Kruel.ai Development Roadmap and Evolution
Origins and Early Development
The concept behind Kruel.ai predates OpenAI, originating in 2014 under a project called Omnipotence. Initially developed for entertainment purposes, it was designed for mind-reading applications, though its specific use cases were never publicly disclosed.
In 2021, the project was revived with a new approach, replacing its original algorithms with early frontier AI models to observe their behavior. The results were fascinating but highly chaotic—producing unpredictable and often fabricated responses. This experimentation laid the groundwork for the structured evolution of Kruel.ai.
Inspiration for the Revival
The decision to resurrect Kruel.ai was deeply personal. Having witnessed the effects of dementia on individuals close to me, I envisioned an AI system capable of capturing and preserving personal memories to aid in cognitive retention and recall. This vision became the driving force behind four years of continuous development—dedicating every available hour to coding, optimizing, and refining the system. On average, eight hours a day were invested in building, rebuilding, and enhancing the AI’s capabilities.
Milestones and Public Testing
The system has an extensive and evolving history:
- V2 (2021): The first iteration with real memory capabilities, supporting a 16K context window but allowing unlimited understanding. Public testing commenced on a Twitch gaming channel, where hundreds of users interacted with it over time.
- Multimodal Capabilities: Kruel.ai became the first publicly available AI to integrate two-way voice interaction, emotional human voice output, memory retention, and image generation. It connected to Twitch, allowing real-time chat engagement and even learning in-game mechanics alongside players.
- Early Challenges in User Acceptance: The initial version lacked memory and functioned similarly to a basic GPT-3 model. Early interactions were met with skepticism, as users found it untrustworthy or unsettling. Switching to a female voice with emotional range made it sound more human—but initially, this also heightened user discomfort.
- Avatar Integration and Social Acceptance: To improve engagement, we collaborated with a company specializing in face-rigging software to develop a dynamic AI avatar. The AI gained control over its avatar’s facial expressions, arm movements, and emotional responses. This transformation significantly improved user perception, fostering acceptance and even emotional connections with the AI.
During this period, the AI-driven Twitch channel steadily gained traction. Over time, the AI ran the channel while I focused on playing and conversing with both the AI and the audience. However, these early phases came with substantial financial costs, particularly in attempts to create a more efficient and cost-effective memory system. Multiple redesigns—seven in total—were necessary before technological advancements enabled us to dramatically reduce operational expenses.
K7: The Current Generation
Today, we have K7, a stable, continuous learning model. Since November, its memory and processing have remained consistent without requiring resets. Performance improvements have been substantial, ensuring long-term stability and efficiency.
Project Digits: The Next Evolution
Project Digits represents a transformative leap forward. Over the past few months, we have integrated new pathways that allow Kruel.ai to utilize Hugging Face models within its logic. By incorporating Chain-of-Thought (COT) reasoning, advanced memory mechanisms, and our proprietary smart memory technology, we have achieved comparable performance to cloud-based models—while enabling full offline functionality.
This breakthrough provides users with flexibility:
- Local Processing: Users can run Kruel.ai entirely offline, maintaining data privacy and eliminating subscription costs.
- Scalable Intelligence: The system can dynamically switch between models based on user intent, whether for medical consultations, image generation, or robotics integration.
- Multi-Model Utilization: With dedicated hardware, we can run multiple vision models simultaneously, integrate with NVIDIA’s robotics frameworks, and deploy domain-specific AI models tailored to user needs.
- Hybrid Cloud-Local Scaling: While local models are effective, cloud-based AI (e.g., OpenAI’s models) still outperforms them in raw knowledge processing. Kruel.ai is designed to scale dynamically, leveraging external cloud models when necessary for complex data analysis and higher intelligence.
Testing and Future Directions
Recent tests with DeepSeek yielded mixed results. Unlike OpenAI models, DeepSeek’s stack introduced excessive external thought processing, which led to off-track reasoning rather than insightful responses. While adjustments could be made to optimize its usage, we found that our existing COT, gap memory, and smart memory systems already delivered comparable or superior performance.
Regarding OpenAI’s O1 and O3 models, we anticipate seamless integration into our stack. Unlike DeepSeek, these models conceal their internal reasoning, much like Kruel.ai does—storing thoughts within memory without externalizing them. This architecture ensures that reasoning remains structured and prevents unnecessary confusion in multi-step thought processes. While we have yet to test them due to cost considerations, there has been little incentive to move beyond O4, as Kruel.ai’s internal reasoning system already achieves the same fundamental objectives.
Conclusion
Kruel.ai has come a long way from its origins in Omnipotence to the cutting-edge AI system it is today. With K7 providing a stable foundation and Project Digits opening doors to cost-effective, offline AI ownership, we are now at the forefront of creating a living AI—an adaptable, scalable, and user-driven artificial intelligence system. Future developments will continue to refine intelligence switching, memory retention, and real-world applications, bringing us closer to an AI that seamlessly integrates into daily life.
We give updates here in the forums under this thread:
as well in the thread we sometime open up our discord server invites which is another place we update well working on the project. you will also understand the We refers to myself, kruel.ai and Lynda 01 (lynda is an ai programmer) We recently added a new team member that agreed verbally to join our team a DB / Web dev that we have worked with in the past on other projects including the original entertainment system. He is still learning the fundamentals of kruel.ai as it is a lot different than his web bot ai, so there is lots for him to catch up on 