Eric Simone 🏢✈🚄🚚

New release from Packt Publishing… “Building Business-Ready Generative #AI Systems — Build Human-Centered Generative AI Systems with Context-Aware Agents, Memory, and LLMs for the Enterprise” See it at https://amzn.to/3Jdcio5 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼: 🔵Build an adaptive, context-aware AI controller with advanced memory strategies 🟢Enhance GenAISys with multi-domain, multimodal reasoning capabilities and Chain of Thought (CoT) 🟠Seamlessly integrate cutting-edge OpenAI and DeepSeek models as you see fit

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As systems with single-node ephemeral engines over #S3 become mainstream (hello bauplan!), a new wave of "format aware" caching tools is inevitable. Our friends at University of Wisconsin-Madison and InfluxData just released LiquidCache, a cloud-native cache built on Apache DataFusion, a disaggregated cache based on logical data representation with incredible performances: go and add a star to Xiangpeng Hao repo now! While bauplan cache works without custom formats (it's specifically built to be native for Apache Iceberg and Apache Arrow), it shares many of the same ideas: extracting #S3 scans from queries, re-using entries on overlapping requests and more importantly, representing scans with *logical* filters, supporting relational algebra inference across languages. Our paper from last year with Ryan Curtin is available here (and perhaps some new papers are brewing as well, who knows 😎): https://lnkd.in/eCmedBgf! Congrats to our friends Xiangpeng Hao, Andrew Lamb and Remzi Arpaci-Dusseau for the incredible work: look forward to geeking out on caching the next time we all chat! #iceberg #s3 #arrow #cache

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I’m excited to share that I’ll be leading an internal AI in 45 professional development session for our City Colleges of Chicago faculty: “Applying Generative AI Through the 9 Principles.” 🚀 This session focuses on a practical, human-centered approach to integrating generative AI into everyday academic and administrative workflows. The framework is based on nine core principles designed to make AI adoption clear, simple, and meaningful. ✨ THE 9 PRINCIPLES ✨ 1. Start from real work   2. Humans stay accountable   3. Everyone is a co-designer   4. Adoption is the primary KPI   5. Experimentation over fixed practices   6. Enablement is continuous   7. Transparency and trust   8. Mutual accountability for outcomes   9. Customer usefulness is the test  If you’d like to explore these principles in more depth, you can read my AI Enablement Manifesto here: https://lnkd.in/g8Sm4j3E  During the workshop, I’ll walk through each principle and share practical examples, teaching-centered scenarios, and actionable strategies that faculty can apply right away. 💡 I’m looking forward to supporting our faculty community as we explore meaningful and responsible uses of generative AI across our colleges. 🙌 #AIin45 #GenerativeAI #AIEnablement #HigherEd #FacultyDevelopment #InnovationInEducation #TeachingAndLearning #ProfessionalDevelopment #HumanCenteredAI

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John Celentano, Inside Towers, I look forward to the fireside chat with Charlie Ergen discussing his master planned Skyhattan. Now that he is free from building the 4th consumer network, he can move full speed ahead with autonomous systems. https://lnkd.in/gyJXAUQY Solutions like Artificial Intelligence, Intelligent Transportation, and Autonomous Systems will require a new network of services to support any scaled adoption. INTELLIGENT INFRASTRUCTURE will be our generation's Interstate Highway. Time to set the millions of autonomous robots free. Autonomous robotics will make the most significant impact on the maintenance and sustainment of $trillions of dollars of infrastructure. Autonomy Institute, ATRIUS Industries, Inc. https://lnkd.in/gzsWcxTr

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LLM Benchmarking Shows Capabilities Doubling Every 7 Months IEEE puts out a projection based on current scaling. Link: https://lnkd.in/gbR2pFty Carl Fraik Zack Huhn Summer Crenshaw Kelly Cohen Elisha Herrmann Josette Riep Ali Minai

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I am excited to share that Related Digital is developing a more than 1-gigawatt data center campus in Saline Township, Michigan exclusively for Oracle as part of OpenAI and Oracle’s previously announced partnership to deliver 4.5 gigawatts of additional Stargate capacity. This multi-billion project will create 2,500+ union construction jobs, 450+ jobs onsite, 1,500 jobs county-wide, as well as thousands more indirect jobs across Michigan and the U.S. Our Related Digital team is especially proud that this campus is being designed and built the right way — with a closed-loop cooling system that limits daily water use to levels comparable to an office building, the preservation of hundreds of acres of farmlands, wetlands, and woodlands, and a LEED-certified, sustainable design. Power to the site is being provided directly by DTE Energy using existing resources augmented by a new battery storage investment – financed entirely by the project – in a way that ensures there is no impact on DTE’s existing customers’ energy supply or rates. In fact, DTE’s customers will benefit from the project contributing its share to the fixed costs of maintaining and improving the grid. I am so proud of our team that has been working non-stop on this project. Read more about the news here: https://lnkd.in/gZJhQxkW

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Spear AI, a startup founded by U.S. Navy veterans, has raised its first round of outside capital to apply AI to submarine data. Spear AI specializes in preparing passive acoustic data (gathered by underwater listening devices) for AI algorithms. The startup's hardware and software platform helps the U.S. military and commercial clients label and sort complex acoustic data to help submarine operators understand whether an object is a whale, a rain squall, or a potential threat. The company raised $2.3 million from AI-focused venture firm Cortical Ventures and private equity firm Scare the Bear Capital. The funding will be used to double the company's headcount to support its government contracts (including a recent $6M U.S. Navy deal) and commercial business prospects, such as monitoring underwater pipelines. Congratulations to co-founders Michael Hunter and John McGunnigle, and the Spear AI team. Reuters: https://lnkd.in/dFqzEFSH #DefenseTech #AI #MaritimeSecurity #AcousticData #NationalSecurity #Funding #GovTech

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Why should Active Metadata Tags be the backbone of your AI strategy? Active Metadata Tags (AMTs) are used for automatic enrichment of metadata. Euno supports two types of custom metadata enrichment capabilities, both of which generate AMTs: #1 Extract structured metadata from unstructured metadata. This involved parsing metadata from elements like code and descriptions. A common application would be to enforce data modeling guardrails. Examples: → Implicit columns schema: Analyze dbt model code to determine whether the resulting schema includes implicit or explicit columns. → Verification checks: Assess naming conventions, detect use of approximate count distinct when querying large tables, evaluate documentation agility, flag full outer joins, and more. #2 Compose new AMTs. This approach combines metadata of a resource, and of any related resources, to set a new property on a resource. Examples: → Non-trivial custom SQL: Tag Tableau Custom SQL nodes that do not add logic. → Certified data source: Tag Tableau data sources as ‘certified’ if they don’t contain non-trivial custom SQL. → Certified dashboard: Tag Tableau dashboards as ‘certified’ if they only depend on certified data sources.   This capability is essential for governance workflows in large organizations where different teams maintain different parts of the stack. So team AI can build on something that team B created. Consider this scenario: → The team maintaining dbt can create a custom property to flag models for deprecation (e.g., models lacking both ‘prod’ and ‘prod_ready’ tags). → Analytics teams can then use this signal to create custom properties for their BI assets to drive workflows to migrate away from those models. Why does this also matter for AI agents? By implementing AMTs to surface trust signals, AI agents can actually tell the difference between exploratory work and official definitions. Example: → Euno’s MCP server surfaces to AI agents only Tableau logic that meets your trust standard and is considered certified such as: ‘depends only on dbt models from the gold layer and was in use in the past 60 days.’ *** Expect to hear much more about Active Metadata Tags! They’re quickly becoming the key to scale AI beyond the sandbox in your organization. #ActiveMetadata

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John Snow Labs Releases #GenerativeAI #Lab 7.0 to Help Domain Experts Evaluate and Improve #LLM Applications and Conduct #HCCCoding Reviews. This is a #NoCode Tool to let your domain experts validate, fine-tune, and provide specific feedback on #AI models. Available now on all the major cloud marketplace or for on-premise deployment. https://lnkd.in/g9UD8mQS

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Everyone thinks AI fails because of tech. But the real challenge? Change. Today, we’re launching a new way forward. To help Ohio lead the next wave of innovation, we’re launching the AI & Data Accelerator—a program built to help small businesses and public institutions not just learn AI, but actually use it. For the last two years collectively, we’ve built AI applications and trained thousands across healthcare, logistics, government, and more—backed by real projects, not theory. Through this new initiative—led by AI Leadership Institute, Big Kitty Labs , and Disruption Now Now—we’ll offer everything from: • AI fundamentals and literacy • Team upskilling and adoption strategy • Scalable, responsible AI implementation • Advanced use cases: building AI pilots and agents And here’s the best part: We have limited learning passes MidwestCon and are fully reimbursable through Ohio TechCred. The future of AI won’t be won by code—it’ll be won by those who know how to drive change. Join us. Brittany Roberts Chantel George Petra Vincent Matthew Sias Iyanuoluwa Odebode, Ph.D Kendra Ramirez Noelle R. Morgan Koth, CFP

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Great to see the administration focused on something really important for the country in the AI space, the AI Action Plan. https://lnkd.in/eSk2z_8h As our company experiences barriers every day in the government sector, some of these "removing red tape" focus areas will absolutely help speed adoption for new capabilities. Hopefully one of these focus areas become ATO processes to enable more rapid deployment of systems directly to end users and analysts on their networks and connected to the data they care about. National level compute, approved foundational models on network etc. are all critical to scale mission applications like Danti and many other application layer technologies. Also one of the paragraphs in how the United States Department of Defense can leverage this technology is particularly important. "Develop a streamlined process within DOD for classifying, evaluating, and optimizing workflows involved in its major operational and enabling functions, aiming to develop a list of priority workflows for automation with AI. When a workflow is successfully automated, DOD should strive to permanently transition that workflow to the AI-based implementation as quickly as practicable." This is the most common area we see related to our company and users where so many workflows today are needlessly done manually wasting our precious time resources where the simple stuff can now be left to the AI systems. Let our valuable resources, analysts, warfighters etc focus on the hard and complex stuff. Have been close with past Executive Orders, especially in the drone domain, lets hope this one gets off paper and into action soon! Bravo to Michael Kratsios and team!

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An important article I wrote that differentiates LLM assistance and agentic AI. Please read. 🔗 https://lnkd.in/eb8mJyjJ A note for those applying to jobs: This matters for your career too. When you're in an interview and someone asks what you built, be precise. If you used an LLM to help you write code faster, say that, don't call it an agent. If you built a RAG pipeline, call it retrieval-augmented generation, don't call it agentic. If you built a chatbot with a system prompt, own it for what it is. Hiring managers who know the difference will respect your precision. Hiring managers who don't know the difference need you to teach them. Either way, you win by naming it correctly. Overselling what you built doesn't just hurt your credibility when someone digs deeper, it tells the room you don't actually understand the architecture you're describing. Know what you built. Know what it's called. Know why it matters at that level. That's what gets you hired. #AI #AgenticAI #LLM #NLP #SportsAnalytics #DataScience #CareerAdvice #MachineLearning

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#AI-powered computer vision is how machines make sense of the world, turning massive amounts of visual data into actionable insights. Learn how computer vision is redefining what’s possible across federal missions in #BoozAllen’s new report. https://lnkd.in/eR55YPzK

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