NICHoLAS WEIGEL

From Reddit threads to million-dollar bidding wars, the short story has become Hollywood's most efficient engine for new IP. I'll do a little exploration as to why 'small' can be the new 'big' for indie creators. https://lnkd.in/gW447uur This post was inspired by "The Big Short" by Antonia Cereijido, originally published in L.A. Material. #213TV #indie #shortstory #film #filmmaker #tv #TheBigShort

1

Emotive AI assisted image by Ivona Tau (Tautkutė - Rustecka, PhD) created using a custom generative model for today's essay Nicole C. Rust, PhD : What can AI teach us about ‘emotions’? Exploring why Anthropic’s AI, Claude, displays something like emotion could ultimately help us better understand the function that emotions serve in humans: https://lnkd.in/eFHfU3t3 for The Transmitter

15

2 Comments

In 2026 half of my work is 3D and half is Gen AI (mostly hybrid). Unreal Engine really has the foundation to be an incredible way to control Generative AI. I've been working A LOT with the different Gen AI platforms that most have their own graph/node workflow but are pretty undercooked compared to Unreal Engine Blueprints, especially the new Control Rig Blueprints which are a generational leap forward from the traditional Actor Blueprints system. To continue to modernize Unreal Engine for the Generative AI era I've put together this simple previs graph. UE is great as coding and working with string aka "TEXT" (I know text this is it's own variable type too) and would make automating annoying text concats programmatically a breeze. Add a simple API call nodes to Google Nano Banana or Epic's own image model. Reference in CG cameras from Sequencer or at run time and have it output textures for clothing, faces, etc. at run time or for offline sequencer use.

357

18 Comments

"What I did On My Winter Break" Happy New Year! Over the holidays, I decided to do a shot-for-shot reviz (or re...dux? re...shoot? re...generate? IDK) of the MECHAGOLDZILLA preview/teaser that I made a little over 18 months ago to give myself a true A/B of how far generative AI video tools have come. There's still a long way to go if consumer products are ever going to be ready for the screen, but this latest reviz tells me that the local tools being built at our better animation studios and post houses will be making content for real audiences in 2026. In fact, some of them already are and you might not have even noticed 🤐 As for MECHAGOLDZILLA, this version has taken my thinking from: "This is something that could potentially be included in a deck" to: "This is absolutely going in a deck, and maybe replacing the one-banger" One of the best parts is how much better (still not perfect but insanely better) my character sheets and storyboards are being interpreted without even modeling. See it in comments 👀 Check it out, and if we haven't caught up in a while, let's make 2026 the year

13

1 Comment

From static render to dynamic story 🧠 We brought our NICO Corporation surgical instrument to life with Vizcom animation. Static renders only tell part of the story. Animation shows how the instrument moves, fits in surgeons' hands, and integrates into operating room workflow. All of this helps clients visualize products before manufacturing. It's especially captivating when applied to medical devices where in-use context and ergonomics can make or break a product’s functionality. #Vizcom #ProductDesign #MedicalDevice #DesignVisualization #Animation #DesignProcess Beyond Design, Inc.

15

1 Comment

It feels like this news didn’t land as loudly as it should have. The app built by Alexander Chen, based on Gemini Intelligence, makes a first step toward something many in the XR industry have been waiting for: spatial AI interacting with the real world through interface-like experiences. I’m confident that development in this direction will give the XR industry a major boost. Link to the app: https://lnkd.in/edfEB6cx

31

1 Comment

Ran a constrained dialogue stress test this week. No action. No spectacle. Static frame. Four characters. One exchange. The variable wasn’t visuals, It was control. > Identity persistence across cuts. > Micro-expression stability under close coverage. > Voice continuity without tonal drift. > Environmental and typography coherence in motion. > Guardrails over IP Dialogue exposes weakness fast. If embeddings aren’t stable, you see it. If temporal consistency slips, you feel it. If the model doesn’t understand power shifts, the scene collapses. I also operated close to recognizable cinematic grammar. There’s a thin line between abstraction and protected territory — and that line is increasingly algorithmic. Guardrails are evolving. So is the model intelligence around likeness and structure. Right now, the boundary is still being defined. What do you notice first — performance, continuity, or structure?

5

3 Comments

Seeing a lot of creators on X especially from the Western side constantly yapping about “Seedance nerf, Seedance nerf.” Bro… what nerf? Everything works perfectly fine on my side. Seedance 2.0 is still one of the best video models right now. At this point it just feels like a black campaign. If you want to compete with China’s AI progress, build better models. Not fake narratives while hyping tools that break the moment you actually use them. #seedance2

7

6 Comments

𝗣𝗹𝗼𝘁 𝘁𝘄𝗶𝘀𝘁: The people designing XR's future aren't living in it yet… and that's actually fascinating 🚀 What XR apps do you actually use regularly outside work? (Skip games - share the utility gems!) I design immersive experiences for a living and advocate for spatial computing, yet my Screen Time report looks embarrassingly traditional. The tools exist and they're genuinely useful:  • 📱 Google Lens: Visual search beats typing  • 🏠 IKEA Place: See furniture before buying    • 📏 Apple Measure: Tape measure in your pocket  • 🗺️ Google Maps AR: Never get lost again  • 🌎 Noun Town VR Language Learning: Immersive language learning But here's the thing - even I barely use these weekly, let alone daily. So here's my challenge: Name ONE XR app you genuinely use regularly and tell us what problem it solves better than traditional alternatives. Bonus points: Include how often you actually use it. Let's collectively prove XR utility exists beyond the hype. #XR #SpatialComputing #UserExperience #Innovation

10

1 Comment

Synthetic research is having its moment. Looking to understand exactly what it is and how it's being used? I just published a two-part series on the TLC blog that digs into what’s happening in the space and why it matters for anyone doing market, user, or community-driven research. • Part I provides an overview of what synthetic research actually is, why companies are adopting it so quickly, and the emerging ways teams are using AI-generated personas, feedback, and simulations. • Part II goes back in time to 2015, when my startup Thicket built the Character Designer Dashboard—an early collaborative AI tool that relied on a very different logic and approach to research and synthesis. I revisit that work to offer a useful contrast to where the field is now. If you’re curious about how gen AI is reshaping research (or if you just want to see how these ideas have evolved), give both posts a read: Part I: https://lnkd.in/gy8gMftN Part II: https://lnkd.in/gsZX5wjr #SyntheticResearch #AIPoweredInsights #FutureOfResearch #ResponsibleAI #DesignStrategy

5

After almost a decade in the XR trenches, I’m hearing a question more often than ever in conversations with brand and agency leaders: “Is VR dead? Is XR over?” The concern is understandable... Meta’s recent XR layoffs and studio closures made headlines. But in my view, we’re far from XR’s demise. Even Oculus founder Palmer Luckey has pushed back on the doomsayers, calling Meta’s downsizing “not a disaster” and rejecting the idea that the company is abandoning VR. He frames the restructuring as “a good thing for the long-term health of the industry” – a necessary reset, not a retreat Before I give my take, here are the facts: 1) Market Momentum: The global XR market was about $50 billion in 2023 and is growing ~30% yearly – projected to exceed $500 billion by 2032. Investors poured $16 billion into XR in 2022 alone, reflecting strong confidence. 2) Tech Titans Betting Big: The XR hardware race has accelerated. Apple’s Vision Pro ecosystem is gaining traction. Meta’s Quest 3 is now mainstream, and Orion AR glasses are expected to ship this year. Major players are doubling down, not pulling back 3) Consumer Engagement Rising: AR is now standard across platforms – more than 2 billion mobile users engage with AR regularly. Over 60% of consumers say they prefer to buy from brands that offer AR, showing sustained demand. 4) VR Usage Up, Not Down: The VR user base is more active than ever. Over $2 billion has been spent on Meta Quest content to date, and time spent in VR continues to rise – clear signs of durable engagement, not decline. So my take is XR is not dead – it’s on the cusp of something big. We’re at the best position I’ve seen yet for an explosion of XR opportunities. The hardware has matured (lighter, faster, more affordable) and the hype has given way to real adoption. Businesses are finding tangible value (training, design, marketing), and consumers are warming up as useful XR experiences emerge. Meta’s shift in strategy isn’t a bad omen but a course correction. It’s refocusing on core tech and empowering the wider ecosystem – exactly what our industry needs for healthy growth, as Luckey pointed out. Far from a “VR winter,” this feels more like spring: the groundwork is laid, the major players are invested, and the ecosystem is more balanced. As a founder, I’m optimistic. The question “Is XR over?” will soon sound absurd. In 2026, all signs point to an XR industry that’s leaner, stronger, and ready to go mainstream, not in some distant future, but now. Let’s get building! Palmer's Opinion: https://lnkd.in/gKKE_CWk Sources in comments

51

36 Comments

How I went from chasing “perfect AI renders” to building AI production systems clients cannot live without by focusing on workflows instead of models. Two years ago when we started the company, all I cared about was image quality. Better prompts, better models, better niches. If the render looked sharper, I considered it a win. Then AI video arrived and I repeated the same mistake. How do we get the cleanest, most cinematic AI video on the market? Today, most leading models are “good enough” and brands can already ship full commercial campaigns with AI video. What changed in 2025 and 2026 is not the pixels, it is the market. → Clients are now openly asking for AI production. AI is no longer a gadget, it is the default solution. So the real question becomes: when everyone has similar models and similar quality, who survives? It will not be the one with the nicest render... It will not be the one with the “craziest” creativity... → It will be the one with the strongest system and the most robust workflows. Enterprises have already understood this. Groups like LVMH are internalizing production, building their own AI pipelines, and reducing dependency on external studios. Soon, many of them will not buy media at all. They will buy an operating system for production, then run it themselves. That realization triggered me to reinvent our role a year ago. Our mission today is simple: help businesses internalize AI production before price wars and global competition erode their margins. We do this by installing real AI workbenches, not “one more SaaS tool”, so internal teams can operate end to end on a controlled production pipeline. This is the system that took me from selling outputs to designing the infrastructure behind those outputs. Once a team owns its AI production system, every campaign becomes a repeatable asset instead of a one-off Saas miracle. PS If you want to stop competing on “nice visuals” and start owning an internal AI production pipeline, send me a message and we can see whether the our approach at Xtendency™ AI Production Consulting House makes sense for your team.

4

OTTODEVELOPMENT is a Los Angeles-based laboratory led by technical polymath Johnny Otto, operating at the intersection of industrial engineering and generative AI. Mirroring the "Director-Inventor" archetype of James Cameron and the "design science" philosophy of Buckminster Fuller, the lab engineers proprietary systems to solve complex mechanical and digital friction while strictly adhering to the federal mandate to use American-produced AI systems. The portfolio ranges from marine robotics and energy systems like SUMDD and DeepSeaGen to cinematic tools such as the patent-pending Silencer and the XØDE AI production environment. By integrating these mechanical artifacts with infrastructure projects like GEOSALVAGE-1, the lab bridges the gap between legacy data and future-facing professional workflows while maintaining full domestic compliance. #create #ottodevelopment #tech #inventor

4

In this guide, I break down exactly how GarageBand’s built in effects work, how third party AUv3 plugins fit into your workflow, and the difference between AUv3 instruments and AUv3 effects in GarageBand for iPhone. 👉 https://lnkd.in/eEHwStc5

4

1 Comment

Did you miss The Developing Life Podcast with scott clum? Catch the replay here: 👉🏻 https://lnkd.in/g7WHdJ53 Scott’s career spans more than four decades of creative exploration, from discovering design through the bold hand-painted packaging of early Hot Wheels toys to becoming a defining voice in counterculture design and creative direction. But this conversation isn’t just about design history. It’s about something much bigger. We explore the tension many creatives feel today as AI, automation, and hyper-efficient digital tools reshape the creative industries. Scott shares why the human process, messy, tactile, and deeply personal, still matters more than ever, and why creativity isn’t something that can be outsourced to a machine.

6

2 Comments

ChatGPT just dropped a new image model. Asked it to create a vinyl record sleeve. First try? Perfect. Not "close enough." Perfect. The detail, the lighting, the physical consistency - all there. What's different: This model actually understands spatial relationships. How objects relate. How lighting should behave. How scenes stay consistent across edits. Previous models? You'd describe "vinyl record on wooden table" and get a table that looks painted on. Or lighting from three different sources that shouldn't exist. This one gets it right. Speed changed everything: Images generate faster now. But here's the clever part - you can create new versions while others are still rendering. No more waiting. No more losing ideas because the previous image took too long. Just keep iterating. New interface: Dedicated images section inside ChatGPT. Dozens of presets. Remix options. Blending tools. Beginners can use templates. Advanced users can fine-tune everything. Same tool, different depths. Here's what matters: This isn't just another image generator. It's ChatGPT understanding visual context the way it understands text. You can have a conversation about an image. "Make the lighting warmer." "Add more contrast to the background." "Keep the person but change the setting." And it remembers. It maintains consistency. It builds on previous iterations instead of starting over. DALL-E was impressive for its time. Midjourney became the artist's choice. Stable Diffusion went open-source. Now ChatGPT is doing what it does best - making powerful technology feel simple. Every AI image tool just got pushed to improve. Because when ChatGPT enters a space, everyone else has to level up. Maybe I'm overselling it. Maybe it's just incremental improvement wrapped in better UI. But when a tool makes you forget you're using AI? That's when it gets dangerous. In the best way. Source: OpenAI #ChatGPT #OpenAI #AIArt #ImageGeneration #GenerativeAI #DALLE #AITools

3