News from the AI & ML world
DeeperML
Kuldeep Jha@Verdict
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Databricks has unveiled Agent Bricks, a new tool designed to streamline the development and deployment of enterprise AI agents. Built on Databricks' Mosaic AI platform, Agent Bricks automates the optimization and evaluation of these agents, addressing the common challenges that prevent many AI projects from reaching production. The tool utilizes large language models (LLMs) as "judges" to assess the reliability of task-specific agents, eliminating manual processes that are often slow, inconsistent, and difficult to scale. Jonathan Frankle, chief AI scientist of Databricks Inc., described Agent Bricks as a generalization of the best practices and techniques observed across various verticals, reflecting how Databricks believes agents should be built.
Agent Bricks originated from the need of Databricks' customers to effectively evaluate their AI agents. Ensuring reliability involves defining clear criteria and practices for comparing agent performance. According to Frankle, AI's inherent unpredictability makes LLM judges crucial for determining when an agent is functioning correctly. This requires ensuring that the LLM judge understands the intended purpose and measurement criteria, essentially aligning the LLM's judgment with that of a human judge. The goal is to create a scaled reinforcement learning system where judges can train an agent to behave as developers intend, reducing the reliance on manually labeled data.
Databricks' new features aim to simplify AI development by using AI to build agents and the pipelines that feed them. Fueled by user feedback, these features include a framework for automating agent building and a no-code interface for creating pipelines for applications. Kevin Petrie, an analyst at BARC U.S., noted that these announcements help Databricks users apply AI and GenAI applications to their proprietary data sets, thereby gaining a competitive advantage. Agent Bricks is currently in beta testing and helps users avoid the trap of "vibe coding" by forcing rigorous testing and evaluation until the model is extremely reliable.
ImgSrc: www.verdict.co.
References :
Agent Bricks originated from the need of Databricks' customers to effectively evaluate their AI agents. Ensuring reliability involves defining clear criteria and practices for comparing agent performance. According to Frankle, AI's inherent unpredictability makes LLM judges crucial for determining when an agent is functioning correctly. This requires ensuring that the LLM judge understands the intended purpose and measurement criteria, essentially aligning the LLM's judgment with that of a human judge. The goal is to create a scaled reinforcement learning system where judges can train an agent to behave as developers intend, reducing the reliance on manually labeled data.
Databricks' new features aim to simplify AI development by using AI to build agents and the pipelines that feed them. Fueled by user feedback, these features include a framework for automating agent building and a no-code interface for creating pipelines for applications. Kevin Petrie, an analyst at BARC U.S., noted that these announcements help Databricks users apply AI and GenAI applications to their proprietary data sets, thereby gaining a competitive advantage. Agent Bricks is currently in beta testing and helps users avoid the trap of "vibe coding" by forcing rigorous testing and evaluation until the model is extremely reliable.
ImgSrc: www.verdict.co.
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References :
- www.bigdatawire.com: Databricks Wants to Take the Pain Out of Building, Deploying AI Agents with Bricks
- siliconangle.com: The best judge of artificial intelligence could be AI — at least that’s the idea behind Databricks Inc.’s new tool, Agent Bricks.
- thenewstack.io: Databricks Launches Agent Bricks, Its New No-Code AI Agent Builder
- www.infoworld.com: Databricks has released a beta version of a new agent building interface to help enterprises automate and optimize the agent building process.
- thenewstack.io: Databricks Launches Agent Bricks, Its New No-Code AI Agent Builder
- AI News | VentureBeat: Databricks Agent Bricks automates enterprise AI agent optimization and evaluation, eliminating manual processes that block production deployments.
- SiliconANGLE: The best judge of artificial intelligence could be AI — at least that’s the idea behind Databricks Inc.’s new tool, Agent Bricks.
- BigDATAwire: Databricks today launched Agent Bricks, a new offering aimed at helping customers AI agent systems up and running quickly, with the cost, safety, and efficiency they demand.
- Analytics India Magazine: Databricks also launched MLflow 3.0, a redesigned version of its AI lifecycle management platform.
- Verdict: Databricks introduces Agent Bricks for AI agent development
- www.verdict.co.uk: Databricks introduces Agent Bricks for AI agent development
- www.bigdatawire.com: Databricks Is Making a Long-Term Play to Fix AI’s Biggest Constraint
- techstrong.ai: Databricks Simplifies Building and Training of AI Agents
Classification:
- HashTags: #AI #Databricks #AIAgents
- Company: Databricks
- Target: AI Developers
- Product: Mosaic AI
- Feature: Agent Bricks
- Type: AI
- Severity: Informative