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Transition...

Think
BIGGER,

with
smaller
models

The
future
of
AI
is
Cooperative:
Community
generated
data
harnessed
by
compact
AI
models
to
produce
results.

Precision
Meets
Efficiency:
7B
Models
Outperforming
70B
Giants

We’re
fine-tuning
the
open-source
LogicNet
7B
parameter
model
to
not
just
match,
but
surpass
the
logical
reasoning
capabilities
of
70B
parameter
models.

Our
Mission

LogicNet-7b
open
source
model
to
top
the
ZebraLogic
Benchmark
.
Build
the
world’s
largest
open-source
Logic
data
set,
called
Aristotle.
Revolutionizing Logical Reasoning

Introducing LogicNet, the pioneering framework that’s redefining the boundaries of logical reasoning in AI models.

Smarter Logic Models
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Versatility: Reduced model size, lower computational overhead.

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Efficiency: Effective in diverse logical reasoning tasks and domains.

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Accessibility: Open-source models, accelerating research and innovation.

Our
Approach

These
approaches
synergize
to
create
a
powerfully
efficient
model,
excelling
in
logical
reasoning
across
various
fields
while
maintaining
a
compact
7B
parameter
size.

Synthetic Dataset Fine-Tuning

/icons/stella.svgMiners generate tailored synthetic datasets
/icons/stella.svgTargets specific improvements in logical reasoning
/icons/stella.svgAddresses data scarcity and enhances model versatility

Multi-Domain Learning

/icons/stella.svgIncorporates diverse data pipelines for comprehensive reasoning skills
/icons/stella.svgSpans philosophy, coding, medicine, economics, law, and academia
/icons/stella.svgBroadens model applicability and deepens analytical capabilities

LogicNet
Roadmap

Advancing
Efficient
Logical
Reasoning
in
AI

Foundation and Benchmarking

/icons/stella.svgEstablish comprehensive logical reasoning benchmark suite using Zebra Bench

/icons/stella.svgDeploy baseline open source 7B parameter model with LogicNet framework integration

/icons/stella.svgImplement synthetic data generation pipeline with validator quality control

/icons/stella.svgDeploy multi-task learning framework for dataset enhancement

/icons/stella.svgCreate evaluation system for model comparison against 70B+ models

/icons/stella.svgMinimize overfitting exploitations

Innovation in Model Architecture, Data Set Growth and Training

/icons/stella.svgLaunch continuous data generation system through a duel-tasked miner network

/icons/stella.svgImplement quality-driven selection mechanisms through validators

/icons/stella.svgDeploy automated curation pipeline for synthetic dataset

/icons/stella.svgDevelop specialized logical reasoning training protocols

/icons/stella.svgCreate robust performance tracking metrics

Scaling and Research

/icons/stella.svgScale architecture to optimize 7B parameter performance

/icons/stella.svgImplement advanced overfitting prevention mechanisms

/icons/stella.svgDeploy continuous model improvement protocols

/icons/stella.svgLaunch research collaboration platform

/icons/stella.svgImplement interpretability analysis tools

/icons/stella.svgDeploy model explainability frameworks

Specialization Platform

/icons/stella.svgLaunch front-end ‘Logical Specialization’ interface

/icons/stella.svgDeploy payment and monetization mechanism for validators

/icons/stella.svgCreate specialized model tuning protocols and implement custom dataset creation tools

/icons/stella.svgDeploy enterprise-grade API access

Inregrated
with
the
Best
Tools

Seamlessly
connect
with
native
integrations
for
X,
Telegram,
Discord,
Github,...