Prometech Computer Sciences Inc PRO
prometechinc
AI & ML interests
Behavior-driven AI architectures, mathematical reasoning models,
controlled decision systems, brain–body AI separation,
safe and auditable AI design, and optimization-oriented language models.
Recent Activity
updated a dataset about 14 hours ago
pthinc/BCE-Prettybird-Nano-Kangal-v0.1 published a dataset about 15 hours ago
pthinc/BCE-Prettybird-Nano-Kangal-v0.1 posted an update 1 day ago
BCE-Prettybird-Nano-Science-v0.1 - 500 Science Q&A Dataset for Instruction-Based Learning
We are excited to introduce a comprehensive math-physics-chemistry-biology dataset containing 500 instruction-based question-answer pairs, designed to support research in science reasoning, problem-solving, and AI training. Generated using Python’s math libraries (e.g., math, numpy, sympy), the dataset covers a diverse range of difficulty levels—from basic arithmetic and algebra to advanced calculus, probability, and number theory.
Each entry follows a structured instruction-input-output format, ensuring clarity and usability for fine-tuning language models, benchmarking AI systems, or educational applications. The problems include word problems, symbolic computations, and real-world scenarios, making it ideal for developing models that require logical reasoning and numerical precision.
Whether for LLM fine-tuning, automated tutoring, or math-focused AI research, this dataset provides a balanced mix of complexity and accessibility, helping bridge the gap between theoretical math and practical problem-solving.Organizations
