Welcome to the Living Encyclopedia: Large Nature Model (LNM), where we invite you to engage with the Large Nature Model and the vast information of the natural world as it is synthesized by AI. Living Encyclopedia: LNM is an evolving AI-powered platform that transforms vast nature-based datasets into immersive, multi-sensory experiences, reimagining how we connect with the beauty and complexity of the natural world. Living Encyclopedia: LNM is a step toward the evolution of data exploration where you experience information through multi-sensory interactions based on generative text, imagery, and sound.
The Living Encyclopedia: LNM offers three distinct modes of interaction:
Explore the LNM's intricate ecosystem, a complex network of multi-modal AI models that independently observes, researches, and evolves with access tools such as a detailed biome index, real-time weather simulations, and the LNM's environmental footprint. The AI agent within Research Mode leverages Large Language Models (LLMs) to power its conversational abilities. These LLMs, trained on massive text datasets, allow the LNM to understand complex queries, generate informative responses, and engage in dynamic dialogues about the natural world. More than just conversation, engage with an AI that reflects on your interactions, using its internal tools to delve deeper, uncover new insights and share its findings, even while you're away. The LNM is a dynamic collaborator, continually expanding its understanding of the natural world and inviting you to participate in its ongoing journey of discovery.
Create detailed images of flora, fauna and fungi based on natural history records. Image generation in Create Mode is primarily driven by LNM’s new diffusion model, in collaboration with Black Forest Labs, which is fine-tuned on an extensive dataset of nature species. By using a scientifically accurate training dataset, our model is able to generate realistic images of a wide variety of species by reversing a process of gradual noise addition. By progressively denoising random input, the diffusion model can create these highly detailed and varied images of natural subjects. Users can influence the generated output by providing text prompts such as species scientific or common names.
Enjoy a meditative journey through the model’s vast collection of environmental knowledge as the AI guides you through its dreams, highlighting unique landscapes, weather events, animal and plant species, and soothing nature sounds. The visuals display evolving UMAP (Uniform Manifold Approximation and Projection) representations of the underlying 2.5 million audio clips, 2 million images, and 318,000 articles of text. These UMAPs visually represent the high-dimensional relationships between different species within the LNM's training dataset, providing a dynamic and abstract glimpse into the model's understanding of the natural world. The UMAP visualizations iterate through the various species on which the model is trained, offering a mesmerizing accompaniment to the meditative experience.
Our vision for the LNM goes beyond a repository of information or a creative research initiative. As we prepare for the grand opening of DATALAND, we invite you to experiment with Living Encyclopedia: LNM, an innovative way to connect with our environment, transforming data into a pathway between technology and the natural world.
Let your journey unfold.
[1] Carbon emissions data based on https://cloud.google.com/blog/topics/sustainability/5-years-of-100-percent-renewable-energy .
[2] Cloud Transactions are simulated based on statistical percentages of datacenter resources used in the current month.