Introduction
Today we are pleased to introduce Bob-1, our state-of-the-art multimodal model that powers boberth.com. After months of research and development, we have created a model that not only understands text but also interprets images with exceptional accuracy.
Key capabilities
-
Advanced visual understanding: Bob-1 not only recognizes common objects but accurately analyzes texts, charts, icons, and layouts within images.
-
Visual agent capabilities: Functions as a visual agent that can reason and dynamically direct tools, being capable of interacting with computer and mobile device interfaces.
-
Precise visual localization: Can accurately localize objects in an image, generating exact coordinates and attributes in structured format.
-
Structured output generation: For data like scanned invoices, forms, and tables, Bob-1 supports structured outputs of their contents, benefiting uses in finance, commerce, and more.
Architectural advancements
We have implemented significant improvements in the model architecture:
-
Optimized vision encoder: We enhanced both training and inference speeds by strategically implementing window attention into the ViT. The ViT architecture was further optimized with SwiGLU and RMSNorm, aligning it with the structure of the base language model.
-
Advanced training techniques: We utilized low-rank adaptation (LoRA) and reinforcement learning from human feedback to significantly improve model performance.
Benchmark performance
Bob-1 has been evaluated on various industry-recognized benchmarks, demonstrating exceptional performance against leading models like GPT-4o and Gemini:
| Benchmark | Bob-1 | GPT-4o | Gemini-2-flash |
|---|---|---|---|
| MMMU_val | 70.2 | 70.3 | 70.7 |
| MMMU_Pro | 51.1 | 54.5 | 57.0 |
| MathVista_MINI | 74.8 | 63.8 | 73.1 |
| MathVision_FULL | 38.1 | 30.4 | 41.3 |
| Hallusion Bench | 55.16 | 55.0 | - |
| MMBench_DEV_EN_V11 | 88 | 82.1 | 83.0 |
| AI2D_TEST | 88.4 | 84.6 | - |
| ChartQA_TEST | 89.5 | 86.7 | 85.2 |
| DocVQA_VAL | 96.4 | 91.1 | 92.1 |
| MMStar | 70.8 | 64.7 | 69.4 |
| MMVet_turbo | 76.19 | 69.1 | - |
| OCRBench | 885 | 736 | 788 |
| OCRBench-V2(en/zh) | 61.5/63.7 | 46.5/32.3 | 51.9/43.1 |
| CC-OCR | 79.8 | 66.6 | 73.0 |
As can be observed, Bob-1 outperforms GPT-4o in most metrics and competes closely with Gemini in several categories, particularly excelling in visual comprehension and document processing tasks.
Use cases
Bob-1's capabilities make it ideal for a wide range of applications:
-
Intelligent visual assistance: Provides accurate responses based on visual content, enhancing user interaction.
-
Document analysis: Extracts structured information from scanned documents, invoices, and forms with high precision.
-
Interactive education: Offers detailed explanations of visual concepts and responds to academic queries with visual context.
-
Enhanced accessibility: Helps users with visual impairments better understand visual content through detailed descriptions.
Commitment to ethics and transparency
We understand the importance of ethics in artificial intelligence. Therefore, Bob-1 has been developed following strict guidelines to ensure responsible responses and avoid biases. Additionally, we maintain a policy of transparency regarding the data sources used and the training processes implemented.
Future of Bob-1
We are committed to the continuous improvement of Bob-1. Our research team is working on:
- Expanding multimodal capabilities to include more types of visual content
- Improving computational efficiency to reduce resource requirements
- Developing industry-specific capabilities for healthcare, finance, and education
Conclusion
Bob-1 represents a significant advancement in our mission to create multimodal artificial intelligence that is useful, accurate, and accessible. Its development reflects our commitment to innovation and technical excellence.
We invite you to experience Bob-1 at boberth.com and discover how it can transform your interaction with artificial intelligence.