March 4, 2025 - Release : Introducing Daddy1...
Introducing the First Generation of Mix-Models
Today, we are thrilled to unveil the first-generation mix-models, a revolutionary step in artificial intelligence. These models seamlessly merge sophisticated reasoning capabilities with a vast repository of pre-trained knowledge, setting a new industry benchmark. Built on our cutting-edge Mixture of AI infrastructure, Daddy 1 and Mommy 1 excel in a wide range of complex tasks, from high-level mathematics and advanced programming to deep contextual analysis and innovative problem-solving.
For users prioritizing efficiency, we also introduce Baby 1, a cost-effective, high-speed model designed for optimal performance.
Scaling LLMs: The Power of Mixed AI Models
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We are advancing AI capabilities by combining multiple AI models during post-training, applying robust supervised learning techniques to orchestrate a network of specialized models. This allows us to break down user requests into precise, well-defined sub-tasks, leveraging the strengths of different architectures for maximum efficiency.
- Daddy 1 offers broad knowledge and deep contextual understanding, significantly reducing hallucinations and enhancing reliability across diverse topics.
- Mommy 1 specializes in contextual reasoning, problem decomposition, and structured execution of complex workflows.
- Baby 1 is optimized for cost-speed efficiency, making it ideal for rapid inference and real-time applications.
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This chart provides a clear performance hierarchy, with Daddy1-adv emerging as the most powerful reasoning model. Baby1 and Baby1-adv maintain efficiency while trading off raw accuracy, making them ideal for applications where speed and cost are prioritized over absolute precision. Mommy1 and Mommy1-adv balance accuracy and efficiency, making them versatile for structured reasoning tasks.
Human-Like AI Reasoning: The Brain Network
At the forefront of AI innovation, we introduce the Brain Network, a capability that enables our models to reason collaboratively across multiple specialized AI models. Inspired by the interconnected nature of the human brain, this approach allows for more intelligent orchestration, dynamic adaptation, and real-time knowledge sharing between different AI agents.
A brain network in neuroscience refers to a complex system of interconnected neurons and functional units that work together to process information, regulate behavior, and support cognitive functions. In AI, we replicate this principle by enabling our models to interact, learn, and refine their decision-making across specialized domains, ensuring more accurate and contextually relevant responses.
The Future of AGI: A Collaborative AI Ecosystem
Since the rise of generative AI in 2023, Humiris has held the belief that true Artificial General Intelligence (AGI) will not emerge from a single massive pre-trained model, but rather from an intelligent collaboration between multiple specialized AI systems.
By leveraging a Mixture of AI approach, we create a scalable, modular framework that ensures each model is fine-tuned for its domain while working together seamlessly for deeper, more precise execution of tasks.
Through advanced reinforcement learning, Daddy 1 and Mommy 1 autonomously plan, self-correct, and evaluate multiple solution paths, producing optimized, insightful responses. The “open thought process” feature further enhances transparency, allowing users to trace the reasoning behind AI-generated solutions an invaluable tool for academic research and high-stakes applications.
Daddy1-adv our advanced reasoning model
Exceptionally Accurate, and Engineered for Advanced STEM Reasoning
Introducing Daddy1-adv, Humiris’ most advanced and intelligent AI model for STEM reasoning and complex problem-solving. Designed to push the boundaries of math, coding, and scientific analysis, Daddy1-adv delivers accurate, more precise, and deeply reasoned responses outperforming its predecessors in both accuracy and efficiency.Through rigorous evaluations, Daddy1-adv has demonstrated:
- Superior logical reasoning compared to o3-mini , o1, Deepseek-R1 and Claude 3.7 sonnet
- Clearer, more structured answers for complex real-world challenges and better human request understanding.
With advanced reasoning capabilities, Daddy1-adv outperforms standard models on key benchmarks such as AIME, GPQA, and SWE-bench Verified, making it the leading AI choice for technical fields requiring deep analytical power.
For users who demand the best in AI-driven reasoning, problem-solving, and efficiency, Daddy1-adv stands as the ultimate choice.
Competition Math (AIME 2025 & AIME 2024)
Daddy1-adv dominates AIME 2025 (89.3%) and AIME 2024 (91.0%), proving its superior mathematical reasoning and problem-solving capabilities, outperforming all competitors. While o3-mini High remains a strong contender, Claude 3.7 Sonnet significantly underperforms, highlighting Daddy1-adv as the best choice for advanced STEM applications.
PhD-level Science Questions (GPQA Diamond)
With an accuracy of 82.4%, Daddy1-adv surpasses competitors by effectively combining deep domain expertise, multi-step reasoning, and knowledge synthesis. This performance demonstrates its ability to tackle highly technical, research-grade scientific inquiries, making it the best choice for AI-driven academic research, technical consulting, and high-stakes scientific problem-solving.
Software Engineering (SWE-bench Verified)
Daddy1-adv the best choice for AI-assisted coding, large-scale software development, and intelligent debugging, proving its ability to enhance productivity and accuracy in real-world engineering applications.With 71.3% accuracy, Daddy1-adv significantly outperforms all other models, demonstrating superior software reasoning and debugging skills. Claude 3.7 Sonnet follows at 62.0%, while other models (o3-mini high, o1, Deepseek-R1) remain clustered around 49%, indicating limited effectiveness in handling complex software engineering challenges.
Fine-Tuning and Reinforcement Learning for Developers
With the Mixture of AI infrastructure, developers gain full control over model optimization. Whether through fine-tuning or reinforcement learning, users can refine AI behavior for increased domain-specific accuracy. This ensures that businesses and researchers can tailor AI capabilities to meet their unique needs, leading to higher precision, reduced biases, and more adaptable AI solutions. At Humiris, we are building the future of AI one where intelligence is decentralized, specialized, and infinitely scalable.
Parallelized Thought Architecture for solving hard problems
Traditional AI models follow a sequential reasoning process, limiting their ability to efficiently tackle highly complex, multi-faceted problems. Parallelized Thought Architecture enables AI models like Daddy1-adv to think in a more human-like way exploring diverse possibilities at once, cross-validating answers, and refining solutions dynamically.This approach bridges the gap between artificial and human intelligence, making AI systems faster, more reliable, and capable of solving real-world hard problems with unprecedented accuracy.
The highly connected network visualization represents multi-threaded cognitive pathways, dynamically interwoven to create a collaborative intelligence system.The color-coded interconnections likely reflect different AI models or sub-networks, each focusing on a unique aspect of reasoning.The "Parallelized" tuning mode confirms that Daddy1-Advanced is optimized for solving complex, multi-step problems with high efficiency.
Agentic tool use
Daddy1-adv demonstrates superior agentic tool use on τ-bench (Retail) and τ-bench (Airline), achieving 94% accuracy in both domains—outperforming both Claude 3.7 Sonnet (81% and 58%) and o1 (73% and 54%). While Claude 3.7 Sonnet is recognized for strong performance on TAU-bench, Daddy1-adv’s higher accuracy across complex real-world tasks involving user and tool interactions solidifies its position as the best AI for operational decision-making and automation in dynamic industries like retail and aviation.
Use case
Autonomous Decision-Making & Tool Use:
Daddy1 interacts dynamically with external tools, APIs, and databases, allowing it to autonomously retrieve information, execute tasks, and optimize workflows.
Start building your AI Agent
AI-assisted scientific research and mathematical problem-solving. Daddy1-adv leverages parallelized thought architecture to solve multi-step math problems, derive proofs, and optimize numerical computations faster than conventional models.
Work with daddy1-adv
AI-assisted debugging, code refactoring, and automated development. Daddy1-adv understands complex software architectures, detects bugs, refactors inefficient code, and suggests highly optimized solutions for development teams.
Try in Humchat
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