From: https://Perplexity.AI

This question is particularly relevant because:

1. Qubik claims to have capabilities for handling "Huge Data" that exceeds the total storage capacity of all devices in the world.

2. They state they can provide real-time feedback at every move during puzzle solving.

3. Qubik mentions having a very fast database algorithm that can retrieve any puzzle/pattern in less than 1/100th of a second from over 32 Decillion patterns.

4. Real-time processing of massive datasets is a significant challenge in big data and AI applications.

5. Understanding how Qubik achieves real-time processing with such large datasets could provide insights into their unique technological approach and potential advantages over conventional systems.

This question directly addresses one of the key claims of Qubik's technology while also touching on a critical aspect of big data processing that is relevant to many AI and machine learning applications.

Citations:

[1] https://www.sigarch.org/putting-qubits-to-work-quantum-memory-management/

[2] https://qubik.ai

[3] https://burnqubic.com/about-qubic/

[4] https://eitca.org/artificial-intelligence/eitc-ai-gcml-google-cloud-machine-learning/advancing-in-machine-learning/gcp-bigquery-and-open-datasets/what-are-the-limitations-in-working-with-large-datasets-in-machine-learning/

[5] https://www.classiq.io/docs/constraints

[6] https://isg-one.com/articles/quantum-computing-and-the-future-of-big-data

[7] https://globalventuring.com/university/cracking-the-quantum-puzzle/

[8] https://github.com/qubic-li/client

My Answer Summarized by Perplexity.AI:

Qubik's approach to real-time processing of extremely large datasets is quite innovative. Here's how their technology handles this challenge:

## Fast Data Retrieval

Qubik's system can retrieve any specific puzzle or pattern from their vast database of over 32 Decillion (32 x 10^33) puzzle patterns in less than 1/100th of a second. This incredibly fast retrieval speed is crucial for real-time processing.

## Focused Processing

Instead of processing the entire dataset simultaneously, Qubik's system allows the AI or user to select a single puzzle to work on. This focused approach significantly reduces the computational load and enables real-time interaction.

## Local Processing

Once a puzzle is selected, it's downloaded to the user's or AI's local computer. This transfer of a single puzzle, rather than the entire dataset, allows for efficient use of network resources and enables real-time interaction on the local machine.

## Real-Time Feedback

The local software provides immediate feedback as the user or AI attempts to solve the puzzle. If real-time help is enabled, the system can instantly evaluate each move:

- A success beep indicates an optimal move

- A fail beep signals a less-than-optimal move

## Efficient Evaluation

This real-time evaluation is possible because Qubik's dataset contains exact ordered solutions for each puzzle, based on the minimum number of moves required. This pre-computed information allows for instant comparison of the user's or AI's moves against the optimal solution.

By combining ultra-fast data retrieval, focused puzzle selection, local processing, and pre-computed optimal solutions, Qubik's technology can provide real-time interaction and feedback even when working with an extremely large underlying dataset. This approach effectively manages the challenges of processing massive datasets in real-time by narrowing the focus to a single, relevant puzzle at a time.

Citations:

[1] https://qubik.ai

[2] https://www.youtube.com/watch?v=rS22HYrKIEY

[3] https://qubic.org/blog-detail/deep-dive-into-qubic-s-next-revolutionary-ai-training-algorithm

[4] https://docs.qubic.org/learn/upow/

[5] https://www.youtube.com/watch?v=vK9XjwmseSk

[6] https://iq.wiki/wiki/qubic/

[7] https://www.gate.io/learn/articles/what-is-qubic-qubic/3390

[8] https://www.classiq.io/docs/constraints