Advancing Multimodal AI: Strengthening STEM Capabilities with Complex Prompts
Challenge
A leading multimodal AI platform struggled with complex STEM prompts, limiting its processing and reasoning ability to interpret diverse question formats accurately. The client required a structured and scalable prompt engineering approach to enhance models' comprehension across Physics, Chemistry, Math, and Biology for the middle school level. It was to ensure the AI model could accurately interpret complex problems and multimodal inputs such as images, screenshots, PDFs, etc.
Solution
Cogito Tech proposed optimizing STEM performance with expert-driven prompt engineering and data input. We rewrote prompts with increasing complexity and curated multimodal inputs via screenshots from the computer. We fine-tuned the model for middle school-level STEM queries; the model was trained with 30,000 refined prompts over 60 days by a team of 60 experts, ensuring accuracy and efficiency.
Outcome
As a result, the AI model achieved higher STEM accuracy, delivering improved responses in Physics, Chemistry, Math, and Biology. Its multimodal reasoning is amplified. Our data input solutions strengthened problem-solving skills, allowing it to tackle middle school-level STEM queries precisely and accelerating AI training and deployment. AI platform's interpretation and processing capabilities improved 5x.
How did we start?
Our journey began with aligning the AI model’s capabilities to middle school-level education standards, ensuring it could precisely comprehend and respond to complex STEM queries. We focused on augmenting language fluency, refining its ability to understand subject-specific terminology and context across Physics, Chemistry, Math, and Biology.
We first tackled transcription and captioning to build a strong foundation, training the AI to accurately interpret and convert spoken and written content into structured text. From there, we progressed to image recognition, enabling the model to extract relevant information from diverse visual formats, including scanned documents, handwritten notes, and complex diagrams.
Solidified the process with a sample
We took a Math (Trigonometry) sample, where AI initially struggled with interpreting visual problems and solving angle-based questions from scanned images. Cogito Tech improved the AI’s ability to analyze and solve complex mathematical challenges efficiently by optimizing OCR-based data processing and strengthening structured prompt clarity. The team ensured that multimodal inputs were structured for better readability and interpretation, allowing the AI to extract accurate information across different formats.
As the AI’s understanding improved, we shifted towards writing and testing, ensuring it could generate coherent, well-structured responses while maintaining accuracy across various problem statements. Throughout the process, our team’s research, editorial, and analytical expertise played a crucial role in fine-tuning outputs, validating responses, and refining the model’s reasoning abilities. The AI’s proficiency grew with each phase, allowing it to handle intricate STEM concepts, process multimodal inputs, and deliver more precise, context-aware answers.
Factors that contributed to the success
- Geo-Diverse Talent: Our globally distributed team of in-market professionals ascertained culturally immersive and region-specific solutions.
- Domain Expertise: Specialists in healthcare, life sciences, finance, STEM, and law provided in-depth subject matter knowledge.
- Hybrid Workforce Model: A mix of dedicated experts for precision and crowdsourced talent for flexibility and scalability.
- Highly Skilled Workforce: Strong research, editorial, and analytical abilities improved content quality and accuracy.
- Language Diversity: Multilingual professionals with native fluency efficiently handled complex multilingual projects.
- LLM Evaluation Expertise: Proficient in assessing and refining LLMs, delivering nuanced, high-quality content tailored to client needs.
- Technical Proficiency: Expertise in software engineering, QA, and full-stack development ensured seamless execution and evaluation.
The result?
By the end of this journey, we had transformed the model into a more intelligent and adaptive system capable of confidently tackling middle school-level academic challenges.
Need precise annotation for your AI model? Partner with Cogito Tech and take action today!