> when i first discovered milady i was so confused. the more i learned about the little people the clearer it became that i'd always been one
> i couldn't afford a milady so i decided to create my own 𖥔 ݁
i wanted it to stay true to the og so those who:
- also missed out could wear a milady-like pfp
- already have one could have fun with the new traits
i'm also buying $CULT with the profits to support the community ꩜
the token will be held in the treasury of a blockchain (Superposition♡) and miawlady owners will have *control* over it 🫶ily
XSY and @re are teaming up to supercharge each other’s points programs🔥
Engage with both ecosystems — and get up to 25% boost on your points 💥🪂
Here's how it works 👇..
XSY and @re are teaming up to supercharge each other’s points programs🔥
Engage with both ecosystems — and get up to 25% boost on your points 💥🪂
Here's how it works 👇..
4/ Token-level Routing
We’re developing algorithms to route intelligence at the smallest possible unit of AI language: the token.
Instead of sending an entire query to a single intelligence (model, agent, data source, etc), the GRID decomposes it into tokens (the smallest unit of text that an AI model processes). Each token can then be independently routed to the most suitable intelligence, and finally stitched back together for a final answer.
Our early experiments show evidence of outperforming large closed-source labs when routing tokens across different models, producing outputs far stronger than any single system alone at a significantly cheaper cost.
👉 Read our Dobby Report that covers token-level routing to various models: https://t.co/Fit1MGQgAW
3/ Recursive atomization & execution
GRID is evolving beyond static workflows with a new architecture for hyper-complex queries.
Each query will be recursively atomized (broken down into smaller sub-queries) until only atomic tasks remain. These are the smallest units of work required to resolve the original query.
Every atomic task is then routed to the most capable intelligence (model, agent, or data source) via a system prompt engine. This engine will itself be community-driven, with users contributing to its refinement.
This recursive architecture enables the GRID to solve problems of arbitrary complexity. Stay tuned for a bigger launch coming soon😁
3/ Backed by data sources from every industry
50+ data sources already fuel GRID, giving Sentient Chat the power to deliver answers grounded in real-world data across industries…and we’re adding more every day.
In this example, our data partners provide information across the industry:
@graphprotocol, @spaceandtime, @Covalent_HQ: Indexed blockchain data
@KaitoAI: Social data for crypto protocols
@nansen_ai: On-chain analytics
@arkham: De-anonymized blockchain activity data
4/ Off-chain Data
As a general platform, we’re partnered with data providers beyond Web3 to ensure broad coverage for a wide range of use cases.
@vana: Human-sourced datasets spanning the broadest and most niche industries such as social media, robotics, Telegram and AI chat conversations, and even vehicle telemetry
Entrova: Consumer behavioral data spanning gaming, health & wellness, fashion, entertainment, travel, and education
@turf_network: Autonomous, on-demand data network—streaming gameplay, financial-market, and e-commerce signals
3/ Data Storage
GRID also integrates secure data storage providers that allow model and agent builders to leverage decentralized storage for model training.
@0G_labs: Modular AI blockchain providing infinite scalability for data availability and storage
@Hyve_DA: Modular DA solution, achieving 1 GB/s bandwidth and sub-second response times, ideal for decentralized infrastructures with high-volume data requirements
@irys_xyz: Permanent data storage network enabling developers to store data forever on-chain with instant retrieval and programmable access controls
@zus_network: Datahub with bulletproof security, featuring ACID-integrity S3 storage on a zero-knowledge network