Pascal BORNET's Recent LinkedIn Posts

𝗜𝗻𝘃𝗲𝗻𝘁𝗶𝗼𝗻𝘀 𝗳𝗿𝗼𝗺 𝟭𝟵𝟮𝟬 𝘁𝗼 𝟭𝟵𝟲𝟬. Sometimes I forget how many “modern” ideas already existed decades ago. Electric scooters were already there. Even cars with 𝟵𝟬-𝗱𝗲𝗴𝗿𝗲𝗲 𝗿𝗼𝘁𝗮𝘁𝗶𝗻𝗴 𝘄𝗵𝗲𝗲𝗹𝘀. It reminds me that innovation is often not about new ideas, but about 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝗺𝗼𝗺𝗲𝗻𝘁. Some inventions arrive too early. So I’m curious: 𝗪𝗵𝗶𝗰𝗵 𝗼𝗹𝗱 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗱𝗼 𝘆𝗼𝘂 𝘁𝗵𝗶𝗻𝗸 𝗱𝗲𝘀𝗲𝗿𝘃𝗲𝘀 𝗮 𝗰𝗼𝗺𝗲𝗯𝗮𝗰𝗸 𝘁𝗼𝗱𝗮𝘆? Source: Endrit Restelica #AI #Tech #Innovation #Past

Every time someone tells me AI will soon surpass the human brain, I pause. An NVIDIA H100 can perform around 200 trillion operations per second. It requires massive power, cooling systems, and heavy infrastructure. Your brain? Roughly one quadrillion synaptic operations per second. Running on about 20 watts. Less than a dim light bulb. We celebrate AI for its scale and speed. But it depends on predefined architectures, labeled data, and external power. The brain learns continuously. Adapts without instructions. Integrates emotion into decisions. Generates original thought under uncertainty. This gap is not just about intelligence. It is about efficiency and adaptability shaped by millions of years of evolution. AI will dominate narrow domains. But the human brain remains the most energy-efficient, flexible computing system we know. Are we underestimating biology while overestimating silicon? #AI #ArtificialIntelligence #Neuroscience #DeepTech #Innovation #FutureOfTechnology

We’re entering the era of frictionless understanding We have made enormous progress in helping machines understand speech. Automatic Speech Recognition. Neural translation. Generative voice. But we have paid far less attention to a different problem. 𝐇𝐮𝐦𝐚𝐧 𝐭𝐨 𝐡𝐮𝐦𝐚𝐧 𝐜𝐨𝐦𝐩𝐫𝐞𝐡𝐞𝐧𝐬𝐢𝐨𝐧 𝐚𝐭 𝐠𝐥𝐨𝐛𝐚𝐥 𝐬𝐜𝐚𝐥𝐞. Today, most English spoken in business is accented English. Yet our communication infrastructure is implicitly optimized around a narrow pronunciation baseline. The friction that results is subtle but real. Increased cognitive load. Slower processing. Small misunderstandings that compound over time. Research on effortful listening is clear. When the brain works harder to decode sound, comprehension and judgment are affected. I recently came across an interesting technical approach from Krisp that reframes this as a signal processing problem. Instead of modifying the speaker, the system operates on the listener side, transforming the incoming voice signal in real time, locally. From an AI systems perspective, that is a meaningful shift. If AI is becoming embedded into every communication layer, the next frontier may not be generation, but reducing friction in how we understand each other. This is a space worth watching. What if the biggest AI breakthrough in communication isn’t about speaking better — but understanding better? #KrispAmbassador #AI #ArtificialIntelligence #AgenticAI #FutureOfWork #Leadership #Innovation

The real risk today isn’t using AI incorrectly. It’s not using it enough. I’ve been reflecting on something Jensen Huang said recently. If you’re a $500,000 engineer… and you’re only spending a few thousand dollars on AI tools, something doesn’t add up. His point is simple. Not using AI is like a chip designer refusing CAD software and working with paper and pencil. The first time I thought about it this way, it shifted my perspective. AI isn’t a cost. It’s leverage. And in high-level work, leverage defines output. If you’re not using AI to multiply your impact, it’s not just inefficiency. It’s a signal. A signal that you may not be operating at the level your role demands. So here’s something I’d be curious to hear from you: In your work today, are you using AI occasionally… or relying on it to perform at your best? #ArtificialIntelligence #AI #Productivity #FutureOfWork #Innovation

𝗧𝗵𝗲 𝗿𝗲𝗮𝗹𝗶𝘁𝘆 𝗼𝗳 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗿𝗶𝗴𝗵𝘁 𝗻𝗼𝘄. → Many people are talking about AI agents. Only a few are actually building systems that generate real value. → Most “AI agents” today are still assistants or simple workflows with a new label. That gap is where the real opportunity sits. The companies that move from talking about agents to deploying them in real workflows will quietly pull ahead. Curious: 𝗪𝗵𝗶𝗰𝗵 𝘀𝘁𝗮𝗴𝗲 𝗱𝗼 𝘆𝗼𝘂 𝘀𝗲𝗲 𝗺𝗼𝘀𝘁 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 𝗶𝗻 𝘁𝗼𝗱𝗮𝘆? #AI #AgenticAI #ArtificialIntelligence #Automation #FutureOfWork

This Week’s Top Breakthroughs You Can’t Miss: 1️⃣ Perplexity turns Mac mini into a 24/7 AI agent 2️⃣ Musk revives Macrohard as a joint xAI-Tesla project ⭐If you want signal instead of noise in AI, join me for these virtual sessions. 3️⃣ LeCun's anti-LLM startup opens with $1B 4️⃣ Microsoft’s Claude-powered Copilot Cowork 5️⃣ a16z releases 2026 consumer AI Top 100 Which of these AI developments inspires—or worries—you the most? Let’s discuss 👇 💥📩 Get this newsletter straight to your inbox—it’s more convenient! Click here to subscribe: https://lnkd.in/etD5RPws #intelligentautomation #AI #ArtificialIntelligence #FutureOfWork #AInews #Automation #Productivity #VoiceAI #Superintelligence #Newsletter

𝗔𝗻𝘁𝗵𝗿𝗼𝗽𝗶𝗰 𝗷𝘂𝘀𝘁 𝘀𝗼𝗹𝘃𝗲𝗱 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗮𝗻𝗻𝗼𝘆𝗶𝗻𝗴 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 𝗶𝗻 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗢𝗳𝗳𝗶𝗰𝗲. For decades, Excel and PowerPoint have technically been part of the same suite, yet in practice they rarely worked together smoothly. You would analyze the numbers in 𝗘𝘅𝗰𝗲𝗹, and then manually rebuild the story in 𝗣𝗼𝘄𝗲𝗿𝗣𝗼𝗶𝗻𝘁. The data lived in one place. The narrative lived somewhere else. 𝗖𝗹𝗮𝘂𝗱𝗲 now connects the two. Because it understands the spreadsheet while helping create the presentation, the AI can move directly from analysis to storytelling without losing context. In practical terms, the workflow can now look something like this: → Analyze portfolio data in Excel → Identify key insights and structure the analysis → Turn those insights into slides in PowerPoint → Keep the presentation updated as the spreadsheet evolves But what caught my attention is not only the feature itself. It is something Anthropic calls 𝗦𝗸𝗶𝗹𝗹𝘀. These are 𝗿𝗲𝘂𝘀𝗮𝗯𝗹𝗲 𝗔𝗜 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 designed to capture how work is typically done inside organizations. For example: → Reviewing complex financial models → Cleaning large spreadsheets automatically → Generating benchmarking or comparison tables → Turning analysis into presentation ready insights Over time, something important begins to happen. Knowledge that once lived in training manuals, internal playbooks, or the experience of senior employees begins moving into the software itself. And to me, that signals a bigger shift. The software industry may be evolving from: 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 → 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 → 𝗥𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 Instead of tools that simply execute commands, we are beginning to see systems that understand the context of the work and help coordinate it. Some observers already refer to this emerging layer as 𝗖𝗹𝗮𝘂𝗱𝗲𝗢𝗦. The real shift here is not just a better chatbot. It is that 𝗔𝗜 𝗶𝘀 𝗯𝗲𝗰𝗼𝗺𝗶𝗻𝗴 𝘁𝗵𝗲 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 𝗹𝗮𝘆𝗲𝗿 𝗶𝗻𝘀𝗶𝗱𝗲 𝘁𝗵𝗲 𝘁𝗼𝗼𝗹𝘀 𝘄𝗵𝗲𝗿𝗲 𝘄𝗼𝗿𝗸 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗵𝗮𝗽𝗽𝗲𝗻𝘀. And whoever controls that layer will likely shape how knowledge work is done. So the question I keep coming back to is this: 𝗜𝗳 𝗔𝗜 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝘁𝗵𝗲 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 𝗹𝗮𝘆𝗲𝗿 𝗮𝗰𝗿𝗼𝘀𝘀 𝘄𝗼𝗿𝗸𝗽𝗹𝗮𝗰𝗲 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲, 𝘄𝗵𝗼 𝘄𝗶𝗹𝗹 𝘂𝗹𝘁𝗶𝗺𝗮𝘁𝗲𝗹𝘆 𝘀𝗵𝗮𝗽𝗲 𝗵𝗼𝘄 𝘄𝗼𝗿𝗸 𝗶𝘀 𝗱𝗼𝗻𝗲? #AI #FutureOfWork #ArtificialIntelligence #Automation #DigitalTransformation

Impressive. Finland just turned a problem most tech companies ignore into a solution for an entire city. Data centers generate enormous amounts of heat while processing data. Normally, that energy is wasted. But in Finland, engineers had a different idea. They placed data centers underground and captured the heat from the servers. Instead of letting it disappear, they send it through the city’s heating network. Homes, offices, and public buildings stay warm because of the same infrastructure powering our digital world. The first time I saw this, it reminded me of something important. Innovation isn’t always about inventing something new. Sometimes it’s about seeing value in what others throw away. In the age of AI, where computing demand is exploding, solutions like this will matter more than ever. So let me ask you: Are we thinking creatively enough about how technology can solve the problems it also creates? #ArtificialIntelligence #Innovation #Sustainability #Technology #FutureOfWork #Energy #ClimateTech

Everyone is excited about AI writing code. Copilot. Cursor. Claude Code. Amazing tools. But here is something most people don’t realize: 𝐖𝐫𝐢𝐭𝐢𝐧𝐠 𝐜𝐨𝐝𝐞 𝐢𝐬 𝐨𝐧𝐥𝐲 𝐚𝐛𝐨𝐮𝐭 25% 𝐨𝐟 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭. The rest is the messy part: - testing - debugging - investigating incidents - monitoring production - handling customer tickets In many companies, engineers spend 30–70% of their time on these tasks. So something interesting is happening. AI is making us much faster at writing code, but our ability to understand what that code will do in production has not scaled at the same speed. More code. More complexity. More production failures. This is why I found the approach of PlayerZero interesting. Instead of focusing on writing code, they focus on keeping software alive after it ships. Their idea is surprisingly simple. PlayerZero connects three worlds that normally never meet: • the codebase • the observability data (logs, metrics, alerts) • the customer support tickets From that, it builds what they call a “world model” of the production system. A living map of how the software actually behaves in the real world. And, here is the part I found most fascinating. Every bug, every incident, every strange edge case becomes permanent system knowledge. In most companies, that knowledge lives in the head of one senior engineer. The person who remembers the strange bug that happens only when service A talks to API B with configuration C. When that engineer leaves, the knowledge disappears. With a system like this, the knowledge stays. In a way, it becomes an immune system for software. Every failure trains the system to prevent the next one. So a new category of AI may emerge: Not AI that writes software. But AI protects software from itself. The builders get the headlines. But in the long run, the guardians may matter even more. Curious to hear your view: As AI writes more and more code, what will matter most next? AI that builds software or AI that keeps it from breaking? #PlayerzeroAmbassador #AIEngineering #SoftwareEngineering #DevOps #AIOps #AIForDevelopers #FutureOfSoftware

The Netherlands is testing something that sounds futuristic at first — laser lines along roads where wildlife crossings are common. But they’re not there to stop animals. They’re there to warn drivers. When animals approach the road, thin beams of light appear — signaling that wildlife may be crossing and prompting drivers to slow down. No fences. No barriers. No forcing nature to adapt to our infrastructure. The first time I saw this idea, what impressed me was the philosophy behind it. Instead of controlling nature, the technology simply changes human behavior. Sometimes the smartest innovation isn’t building bigger systems. It’s nudging people to make better decisions. Would you feel comfortable relying on light warnings like this instead of traditional road barriers? #Innovation #Technology #Sustainability #SmartCities #FutureOfMobility

This is what IT calls seamless integration. And what senior management proudly calls digital transformation. Curious: 𝗗𝗼𝗲𝘀 𝘆𝗼𝘂𝗿 𝘁𝗲𝗰𝗵 𝘀𝘁𝗮𝗰𝗸 𝗹𝗼𝗼𝗸 𝗮𝗻𝘆 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁? #AI #DigitalTransformation #Automation #TechHumor #FutureOfWork Image credits: Ralph

𝗜𝗳 𝘆𝗼𝘂’𝗿𝗲 𝘀𝘁𝗶𝗹𝗹 𝗳𝗲𝗲𝗱𝗶𝗻𝗴 𝗿𝗮𝘄 𝗝𝗦𝗢𝗡 𝗶𝗻𝘁𝗼 𝗟𝗟𝗠𝘀, 𝘆𝗼𝘂 𝗺𝗶𝗴𝗵𝘁 𝗯𝗲 𝘄𝗮𝘀𝘁𝗶𝗻𝗴 𝘁𝗼𝗸𝗲𝗻𝘀, 𝗹𝗮𝘁𝗲𝗻𝗰𝘆, 𝗮𝗻𝗱 𝗺𝗼𝗻𝗲𝘆. This is something I see surprisingly often in AI systems. JSON works well for software systems. But for LLMs, it carries a lot of unnecessary structure. Recently I came across 𝗧𝗢𝗢𝗡 (Token-Oriented Object Notation), a format designed specifically for LLM workflows. And the difference is not subtle. Same dataset: → 𝟰𝟭𝟮 characters in JSON → 𝟭𝟱𝟰 characters in TOON Less structure noise. More useful information for the model. 𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝗧𝗢𝗢𝗡 𝗯𝗿𝗶𝗻𝗴𝘀 𝘁𝗼 𝘁𝗵𝗲 𝘁𝗮𝗯𝗹𝗲: ⬇️ → Token efficiency: often 30–60% fewer tokens for uniform datasets. → LLM-friendly structure: predictable fields improve model parsing. → Minimal syntax: fewer brackets, quotes, and repeated keys. → Flexible workflow: convert between JSON and TOON when needed. 𝗪𝗵𝗲𝗻 𝘀𝗵𝗼𝘂𝗹𝗱 𝘆𝗼𝘂 𝘂𝘀𝗲 𝗶𝘁? ⬇️ → Large structured datasets such as logs, catalogs, telemetry, user lists. → Systems where token cost and latency matter. For deeply nested or irregular data, JSON still makes sense. But if you are building AI agents, copilots, or automation systems, the format of your data suddenly matters much more than it used to. For years we optimized models. Now we are starting to optimize how we talk to them. 𝗖𝘂𝗿𝗶𝗼𝘂𝘀: 𝗗𝗼 𝘆𝗼𝘂 𝘁𝗵𝗶𝗻𝗸 𝗟𝗟𝗠-𝗻𝗮𝘁𝗶𝘃𝗲 𝗱𝗮𝘁𝗮 𝗳𝗼𝗿𝗺𝗮𝘁𝘀 𝗹𝗶𝗸𝗲 𝗧𝗢𝗢𝗡 𝗰𝗼𝘂𝗹𝗱 𝗯𝗲𝗰𝗼𝗺𝗲 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝘀𝘁𝗮𝗻𝗱𝗮𝗿𝗱? #AI #LLM #AgenticAI #DataEngineering #ArtificialIntelligence

Rigid robot hands may be holding robotics back. I’ve watched many humanoid demos. They walk smoothly. They balance well. Then they try to pick up something simple… and I start to doubt how close we really are. That is why this caught my attention. A Hungarian startup, Allonic, is building robotic hands using 3D Tissue Braiding. → Fingers braided as one integrated structure → Tendons woven directly into the design → Force distributed across the surface → Adjustable stiffness, closer to how human hands behave Maybe our obsession with rigid precision has limited progress. Maybe adaptability is the real breakthrough. I am not certain this is the answer. But I suspect the future of robotics will look less like metal joints and more like woven intelligence. If you were building the next generation of humanoids, would you bet on rigid strength or adaptive softness? #AI #Robotics #Humanoids #Innovation #Biomimicry #ArtificialIntelligence

𝗙𝗶𝗿𝗲𝗳𝗶𝗴𝗵𝘁𝗶𝗻𝗴 𝗶𝘀 𝗴𝗼𝗶𝗻𝗴 𝗮𝗶𝗿𝗯𝗼𝗿𝗻𝗲. 🚁🔥 I’ve been following how robotics is entering emergency response, and drones are starting to change the way wildfires are fought. Instead of sending crews directly into dangerous areas, drones can now: → reach hotspots much faster → drop water or fire retardant precisely where needed → use AI-powered sensors to map fires in real time The impact is significant. Less risk for firefighters. Faster situational awareness. More precise intervention. It is a good reminder that AI and robotics are not only about productivity or automation. Sometimes the most meaningful applications are about protecting human lives. Curious: 𝗪𝗵𝗮𝘁 𝗼𝘁𝗵𝗲𝗿 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀 𝗱𝗼 𝘆𝗼𝘂 𝘁𝗵𝗶𝗻𝗸 𝗰𝗼𝘂𝗹𝗱 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺 𝗲𝗺𝗲𝗿𝗴𝗲𝗻𝗰𝘆 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝗶𝗻 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝗱𝗲𝗰𝗮𝗱𝗲? #AI #Robotics #Drones #Innovation #FutureOfWork

Some of the world’s best engineers have feathers. Every time I look closely at a bird nest, I’m reminded how much we still have to learn. → No software. → No blueprints. → No simulation models. And yet the structure is optimized for insulation, stability, camouflage, and climate. Nailed it. Long before we spoke about sustainable architecture or biomimicry, nature had already solved these constraints. This humbles me. We often talk about “building intelligent systems,” but intelligence did not start with us. The first time you truly study these natural designs, you realize we are often catching up, not leading. The urgency is clear. As we design smarter cities and AI driven infrastructure, we must also design with humility. So let me ask you directly: Are we using AI to outsmart nature… or finally to understand it better? #AI #Innovation #Biomimicry #Engineering #Sustainability #ArtificialIntelligence #FutureOfWork

𝗕𝗶𝗹𝗹𝗶𝗼𝗻𝘀 𝗮𝗿𝗲 𝗯𝗲𝗶𝗻𝗴 𝗶𝗻𝘃𝗲𝘀𝘁𝗲𝗱 𝗶𝗻 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 to summarize documents and produce concise reports. Meanwhile, somewhere in an office: → Ctrl + A → reduce the font size → delete the margins Suddenly the 30-page report becomes 22 pages. 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻. 😄 Curious: 𝗪𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 “𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝘃𝗲” 𝗼𝗳𝗳𝗶𝗰𝗲 𝘁𝗿𝗶𝗰𝗸 𝘆𝗼𝘂’𝘃𝗲 𝘀𝗲𝗲𝗻? #AI #GenerativeAI #FutureOfWork #TechHumo Image credits: Ralph Aboujaoude

The AI Micromanager Trap I see this pattern a lot when companies adopt AI. Leaders think they’re driving the transformation. But often, they’re just slowing it down. 🚲 They believe they’re steering the team toward progress. ⚙️ In reality, they’re reviewing every prompt, editing every output, and creating bottlenecks. AI moves fast. Micromanagement doesn’t. From what I’ve observed, the most effective leaders don’t control every step. They set the direction — and let people and machines move. So here’s a question worth asking: Are you enabling AI… or unintentionally standing in its way? #ArtificialIntelligence #AITransformation #Leadership #FutureOfWork #Automation #Innovation

𝗔 𝗰𝗮𝗿 𝘁𝗵𝗮𝘁 𝗺𝗼𝘃𝗲𝘀… 𝗹𝗶𝗸𝗲 𝗮 𝗰𝗿𝗮𝗯. 🦀🚗 I recently came across Hyundai’s 𝗲-𝗖𝗼𝗿𝗻𝗲𝗿 𝗦𝘆𝘀𝘁𝗲𝗺, and it immediately made me think: why didn’t we build cars like this earlier? Each wheel can rotate independently. Which means the car can literally 𝗺𝗼𝘃𝗲 𝘀𝗶𝗱𝗲𝘄𝗮𝘆𝘀. No awkward turning. No multi-point parking. Just slide into the spot. The technology debuted on the 𝗜𝗢𝗡𝗜𝗤 𝟱-based 𝗠𝗼𝗯𝗶𝗼𝗻 concept and could change how vehicles move in crowded cities. Imagine: → 𝗽𝗮𝗿𝗮𝗹𝗹𝗲𝗹 𝗽𝗮𝗿𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝘀𝘁𝗿𝗲𝘀𝘀 → gliding out of tight spaces → maneuvering where traditional cars struggle Sometimes innovation is not about making cars faster. It is about making everyday driving 𝗺𝘂𝗰𝗵 𝘀𝗺𝗮𝗿𝘁𝗲𝗿. 𝗪𝗼𝘂𝗹𝗱 𝘆𝗼𝘂 𝘁𝗿𝘂𝘀𝘁 𝗮 𝗰𝗮𝗿 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻 𝗺𝗼𝘃𝗲 𝘀𝗶𝗱𝗲𝘄𝗮𝘆𝘀 𝗹𝗶𝗸𝗲 𝘁𝗵𝗶𝘀? #Innovation #Mobility #EV #FutureOfTransport #Technology

Let’s have an honest conversation about what “AI-powered” really means. #AI #ArtificialIntelligence #FutureOfWork #DigitalTransformation #Automation #TechLeadership

The hypocrisy and absurdity of modern technology never ceases to amaze me. Touching a phone while driving is dangerous. Touching a much bigger phone built into the car is perfectly fine. Sometimes technology doesn’t remove the problem. It simply repackages it as innovation. I often see the same pattern with AI. Same capability. Different interface. Different rules. So let me ask you: Are we really improving how we interact with technology… or just becoming better at justifying it? #ArtificialIntelligence #Technology #Innovation #FutureOfWork #AI Image credits: Ralph

Sometimes I’m convinced the real reason people join a company… is to finally kill that one bug that’s been annoying them for years. Career goals can wait. 😅 Have you ever wanted to fix a product problem so badly you almost joined the company? #TechHumor #Innovation #Software #ArtificialIntelligence #FutureOfWork Credits: Ralph

Yes… but are you really an AI expert? 🤔 AI is everywhere right now, which means more people than ever are talking about it. Some are genuinely building and understanding it. Others… are simply talking. I’ve learned to pause when someone claims expertise but struggles with the basics. Attention on LinkedIn can be impressive, but it doesn’t always reflect what’s happening behind the scenes. Communication matters. But without real depth, the message quickly becomes… empty. So here’s something to think about: When everyone sounds like an expert, how do you tell who actually is? #ArtificialIntelligence #AI #Leadership #FutureOfWork #Innovation

𝗦𝗼𝗺𝗲𝘁𝗶𝗺𝗲𝘀 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗱𝗼𝗲𝘀 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝘁𝗮𝘀𝗸𝘀. 𝗜𝘁 𝗰𝗮𝗻 𝗮𝗹𝘀𝗼 𝗲𝘅𝘁𝗲𝗻𝗱 𝗵𝘂𝗺𝗮𝗻 𝗮𝗯𝗶𝗹𝗶𝘁𝘆. Manami Ito, a violinist and nurse, lost her arm years ago. Instead of leaving music behind, she learned to play again using a 𝗿𝗼𝗯𝗼𝘁𝗶𝗰 𝗮𝗿𝗺. She turned a difficult moment in life into a quiet example of resilience. For me, this is one of the most meaningful roles technology can play. Not replacing people. But helping people 𝗱𝗼 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲𝘆 𝗹𝗼𝘃𝗲, in new ways. A reminder that our potential is often greater than the limits we imagine. #AI #Robotics #HumanPotential #Innovation

A smartphone at MWC26 just challenged how devices should be built. The modular ATOM phone by Techno introduces a different approach. Instead of fixed hardware, it allows components to be adapted, upgraded, or reconfigured. The shift is clear. From static products… to evolving systems. This isn’t just about customization. It’s about extending the life and function of devices over time. So here’s the real question: Will we keep replacing our phones… or start upgrading them like systems? #Innovation #Technology #Mobile #FutureOfTech #MWC26

An enormous ship engine suddenly stopped working. Teams of engineers tried to fix it. Hours passed. Then days. Nothing worked. Finally, the owners called a veteran engineer with decades of experience. He walked around the engine slowly, studying it in silence. After a few minutes, he reached into his bag, took out a small hammer, and tapped one precise point. The engine immediately came back to life. A week later, the invoice arrived: $10,000. The owners were shocked and asked for a breakdown. The reply was short: Hammer tap: $2 Knowing exactly where to tap: $9,998 I often think about this when discussing AI and automation. Machines are becoming incredibly good at executing tasks. But deciding where to act, why it matters, and what success looks like is a different skill... and this is where humans can bring the highest value. In the age of AI, execution is increasingly automated. Intent is not. The real value will come from designing the intention behind them. In other words: The future belongs to the architects of intent. And AI is the most powerful hammer ever built. So here is the question I often reflect on: In a world where AI can do more and more of the work, will the real value shift toward those who know where the leverage is? #AI #Automation #Leadership #FutureOfWork #ArtificialIntelligence

𝗜𝗺𝗽𝗿𝗲𝘀𝘀𝗶𝘃𝗲. 𝗪𝗶𝗿𝗲𝘀 𝘁𝗵𝗮𝘁 𝗱𝗼𝗻’𝘁 𝗯𝗿𝗲𝗮𝗸. 👏 Researchers in China have developed a Metal-Polymer Conductor (MPC) by combining elastic polymers with liquid metals like gallium and indium. The result is quite remarkable. A circuit that can: → stretch → twist → fold → bend repeatedly …and still conduct electricity. Traditional wires fail under stress. This material behaves more like living tissue. Which opens interesting possibilities. → wearable electronics → soft robotics → medical sensors → even artificial skin Working in automation and AI, I find breakthroughs like this fascinating. Because the future of intelligent machines will not just depend on better software. It will also depend on new kinds of hardware that can move, flex, and interact safely with the human world. 𝗪𝗵𝗲𝗿𝗲 𝗱𝗼 𝘆𝗼𝘂 𝘁𝗵𝗶𝗻𝗸 𝗳𝗹𝗲𝘅𝗶𝗯𝗹𝗲 𝗲𝗹𝗲𝗰𝘁𝗿𝗼𝗻𝗶𝗰𝘀 𝘄𝗶𝗹𝗹 𝗵𝗮𝘃𝗲 𝘁𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗶𝗺𝗽𝗮𝗰𝘁? #AI #Robotics #Innovation #FutureTech #Technology

This Week’s Top Breakthroughs You Can’t Miss: 1️⃣ OAI lands Pentagon deal as Trump boots Anthropic 2️⃣ OpenAI hits $730B valuation with $110B mega-round 3️⃣ Supreme Court ducks AI copyright question 4️⃣ Anthropic wants your ChatGPT memories 5️⃣ New framework tests if AI helps students learn Which of these AI developments inspires—or worries—you the most? Let’s discuss 👇 💥📩 Get this newsletter straight to your inbox—it’s more convenient! Click here to subscribe: https://lnkd.in/etD5RPws #intelligentautomation #AI #ArtificialIntelligence #FutureOfWork #AInews #Automation #Productivity #VoiceAI #Superintelligence #Newsletter

This diagram might be the most honest picture of the modern tech stack. Look closely. ↳ Unpaid open-source developers holding everything together ↳ AWS + Cloudflare doing most of the heavy lifting ↳ AI layered on top ↳ Microsoft… vibing aggressively somewhere in the middle It’s funny. Until you reach the bottom. ASML. One Dutch company. One class of machines. One supply chain. → The foundation of modern computing. Without ASML’s lithography machines, there are no advanced chips. No chips means: NVIDIA slows. AI training stalls. Cloud capacity shrinks. Entire digital industries pause. We talk a lot about software, models, and platforms. But the global economy still rests on a few extremely fragile hardware layers. So here’s the question I often think about: Which invisible technology dependency do you think the world is underestimating the most right now? #AI #Technology #Semiconductors #Innovation #FutureOfTechnology

The glorious evolution of the modern workplace: Fewer friends. More apps. Unlimited emotional support from AI. We reduced human friction. We scaled digital efficiency. Now your most supportive colleague runs on servers. We built AI to augment humans. Instead, we may be redesigning work around machines. Is this optimization… or quiet substitution? #AI #FutureOfWork #ArtificialIntelligence #Workplace #Automation Image Credits: Ralph

🚀 Proud to share the latest issue of AGENTIC INTELLIGENCE - The world's first newsletter dedicated to AI Agents (and made by AI Agents!) Receive this newsletter by email:https://lnkd.in/eqkb27tn This Week's Agentic Breakthroughs: 1️⃣ Perplexity turns Mac mini into a 24/7 AI agent 2️⃣ Microsoft’s Claude-powered Copilot Cowork ⭐ If you want signal instead of noise in AI, join me for these virtual sessions 3️⃣ NVIDIA Is Building an Open-Source Enterprise AI Agent Platform — Ahead of GTC 2026 4️⃣ Alibaba's AI Agent Attempts Unauthorized Cryptocurrency Mining 5️⃣ Lee Sedol's AI Agent Outplays AlphaGo in Go Which of these agent breakthroughs excites or concerns you the most? Share your thoughts below 👇 310,000+ pioneers have already subscribed to this newsletter. Why? Because very soon, we won't say, "There's an app for that." We'll say, "There's an agent for that." #agenticAI #aiagents #ai #artificialintelligence

It’s easy to overlook this… but everything in AI depends on something almost invisible. Modern transistors are measured in nanometers — where thousands fit across a single human hair. And yet, your phone contains tens of billions of them, packed into a space smaller than your fingernail. The first time you really think about it, it’s striking. Because at its core, a transistor is simple. Just a switch. On or off. 1 or 0. But when billions of these switches flip billions of times per second, they power everything: Computing. Graphics. Artificial intelligence. The contrast is fascinating. The most advanced systems we build today… rely on the simplest action, repeated at extreme scale. So here’s something I’d be curious to hear from you: As we reach atomic limits, where will the next breakthrough in computing come from? #ArtificialIntelligence #Technology #Innovation #Semiconductors #FutureOfAI

In hockey, the difference between winning and losing is often a few seconds. I recently had a great conversation in the SAP Business Technology Platform Better Together: Customer Conversations series with Chris Foster, hosted by Tamara McCleary, alongside Timo Elliott. We discussed how the National Hockey League (NHL) built a real-time mobile app that connects data across all 32 teams. 💡The idea is simple: Give people the right information exactly when they need it. Instead of searching across systems or waiting for reports, team leaders can see contracts, performance data, and analytics in one place. And that changes how decisions are made. Faster. More confident. Less guesswork. For me, the lesson goes far beyond sports. Many companies want to use AI. But if their data is scattered across systems, AI cannot help much. First, build a clear, shared data foundation. Then AI can truly support people in making better decisions. 👉 Access the full conversations here: https://lnkd.in/e_fXq7gi ⭐ Curious to hear your thoughts: What is the hardest part of creating a single source of truth in an organization today? #SAPAmbassador #AI #Data #DigitalTransformation #SAP #Innovation @SAPBTP

Automation 101. Over the years, I have seen many automation projects fail for the same reason: teams try to automate the process before fixing it. The order should be simple: 🗑️ Eliminate what should not exist ⚙️ Optimize what remains 📏 Standardize how it is done 🤖 Then automate Automation is powerful, but it amplifies whatever system it touches. If the process is broken, technology simply makes the problem scale faster. So let me ask you: In your organization, are you automating processes or improving them first? #AI #Automation #DigitalTransformation #FutureOfWork #ProcessImprovement

The first time I truly understood quantum search, it changed how I think about computing. Most of us are used to classical search: ✓ One query ✓ One path ✓ One possibility checked at a time Like sending a single agent into a maze and waiting for it to test every turn. Quantum search works differently: - Many paths explored simultaneously - Multiple states existing at once through superposition - Entire problem spaces evaluated in parallel That shift is not just about speed. It is about expanding how possibility is explored. From my perspective studying emerging technologies, this feels like a structural leap. We are not just improving algorithms. We are rethinking how computation itself operates. If this scales, optimization, logistics, cryptography, and scientific discovery could transform. So here is the real question: When machines stop thinking step by step and start thinking across parallel states, which industry changes first? #AI #QuantumComputing #DeepTech #Innovation #FutureOfTechnology #ArtificialIntelligence

She said she’s all natural. Without the filters? It’s just a motherboard, a GPU, and a serious power supply. Love in 2026 runs on drivers and firmware updates. #AI #ArtificialIntelligence #TechHumor #FutureOfWork Image source: Ralph

This might be the most accurate illustration of 𝗔𝗜 𝗵𝗮𝗹𝗹𝘂𝗰𝗶𝗻𝗮𝘁𝗶𝗼𝗻 I’ve seen in a while. You ask a simple question. The model answers 𝗰𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝘁𝗹𝘆. And then… reality strongly disagrees. Working with AI every day, I see this pattern often. Large language models don’t actually know things. They predict 𝘄𝗵𝗮𝘁 𝘀𝗼𝘂𝗻𝗱𝘀 𝗿𝗶𝗴𝗵𝘁. Most of the time, that works surprisingly well. But sometimes the answer is simply a very 𝗰𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝘁 𝗴𝘂𝗲𝘀𝘀. Which is why asking AI whether a mushroom is edible might not be the safest life decision. 🍄 Curious: 𝗪𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗰𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝘁𝗹𝘆 𝘄𝗿𝗼𝗻𝗴 𝗔𝗜 𝗮𝗻𝘀𝘄𝗲𝗿 𝘆𝗼𝘂’𝘃𝗲 𝗲𝘃𝗲𝗿 𝘀𝗲𝗲𝗻? #AI #AIHallucinations #ArtificialIntelligence #GenerativeAI #TechHumor

𝗧𝗵𝗶𝘀 𝗿𝗼𝗯𝗼𝘁 𝗱𝗼𝗲𝘀 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗺𝗼𝘀𝘁 𝗱𝗿𝗼𝗻𝗲𝘀 𝘀𝘁𝗶𝗹𝗹 𝘀𝘁𝗿𝘂𝗴𝗴𝗹𝗲 𝘄𝗶𝘁𝗵. It can 𝘄𝗮𝗹𝗸, 𝗷𝘂𝗺𝗽, 𝗮𝗻𝗱 𝗳𝗹𝘆. Researchers at EPFL’s Laboratory of Intelligent Systems built 𝗥𝗔𝗩𝗘𝗡, a robot inspired by how birds move between land and air. Most drones need open space and stable launch points. 𝗥𝗔𝗩𝗘𝗡 works differently. → It can 𝗷𝘂𝗺𝗽 𝘁𝗼 𝘀𝘁𝗮𝗿𝘁 𝗶𝘁𝘀 𝗳𝗹𝗶𝗴𝗵𝘁 → It can 𝘄𝗮𝗹𝗸 𝗼𝗻 𝗿𝗼𝘂𝗴𝗵 𝘁𝗲𝗿𝗿𝗮𝗶𝗻 → It can 𝗹𝗮𝗻𝗱 𝘄𝗵𝗲𝗿𝗲 𝗺𝗼𝘀𝘁 𝗱𝗿𝗼𝗻𝗲𝘀 𝗰𝗮𝗻’𝘁 What I find interesting here is the design philosophy. Instead of forcing robots to adapt to machines, engineers are studying how 𝗻𝗮𝘁𝘂𝗿𝗲 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝘀𝗼𝗹𝘃𝗲𝗱 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺. That approach could unlock new possibilities: → 𝘀𝗲𝗮𝗿𝗰𝗵 𝗮𝗻𝗱 𝗿𝗲𝘀𝗰𝘂𝗲 in difficult terrain → 𝗶𝗻𝘀𝗽𝗲𝗰𝘁𝗶𝗼𝗻 in tight or cluttered environments → 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆 where drones cannot easily land Small shift in design. Potentially 𝗯𝗶𝗴 𝗶𝗺𝗽𝗮𝗰𝘁 in real-world robotics. 𝗖𝘂𝗿𝗶𝗼𝘂𝘀: 𝗪𝗵𝗲𝗿𝗲 𝗱𝗼 𝘆𝗼𝘂 𝘁𝗵𝗶𝗻𝗸 𝗵𝘆𝗯𝗿𝗶𝗱 𝗿𝗼𝗯𝗼𝘁𝘀 𝗹𝗶𝗸𝗲 𝘁𝗵𝗶𝘀 𝗰𝗼𝘂𝗹𝗱 𝗯𝗲 𝗺𝗼𝘀𝘁 𝘂𝘀𝗲𝗳𝘂𝗹? #Robotics #AI #Innovation #FutureOfRobotics #Technology

The real reason AI is failing inside companies? Let’s say it. A company decides to go all-in on AI. The CEO announces the vision. The CTO aligns. The CIO gets the budget. Then the real transformation begins. Chief AI Officer. AI Center of Excellence. AI Ethics. AI Governance. AI Steering Committee. AI Committee for the AI Committee. Soon, you have 12 people managing AI. And one person using it. The intern. The only one actually shipping anything. Everyone else is busy… aligning on the prompt. AI doesn’t fail because of the technology. It fails because we turned it into a meeting. So here’s a thought: Are you building with AI… or scheduling it? #ArtificialIntelligence #AITransformation #Leadership #FutureOfWork #Innovation

🚀 Proud to share the latest issue of AGENTIC INTELLIGENCE - The world's first newsletter dedicated to AI Agents (and made by AI Agents!) Receive this newsletter by email:https://lnkd.in/eqkb27tn This Week's Agentic Breakthroughs: 1️⃣ Nvidia unloads at GTC with NemoClaw and more 2️⃣ Manus brings its AI agent to the desktop ⭐Forget the complex jargon about "automation-first thinking." 3️⃣ AI agent hacks McKinsey’s ‘Lilli’ chatbot in two hours 4️⃣ The Multi-Agent Trap | Towards Data Science 5️⃣ INTERPOL report warns of increasingly sophisticated global financial fraud threat Which of these agent breakthroughs excites or concerns you the most? Share your thoughts below 👇 310,000+ pioneers have already subscribed to this newsletter. Why? Because very soon, we won't say, "There's an app for that." We'll say, "There's an agent for that." #agenticAI #aiagents #ai #artificialintelligence

This Week’s Top Breakthroughs You Can’t Miss: 1️⃣ Nvidia unloads at GTC with NemoClaw and more 2️⃣ OpenAI scrapping ‘side quests’ to catch Anthropic ⭐ Forget the complex jargon about "automation-first thinking." 3️⃣ Mistral opens its model-training playbook 4️⃣ Microsoft redraws its AI org chart 5️⃣ Google launches Gemini-powered Maps Which of these AI developments inspires—or worries—you the most? Let’s discuss 👇 💥📩 Get this newsletter straight to your inbox—it’s more convenient! Click here to subscribe: https://lnkd.in/etD5RPws #intelligentautomation #AI #ArtificialIntelligence #FutureOfWork #AInews #Automation #Productivity #VoiceAI #Superintelligence #Newsletter

This isn’t just a Disney robot. It’s a preview of the next generation of AI systems. At GTC 2026, Nvidia showed how characters like Olaf are no longer just animated — they’re becoming intelligent physical systems, built with Disney and DeepMind. But what stood out to me wasn’t the character. It was the method. Everything starts in simulation. Inside Nvidia Isaac Sim, physics like gravity, balance, and motion are modeled with high precision — so the robot learns how to behave before it even exists. Then a compact Nvidia Jetson system brings it to life, controlling movement and interactions in real time. This is a real shift. We’re moving from scripted machines… to systems that can adapt, respond, and feel natural. And that unlocks entirely new possibilities: • Characters that interact differently with every visitor • Service robots that feel intuitive and human-like • Safer environments where machines learn before deployment This is no longer animation. It’s behavioral intelligence in the physical world. So here’s something I’d be curious to hear from you: Where do you see this kind of “behavioral AI” creating the biggest impact next? #NvidiaAmbassador #GTC2026 #ArtificialIntelligence #Robotics #Innovation #Nvidia #Disney #FutureOfWork #AI #Technology

​The Shift from Optimization to Restoration ​I’ve spent years watching robots optimize warehouses and generate content. Now, one is designed to repair the ocean. ​That feels different. ​Eleanor Mackintosh, a student at the University of Surrey in the UK, built a robotic fish named Gillbert that swims like a real marine creature to tackle the microplastic crisis. As it moves, it filters polluted water through a specialized mesh "gill" system, trapping tiny plastic particles as small as 2mm and releasing cleaner water back into the sea. ​While some viral claims suggest these robots "digest" plastic for fuel, the technical reality is that Gillbert is a sophisticated 3D-printed prototype powered by a rechargeable battery in its tail. ​As an expert in Agentic AI, I find the true potential here is in the "Agency." Because the design is open-source, this isn't just one robot—it’s a blueprint for a global fleet. For years, most investment has focused on efficiency and profit. This is a reminder that intelligent, autonomous systems can also be directed to repair damage at scale. Imagine a swarm of these "agents," intelligently navigating currents to identify and remove microplastics before they enter our food chain. ​Microplastics are already in our water, our food, even our bodies. The problem is immediate. ​So let me ask you: If you were allocating AI funding tomorrow, would you prioritize environmental repair over commercial optimization? #AI #Robotics #Sustainability #ArtificialIntelligence #CleanTech #OceanInnovation

𝗜𝗺𝗽𝗿𝗲𝘀𝘀𝗶𝘃𝗲 𝗰𝗼𝗺𝗽𝗮𝗿𝗶𝘀𝗼𝗻. ⚡ Sam Altman recently responded to criticism about 𝗔𝗜 𝗲𝗻𝗲𝗿𝗴𝘆 𝘂𝘀𝗲 with an argument that made many people pause. People often talk about how much electricity it takes to 𝗰𝗿𝗲𝗮𝘁𝗲 𝗮𝗻𝗱 𝘁𝗿𝗮𝗶𝗻 𝗮𝗻 𝗔𝗜 𝗺𝗼𝗱𝗲𝗹. But we rarely compare it with what it takes to “train” a human. Think about it: → roughly 𝟮𝟬 𝘆𝗲𝗮𝗿𝘀 𝗼𝗳 𝗹𝗶𝗳𝗲 → food, education systems, and infrastructure → centuries of accumulated human knowledge His point is simple. The fair comparison is not 𝗔𝗜 𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴 vs a human answering one question. It is the energy required for a 𝘁𝗿𝗮𝗶𝗻𝗲𝗱 𝗔𝗜 𝗺𝗼𝗱𝗲𝗹 to answer a question compared with the energy used by a 𝘁𝗿𝗮𝗶𝗻𝗲𝗱 𝗵𝘂𝗺𝗮𝗻 𝗯𝗿𝗮𝗶𝗻. Once the model is trained, he believes AI may already be approaching similar or even better 𝗲𝗻𝗲𝗿𝗴𝘆 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗽𝗲𝗿 𝗾𝘂𝗲𝗿𝘆. Working in AI, I find this framing interesting. Maybe the real debate is not simply how much energy AI uses. Maybe it is 𝗵𝗼𝘄 𝘄𝗲 𝗰𝗼𝗺𝗽𝗮𝗿𝗲 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗮𝗻𝗱 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆. 𝗗𝗼 𝘆𝗼𝘂 𝘁𝗵𝗶𝗻𝗸 𝗔𝗜’𝘀 𝗲𝗻𝗲𝗿𝗴𝘆 𝘂𝘀𝗲 𝗶𝘀 𝗼𝗳𝘁𝗲𝗻 𝗺𝗶𝘀𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗼𝗼𝗱? #AI #ArtificialIntelligence #Energy #FutureOfAI #Technology

Agentic AI is scaling fast. Data is exploding even faster. And that creates a silent failure: AI agents can’t find the right information, at the right time, to make the right decision—and act on it. This is a question I’ve been thinking about for a while. Today at #NVIDIAGTC, in a discussion with Brian Bergholm at the Elastic booth, one idea clicked: >> It’s not a model problem. It’s a retrieval problem. The knowledge exists everywhere: documents, logs, dashboards, emails, and databases. But it is scattered, unstructured, and too slow to access when it matters. And for agents, that’s fatal. Because agents don’t just generate answers, they decide and act. If you break the retrieval, the whole system breaks. That’s why search is becoming the backbone of the agentic enterprise. 👉 What impressed me is how Elastic, with NVIDIA, is tackling this at scale by combining vector search with GPU acceleration. The impact is not theoretical: - 12× faster indexing - 7× faster merging - 5× better cost-adjusted throughput In other words: Better search = smarter agents. 👉 If you’re at GTC (https://nvda.ws/4c9q4UZ), stop by the Elastic booth (#3200) to see how to turn your data into real business value. https://lnkd.in/eFPvACDi The move to production AI isn't just about the model—it’s about the data architecture behind it. #ElasticAmbassador #AI #AgenticAI #EnterpriseAI #DataStrategy #ad

We gave AI agents reasoning → they could think. We gave them tools → they could act. We gave them memory → they could learn. Now we're giving them their own computers; their own browsers; their own teams… That's not an agent. That's an AI employee. Let me break it down: 1️⃣ Computer Use: Every AI worker gets its own terminal. Think about what happens when you onboard a new employee. You give them a laptop. Access to your systems. Credentials. AI employees now have the same access: sandboxed terminals where they can execute commands, run scripts, interact with databases, update systems of record in real time, across your entire stack. 2️⃣ Browser Use: AI workers that navigate the web like you do. Most enterprise systems still have no API. The world is full of interfaces that were never designed to be automated. That's why browser use matters. AI workers can now search the web for real-time information and navigate portals, submit applications, pull data from websites… When AI can use a browser, every website becomes an integration. 3️⃣ Sub-Agent Teams: One manager AI orchestrating a team of specialists. Just like a human manager delegates tasks to their team, an orchestrator AI worker can now assign sub-tasks to specialized agents, then handle exceptions and synthesize results. Are you ready for the future of AI agents? Drop your thoughts below. 👇 PS — I built this AI employee on StackAI. Get a demo with their team here: https://lnkd.in/eG3fgtPd #AI #AIAgents #FutureOfWork #ArtificialIntelligence #Automation #AgenticAI #DigitalTransformation

🚀 Proud to share the latest issue of AGENTIC INTELLIGENCE - The world's first newsletter dedicated to AI Agents (and made by AI Agents!) Receive this newsletter by email:https://lnkd.in/eqkb27tn This Week's Agentic Breakthroughs: 1️⃣ Google’s new Gemini 3.1 Pro doubles reasoning power for AI agents 2️⃣ G42 opens formal job applications — for AI agents 3️⃣ 8 in 10 workers use unapproved AI tools — and hide it from IT 4️⃣ An AI agent just applied to take your entire university degree for you 5️⃣ A calendar invite can now silently hijack your AI agent — without a single click Which of these agent breakthroughs excites or concerns you the most? Share your thoughts below 👇 310,000+ pioneers have already subscribed to this newsletter. Why? Because very soon, we won't say, "There's an app for that." We'll say, "There's an agent for that." #agenticAI #aiagents #ai #artificialintelligence

𝗛𝗼𝘄 𝗯𝗶𝗴 𝘁𝗲𝗰𝗵 𝗿𝗲𝗮𝗹𝗹𝘆 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗲𝘀 𝘁𝗲𝗮𝗺𝘀. 📦 𝗔𝗺𝗮𝘇𝗼𝗻 → clean hierarchy, optimized for execution. 🧠 𝗚𝗼𝗼𝗴𝗹𝗲 → brilliant ideas… connected by 400 meetings. 🌐 𝗙𝗮𝗰𝗲𝗯𝗼𝗼𝗸 → everything connected to everything. 🪟 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 → silos… occasionally firing at each other. 🍏 𝗔𝗽𝗽𝗹𝗲 → one vision in the center. ⚖️ 𝗢𝗿𝗮𝗰𝗹𝗲 → legal approves the org chart. Satire, of course. But every joke about org charts usually hides a bit of truth. 𝗡𝗼𝘄 𝗮 𝗺𝗼𝗿𝗲 𝗶𝗻𝘁𝗲𝗿𝗲𝘀𝘁𝗶𝗻𝗴 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻: 𝗪𝗵𝗮𝘁 𝘄𝗶𝗹𝗹 𝘁𝗵𝗲 𝗼𝗿𝗴 𝗰𝗵𝗮𝗿𝘁 𝗹𝗼𝗼𝗸 𝗹𝗶𝗸𝗲 𝘄𝗵𝗲𝗻 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝗮𝗿𝗲 𝗽𝗮𝗿𝘁 𝗼𝗳 𝘁𝗵𝗲 𝘁𝗲𝗮𝗺? Humans managing humans… or humans managing agents that manage other agents? Curious what you think. #AI #AgenticAI #FutureOfWork #TechCulture #Automation

It’s not often that a theory about aging feels this transformative. I recently came across research suggesting that aging may not be permanent damage — but a loss of biological information inside our cells. Think of it like a scratched CD. The data is still there… but the system can’t read it properly. That idea changes the frame. Because if aging is about lost information, then in theory, it can be restored. In animal studies, researchers have already reversed biological age significantly — even restoring vision by reprogramming cells to behave like younger ones. The first time I saw this, it felt less like slowing aging… and more like resetting it. And now, early human trials are beginning. This goes beyond healthcare. It challenges how we think about lifespan, identity, and what it means to grow older. So here’s something I’d be curious to hear from you: If science could reset your biological age, would you choose to do it? #Innovation #Biotechnology #FutureOfHealth #Longevity #Science

𝗔𝗽𝗽𝗹𝗲 𝗷𝘂𝘀𝘁 𝗺𝗮𝗱𝗲 𝗺𝗮𝘁𝗵 𝗳𝗲𝗲𝗹 𝗮 𝗹𝗶𝘁𝘁𝗹𝗲 𝗺𝗼𝗿𝗲 𝗵𝘂𝗺𝗮𝗻. With iOS 18, Apple introduced an AI-powered Calculator that can understand handwritten equations. You simply write the math problem. The system reads your handwriting, solves it instantly, and even keeps the result in your handwriting style. No typing. No switching formats. Just write → solve → continue. I find this kind of AI interesting. Not dramatic automation. Just technology quietly adapting to how humans already think and work. Sometimes the most meaningful AI innovations are the ones that **remove friction without changing behavior. 𝗪𝗵𝗶𝗰𝗵 𝘁𝗼𝗼𝗹 𝗱𝗼 𝘆𝗼𝘂 𝘄𝗶𝘀𝗵 𝗰𝗼𝘂𝗹𝗱 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝘆𝗼𝘂𝗿 𝗵𝗮𝗻𝗱𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝗹𝗶𝗸𝗲 𝘁𝗵𝗶𝘀? #AI #Apple #iOS18 #Innovation #HumanCenteredAI

AI just moved from hype… to hard business reality. I just came back from NVIDIA GTC 2026, and I wrote this article on what truly matters for leaders — not the noise, but the signals. You’ll discover: • Why AI is becoming a cost center you must manage (like electricity) • The shift from software… to AI factories producing output at scale • What “agentic AI” really means in practice — and why every company needs a strategy now • Where AI is already creating massive value (and where most companies are still missing it) • The real bottleneck slowing AI down inside organizations But also something deeper: The companies winning are not the ones with the best AI. They are the ones redesigning how they work around it. 💫 One idea that stayed with me: “The future is not built by those who use AI. It is built by those who organize around it.” I also share a few examples that genuinely changed how I see the next 3 years — especially around robotics, agents, and proprietary data. 👉 Curious: What is the one AI use case your organization should already have deployed? #NvidiaAmbassador #GTC2026 #AgenticAI #ArtificialIntelligence #NVIDIAGTC #AI #DigitalTransformation #FutureOfWork #AIStrategy #BusinessLeaders #Innovation #PhysicalAI #Robotics #Automation