AI is in significant evolution, with emergent capabilities and potential to outstrip human cognition. However current approaches to AI have significant limitations.
Large language models have significant limitations. They are fixed on inputs and outputs and need brute-force training. They have no true understanding of what they are doing, are expensive to run, and only address shallow use-cases (question – answer; or single turn prompt – output).
GEAR (Goal Event Alignment and Resonance) has significant potential to solve some of the challenges in generative AI:
We are developing a novel approach to Generalizable Artificial Intelligence. Unlike classic statistical learning like large language models, Akin’s AI has great potential to autonomously solve complex problems in unpredictable environments, and form deep relationships with humans.
As a platform with a frontier model, we have focussed on several key differentiators:
We have benchmarked and deployed our AI across a number of sectors, including a Personal AI to support daily living, health management, ecosystem modeling, robotics, Space Industry, advanced manufacturing (AI and robots working alongside humans in high-compliance environments), complex task support and adaptive reasoning, social companions, ambient AI systems to run a habitat or environment, and complex systems management.
We are benchmarking our AI systems for future roles in human cognitive augmentation, autonomous adaptive reasoning, complex task support, ability to operating with high efficacy in environments with minimal data dependency; and potential for future alternate computing systems like Quantum Computing.
“[Akin AI]... is not limited to single-turn prompts, but can handle complex problems. The AI must work in an environment without cloud compute resources, so it has been designed to be more efficient and less reliant on brute-force learning. This is a significant development given the costs of running generative AI foundation models.”
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