The Heart of Decompute

Redefining AI for a Scalable Future: Building Infrastructure for AGI and the Masses

Humanity is entering an era of profound transformation driven by Artificial General Intelligence (AGI). This technological leap demands more than incremental progress—it requires a fundamental rethinking of how AI is built, scaled, and deployed. As AGI emerges, our focus must shift toward creating systems that are accessible, scalable, and optimized to empower individuals and organizations alike, reducing costs and enabling ownership of models and data.

For example, a part of the recent interest and excitement in DeepSeek is the claim that it has been trained with significantly fewer resources than the other models that it either outperforms or matches. If we distill the core of this excitement, it illustrates a critical and often overlooked truth: the economy still matters. Despite the extraordinary capabilities of AGI, cost, efficiency, and scalability remain essential constraints. These factors shape how broadly AI can be adopted, who can access it, and what kind of innovation it can power.

Another major point that has been discussed is whether or not DeepSeek was trained using private data; with the argument being made that comparing training using private data vs. training using publicly available data is incomparable. These recent events reinforce that even in the age of AGI, economic principles are foundational for ensuring that AI is a tool for collective progress, not a luxury for a privileged few, and the long-held belief that harnessing private data can be the gamechanger..

To truly democratize AI and prepare for the challenges of AGI, we must move away from legacy infrastructures that are ill-suited for the unique demands of large language models (LLMs). Current cloud-based systems were designed for web applications—not for the immense computational requirements of training and deploying AI at scale. The result is inefficiency, higher costs, and limited accessibility for those wishing to harness AI's power.

At the heart of this transformation lies a bold and timely reimagining of AI infrastructure.

We are discarding outdated paradigms and rebuilding the foundational pieces of AI from the ground up. Every decision and every design choice are driven by the pursuit of optimization—minimizing latency, maximizing energy efficiency, and ensuring scalability to make AI technology more affordable and accessible to everyone.

Scalable AGI: Bringing AI to the Masses

The potential of AGI extends far beyond research labs and tech giants; it has the power to redefine industries, reshape economies, and solve humanity’s most pressing challenges. However, achieving this vision requires removing the barriers that limit access to AI. One major obstacle to this goal is cost, i.e.,  high expenses driven by inefficient infrastructure and reliance on proprietary cloud systems.

To overcome these limitations, we are developing a new AI ecosystem that prioritizes affordability and ownership. By enabling individuals and organizations to train, deploy, and own their models, we ensure that AI is no longer an exclusive tool of the few.

This paradigm shift empowers users to leverage their data securely and independently, unlocking personalized solutions without sacrificing control, transparency, or confidentiality of their data.

This democratization of AI requires a commitment to innovation at every layer of the stack, ranging from hardware and software to algorithms and deployment strategies. By optimizing infrastructure specifically for LLMs and AGI, we are paving the way for AI systems that are not only powerful but also accessible to a broader audience.

Rethinking AI Infrastructure

The traditional cloud model, built for the era of web-based applications, is fundamentally misaligned with the requirements of modern AI systems. Training and running LLMs demand unparalleled computation, memory, and parallelism levels. Instead of retrofitting existing infrastructure, we design engineering solutions for these challenges.

This shift involves rethinking everything:

1. Hardware/Software Optimization: Developing specialized low level code, owning compiler, GPU & CPU scheduling, orchestration and memory management that prioritizes energy efficiency, scalability, and low latency for LLM workloads.

2. Decentralized Architectures: Exploring alternatives to centralized cloud systems, such as edge computing and distributed networks, to reduce costs and latency.

3. Software Efficiency: Designing leaner algorithms and frameworks that minimize resource consumption while maximizing performance.

4. Sustainability: Optimizing every component to reduce environmental impact while meeting the growing demand for AI.

   
   

These innovations contribute to a future where AI infrastructure is no longer a bottleneck but a catalyst for widespread adoption and impact.

Owning the AI Revolution

True empowerment in the era of AGI means ownership—of data, models, and decisions. By enabling users to build and deploy their own AI systems, we are shifting control away from centralized entities and into the hands of individuals and communities. This is not just a technical shift but a philosophical one, aligning the development of AI with principles of transparency, inclusivity, and agency.

In this new paradigm:

1. Data Sovereignty: Users retain full ownership of their data, ensuring privacy and security while unlocking the value of personalized AI.

2. Custom Models: Individuals and organizations can fine-tune models to meet their unique needs without relying on generic, one-size-fits-all solutions.

3. Cost Efficiency: By designing scalable and cost-effective systems, we are enabling broader access to AI technologies.

   
   

This approach ensures that AGI serves as a tool for collective progress, not a means of centralized control.

A Future Built for AGI

As we stand at the threshold of the AGI era, our choices today will shape the trajectory of humanity’s future. The advent of AGI is not just a technological milestone; it is an opportunity to redefine our relationship with technology and one another. By optimizing AI infrastructure and making it accessible to all, we ensure that AGI becomes a tool for empowerment, collaboration, and progress.

This journey is not merely about building better systems—it is about creating a future where AI catalyzes human potential. The road ahead demands bold ideas, relentless innovation, and a commitment to equity and inclusivity.

Together, we can shape an AGI-driven world that benefits everyone, unlocking the infinite possibilities of human ingenuity.

Written by: Hina Dixit, Tom St. John & Jalaj Upadhyay