AINETUS
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Overview
HEALTH SCORE
Concerning
44out of 100
Maintainer coverage is the lead risk. Development cadence and security posture are present but not enough to offset the structural risk.
LIFECYCLE
Active
Consistent commits, responsive maintainers, regular releases, and healthy issue triage.
Health breakdown
Concerning(44/100)
Maintainer availability, known risks and supply chain posture, and whether the project is actively developed or appropriately stable.
Maintainer responsiveness
No PRs or issues were opened in the review window, so response time could not be measured.
Bus factor
Only 1 active maintainer currently has merge rights.
Organization Diversity
Contributors come from 1 organization only.
Project Achievements
Leaderboards
About
AI algorithms mainly composed by supervised and reinforcement learning. Unifying the benefits of existing heuristics, physical modelling of these complex systems and learning methods, as well as a set of complementary techniques to enhance transparency, safety, explainability and human acceptance.
Human-in-the-loop decision making for co-learning between AI and humans. Considering integration of model uncertainty, human cognitive load and trust.
Autonomous AI systems relying on human supervision.
Embedded with human domain knowledge and Safety rules.
First commit
Software value
$49M
Maturity
Sandbox
Tags
artificial-intelligence
machine-learning
neural-networks
deep-learning
data-science
License(s)
MPL-2.0
Other
Data sources
Groups.io
GitHub
Git