Digital twins are virtual models of physical entities used to optimize business operations. Success lies in understanding best practices, defining business goals, testing via prototyping, assessing organizational readiness, and adopting an agile approach. RT @antgrasso

📍 NYC data folks—mark your calendar! We're at the KNIME Data Summit New York on June 18—a one-day event built for data and AI leaders who are done talking about AI and ready to actually scale it. Expect keynotes, customer stories, and peer roundtables on embedding AI into everyday decisions, scaling analytics, navigating governance, and proving ROI. Speakers include leaders from Forrester, AMD, Siemens Healthineers, DTCC, and AWS. Stop by our booth to chat about data skills, career paths, and what's next in AI. Free to attend! Register here → ow.ly/9cOM50Zba5k

Next week on DataCamp: 4 free live sessions, each one packed with hands-on takeaways: 🗓️ Mon Jun 15—Build a Dashboard with Databricks Agents Walk away with a working AI-powered dashboard. Learn how to use Databricks agents to automate data retrieval and build interactive visualizations without writing complex queries from scratch. 🗓️ Tue Jun 16—Analytics Magic with Databricks Genie See how Genie turns natural language into SQL and dashboards — so your whole team can explore data without waiting on analysts. Great for team leads and data-curious folks. 🗓️ Wed Jun 17—Physical AI in Manufacturing & Construction Beyond chatbots — this one covers how AI is being deployed on factory floors and construction sites. Robotics, computer vision, predictive maintenance. Real industry use cases. 🗓️ Thu Jun 18—How Does AI Affect your ESG Goals? AI has a carbon footprint. But it can also accelerate sustainability reporting and energy optimization. This session unpacks both sides, the costs and the opportunities. All free. All live at 11 AM ET. Register even if you can't attend, and you'll get the recording. Save your spot → ow.ly/yca750ZbbYF #DataCamp #Webinars #Databricks #AI #ESG #Manufacturing #FreeLearning

AI is entering school administration through automation of repetitive processes, changing how time and attention are allocated across staff. Institutions are pushed to rethink roles and data practices to keep operations consistent and accountable. Microblog @antgrasso

AI is expanding who gets to build software. It’s also expanding risk. Anaconda CEO @david_desanto recently joined @theCUBE’s @GemmaAllenSays to discuss why as more hobbyists and AI agents build applications, secure foundations matter more than ever. bit.ly/4xFUxma

We are gathering evidence on facial recognition in education settings. If you are aware of deployments in your country, your insight matters. pvcy.org/frtmap

🐍🛞 Python wheels are pre-built binary packages that let tools like pip skip compilation and install packages directly. They make setup faster, reduce build failures, and help create more consistent environments. Explore our guide on Python wheels: bit.ly/43pbQtL

AI earns its place when it moves conversion and shortens time to value. Execution becomes the constraint: teams must test in real contexts and connect use cases to revenue, where decisions accelerate. Source @Gartner_inc Link gtnr.it/3NV9lv2 via @antgrasso

🌍 What if your biggest business challenge isn’t technology… but policy? Today, regulation is shaping access to talent, tech, and markets more than ever. Follow @LindaGrass0 for more insights 💡

That's a wrap on The AI Summit London! 🤖 Two great days at Tobacco Dock talking AI and data upskilling with leaders across industries. Thanks to everyone who visited us at Booth 314 — see you next time, London! 👋

Parents report loving their partners less within the first year of having a child, but that doesn't mean the feeling is permanent or inevitable newscientist.com/article/252…

AI ethics becomes practical when companies work with regulators early. Clear rules help teams design safer systems, reduce legal risk, and explain AI decisions with more confidence. Microblog @antgrasso

📡 Is your workforce evolving as fast as your technology? In telco and beyond, transformation isn’t just about networks—it’s about people. Follow @LindaGrass0 for more insights 💡

Django Girls workshop is happening in Kraków! Apply here: djangogirls.org/en/krakow2/
Learn and write your first blog with Django guided by coaches.
The workshop is free 🧡 Do you know someone who will be interested? Spread the word! ✨ 🧁 The application will close on July 10th.

Agentic AI is pushing tech services to pick a clear role, from enabler to full solution builder. Each choice affects skills and delivery, so organizations must decide where to invest and how to scale. Source @McKinsey Link mck.co/4cCZTGm via @antgrasso

How much do ports shape global trade? A lot more than we think. The latest Container Port Performance Index (CPPI) offers a global, data-driven view of port efficiency—and why it matters for trade, jobs, and growth. Learn more: wrld.bg/TUUi50ZacWN #CPPI2025

We partnered with @trajectorylabs to post-train NVIDIA Nemotron 3 Ultra for legal. Here’s what we found: 1) Open-weight models can reach frontier legal performance. On our Legal Agent Benchmark (LAB), Nemotron 3 Ultra started at a 0% all-pass rate. After post-training, it reached 5.8%, placing it between Sonnet 4.6 at 4.2% and Opus 4.6 at 6.6%. 2) Post-training dramatically improves reliability. Before training, many held-out tasks missed enough rubric dimensions to land around ~70% pass rates. After training, those tasks shifted toward ~95% pass rates. 3) Open-weight performance comes at much lower cost. Post-trained Nemotron 3 Ultra reached a similar quality band to leading closed models while running at roughly 1/8th to 1/50th the per-token price of Sonnet 4.6 and Opus 4.6. Most importantly: we post-trained this model on the @trajectorylabs platform less than 24 hours after Nemotron 3 Ultra launched, using the same harness, data, and recipe we used for Nemotron 3 Super. More to come as we continue to experiment with open-weight legal agents. Read more on post-training with Trajectory below:

Ages 40 to 65 see a period of turmoil in the brain that has previously been overlooked. But identifying problems during this time can protect your cognitive health for decades to come newscientist.com/article/252…

We're moving from "do this task" to "achieve this outcome." That's a much bigger change than most people realize. The most interesting AI systems won't just execute instructions—they'll continuously improve their path to the goal. #HyperagentPartner

XGBoost for Regression, Predictive Modeling, and Time Series Analysis — Learn how to build, evaluate, & deploy predictive models: amzn.to/4l2YcU9 v/ @PacktDataML — My review: 🟠XGBoost is definitely the focal point and central contribution of this book, along with all those other things: Regression Trees, Predictive Modeling, Time Series Analysis, and Forecasting. 🟠This book’s added value comes in its thorough progression from start to finish with comprehensive coverage of all the major steps and issues in data science and machine learning modeling: data cleaning, imbalanced data, feature engineering, feature engineering pipeline, feature importance, categorical data encoding, model interpretability and explainability, ensembles, model training, model evaluation metrics, hyperparameter tuning, model deployment, and more - including a quick-start case study starter project that feeds into next-level projects. 🟠I highly recommend this broadly useful book for all levels of practitioners.