GRID is the core of @SentientAGI
ROMA, ODS, Dobby, Chat, Fingerprinting
…together supercharges the tool
Here’s How GRID Orchestrates all 🧵
Sentient GRID is the world’s largest open-source AI network
The tool unites agents, models, data, and compute to deliver high-quality answers
Queries are solved through coordinated workflows across tools and sources, making open-source AI as powerful as closed-source
You can access the GRID in two ways:
a) Builders
plug in models, data, agents, and tools to share with the network & earn as users pay for access
b) Users
- connect through Sentient Chat, the gateway to all GRID intelligence
- shows, in real time, which agents and models are being tapped to answer queries
GRID Products:
1. ROMA: multi-agent framework that splits complex queries into smaller tasks
2. ODS: search framework that splits reasoning, search, and calculation tasks, achieving SOTA performance on standard search benchmarks
3. Dobby: open-source model shaped by feedback from 2M+ community members, designed to prioritize human-like values such as tone, loyalty, and core beliefs
4. Fingerprinting: training method that lets open-source developers prove model ownership, even if the weights are fully public
5. Sentient Chat: UI gateway to the GRID, coordinating and delivering its network of intelligence
Now the big question: How GRID Orchestrates everything?
By routing, combining, and coordinating thousands of models, agents, and data streams, GRID scales its collective intelligence as it grows, delivering toward AGI-level output
Here's how the underlying algorithms make this possible:
1. Expert and community-defined workflows
For simpler queries, GRID uses expert-designed workflows
Each query gets analyzed, classified, and routed into the most relevant workflow for that use case
eg "Which European SaaS startups have raised over $50M in the last year?" gets identified as research analysis and routed to the research workflow
2. Recursive atomization & execution
GRID is evolving beyond static workflows with a new architecture for hyper-complex queries
Each query gets 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
3. Token-level Routing
GRID is developing algorithms to route intelligence at the smallest possible unit: the token
Instead of sending an entire query to a single model, GRID decomposes it into tokens, routes each to the most suitable intelligence, then stitches them back together
Early experiments show evidence of outperforming large closed-source labs at significantly cheaper cost
GRID is one of the OG innovations our space has seen in a long time (last time it was @eigenlayer restaking imo)
If done right, the tool ’ll /acc the Crypto x AI adoption & make the sector mainstream
Booish GRID. Booish Sentient. Booish OpenAGI.
Tagging @SentientAGI GRID maxis:
@YashasEdu
@bullish_bunt
@The_Tradeguru
@Kruys_Collins
@0X_Vetra
@DeFiScribbler
@thelearningpill
@90s_DeFi
@iam_LeriK
@eli5_defi
@Gyokeres_eth
@tanmaytarte3
@RubiksWeb3hub
@SheTalksCrypto
@Slappjakke
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