Hallucinations
Generation of inaccurate information by relying on learned patterns without verifying facts.
Generation of inaccurate information by relying on learned patterns without verifying facts.
No insight into reasoning or decision-making makes understanding and validating outputs impossible.
Attention constraints limit the ability to process long sequences, hindering effective reasoning over extensive data.
Training data limits responses, excluding recent developments.
Multistep reasoning and execution
The KPU is built around two core components: the Reasoning Engine, which analyzes and plans, and the Execution Engine, which carries out tasks. Together, they enable multistep reasoning and execution by breaking challenges into manageable steps. This architecture ensures precise, flexible handling of complex tasks, delivering nuanced solutions tailored to real-world needs.
It calculates and validates each step of the process, significantly reducing errors and mitigating hallucinations.
Visibility and explainability of reasoning, decisions, and actions. Provides auditability and control over agentic functions.
The KPU automates workflows by executing actions across tools, APIs, and systems, handling dynamic scenarios with ease.
Benchmarks
The KPU has been tested with challenging benchmarks designed to evaluate its reasoning capabilities and complex problem-solving.
"In 3 minutes, it has constructed me a pretty cool code to download large subset of OpenStreetMap data. When asked o1 to do that, it constructed a pretty basic code logic, while using the same exact prompt Maisa has implemented all the logic to speed up the download speed as much as possible without being ratelimited as it was asked in the prompt.”
"I love the system so far. For some of my programming tasks it outperforms the most powerful AI model specified for programming tasks”
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