Announcing SIA: an Open-Source Self-Improving AI framework
[Explore on GitHub]
Announcing SIA: an Open-Source Self-Improving AI framework
[Explore on GitHub]
Announcing SIA: an Open-Source Self-Improving AI framework
[Explore on GitHub]
Accelerating Superintelligence
Accelerating Superintelligence
Hexo Labs is building Self-Improving AI, we call it SIA. The last AI system that humans build will be a Self-Improving AI system. Once this framework is in place, AI will continue to build better versions of itself while humans move on to focus on other frontiers.
Hexo Labs is building Self-Improving AI, we call it SIA. The last AI system that humans build will be a Self-Improving AI system. Once this framework is in place, AI will continue to build better versions of itself while humans move on to focus on other frontiers.
Accelerating Superintelligence
SIA: the next stage of agentic evolution
The bottleneck to get to superintelligence is the static nature of agent harnesses, model weights and memory systems. Current agentic systems execute tasks but do not improve from that execution, requiring humans to make improvements to the system. SIA is an agentic system that improves its components autonomously.
SIA (Self-Improving AI) is the framework behind the AI system’s ability to improve itself.
SIA focuses on one problem: how do you design structured feedback loops that allow a system to evaluate its own performance, adapt its strategy, & get better. Infinitely.
The bottleneck to get to superintelligence is the static nature of agent harnesses, model weights and memory systems. Current agentic systems execute tasks but do not improve from that execution, requiring humans to make improvements to the system. SIA is an agentic system that improves its components autonomously.
SIA (Self-Improving AI) is the framework behind the AI system’s ability to improve itself.
SIA focuses on one problem: how do you design structured feedback loops that allow a system to evaluate its own performance, adapt its strategy, & get better. Infinitely.
The bottleneck to get to superintelligence is the static nature of agent harnesses, model weights and memory systems. Current agentic systems execute tasks but do not improve from that execution, requiring humans to make improvements to the system. SIA is an agentic system that improves its components autonomously.
SIA (Self-Improving AI) is the framework behind the AI system’s ability to improve itself.
SIA focuses on one problem: how do you design structured feedback loops that allow a system to evaluate its own performance, adapt its strategy, and get better. Infinitely.
Built for
real-world
complexity
Built for real-world
complexity
Self-improving agents must operate in real-world environments where problems are open-ended and outcomes are measurable, requiring continuous iteration, experimentation, and refinement.
By operating in real-world environments, SIA is trained on problems where progress is tied to actual performance across domains that uplift humanity including (but not limited to) science, engineering, strategy, business and the economy.
Self-improving agents must operate in real-world environments where problems are open-ended and outcomes are measurable, requiring continuous iteration, experimentation, and refinement.
By operating in real-world environments, SIA is trained on problems where progress is tied to actual performance across domains that uplift humanity including (but not limited to) science, engineering, strategy, business and the economy.
Self-improving agents must operate in real-world environments where problems are open-ended and outcomes are measurable, requiring continuous iteration, experimentation, and refinement.
By operating in real-world environments, SIA is trained on problems where progress is tied to actual performance across domains that uplift humanity including (but not limited to) science, engineering, strategy, business and the economy.
Self-improving agents must operate in real-world environments where problems are open-ended and outcomes are measurable, requiring continuous iteration, experimentation, and refinement.
By operating in real-world environments, SIA is trained on problems where progress is tied to actual performance across domains that uplift humanity including (but not limited to) science, engineering, strategy, business and the economy.
Frontier Research Grant Program
With the goal to enable faster iteration in real-world environments and remove barriers to experimentation, we partner with researchers, engineers, and domain experts working on ambitious problems.
Selected researchers receive access to SIA, infrastructure, and direct collaboration with the Hexo Labs team. The goal is simple.
Frontier Research Grant Program
With the goal to enable faster iteration in real-world environments and remove barriers to experimentation, we partner with researchers, engineers, and domain experts working on ambitious problems.
Selected researchers receive access to SIA, infrastructure, and direct collaboration with the Hexo Labs team. The goal is simple.
With the goal to enable faster iteration in real-world environments and remove barriers to experimentation, we partner with researchers, engineers, and domain experts working on ambitious problems.
Selected researchers receive access to SIA, infrastructure, and direct collaboration with the Hexo Labs team. The goal is simple.
Frontier Research Grant Program
Work on humanity’s last invention
Work on humanity’s last invention
Work on humanity’s last invention
Hexo Labs is building the machine that builds every future machine. The machine that turns the wheels of evolution, creates a future of abundance for all and accelerates evolutionary progress.
Hexo Labs is building the machine that builds every future machine. The machine that turns the wheels of evolution, creates a future of abundance for all and accelerates evolutionary progress.
