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As enterprises struggle to balance AI capabilities against data privacy concerns, federated learning provides the best of both worlds.
Vertex AI RAG Engine streamlines the complex process of retrieving relevant information from a knowledge base and feeding it to an LLM, Google said.
SwiftKV optimizations developed and integrated into vLLM can improve LLM inference throughput by up to 50%, the company said.
While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge graph.
Open-source software will continue its march through the enterprise technology stack, buoyed by AI and (hopefully) transformative funding solutions that address sustainability.
Use of AI has increased both the amount of code delivered and the amount of code that needs reworking. Don’t use more AI than you can handle.
Cohere is positioning North for its ease of use for building and deploying agents, a growing concern among developers.
A new survey reveals that AI developers face many challenges, including a skills gap and frustration with immature processes and inadequate tools.
The future of work requires data teams to lead with data governance, ops, and products that make data reliable and discoverable for business users and use cases.
Before deploying agentic AI, enterprises should be prepared to address several issues that could impact the trustworthiness and security of the system.