Wayve
•81% Informative
LINGO-1 is an open-loop driving commentator that combines vision, language and action to enhance how we interpret, explain and train our foundation driving models.
The use of natural language in training robots is still in its infancy, particularly in autonomous driving.
VLAMs open up the possibility of interacting with driving models through dialogue, where users can ask autonomous vehicles what they are doing and why.
We train LINGO-1, our open-loop driving model, on various vision and language data sources to perform visual question answering ( VQA ) on tasks such as perception, counterfactuals, planning, reasoning and attention.
We train each expert driver to follow a commentary protocol to maintain dataset quality.
This protocol includes paying attention to relevance and density of words spoken, the temporal synchronisation between commentary and driving actions, and the terminology used to describe events.
Microsoft hopes to harness LINGO ’s natural language, reasoning and planning capabilities to enhance our closed-loop driving models.
The two main factors affecting driving performance are the ability of the language model to accurately interpret scenes and the proficiency of the driving model in translating mid-level reasoning into effective low-level planning.
VR Score
84
Informative language
86
Neutral language
42
Article tone
informal
Language
English
Language complexity
60
Offensive language
not offensive
Hate speech
not hateful
Attention-grabbing headline
not detected
Known propaganda techniques
not detected
Time-value
long-living
External references
1
Source diversity
1
Affiliate links
no affiliate links