Steve Brown

Ray-Ban Meta Stunt Test is Crazy 💀🔥 Yesterday, Meta unveiled their latest AR innovation, the Orion glasses, and today they're putting Ray-Ban Meta to the ultimate test. Joining forces with the unstoppable duo of @John Cena and @Benson Boone, Zuck himself is taking these glasses on an epic stunt-filled adventure. Mark on Fire 🔥 Mark with a Katana 🥷🏽 Mark vs a WWE Legend 🛎 Guess what? Glasses are holding up like champs! This is more than just a product demo; it's a masterclass in how to launch a new tech gadget. By combining humor, action, and a touch of celebrity, Meta has created a viral sensation that's already taking over social media. I love how Mark balances the serious side of tech with a playful spirit. It's a refreshing approach that makes you want to be a part of the Metaverse 👽 What do you think of this epic crash test? Let me know in the comments! #Meta #RayBan #AR #VR #Zuckerberg #JohnCena #BensonBoone #crashtest #tech #innovation #seriouslyfun

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Some nice tips about using ElevenLabs Text-To-SFX feature. Feel free to try them out. My first tests were not that successful, but in the end, I am not the expert user and I only tested for a couple of minutes. Question is, if it will currently help professional sound designers to really be more efficient? I suppose not yet, as I am pretty sure you are faster when you know your existing library inside out. But as an additional tool, when looking for something you do not yet have, this will come in pretty handy very soon I guess. #ai #genai #elevenlabs #soundeffects #sounddesign #postproduction

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Reimagining Healthcare Workforce Platfforms: Turning Capital Into Labor The future isn’t just about filling shifts. It’s about scaling labor intelligently, driving better outcomes for systems, staff, and patients alike. Andreessen Horowitz and Alastair (Alex) Rampell reinforced this Vision in a recent post and it applies to the next phase of healthcare workforce evolution. Healthcare workforce marketplaces plus AI are at the tipping point of transformation, evolving into systems of record that don’t just manage labor—they optimize it. Much like EHRs centralized patient care data, these marketplaces can centralize workforce operations, aligning talent supply with clinical demand. But there’s a bigger opportunity here: turning capital into labor. Here’s what I mean. Historically, industries (including healthcare) have focused on enterprise computing tasks—streamlining data entry, compliance, and back-office functions. While valuable, this approach often stops short of transforming the real-world, repetitive processes that make up the bulk of work in healthcare. Think beyond enterprise software. The next frontier lies in leveraging embodied AI and workforce marketplaces to automate and enhance labor-driven processes, transforming capital investments into productive labor outputs. For healthcare, this means turning staffing costs into scalable, dynamic systems that deliver value far beyond filling shifts: 1. Dynamic Labor Matching: Capital invested in marketplace platforms enables real-time matching of labor supply with patient demand, replacing outdated scheduling models with predictive, automated systems. 2. Workflow Automation: From credentialing to compliance and shift bidding, embodied AI can streamline traditionally manual tasks, freeing human resources for higher-value work. 3. Labor as a Strategic Asset: Workforce marketplaces shift the focus from static staffing budgets to proactive labor deployment, ensuring that every dollar invested in labor drives outcomes and efficiency. It is about the billions of repetitive, planned tasks that AI can improve. In healthcare, that means automating everything from staffing logistics to clinical task assignments, creating a horizontal system of engagement for labor (think Zendesk) that integrates seamlessly with vertical, workflow-specific platforms (think Toast for staffing operations). The result? Hundreds of billions in untapped market potential—and a healthcare workforce model that transforms how care is delivered. By turning capital into labor through smarter marketplaces and automation, we don’t just solve staffing challenges; we redefine what’s possible in healthcare operations and ShiftMed is leading the way with health systems moving beyond tired models. #capitalintolabor #systemsofrecord #healthworkforce #aiworkforce #healthsystems #hospitals #cno #hospitalceo #healthcareinnovation

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Dimensional video can be used to store and catalog historic video memories in a virtual wireframe of space and time. The simplest and least expensive Televerse rig is (4) cellphone cameras streaming over WiFi or 5G to an IP video multiplexer. An (8) cellphone rig for the fully Immersive Teledeck format is light enough to start planning drone payloads. Imagine 15 seconds of immersive 4K 3D video in a Teledeck from Butler PA two weekends ago. Extracting an (8) screen wireframe to run thousands of eyewitness photos and videos against using AI grid coordinates. Locating eyewitness photo/video’s spatial relationship to the wireframe reference… then temporal. Hardware based 4K encoders with HDMI inputs offer maximum plug and play versatility for a real-time mobile or fixed studio. A car outfitted with (16) cameras would create a moving cube of immersive 4K 3D video that could be GPS mapped to street addresses and split into video segments by intersections. The MPTS Teledeck format is encoded/multiplexed in real-time to a VOD server at 30 or 60 frames per second. The video segment between each street intersection would contain synchronized video I-frames from all (16) cameras in a single sharable video transport stream. Those (16) .jpg/.png, extracted and applied as a L/R view on the (8) screens of the virtual wireframe, could be mapped to a headset view. This would allow a creator to share a static 16' cube of fixed spacetime with another viewer. In the case of 3D Immersive street mapping... AI analysis could locate manhole covers, telephone poles, electric transformers, fire hydrants, etc... all GPS mapped/displayed in continuous searchable cubes of street grid video. Dimensional Video Networks run on WebRTC. Web3 provides decentralized VOD servers and blockchain. Starlink provides a global footprint. Hardware encoded real-time 4K with MPTS multiplexer https://lnkd.in/gU5y4Sqw Receive IPTV and output to a CATV channel for direct TV tuning… scramblers allow STB encryption. https://lnkd.in/gGEpycZa 10,000 stream licence VOD server for Android based STBs. https://lnkd.in/gAR9Jckv Host the video server on Web3 and get paid for being a node on the blockchain. https://lnkd.in/gysVQvQu Threefold had different vendors throughout the world but something like this could be used beside each VOD server to also become a home Web3 node. https://lnkd.in/gs7PqEbV

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China's Next-Gen AI Sexbots: Revolutionizing Intimacy with Advanced Robotics: Imagine waking up one day to a world where the line between human and machine becomes tantalizingly blurred. That day may... https://lnkd.in/ga4pF4Ye

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Ruminations on Mythos: The term is not "cinematic universe". Cinematic universe means one is making shared IP films. Mythos is the correct term. Myth·os - (in literature) "a traditional or recurrent narrative theme or plot structure". A mythos is a fictional universe for stories by one writer or many that has a consistency of characters, setting, events, style, and world. The Cthulhu Mythos is one of the best known examples. 78 writers have contributed to HP Lovecraft's Cthulhu Mythos over the past 96 years (1928-2024). While HP Lovecraft was alive, a circle of writers contributed to the Cthulhu Mythos including: August Derleth, RE Howard, Fritz Leiber, Robert Bloch, Frank Belknap Long, Donald Wandrei, and Clark Ashton Smith. Many more added to the mythos after his death. They wrote stories in the shared universe of the Cthulhu Mythos. That is a mythos. Or one can just give a name to the universe that one creates. JRR Tolkien - Middle Earth, Terry Brooks - Shannara, CS Lewis - Narnia, George RR Martin - The Song of Fire and Ice, Fritz Leiber - Nehwon, RE Howard - The Hyborian Age, Larry Niven - Known Space Universe. Writers do this all the time, alone or together. Now if game creatives build the consistency of a mythos around their work, like with Halo, Resident Evil, and others, then the pitch process to publishers or consumers is different. One understands the basics of Assassin's Creed, Dead Space, Mass Effect, or Dragon Age. One knows what to expect not just for sequels but for different games around different characters in different genres in the same world setting. Fallout is more mythos than just IP. By contrast, Mario is more an IP than a mythos. Interestingly Mario as an IP has done more genre shifts than is often done with an IP that is a Mythos. The Legend of Zelda is more mythos than Mario, but in one genre. Mario is many genres in one world setting or IP. ---- VideoGameChronicle: "Dave the Diver’s creator wants to create a ‘Dave cinematic universe’ of games. Jaeho Hwang reveals future games will explore different characters and genres" “Actually, I want to expand Dave the Diver IP itself,” Hwang said, when asked what the future holds for Mintrocket. “I think that’s every director’s dream, since we have a relatable character. “But actually, we didn’t go really deep into the personal stories in Dave the Diver, because we wanted to keep the game very casual. “So as a director, besides the story DLC that we’re working on right now, I also want to make separate games about each character to show how they met, what they did before coming to the Blue Hole. “In that sense, the games’ genres can be different. Maybe one day, if we start to make a Dave’s backstory game, we could make Dave another profession. Hwang said he wants to flesh out the Dave the Diver story by telling the backstories of both its protagonist, and main side characters." VideoGameChronicle: https://lnkd.in/gUs-d23W #gameindustry #gamedev #worldbuilding

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Matrix Thoughts The MATRIX framework is undeniably impressive, pushing the limits of AI training through multi-agent simulations. But when I reflect on this approach, it feels like we’re still missing a vital piece in the larger puzzle. Right now, training agents on diverse, simulated data teaches our models what happened, but does it really help them grasp why things happen? That distinction matters. As humans, we don’t just passively collect data—we evolve and adapt because we have to. We’re driven by our needs, desires, and experiences, which push us to understand the why behind everything we encounter. Think about how we learn as kids. We’re born with a genetic “operating system,” ready to learn, but it’s through our interactions with the world that we start to understand cause and effect. We learn by doing, by seeing consequences, by figuring out why things work the way they do. So, what if we could build an agent architecture that learns more like we do—evolving through experience? Imagine starting with a foundational “genetic” layer that encodes basic learning and reasoning skills. We could then drop this agent into a multi-agent environment where it has to navigate diverse goals and needs. In this world, the agent wouldn’t just soak up information passively—it would be actively experimenting, gathering experiences, and most importantly, inferring causal relationships. With the right mix of adaptive learning modules and causal reasoning engines, it could start understanding not just what’s happening, but why. Obviously, building something like this is a massive challenge. The computational requirements would be off the charts, and we’d need environments complex enough to foster real, meaningful learning. Plus, there’s an ethical minefield in simulating evolutionary pressures and human-like needs. But if we could pull this off, the potential would be huge. By focusing on why things happen and letting agents learn through experience, we might be able to close some of the gaps between where AI is now and where we want it to be. In my work in VFX and AI, I’ve seen firsthand that it’s not enough to just understand what makes something look real—you have to understand why it looks real. It’s the difference between someone who follows directions and someone who can truly innovate and solve problems. The MATRIX framework is promising, but it’s just one of many paths we could take. The idea of evolving AI through experience is exciting, but it’s going to be incredibly complex to implement. Still, I’m convinced that current AI, as powerful as it is, doesn’t really understand. This evolutionary approach might not be the silver bullet, but it’s at least taking a shot at understanding the ‘why’ behind intelligence, not just the ‘what.’

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The bigger issue is data protection. Stop getting wound up into hype. Show me a system where I can lock up my data and localize the interactions without having to send my queries into an LLM owned by big data and I’ll be interested. But I’m not sure how your data isn’t “stolen” and used to train on you as the product. RAGs are the closest structures that could provide security. We need to own our knowledge graphs. Question everything, trust nothing. Nothing is always the beginning of everything to shake your up life 😉

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Imagine this: You create a low-poly game that feels like it’s straight out of a 1989 arcade. Then, run it through an AI filter that enhances the graphics in real-time to a high-fidelity experience. We’re not there yet of course — processing speed and render times are still catching up to the concept — but just like Toy Story was once rendered offline and today we can play in real-time games with better graphics than that movie… it's only a matter of time in the world of faster, better, cheaper. Could visual fidelity in games soon become less about technical expertise and more about the power of AI rendering on the fly? #videogames #genai #ai #gamedev #rendering #unreal #unity #technicalartists #toystory

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