Razi Raziuddin

Super excited about the Databricks AI Summit next week! If you are there, come check out my session. I'll be talking with Mitchell Weiss (@mitchbweiss ) from Vail Resorts about all the unique needs Vail has as a company and how they are building a great modern architecture tailored to their needs, as well as how they are embracing a #lakehouse architecture and Amperity. "MODERNIZING DATA: LEVERAGING LAKEHOUSE ARCHITECTURE & DELTA SHARING" https://lnkd.in/g-n-YNVp

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The Forbes 2024 Cloud 100 List is live ☁ Congrats to all the honorees – the world's top 100 private cloud companies –including the 3 healthcare and life sciences companies featured this year: • Benchling - biotech R&D platform • Komodo Health - healthcare data analytics • Abridge - AI for clinical documentation For more on how AI is colliding with cloud computing, check out Bessemer Venture Partners's 2024 Cloud 100 report. Personally I'm focused on advancements in multi-modal AI, as applied to biomedical applications (Trend 3!): https://lnkd.in/euzurvQV

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🚀 "Came for the speed, stayed for the syntax."💡 That's what Marco Gorelli had to say about using Polars. 🐻‍❄️ This educational session from our recent Plotly Community call, presented by Mike Purtell, provides a data scientist's perspective on use of Polars with Plotly. https://lnkd.in/esyKAJv3 #datascience #python #pandas #polars #plotly

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My first thought when I saw this story from VentureBeat was 'Chainsaw Massacre'. Thankfully, this is more of a #dataanalytics solution from Stream Analyze "But Stream Analyze believes its tech is superior to others because it is an “end-to-end platform for machine learning op[erations]” according to Spahr, one that identifies the correct data to record and upload from the field back to cloud servers, without capturing needless data that would increase the cost, computational and energetic requirements." ________________________ Catch up on #technews like this on Teckedin.com - my public knowledge base site. _______________________ #ai #automation #datamanagement https://lnkd.in/gBcnNuRR

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Check out our latest blog from Adam Gloe TribalScale #AITransformation #DigitalTransformation #RightTheFuture https://lnkd.in/eBW8RjwY

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More TI (ServiceTitan AI initiative aka Titan Intelligence) features were also announced during ServiceTitan CEO, Ara Mahdessian, keynote including our first Agentic AI solution, The Virtual AI Agent, within Contact Center Pro, which captures calls on nights and weekends and decreases the call center burden by half. We also released to all Phones customers Second-Chance Leads, TI-powered feature that identifies calls that could have been booked by the call center but weren’t — and alerts contractors that they should call back to win the job. Ara called it “one of the most powerful capabilities we have ever built at ServiceTitan." https://lnkd.in/ginaepVK

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This acquisition highlights the importance of data management as a critical precursor to implementing generative AI. From the WSJ: "Data is a critical part of enabling generative AI because vast quantities of it are needed to train AI models like OpenAI’s GPT-4 and Anthropic’s Claude. For businesses, their private data is needed to customize those AI models to perform data analysis, summarization and other tasks with it. Without it, AI models are limited to what they have learned from their initial training on public data online, up to a certain point in time." https://lnkd.in/gXMAhJ26

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Success with generative AI can only be unlocked by strategically using an organization’s unstructured data. This is giving rise to an emerging unstructured data stack, which consists of three crucial components: 1️⃣ data extraction and ingestion 2️⃣ data processing 3️⃣ data management In this post, I share more context about the solutions in these spaces and how they are used: LlamaIndex Reducto Tensorlake unstructured.io Vectorize Eventual Databricks Polars Anyscale Pandas Onehouse Tabular (now part of Databricks) Chroma Pinecone Supabase Spiral LanceDB MongoDB Stately Neo4j FalkorDB TigerGraph https://lnkd.in/dT74Yj3C

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Great to see not only one but two of our portfolio companies in a podcast! If you want to learn how you can squeeze double (or more) the performance out of your database, have a look.

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I will be speaking at the Generative AI & ML tech series in Los Angeles in October. For more details check out the post below. #genAI #ml #ai #speaker

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At a Generative AI thought leadership dinner with other CTOs in NYC today and some interesting trends are emerging: * a consensus that LLMs are converging on a general set of features and basically comparable performance * a consensus that an org's data pipelines will matter more than the LLM chosen * and a group of people who read the TOS that are really scares about what these LLMs will do with access to all your data. Lastly, my prediction: the work of tech is moving from the keyboard to the whiteboard. Ai as microservice means structuring your data, thinking with ai, and chaining ai agents will supercharge your career and your cause -- but only if social change orgs platform their data. In my study of polymaths, Charles Babbage designed the basic idea for a unit of computing being something that takes an input, does something to it and gives an output -- the so called Babbage difference engine. In a real way, GenAI is approaching a world where chaining inputs ala a babbage difference engine is accessible to all. This can be an awesome opportunity if we get Non profits to work together!

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Excited to share an update on one of our collaboration projects at CATO AI! We’ve partnered with Perspect Analytics Inc. and Conscious Asset to design and build an AI-enabled maintenance planning support tool. In his blog, James Reyes-Picknell describes some of the challenges maintenance organizations face, and how this tool will greatly help planner productivity. Check it out. An excerpt below: “The tool will create high quality, draft maintenance job plans in mere seconds, as opposed to days (the manual way). The plans will require planner review, but it’s far less effort than starting with a blank screen. It can be used to rapidly build that library of saved standard jobs. It won’t take planner jobs away, but it will make them far more productive. That tool is already in advanced stages of development, and it is already producing results. It will soon be available for Beta testing in the field, and then deployment in basic, premium, and enterprise variants. We believe it will disrupt the planning “world” as it is today, greatly enhance planner productivity, the quality of job plans, and it is coming soon. If you are interested in being involved in our Beta-testing, please let us know. If you want updates on our progress towards a launch, then let us know.

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🚀 The Evolution of AI Chatbots: Agentic Workflows in Business 🚀 Interested in learning how AI is transforming workflows and enhancing business processes? Join Michael Slater, Technical Director at Improving, for a deep dive into agentic workflows and the next generation of AI chatbots. Discover how these advanced systems move beyond basic RAG (Retrieval-Augmented Generation) to deliver autonomous, multi-functional support in business environments. 🗓 November 11, 2024 | 11amMT/12pmCT Key takeaways: ➤ How RAG systems are advancing beyond basic chat over docs/data ➤ The role of agentic workflows in enhancing AI chatbot capabilities ➤ Real-world applications of advanced AI for business transformation   Register here 👉 https://lnkd.in/gkK9si8N #LifeAtImproving #AIChatbots #AgenticWorkflows #BusinessTransformation #TechWebinar #AIInnovation

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There is no AI if your data isn’t in order! And that’s not any data, ALL data wherever it lives, however it looks and whenever you need it! CrateDB the dark horse of the high volume, realtime, distributed database architecture and high performance. You know what, we index it all by default at ingestion so you don’t have to pick your favorite field! You love all your fields and you need them to be ready to be part of your insight on demand. Complex queries made easy when all your data can speak SQL no matter where it was born! That’s the Power of Simplicity.

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This was a great conversation with a great partner, Neo4j. If you want to hear more about the collision of knowledge graphs and gen AI, see the information below! #ExplainableAI #TrustworthyAI #KnowledgeGraphs

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In the world of data, we always hear people talk about centralized vs decentralized data architecture.  Why does it have to be either or?  Why not both?  Hear me out… Centralized and decentralized data strategies can co-exist.  Centralize your most critical, everyday analytics data for your daily dashboards and daily reports.  These don’t change often and it makes sense to build the pipelines to pull this data together reliably and cheaply. Decentralize everything else.  Why keep moving bits around when your boss only asks for something remotely related once in a blue moon?  Better off saving time, effort, and cost, without sacrificing access (if you have the right tool 😉) That’s the beauty of an open data lakehouse and the topic of discussion I had with Eric Kavanagh on in the latest episode of the #InsideAnalysis podcast.  We covered a few other hot topics: 1. The data landscape is never going to get simpler.  As Matt Turck can attest, the data landscape gets more complicated every year, a pure centralization strategy would require more and more complex data pipelines ad infinitum.  2. Keeping your architecture open allows you to stay agile and adaptable to the next big innovation (See bullet #1 above) 3. Trino (and Starburst) gives you what I call the “top half of the database” — just the powerful SQL engine without the underlying storage, so you can run it on whatever data you want. 4. For all the centralized stuff, we think Iceberg has been established as the industry standard, and Galaxy is the easiest way to get started with #Icehouse architecture. Listen to the full podcast here:

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Exploring AI? Let's start with the fundamental question... Do you have the right data? Get Tealium's complimentary data guide. Together, we'll get you on the right track for the best AI outputs: https://gag.gl/O08Ylv.

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Congrats to the companies spotlighted on CRN’s inaugural AI 100 list! From NVIDIA and Microsoft to Dell Technologies and Wiz, these 100 artificial intelligence market leaders are the ones making waves in the boiling-hot AI industry with billions of dollars expected to be poured into new AI technology this year. #CRNAI100

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Observability tools should be your system's therapist, not its librarian. The data haystack is growing faster than our ability to find the needle—a useful piece of data. To keep up with skyrocketing data volumes, enterprises today find themselves trapped in an observability maze that’s extremely complex and costly. Traditional solutions have actually exacerbated the problem, creating new traps organizations struggle to escape.AI is driving us toward the brink of a new and necessary wave of observability: one that addresses data overload, high costs, human bottlenecks, and persistent downtime. Our path out of the observability maze is becoming clearer. Here’s how. Ping if you're thinking about the space https://lnkd.in/gmrYVzrY

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