Home/Beyond/Title: Building Super Cars in a World Asking for Faster Horses

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Imagine you are in the early 20th century, surrounded by horse-drawn carriages. Amidst the clatter of hooves, Henry Ford is credited with famously saying, “If I had asked people what they wanted, they would have said faster horses.” This visionary quote captures the innovative spirit required to transcend traditional boundaries.

At MindAptiv, we find ourselves in a similar position. The world clamors for “faster horses” in the form of more efficient software, more powerful coding languages, more complex code libraries, and AI that mimics what coders do. But like Ford, we see beyond the current paradigm. We are not here to make faster horses; we are here to build automobiles, or in our case, wantware powered by Meaning Coordinates.

The Essence of Wantware

MindAptiv is not a software company; we are a Wantware company. Our mission is to bypass the constraints of programming languages entirely. Instead of writing lines of code, we use Meaning Coordinates to translate human intent directly into machine-level instructions. This approach is not about enhancing the old; it’s about inventing the new.

The Pitfall of AI-Generated Code

In the current landscape, there is a growing trend to use AI to generate code that mimics what human coders do. While this can speed up development, it fundamentally misses the mark. This approach still relies on traditional coding paradigms without addressing the root issue: the lack of a meaning representation system. AI-generated code may be faster, but it perpetuates the same limitations and vulnerabilities inherent in conventional software development. It’s like asking an AI to build faster horses instead of designing automobiles.

The Reality of Current Expectations

Despite publishing a large amount of information about wantware—because there is no other source for it—we often are asked to create an app. Sometimes the request reflects an expectation that we will produce software from code or quickly make a product with our technology. The former implies that we will use coders, and the latter suggests that we can use our platform before it is ready to generate machine code.

We are neither a software company that writes code nor are we able to generate machine code until we are ready. “Ready” means we are generating machine code for CPUs, GPUs, storage, memory, I/O, network packets, data models, algorithms (AI, encryption, etc.), and more—all from natural language. To all comers, we are writing software for the purpose of generating machine code. We are only packaging existing code with Meaning Coordinates so that it is better code or generating machine code because that’s what a wantware company does.

Asking us to stop what we are doing and just make software from code is like asking Henry Ford to make a buggy because his auto assembly line needs a repair.

Generating and Optimizing Code

Despite the fact that we can and do generate code in programming languages (read about Chameleon on our website), our goal is not to mimic what coders do. Typically, coders do not write optimal code. That requires iterations that most coders lack the time, patience, and skills to achieve. Instead, Essence automatically optimizes machine code by performing the following:

• Scalability & Simplicity: Simplifies scaling and operation, reducing the need for extensive software and hardware networking technology.
• Task Management: Manages tasks via independent worker threads that schedule and fill task queues based on priorities, quality, and deadlines.
• Task Queuing: Automatically schedules nearby and remote tasks with goals based on estimated durations.
• Probability Estimates: Improves accuracy by annealing estimates toward reliable probabilities, considering best-case, worst-case, average-case, and past-predicted scenarios.
• Time & Cost Estimates: Estimates completion times and costs for computing tasks, accounting for risks and costs such as cache misses and CPU/GPU stalls.

By performing these tasks in real-time, we achieve these and many other benefits:

• Bandwidth Optimization: Streamlines data transfer by regenerating visuals and other data locally at desired quality levels, even over low-speed connections.
• Multi-way Presence: Enables massive-scale collaboration, sharing, monitoring, and training within unified machines without virtualization.
• HPC Optimization: Automates the generation, tuning, syncing, and scaling of highly parallelized machine instructions in real-time. This approach reduces energy consumption and enhances security and performance by adapting to changing environments.
• Dynamic Resource Control: Saves costs by dynamically sensing and communicating directly with hardware resources, eliminating the need for VMs.
• User-level Control: Allows users to describe their needs, generating interfaces in real-time without complex tech-heavy interfaces. Enterprise policies can be simply described without backend coding.
• Quantum-ready Security: Automates the process of generating, tuning, syncing, and scaling highly parallelized machine instructions, incorporating multiple encryption algorithms for enhanced security.

Indeed, this is not normal software. It is software evolved.

Beyond Traditional Coding

Creating solutions from traditional code would require hiring an army of coders, who’s output perpetuates the very problem we aim to solve. We are not seeking to get rid of coders. We are focused on solving the root cause of software failures, which is programming languages. Our short-term approach is to package select code as needed, but our long-term and preferred solution is to create software from natural language. This method allows us to generate pristine machine code, free from the limitations and inefficiencies of traditional coding practices.

A Revolutionary Impact

Just as the automobile revolutionized transportation, our wantware is set to transform the digital landscape. By focusing on Meaning Coordinates, we achieve unparalleled interoperability, scalability, and precision. This isn’t just an improvement—it’s a fundamental shift in how we interact with and control technology. We expect that coders and society as a whole will benefit from a better digital landscape.

Conclusion: Building the Future

If we merely asked our clients what they wanted, they might indeed ask for faster, more efficient software. But at MindAptiv, we see a different future—one where the limitations of traditional coding are left behind. We are building the automobiles of the digital world, driven by Meaning Coordinates and the power of wantware.

Upon observation, some may conclude that we are flying or even teleporting data. After all, we have three patents that describe how the output signal has greater detail than the input. Remarkably, our approach applies to 2D, 3D, and higher dimensions (e.g., text, images, video, audio, X-rays, MRIs, holograms, network packets, code, and more). Even more remarkably, we apply our revolutionary methods using natural language dialogue—not code.

So, the next time you hear the clamor for “faster software,” think of us and remember: true innovation lies not in improving the past but in creating the future.