What happens when marketing teams spend countless hours on manual campaign analysis while missing critical market opportunities? In this session, discover how AI is transforming marketing from a cost centre into a revenue-driving powerhouse. You'll see how Snowflake's Cortex AI enables marketers to automatically classify campaign assets, analyse multimodal performance data, and generate personalised content at scale—all without waiting for post-campaign analysis. This is marketing analytics reimagined—where AI democratizes data science, accelerates decision-making, and turns every campaign into a learning opportunity that drives immediate business impact.

This customer-led session will outline how Storio, a data-powered ecommerce business specialising in personalised photo products, has unified a fragmented ML development process onto a single platform, on Snowflake. The result - a streamlined, high quality, self-serve workflow for data scientists to build and deploy models towards efficient business decision-making and delightful end customer experiences alike.

This session will focus on how organizations are extracting significant business value by democratizing their data and optimizing resources through the Snowflake AI Data Cloud. The first part of the presentation will showcase how Snowflake helps customers craft compelling value stories for diverse AI use cases and strategic migrations, alongside best practices for optimizing cloud spend. The second part will feature a conversation highlighting how a leading enterprise overcame the common challenges of data silos and dashboard sprawl by simplifying processes with Snowflake AI capabilities. Attendees will learn actionable strategies for accelerating their AI journey and achieving measurable impact.

The retail and consumer goods sector is at a crossroads. As AI becomes integrated into every application and data floods the industry, companies are in a race to adapt to the new digital-first reality, reinventing their business for the digital shelf. This session will explore how a unified AI and data strategy can empower your business to master the omnichannel and "phygital" marketplace, build a more resilient supply chain, and unlock peak operational efficiency. Learn how putting centralized governance and open collaboration on Snowflake at the core of your strategy can help you win in this new era.

This session is for builders who want to move fast. Daniel Myers will kick things off by showcasing how Snowflake's AI Data Cloud helps startups accelerate their time to market. Then, hear directly from Panaseer and Eunice AI as they share their journeys, technical architectures, and the lessons they learned while building cutting-edge AI products on Snowflake.

This panel brings together industry leaders to explore how they are harnessing data and AI to drive customer engagement, optimise operations and fuel business growth. From unifying customer data across channels, to leveraging AI for predictive insights and automation, our panelists will share real-world strategies and success stories showing how they are moving beyond basic analytics to create intelligent, data-driven strategies that impact every part of the business.

Navigating an AI-powered, data-driven financial services future can be challenging, particularly as the industry faces greater pressure to demonstrate tangible returns on their AI investments. Join the Financial Services keynote at London Snowflake World Tour and hear directly from industry leaders about their partnerships with Snowflake, the business and technology challenges they’re looking to solve and the key use cases they’re implementing. And learn what the latest Snowflake announcements mean for the industry. Whether you’re a business executive, a technology leader or a Snowflake user, this session will provide actionable insights on how to architect for data and AI ROI.

This session will explore why and how Snowflake's unique capabilities are crucial to enable, accelerate and implement industrial IoT use cases like root cause analysis of asset failure, predictive maintenance and quality management. The session will explain the use of specific time series capabilities (e.g. asof joins, CORR & MATCH function), built-in Cortex ML functions (like anomaly detection and forecasting) and LLMs leveraging RAG to accelerate use cases for manufacturing customers.

In the era of accelerated digital transformation, the UK public sector stands at the crossroads of unprecedented opportunity and significant responsibility. Aligning with critical administrative priorities — such as enhancing citizen experience, improving cybersecurity posture and increasing government efficiency — requires practical, innovative solutions. Join us to explore how Snowflake's AI Data Cloud for Government & Education enables AI-driven analytics and data collaboration to deliver measurable impact on mission-critical operations. Showcasing real-world UK public sector use case demos, we will highlight how leading government organisations can leverage AI to drive data-informed decision-making, automate processes and transform public service delivery.

Learn how to seamlessly build, distribute, and deploy advanced enterprise-grade AI and data apps with efficiency. Discover built-in tools and programs that streamline commercialization for both you and your customers. Join us for new product and feature overviews, best practices, and live demos.

What if you could turn all of your company's data into a single, intelligent conversation? That's the promise of agentic AI. In this session, you'll see how to create and deploy a no-code agentic AI solution directly using Snowflake Intelligence. Get ready for a live demo that proves you can make critical insights instantly accessible to everyone, with a simple, conversational interface. No more sifting through dashboards. You will discover how to just ask your data a question and get an answer you could trust with Snowflake Intelligence.

Está no ar, o Data Hackers News !! Os assuntos mais quentes da semana, com as principais notícias da área de Dados, IA e Tecnologia, que você também encontra na nossa Newsletter semanal, agora no Podcast do Data Hackers !! Aperte o play e ouça agora, o Data Hackers News dessa semana ! Para saber tudo sobre o que está acontecendo na área de dados, se inscreva na Newsletter semanal: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.datahackers.news/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Conheça nossos comentaristas do Data Hackers News: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Monique Femme⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠Matérias/assuntos comentados: Demais canais do Data Hackers: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Site⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tik Tok⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠You Tube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

You have likely witnessed the hype-cycle around MCP (the Model-Context Protocol) for LLMs. It was heralded as \"the universal interface between LLMs and the world\" but then faded into the background as attention shifted towards AI Agents. Yet, the background of your AI app is exactly where an MCP should be, and in this talk we cover why. We will tour the MCP protocol, the Python reference implementation, and an example agent using an MCP. Expect protocol flow-charts, architecture diagrams, and a real-world demo. You will walk away knowing the core ideas of MCP, how it connects to the broader ecosystem, and how to power your AI agents.

Sewage pipes may not be the most glamorous subject, but they are critical to how our cities function. Me and my team have been developing tools to automatically annotate faults in sewage pipes. One of the functionalities we explored is to predict and record water level during the surveys, since it affects how much of the pipe can be inspected. In this talk, I will share the approaches we have explored and some insights into their effectiveness and the challenges we faced.

Brought to You By: •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more. Most teams end up in this situation: ship a feature to 10% of users, wait a week, check three different tools, try to correlate the data, and you’re still unsure if it worked. The problem is that each tool has its own user identification and segmentation logic. Statsig solved this problem by building everything within a unified platform. Check out Statsig. •⁠ Linear – The system for modern product development. In the episode, Armin talks about how he uses an army of “AI interns” at his startup. With Linear, you can easily do the same: Linear’s Cursor integration lets you add Cursor as an agent to your workspace. This agent then works alongside you and your team to make code changes or answer questions. You’ve got to try it out: give Linear a spin and see how it integrates with Cursor. — Armin Ronacher is the creator of the Flask framework for Python, was one of the first engineers hired at Sentry, and now the co-founder of a new startup. He has spent his career thinking deeply about how tools shape the way we build software. In this episode of The Pragmatic Engineer Podcast, he joins me to talk about how programming languages compare, why Rust may not be ideal for early-stage startups, and how AI tools are transforming the way engineers work. Armin shares his view on what continues to make certain languages worth learning, and how agentic coding is driving people to work more, sometimes to their own detriment.  We also discuss:  • Why the Python 2 to 3 migration was more challenging than expected • How Python, Go, Rust, and TypeScript stack up for different kinds of work  • How AI tools are changing the need for unified codebases • What Armin learned about error handling from his time at Sentry • And much more  Jump to interesting parts: • (06:53) How Python, Go, and Rust stack up and when to use each one • (30:08) Why Armin has changed his mind about AI tools • (50:32) How important are language choices from an error-handling perspective? — Timestamps (00:00) Intro (01:34) Why the Python 2 to 3 migration created so many challenges (06:53) How Python, Go, and Rust stack up and when to use each one (08:35) The friction points that make Rust a bad fit for startups (12:28) How Armin thinks about choosing a language for building a startup (22:33) How AI is impacting the need for unified code bases (24:19) The use cases where AI coding tools excel  (30:08) Why Armin has changed his mind about AI tools (38:04) Why different programming languages still matter but may not in an AI-driven future (42:13) Why agentic coding is driving people to work more and why that’s not always good (47:41) Armin’s error-handling takeaways from working at Sentry  (50:32) How important is language choice from an error-handling perspective (56:02) Why the current SDLC still doesn’t prioritize error handling  (1:04:18) The challenges language designers face  (1:05:40) What Armin learned from working in startups and who thrives in that environment (1:11:39) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode:

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Are dashboards dead? For complex enterprise use cases, the answer might be yes. In this episode, I'm joined by Irina Malkova (VP Data & AI at Salesforce), to discuss her team's transformational journey from building complex dashboards to deploying AI-powered conversational agents. We dive deep into how this shift is not just a change in tooling, but a fundamental change in how users access insights and how data teams measure their impact.

Join us as we cover: The Shift from Dashboards to Agents: We discuss why dashboards can create a high cognitive load and fail users in complex scenarios , and how conversational agents in the flow of work (like Slack) provide targeted, actionable insights and boost adoption.What is Product Telemetry?: Irina explains how telemetry is evolving from a simple engineering observability use case to a critical data source for AI, machine learning, and recommendation systems.Why Standard RAG Fails in the Enterprise: Irina shares why typical RAG approaches break down on dense, entity-rich corporate data (like Salesforce's help docs) where semantic similarity isn't enough, leading to the rise of Graph RAG.The New, Measurable ROI of Data: How moving from BI to agents allows data teams to precisely measure impact, track downstream actions, and finally have a concrete answer to the ROI question that was previously impossible to justify.Data Teams as Enterprise Leaders: Why data teams are uniquely positioned to lead AI transformation, as they hold the enterprise "ontology" and have experience building products under uncertainty.

Send us a text This week, we’re rewinding one of our most talked-about episodes! Richmond Alake, Developer Advocate at MongoDB, joins us to explore how databases power the future of AI. From RAG best practices to the truth behind AGI hype, Richmond breaks down what it takes to build systems that scale — and think. Show Notes 02:05 Meet Rich Alake 03:57 A Developer Advocate at MongoDB 05:57 Passions and Fate! 08:52 AI Hype 13:14 Oh No… AGI Again 17:30 What Makes an AI Database? 20:42 Use Cases 25:41 RAG Best Practices 27:40 The Role of Databases 30:05 Why MongoDB Does It Better 32:43 What’s Next 36:13 Advice on Continuous Learning 38:44 Where to Find RichConnect with Richmond: 🔗 LinkedIn 🌐 MongoDB Website 🧠 Register for MongoDB 🤖 AI Agents Article 💾 Best Repo for AI Developers Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

In this episode, we dive into a new version of WormGazer as described in a recent GeroScience paper. This implementation automates movement monitoring in C. elegans populations as a rapid healthspan measure, offering a shortcut to detect ageing interventions and trade-offs.

Highlights include: • Monitoring multiple Petri dishes in parallel with cameras and image analysis over 7–14 days  • Showing that most functional decline happens in the first week of adulthood  • Validating with age-1(hx546) mutants, which remain active longer but move more slowly early on  • A dose-response test with sulfamethoxazole (SMX) where movement improvements are detectable within 7 days, compared to 40 days needed for traditional lifespan assays  • The benefit: non-invasive, scalable, and faster detection of ageing effects and negative trade-offs 

📖 Based on the research article: “Rapid measurement of ageing by automated monitoring of movement of C. elegans populations”

Giulia Zavagno, Adelaide Raimundo, Andy Kirby, Christopher Saunter & David Weinkove Published in GeroScience (November 2023) 

🔗 https://doi.org/10.1007/s11357-023-00998-w 

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This podcast is generated with artificial intelligence and curated by Veeren. If you’d like your publication featured on the show, please get in touch.

📩 More info: 🔗 ⁠⁠www.veerenchauhan.com⁠⁠ 📧 [email protected]