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  • Meeting Your Future Manager: Identify Technical Bottlenecks

    9/ Meeting Your Future Manager Ask them one question before the interview ends. "What is the single technical bottleneck slowing your team down most right now?" Then spend the rest of the conversation proving you have solved that exact thing before.

    → View original post on X — @aihighlight,

  • Lead Smarter Hospital Operations with AI and Machine Learning
    Lead Smarter Hospital Operations with AI and Machine Learning

    Lead Smarter Hospital Operations with #AI by @antgrasso #MedTech #ArtificialIntelligence #MachineLearning #ML

    → View original post on X — @ronald_vanloon, 2026-04-14 08:45 UTC

  • BMW Tests AEON Humanoid Robot in Leipzig Factory

    One of the first real world pilots is already underway. At BMW’s Leipzig factory, BMW Group is testing the humanoid robot AEON together with Hexagon Robotics. Early focus areas: → Battery assembly → Component manufacturing If this works at scale, the future factory workforce could look very different. Watch the full video to see what this means for manufacturing. Don't miss out on the latest AI advancements! Sign up here to stay informed! intelligentworld.org/discove…

    → View original post on X — @ronald_vanloon, 2026-04-14 08:30 UTC

  • Humanoid Robots Now Working on Real Factory Production Floors

    What if the most flexible worker in your factory never gets tired, never calls in sick, and can switch jobs instantly? That’s the promise behind a new wave of humanoid robots now entering real factories. Not labs. Not demos. Actual production floors. One example is happening right now at @BMWGroup. Here is what I found fascinating.

    → View original post on X — @ronald_vanloon, 2026-04-14 08:30 UTC

  • Engineer Skills Transfer Path to AI Agents Market

    For engineers concerned about the future this is the clearest adjacent path. The skills transfer directly and the demand is already outpacing supply at companies taking agents seriously.

    → View original post on X — @aihighlight,

  • AI transforms fraud prevention for modern businesses

    #Ad #MastercardPartner @mastercard AI is changing fraud prevention fast, and businesses need to move faster too. In this video, I explore how AI is reshaping the fraud landscape, why traditional approaches are starting to fall behind, and why smarter intelligence is becoming

    → View original post on X — @bernardmarr,

  • AI Agent Deployers: The New Essential Enterprise Role

    this is a very very good write up not enough time being spent right now thinking clearly like this about AI outside of R&D I think this post nails it. start with the job-to-be-done, rethink the factory, and empower super operators Aaron Levie (@levie) The more enterprises I talk to about AI agent transformation, the more it’s clear that there is going to be a new type of role in most enterprises going forward. The job is to be the agent deployer and manager in teams. Here’s the rough JD: This person will need to figure out what are the highest leverage set of workflows on a team are (either existing or new ones) where agents can actually drive significantly more value for the team and company. In general, it’s going to be in areas where if you threw compute (in the form of agents) at a task you could either execute it 100X faster or do it 100X more times than before. Examples would be processing orders of magnitude more leads to hand them off to reps with extra customer signal, automating a contracting review and intake process, streamlining a client onboarding process to reduce as many straps as possible, setting up knowledge bases than the whole company taps into, and so on. This person’s job is to figure out what the future state workflow needs to look like to drive this new form of automation, and how to connect up the various existing or new systems in such a way that this can be fulfilled. The gnarly part of the work is mapping structured and unstructured data flows, figuring out the ideal workflow, getting the agent the context it needs to do the work properly, figuring out where the human interfaces with the agent and at what steps, manages evals and reviews after any major model or data change, and runs and manages the agents on an ongoing basis tracking KPIs, and so on. The person must be good at mapping the process and understanding where the value could be unlocked and be relatively technical, and has full autonomy to connect up business systems and drive automation. This means they’re comfortable with skills, MCP, CLIs, and so on, and the company believes it’s safe for them to do so. But also great operationally and at business. It may be an existing person repositioned, or a totally net new person in the company. There will likely need to be one or more of these people on every team, so it’s not a centralized role per se. It may rile up into IT or an AI team, or live in the function and just have checkpoints with a central function. This would also be a fantastic job for next gen hires who are leaning into AI, and are technical, to be able to go into. And for anyone concerned about engineers in the future, this will be an obvious area for these skills as well. — https://nitter.net/levie/status/2043883641366032638#m

    → View original post on X — @scobleizer, 2026-04-14 07:02 UTC

  • AI Agents Require Infrastructure and Security Strategy Overhaul

    Your AI Strategy Needs A Rebuild Before Agents Break It #AI agents are moving from pilot projects into real business roles, but many companies are discovering that their #cloud #infrastructure, #security models, and #workflows were built for people, not #autonomous systems.

    → View original post on X — @bernardmarr,

  • Enterprise Search: Deploying NVIDIA AI-Q for Secure Production
    Enterprise Search: Deploying NVIDIA AI-Q for Secure Production

    Moving enterprise search from a prototype to a secure, full-scale production environment is a complex hurdle. 🔍 There is a great step-by-step blueprint available for deploying the open-source NVIDIA AI-Q template to build scalable, "agentic" search stacks integrating private data. Read the Blog: developer.nvidia.com/blog/ho… #EnterpriseAI #LangChain @nvidia

    → View original post on X — @haroldsinnott, 2026-04-14 04:00 UTC

  • SAS Viya accelerates insurance claims processing from months to days

    At @Shriram_GI
    , every claim is more than data, it is a moment that demands clarity and speed. But manual reporting created delays when it mattered most. With SAS Viya, that changed. Claims that once took months are now settled in days, with significantly reduced manual

    → View original post on X — @sassoftware,