How to get frontier AI performance at 1/10th the cost with Databricks and GEPA

Controversial take: Always jumping on the newest OpenAI model for every GenAI task on Databricks? 🚨 That’s a fast track to exploding costs without guaranteed ROI. Here’s what enterprise teams often overlook: - **Cost vs. Performance:** The latest LLMs (large language models) are undeniably powerful, but they come with premium pricing. For many routine or less complex tasks, older models deliver *very* close results at a fraction of the cost. - **Task Suitability:** Not every AI workload demands the bleeding edge. For example, data preprocessing, simpler question answering, or low-risk coding assistance can run efficiently on more cost-effective models. - **Strategic Model Selection:** Enterprises scaling GenAI on Databricks benefit from a hybrid approach—deploying newer models selectively where precision justifies expense, while leveraging older or fine-tuned models for bulk operations. - **Benchmark and Monitor:** Continuously measure your model’s business impact versus cost. Blind adoption of every new OpenAI release often leads to budget overruns with marginal utility gains. The real win? Thoughtful, use-case-driven model choices—not a “latest model at all costs” mentality. Have you encountered budget surprises chasing every new AI upgrade? How do you balance innovation and pragmatism in your AI deployments? I’d love to hear your strategies. #EnterpriseAI #DataStrategy #GenAI #OpenAI #CostOptimization #MLops #AIPragmatism #Databricks #AIEconomics

🚀 San Francisco-based Databricks has signed a $100M multi-year deal with OpenAI to bring GPT-5 and other cutting-edge models directly into the Databricks Data Intelligence Platform and Agent Bricks. 👉 This integration gives 20,000+ Databricks customers seamless access to OpenAI’s latest models, making GPT-5 a flagship tool for enterprise AI adoption. ✨More details: https://lnkd.in/d4YEGDRF Ali Ghodsi Dave Conte Amy Reichanadter Ron Gabrisko Rick Schultz Hatim Binani #ai #data #innovation #partnership #openai #investment #ustech #gpt5 #enterpriseai #artificialintelligence

Excited by the pace of innovation in #AI, #MachineLearning, and #CloudComputing! In recent months, I’ve been exploring how platforms like AWS SageMaker, Azure ML Studio, and emerging frameworks such as PyTorch and Hugging Face are transforming the way financial and healthcare organizations harness data for real-time insights and smarter decisions. Automated ML pipelines with tools like Apache Airflow and Docker are making deployments faster and more reliable than ever. The rise of generative AI, advanced NLP techniques, and scalable data engineering with Spark and Snowflake have opened up new possibilities—from enhancing fraud detection to optimizing patient outcomes and portfolio risk analytics. I’m continually impressed by the growing impact of interactive dashboards (Tableau, Power BI, Streamlit) in driving business transparency and empowering cross-functional teams. As we move into 2026, the synergy of AI, automation, and cloud-driven analytics will reshape how we deliver value in every industry. Excited to connect with fellow innovators and share thoughts on driving impact with these technologies! #DataScience #Fintech #HealthcareAI #MLops #CloudTech #Innovation #TechLeadership Let me know if you’d like a version focused more specifically on a single domain (finance, healthcare, etc.) or with a personal project highlight!

🚨 Breaking: OpenAI × Databricks just announced a $100M partnership — and it could change enterprise AI forever. Meaning - ✅ OpenAI models (including GPT-5) are now natively integrated into Databricks. You can run OpenAI directly inside the Databricks Data Intelligence Platform and its agent framework, Agent Bricks. ✅ No data movement needed → Instead of exporting data to external APIs, the models now live where your enterprise data lives. ✅ Governance + security included.→ Integration leverages Unity Catalog, meaning compliance and audit trails are built in. 🚀 Why this matters 👉 Data + AI finally converge 👉 Cost + performance optimization 💡 My take This isn’t just hype. It’s a clear signal that the next wave of AI adoption will be data-centric. Models + data + governance, all in one stack. ⚡ Follow Sagar Agarwal for more on GenAI + Data Engineering updates. #databricks #openAI

🚀 What is AI Query in Databricks? Let’s break it down simply! 🧠✨ Imagine you have a magical assistant who can instantly read heaps of information, understand it, and then give you quick answers or summaries—without you having to dig through all that data yourself. That’s exactly what AI Query in Databricks does! The ai_query function provides a simple way to apply AI directly on your data within Databricks. It supports querying powerful AI models from different sources: the Databricks foundation model endpoint, external model endpoints, and even your own custom model endpoints using Databricks Model Serving. How to use AI Query? Here’s the basic syntax: #sql ai_query(endpoint, request) endpoint: The name of the AI model endpoint you want to query. request: The question or command you want to ask the AI about your data. For example, to summarize customer reviews, you might write: #sql SELECT ai_query('databricks-meta-llama-3-3-70b-instruct', 'Summarize the key points of these reviews') AS summary FROM customer_reviews; With AI Query, you can: Summarize content Extract insights Detect fraud Forecast trends ... all with a simple query. And you don’t need to be a tech expert! Whether it’s summarizing feedback, translating text, or predicting sales, AI Query lets you unlock AI insights directly where your data lives—easily and efficiently. Imagine telling your data, "Give me a quick summary of these reviews," and getting an instant, clear answer – right inside Databricks. No jargon, no complexity, just actionable insights. This is a game changer for businesses wanting to benefit from AI without the tech headache. Ready to simplify your data with AI? 🔥 #AI #Databricks #DataScience #BusinessInsights #EasyAI #DataMagic

Databricks now lets you run OpenAI models (like GPT-5) directly on your enterprise data. Most AI tools or products force you to move your data into their product — adding cost, risk, and endless API hops. This changes that. Now, agents inside Databricks can securely work with large, complex business datasets — accelerating AI-driven processes and giving you faster answers to your most critical questions. At LBMC we remain committed to building AI readiness through data readiness in Databricks. #AI #Databricks #EnterpriseAI #Agents https://lnkd.in/eUYefPhR

🔥 Databricks + OpenAI = Enterprise AI leveled up 🔥 When I saw this partnership, the only thing that came to mind was Goku and Vegeta doing the fusion dance. But in all seriousness, this changes a lot. Running OpenAI models directly inside Databricks means: ✅ No more juggling tools and moving data around ✅ Governance and compliance built in from the start ✅ AI agents that actually scale with enterprise data, not just toy demos At ⋮IWConnect, we already see how powerful it is when data and intelligence sit closer together. This partnership takes it to a whole new level. 👉 The question is: if you had enterprise-grade AI running natively on your data, what’s the first use case you’d unlock? (And yes… automating inbox replies is still everyone’s secret wish 😉)

🚀 𝐆𝐚𝐦𝐞-𝐂𝐡𝐚𝐧𝐠𝐞𝐫: 𝐑𝐮𝐧 𝐎𝐩𝐞𝐧𝐀𝐈 𝐌𝐨𝐝𝐞𝐥𝐬 𝐃𝐢𝐫𝐞𝐜𝐭𝐥𝐲 𝐢𝐧 𝐃𝐚𝐭𝐚𝐛𝐫𝐢𝐜𝐤𝐬! 🤖✨ Databricks just announced a powerful new integration — you can now run OpenAI models directly within Databricks. This unlocks seamless AI workflows by bringing LLMs closer to your data, enabling: ✅ Faster AI development ✅ Secure, governed access to enterprise data ✅ Simplified deployment for real-world use cases ✅ Run GPT-5 with API or SQL — no extra setup required ✅ Build domain-specific AI agents powered by your own enterprise data ✅ Ensure secure, governed integration to stay compliant and trusted This is a game-changer for teams looking to combine data, governance, and cutting-edge AI in one seamless platform. 🌐💡 🔗 𝙍𝙚𝙖𝙙 𝙢𝙤𝙧𝙚: https://lnkd.in/gRUZkPr9 #databricks #openai #generativeai #machinelearning #llm #dataengineering #aiinnovation #enterprisedata ✨ 💥𝙁𝙤𝙡𝙡𝙤𝙬 𝙢𝙚 for more interesting posts on #farbic #databricks, #ai, and #data tech updates 🚀

Databricks + OpenAI: The Platform Bet You Should Be Watching This is more than another product deal. Databricks is turning OpenAI from “API you call externally” into a native service on its data platform. No more data extraction, no more tool sprawl. Cost, speed & scale are being rewritten. In tests, Agent Bricks + GPT‑5 can operate 90× cheaper than traditional setups. That opens the door for signal hubs inside enterprises to scale affordably. Boards and C‑suite: this shifts your ask from “should we AI?” to “how fast can we pivot infrastructure?” Because when your data platform includes the AI models, you go from experiment to authority. Security & trust have to be baked in, not bolted on. Any signal hub built on this must deliver explainability, audit trails, governance, human‑in‑the‑loop oversight. Otherwise, you risk “AI decisions from a black box.” The signal is: Infrastructure is the future of AI. What used to be “app layer AI” is now moving downwards, into data systems, not sitting on top. Your next competitive margin is whether your org can move with that shift. If you’re advising boards or preparing a 2026 strategy, this is your “moment of rebase.” • What’s your org’s plan for embedding AI as infrastructure? • Are your leaders ready to shift from “pilot projects” to “platform bets”? Drop a comment or DM me.

• Databricks inks a multi-year deal with a $100M minimum commitment to integrate OpenAI’s latest models—including GPT-5—into its data platform and Agent Bricks. • GPT-5 is positioned as the flagship option; models are accessible via SQL and API to build AI apps and agents on secure enterprise data. • Agent Bricks now benchmarks model performance per task and fine-tunes for accuracy; support includes OpenAI’s open-weight gpt-oss 20B and 120B. • The structure guarantees revenue for OpenAI and shifts downside risk to Databricks, as the AI leader scales data center buildout. • Mirrors Databricks’ Anthropic deal and underscores accelerating enterprise demand, with customers like Mastercard seeking native access. 🔔 Follow us for daily AI updates! 📘 Facebook: https://lnkd.in/gxDt7PJa 📸 Instagram: https://lnkd.in/gmYfWDbF #Databricks #OpenAI #GPT5 #EnterpriseAI #AIGenerated #CreatedWithAI