Building AI With MongoDB: How Gradient Accelerator Blocks Take You From Zero To AI in Seconds
Blog post from MongoDB
Gradient is a platform founded by former leaders of AI teams at Google, Netflix, and Splunk that enables businesses to create custom high-performing AI applications with its Accelerator Blocks, which provide a comprehensive, fully managed building block for AI use cases. The blocks can be used as-is or combined to create more robust solutions, reducing developer workload and achieving goals in a fraction of the time. Gradient's newest Accelerator Block focuses on enhancing performance and accuracy through retrieval augmented generation (RAG) using MongoDB Atlas Vector Search and LlamaIndex. This block improves development velocity by up to 10x by removing the need for infrastructure or in-depth knowledge around retrieval architectures. The platform also provides customization, industry edge, and best-of-breed technologies, including Llama-2 and Bloom LLMs, alongside MongoDB Atlas as a core part of the stack available in the Gradient platform.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 10 | 2,087 | 216 | 81 | +23% |
| RAG | 6 | 1,125 | 154 | 56 | -17% |
| LLM | 3 | 2,401 | 292 | 122 | -7% |
| Data Pipeline | 1 | 348 | 132 | 56 | -36% |
| Real-time | 1 | 2,379 | 618 | 172 | -8% |
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