Generative BI is not just an evolution of Business Intelligence.
It’s a structural shift in how organizations think, interact, and decide with data.
For years, BI promised democratization. In reality, many companies are still stuck between: IT bottlenecks Low data literacy
ENTERPRISE AI
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Generative BI: Beyond Evolution, a Structural Shift in Data Decision-Making
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Banking Unfiltered: Separating AI Reality from Hype
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SAS' Diana Rothfuss hosts the new short video series, Brewing Curiosity: Banking Unfiltered, to help separate AI reality from AI hype in this highly regulated industry … Less than 10 minutes and 0 fluff.
— SAS Software (@SASsoftware) 30 mars 2026
Watch the first full episode on YouTube now: https://t.co/lwSFTcwNdp ☕ pic.twitter.com/r993H3XV7dSAS' Diana Rothfuss hosts the new short video series, Brewing Curiosity: Banking Unfiltered, to help separate AI reality from AI hype in this highly regulated industry … Less than 10 minutes and 0 fluff. Watch the first full episode on YouTube now: http://
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Sycamore: New Enterprise Agent OS from Sri’s Team
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Sri is building Sycamore: an agent OS for the enterprise. Great team and great product concept. Can't wait for the launch 🙂
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Jensen Huang at Interrupt: Enterprise Agents and LangChain Partnership
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Jensen Huang is coming to Interrupt. May 13-14 in SF. Join Jensen and Harrison for a fireside chat to learn where enterprise agents are headed. We'll dive into the LangChain x @nvidia partnership and how Deep Agents, NVIDIA Nemotron models, and the NVIDIA Agent Toolkit enable production-grade claws for the enterprise. Get tickets: interrupt.langchain.com/
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AI agents integration in modern workflows
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These impacts were measured before practical agents (like Claude Code) and companies are still early in figuring out how to incorporate AI into their workflows.
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Multi-outcome prediction model achieves 14% improvement in 10ms
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We built a model that predicts multiple correlated outcomes simultaneously: portfolio risk, grid balancing, supply chains. In 10ms with no calibration required and it's 14% better than the best alternative. Check out the research: https://
arxiv.org/pdf/2603.20266 -
Running Operational Workloads with Lakebase, Databricks Apps, Agents
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See how to run operational workloads on the lakehouse using Lakebase, Databricks Apps, and Agent Bricks. This BrickTalks session covers how teams are building data apps and AI agents on top of serverless Postgres to automate workflows and make data usable in real applications.
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Clinical Teams Build Interactive Apps with Real-Time Results
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Clinical and RWE teams are building interactive applications with real-time results But adoption stalls without clear use cases, intuitive design, and the right governance model. Join us on 4/16 for lessons applicable to the whole organization. https://
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CAID: Multi-Agent Coordination Improves Coding Task Accuracy
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NEW research from CMU. (bookmark this one) The biggest unlock in coding agents is understanding strategies for how to run them asynchronously. Simply giving a single agent more iterations helps, but does not scale well. And multi-agent research shows that coordination > compute. A new paper from CMU proves this with a practical multi-agent system. CAID (Centralized Asynchronous Isolated Delegation) borrows proven human SWE practices: a manager builds a dependency graph, delegates tasks to engineer agents who work in isolated git worktrees, execute concurrently, self-verify with tests, and integrate via git merge. CAID improves accuracy over single-agent baselines by 26.7% absolute on paper reproduction tasks (PaperBench) and 14.3% on the Python library development tasks (Commit0). The key insight is that isolation plus explicit integration beats both single-agent scaling and naive multi-agent approaches. For long-horizon software engineering tasks, multi-agent coordination using git-native primitives should be the default strategy, not a fallback. Paper: arxiv.org/abs/2603.21489 Learn to build effective AI agents in our academy: academy.dair.ai/
→ View original post on X — @debashis_dutta, 2026-03-30 14:41 UTC
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NVIDIA Unveils ProRL Agent for Reinforcement Learning of LLM Agents
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NVIDIA AI Unveils ProRL Agent: A Service Infrastructure for Reinforcement Learning of Multi Turn LLM Agents at Scale! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang