Wuwen Xinqiong 99

Infinigence is committed to providing excellent AGI computing solutions, with a large model energy-efficiency optimization tool kit as the core, collaborating downward with multiple domestic chip companies, and serving large model algorithm enterprises upward through intelligent computing cloud services and intelligent computing all-in-one machines in various ways. By coordinating computing power, algorithms, and ecosystem, it promotes the efficient implementation of industry large models, building the large model infrastructure for the AGI era.

Infinigence Official Website: https://www.infini-ai.com

Infinigence Core Products:

Based on the Infinigence large model energy-efficiency optimization toolkit, integrating domestic chip computing power, it builds a unified computing foundation, providing cloud services for various accelerated computing powers including NVIDIA, AMD, Hygon, and Tianshu, shielding hardware differences and being ready to use out of the box.

For private deployment scenarios of large models, it integrates computing accelerator cards, self-developed IP, optimization toolkits, and industry large models to build large model all-in-one machines, maximizing the ROI of large model implementation.

Infinigence Solutions:

Infinigence provides end-to-end training services from installation to usage, as well as model customization services, lowering the threshold for using large models, and customizing personalized solutions according to your needs.

1. Intelligent Computing Cloud Service

• GPU-accelerated instances

• Ready to use out of the box, unified acceleration, deep performance optimization, open-source compatible

• Support for multi-source domestic chips

• Large model training acceleration service

• Large model inference acceleration service

2. Intelligent Computing All-in-One Machine

• Deep software and hardware collaboration

• Self-developed accelerator card IP

• Industry large model empowerment

3. Large Model Energy-Efficiency Optimization Toolkit

• Self-developed multi-backend universal high-performance operator library

• Model quantization and compression library

• Distributed training acceleration library

• Multi-backend model inference engine

4. Self-developed Industry Large models

• Government affairs large model

• Legal large model

• Securities large model

5. Large model application development tool chain

• Multi-agent engine

• Model fine-tuning service

• RAG toolkit

• Effect evaluation tool

6. industry intelligent agent applications based on large model

• Investment Assistant

• Algorithm assistant

Infinigence Team Members:

The founding team members come from the Department of Electronic Engineering at Tsinghua university and leading internet/AI companies, with rich industry experience and successful entrepreneurialial track records. They have profound technical accumulation and academic expertise, having published more than 200 high-level academic papers in the field of artificial intelligence system optimization.

Related achievements include: (1) GPU high-efficiency operator library surpassing NVIDIA's commercial library, achieving better performance on mid-end process GPUs than commercial software on high-end process GPUs; (2) Efficient sparse inference acceleration architecture supporting large models, improving the computing speed of sparse neural networks, graph neural networks, etc. by 1-3 orders of magnitude. The team has achieved a 50% reduction in latency for large language models on NVIDIA GPUs, and will further combine underlying operator optimization, sparse acceleration, hardware feature awareness, and efficient interconnection capabilities to increase the overall system acceleration ratio to 10 times.