Top Highlights
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Enhance User Experience: Leverage Cerebras’ high-speed inference endpoints to significantly reduce latency, allowing LLMs like Llama 3.1-70B to respond more rapidly without compromising quality.
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Streamlined Development: Utilize a unified environment in DataRobot for prototyping, testing, and deploying LLMs, enabling faster iteration and reducing complexity through integrated tools.
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Performance Metrics: Cerebras delivers 70x faster inference than traditional GPUs, facilitating smoother interactions in real-time applications across various industries, including pharmaceuticals and voice AI.
- Simplified Customization: Follow six straightforward steps to integrate and deploy Llama 3.1-70B, allowing for easy testing and optimization of AI applications while maintaining high performance and responsiveness.
Cerebras and DataRobot Transform AI App Development
Faster, smarter, and more responsive AI applications are critical in today’s tech landscape. Users expect quick responses, and delays can lead to frustration. Each millisecond counts.
Cerebras’ high-speed inference technology significantly reduces latency. This innovation allows developers to speed up model responses with enhanced quality, specifically using models like Llama 3.1-70B. By implementing straightforward steps, developers can customize and deploy their own large language models (LLMs). This process grants developers better control to balance speed and quality.
A recent blog post outlines key steps to harness these capabilities:
- Set up the Llama 3.1-70B model in the DataRobot LLM Playground.
- Generate and apply an API key for using Cerebras for inference.
- Customize and deploy applications that operate smarter and faster.
In just a few steps, developers become equipped to deliver AI models that demonstrate speed, precision, and real-time responsiveness.
Developing and testing generative AI models traditionally required juggling various disconnected tools. Now, with an integrated environment for LLMs, retrieval methods, and evaluation metrics, teams can transition from concept to prototype more efficiently. This shift simplifies the development process, enabling creators to focus on impactful AI applications without the hassle of switching between different platforms.
Consider a real-world example: Cerebras’ inference technology enables rapid model deployment without compromising quality. A low-latency environment is essential for fast AI application responses. Companies like GlaxoSmithKline (GSK) and LiveKit have already begun leveraging this speed. GSK accelerates drug discovery, while LiveKit enhances ChatGPT’s voice mode for quicker response times.
Cerebras boasts a remarkable capability, achieving 70 times faster inference than standard GPUs when using Llama 3.1-70B. This impressive performance comes from their third-generation Wafer-Scale Engine (WSE-3), crafted specifically to optimize the operations fueling LLM inference.
To easily integrate Llama 3.1-70B into DataRobot, developers follow a clear sequence. After generating an API key in the Cerebras platform, they create a custom model within DataRobot. By placing the API key in the relevant file and deploying the model to the DataRobot Console, teams can quickly begin utilizing Llama 3.1-70B. Testing become interactive and immediate, allowing developers to refine outputs in real time.
As LLMs continue to evolve and grow, having a streamlined process for testing and integration becomes vital. By pairing Cerebras’ optimized inference with DataRobot’s tools, developers can foster a faster, cleaner approach to AI application development. This partnership creates opportunities for innovation, helping teams adapt to the increasing demands for responsive and effective AI solutions.
Explore the potential of Cerebras Inference today. Generate your API key, integrate it within DataRobot, and start building groundbreaking AI applications.
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