Artificial Intelligence is on everyone’s lips these days, but its training complexity is less talked about. Maybe it’s the talent shortage or the unexpected situation, but training AI models is challenging, especially with the lack of regulation.
In theory, training an AI program requires a lot of data preparation and a specific training technique, but what few know is that this process can take up to a few months. Several aspects, like the model size and the hardware used, can interfere with the timeframe.
The solution for efficient and sustainable AI training models seems to come from the blockchain and cryptocurrency industries, the two emerging sectors where developers shape our future. The Distributed GPU Render Network is exploring the possibility of high-quality 3D models being useful in AI training through a unique framework on the market. The blockchain-managed cloud rendering and the ecosystem rely on the Render price, the token users hold for governance.
Render is all about speed and scale, so it developed the Render Network Proposals (RNPs).
Creating a framework for training high-quality AI models
The Render Network Proposal aims to implement a dataset of one billion 3D assets as a starting point for 3D artificial intelligence. Along with Stability AI, a generative technology, Render participants, from nodes to community members, will participate in the development of the dataset.
Those interested will be able to run an external client from GitHub and receive incentives through staking. This will ensure everyone works fairly and that more people engage with this emerging plan.
The process will also include NFTs on Solana, as they’ll contain all the information necessary for the generated 3D data. The RNP-011 initiative will foster an ethical and efficient network where AI training and licensing 3D assets are possible.
The Render Network already approaches more 3D tools
Render is a unique decentralized solution on the market, combining the power of multiple platforms with 3D software tools. C4D rendering is a native plugin artists can access to benefit from distributed GPU rendering services.
Key features include OCIO configurations, scenes available in .zip files, and a user-friendly interface. The possibility of making the production process easier attracted Hollywood leaders to approach Render for Augmented and Mixed Reality use cases.
Render also leverages functionalities from:
- Blender, accessing unique visual effects, designs, and archives;
- Houdini, scaling production for film, TV, and games;
- Unreal Engine, using 3d software through Octane;
The future of Render lies in media development
Besides the blockchain solution and token distribution, the Render Network focuses on establishing a new era of media. GPU rendering makes spatial computing, artificial intelligence, and blockchain easier to implement.
The Render vision involves an open global rendering system slowly building upon GPU Providers and GPU Requestors ― a marketplace, in other words. High-performance technology uses software to connect GPU owners with creators so they can access computing power for rendering tasks.
The founder of Render envisioned a world in which the human metric is the most important, and it can be used well with the right technology. While the beginnings of the Internet were based on distributed computing, the future moves us to immersive metaverses and 3D scenes.
Still, how are 3D models efficient for AI training?
AI in smartphones’ voice assistants or smart home systems is nothing new to our society, but we can push far from that and make models recognize patterns and evaluate data. Usually, an AI model lacks the understanding of what it sees, so it categorizes it according to color and shape. However, when the image doesn’t conform to its knowledge, the AI deviates from the data and fails.
Training AI with 3D models would be more efficient because the rendering process feeds the AI with many perspectives of the concept. So, with technologies like Apple Vision Pro, users with access to high-end GPUs can offer clear images and information to the AI through cloud streaming.
The Render Network has the opportunity to be the first to offer live-streaming 3D content to VR headsets. This could set the bar high for competitors, as it would be one of the most innovative forms of expression and interactivity.
The Render Network is an advantageous tool for developers
Render is a fantastic tool because it leverages GPU-distributed rendering, targeting huge scalable networks. The high-performance GPUs allow for the fastest rendering on the network of even the most challenging scenes. The multiple nodes working on a task are also why the network is so fast.
Hence, Render is a leader on the market due to:
- A seamless creative network integrating in 3D applications;
- Cost-effective pricing with on-demand rendering and fair billing;
- Beginner-friendly interface with intuitive plugins and ample documentation;
Still, there are challenges in using and adopting AI
While the Render Network shapes the future, we still have a lot to catch up on. The lack of regulation around artificial intelligence hinders companies’ capacity to use it to its full advantage, especially since few experts truly understand how AI could be grounded.
It is challenging to stay compliant with every region’s requirements. While the world’s technology hardware is becoming outdated by the day, limiting AI capabilities is a step behind. Moreover, AI innovation is much faster than regulation, so governments should act as fast as possible.
The biggest issues of AI regulations include:
- Velocity, meaning the AI-driven change will only move faster;
- Avoiding the “one-size-fits-all” approach;
- Finding the right body to regulate;
These complex aspects of regulating AI make it difficult for solutions like Render to access the full capabilities of changing the world. However, as times change, we expect brighter days for blockchain.
So, what does the future look like?
Rendering the future might be possible now, with the Render Network offering unique features that connect GPU-power owners with creators. Render also works hard to create 3D models to train different AI tools and create a new path for media. The network is cost-effective and provides friendly interfaces, so developers can start rendering and contribute to the market growth early on.
