FriendliAI has integrated with Weights & Biases to streamline generative AI deployment workflows. This collaboration empowers ML developers to leverage the rich toolset of Weights & Biases while fine-tuning and deploying models on FriendliAI’s high-performance engine. The integration handles everything from resource management to efficient inference serving.
FriendliAI has integrated with Weights & Biases to streamline generative AI deployment workflows. This collaboration empowers ML developers to leverage the rich toolset of Weights & Biases while fine-tuning and deploying models on FriendliAI’s high-performance engine. The integration handles everything from resource management to efficient inference serving.
Resource Management: FriendliAI’s infrastructure manages resources efficiently, allowing developers to focus on model innovation rather than backend logistics. This ensures optimal use of computational resources.,Efficient Inference Serving: The integration offers efficient serving of generative AI models, reducing latency and improving throughput. This ensures faster deployment and real-time performance.,Seamless Workflow: Developers can deploy models trained on the Weights & Biases platform through FriendliAI’s dedicated endpoints effortlessly. This streamlined process reduces the need for manual intervention, enhancing productivity.
FriendliAI empowers organizations to harness the full potential of their generative AI models with ease and cost-efficiency. The company offers infrastructure solutions that accelerate and optimize the deployment of generative AI models. Key features include groundbreaking performance metrics: up to 8.9x cheaper, 11.0x cheaper with dedicated endpoints, 10.7x higher throughput, and 6.2x lower latency compared to competitors. Founded in 2021 and headquartered in Redwood City, California, FriendliAI is dedicated to making generative AI accessible and efficient.
Friendli Container: This product allows users to serve large language models (LLMs) and language multimodal models (LMMs) with FriendliAI’s proprietary engine in their GPU environment. It ensures high performance and cost savings, cutting GPU costs significantly.,Friendli Dedicated Endpoints: These endpoints enable organizations to build and run LLMs and LMMs on autopilot without the need for self-management. This product offers a hands-off approach, ensuring efficiency and reducing operational overhead.,Friendli Serverless Endpoints: Providing a fast and affordable API for open-source generative AI models, this product allows seamless integration and scalability. It is designed for developers looking for a cost-effective solution without compromising on speed.
Cost Efficiency: FriendliAI offers up to 8.9x cheaper solutions for running large language models compared to competitors. This significant cost reduction makes generative AI more accessible to a wider range of organizations.,High Throughput and Low Latency: With 10.7x higher throughput and 6.2x lower latency, FriendliAI provides a performance edge that ensures faster and more reliable AI model deployment.,Seamless Integration: FriendliAI’s products integrate effortlessly into existing workflows, reducing the complexity and time required for deployment. This ease of integration allows organizations to focus more on innovation and less on infrastructure management.
Chatbot Companies: NextDay AI reduced its GPU costs by over 50% using Friendli Container. This cost efficiency allows chatbot companies to scale their operations without breaking the bank.,Emotional AI Services: TUNiB uses Friendli Dedicated Endpoints for its emotional chatbot services, benefiting from the hands-off management and reliable performance. This supports the delivery of more responsive and emotionally intelligent AI interactions.,Creative Writing Platforms: NaCloud, a novel writing service, reduced its LLM serving costs with Friendli Container. This enables creative platforms to offer more advanced features without incurring high operational costs.
