What's happaning on $RENDER Discord, what's currently being discussed in the channels? Let's dive in 🧵👇🏻👇🏻👇🏻🧵 🧵 general @tokai_spy is asking where to get advice for their own “restir engine,” but the exact tool/product and intended support channel are unclear. ⭕️ @tokai_spy asked which “canal”/channel is the right place to receive guidance about their own “restir engine.” No team response or technical details were provided in the current messages, so the request likely needs routing clarification first. ❗ Focus for the team: clarify what @tokai_spy means by “restir engine” and point them to the correct support/help channel for technical advice.
🔥Burns Update🔥 $1,716 (1,084 $RENDER) across 63 tx burned. Median $7, biggest burn $349. Burns removed 6.83% of daily emissions. https://t.co/qoRl399EZc
In response to a question about autonomous agents creating scenes in Blender and how long until AI can complete a series without human interaction: “Claude 3.7 can do that already but the scenes aren’t great. Feeding them into vtv + first frame as style reference can lead to promising results. Today this isn’t quite production ready yet, but it’s an impotent step to getting there. I see a ton of immediate utility once Luma , ltx, wan and others get full v2v working - then we can pass render jobs frame output to this process for post / comp work in 2.5d with full artistic control and all the benefits of path tracing as well” @JulesUrbach 13.03.25 $RENDER
🔥Burns Update🔥 $4,906 (2,924 $RENDER) across 125 tx burned. Median $6, biggest burn $1,013. Burns removed 18.42% of daily emissions. https://t.co/rwS21vMVOy
What's happaning on $RENDER Discord, what's currently being discussed in the channels? Let's dive in 🧵👇🏻👇🏻👇🏻🧵 🧵 general Render’s expansion from GPU rendering into AI compute is being framed as a potential second demand engine beyond 3D artists. ⭕️ @psalmist0919 asked @530441868945653771 whether AI workloads could eventually become as important to Render as rendering itself. The core point: moving from traditional GPU rendering into AI compute may open the network to a broader customer base beyond 3D artists. Historical context: this question lines up with prior network discussions around expanding compute demand. Team member Sunny previously shared RNP-019, which proposed expanding emissions and rewards to include AI compute and general workloads beyond rendering. More recently, Team member Silvia introduced RNP-021, which builds on that direction by proposing support for enterprise-grade GPUs such as NVIDIA H100/H200 and AMD MI300 series for AI training, video generation, and large-scale image models. ❗ Focus for the team: clarify how Render expects demand to balance between existing 3D/rendering workloads and future AI/general compute, including what metrics will show whether AI workloads are becoming a major network usage driver.
🚀 Monster $RENDER burns!🚀 $25,815 (15,693 RENDER) destroyed in 164 tx! Median $7, biggest burn $7,353. 🔥 98.85% of daily emissions wiped out! https://t.co/YlfEQQSg96
🔥Burns Update🔥 $7,566 (4,483 $RENDER) across 155 tx burned. Median $6, biggest burn $3,777. Burns removed 28.24% of daily emissions. https://t.co/ZsCoqtiOPv
“NeRFs are a very important intermedia format intersecting latent space (AI) and ray tracing space - but the goal is to convert NeRF to full scene graph model (mesh, volume , or more useful - SDF/ Vectron) for full composability and speed - but with Neural Rendering coming in the roadmap we also plan to render NeRF and related AI generated objects directly without any conversion - so we can apply AI effects and operators- it’s very similar to how we have done Vectron (SDF) which are pure code shaders for meshes , volumes and scene graph composition operators - neural rendering nodes will work a lot like that” @JulesUrbach 18.11.22 $RENDER
What's happaning on $RENDER Discord, what's currently being discussed in the channels? Let's dive in 🧵👇🏻👇🏻👇🏻🧵 🧵 rnp-024-forth Core tension: frustration over slow RNP execution vs. an attempt to make this proposal improve implementation speed. ⭕️ @a28z voiced concern that RNP implementation could still be “another 2–3 years” away, calling the current pace ridiculous and saying RNPs “take forever.” The concrete worry is not about the content of RNP-024 itself, but about the governance-to-implementation timeline and whether approved changes actually ship fast enough. ⭕️ @rshea replied that they are “trying to change that with this,” positioning RNP-024 as an attempt to address the delay problem rather than repeat it. Relevant context: @rshea has previously raised broader concerns about Render timelines and delayed network functions, including in earlier RNP discussions, so this response fits a longer-running push for more realistic timelines and better execution focus. ❗ Focus for the team: clarify what RNP-024 changes operationally to reduce implementation delays, who owns execution after approval, and whether there is a target timeline or milestone schedule beyond the currently feared 2–3 year window.