
A network for collaboratively building composable specialized AI on decentralized infrastructure (Bittensor SN102): train partial expert models that improve the whole system via open competition.
The Hook
“and billions of dollars in AI infrastructure, impressively won gold at the math olympiad, but still failed to read an analog clock. And now I've created subnet Connito.”
Problem Agitation
“It is actually hard for a single AI model to be good at everything, but an open and composable library of specialized models, we can empower every SME.”
Product Reveal
“To begin with, we extract parts of the model that specialize in a domain, such as finance or medicine. Then, we take the parts and build an arena around it. Competitors try everything to improve the model, because whoever does it best gets paid by a lot.”
Feature Teaser
“we have been receiving 3500 submissions daily, with 5 times less GPU usage than full parameter fine tuning. Through this competition, we are able to harness, and by being filled with more experts in our library, day after day, competition after competition.”
Call to Action
“(No spoken dialogue — Final impactful sub-bass drop with ambient electronic score. The sound design emphasizes a conclusive and powerful statement.)”
Synthesizable in Remotion · key components of the connito-ai-tech-launch template.
A grayscale dithered globe rotates into view, with bright yellow icons representing specialized entities appearing and orbiting around it. The icons animate with a subtle bounce.
Use a Canvas component for the dithered globe effect, applying a pixelation shader or custom fragment shader. Implement SVG icons for the specialized entities, animating their position and scale using `spring()` for a bouncy effect, and `interpolate()` for rotation.
A grid of gray squares progressively fills with bright yellow squares, often containing a subtle animated icon, symbolizing growth or completion.
Render a grid of `Rect` components. Use `interpolate()` to animate the `backgroundColor` and `opacity` of individual squares from gray to yellow, potentially with a `delay` based on grid position. Animate an SVG icon within the yellow squares using `spring()` for a subtle entrance.
A dithered, grayscale image of a historical landmark (e.g., Colosseum) appears, with bright yellow shapes or icons dynamically highlighting specific areas or elements.
Import a grayscale image and apply a dither effect using a custom shader or SVG filter. Overlay `Path` or `Rect` components with a bright yellow fill, animating their `scale` and `position` using `interpolate()` to reveal or highlight parts of the underlying image.
Purpose. Establish the core problem: current AI models are impressive but lack specific, nuanced capabilities.
Execution. Quick cuts between the founder, news headlines, and simple, illustrative animations (e.g., clock) to demonstrate AI's limitations.
Purpose. Present Connito AI's innovative approach to specialized, collaborative AI.
Execution. Animated bar charts and a dithered globe with orbiting icons visually explain the concept of specialized models and collaborative networks.
Purpose. Detail the mechanism by which specialized models are improved through open competition.
Execution. Grid animations and the Colosseum metaphor illustrate the extraction of model parts and the competitive environment for improvement.
Purpose. Showcase the tangible benefits and future potential of Connito AI.
Execution. On-screen statistics and dynamic grid-filling animations demonstrate efficiency gains and continuous growth, leading to a brand reveal.
Objective
Launch a new blockchain-based decentralized storage solution called 'VaultChain'.How the recipe adapts
For VaultChain, the DitheredGlobeReveal primitive would show data packets (yellow icons) securely orbiting a dithered blockchain network. The GridFillProgress would illustrate storage capacity increasing or data blocks being validated. HistoricalMetaphorOverlay could use a dithered image of a vault or fortress, with yellow highlights showing secure access points. The overall pacing would remain fast, explaining the problem of centralized storage, introducing VaultChain's decentralized solution, demonstrating its security and scalability, and concluding with the brand reveal.Scene durations (5 scenes, 93s)
Key Remotion components
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