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Neil Abernethy@neil_a
is under improvement
2
Events attended
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Submissions made
Data Scientist
United States
8 years of experience
About me
B.S. in Applied Mathematics and Biochemistry from North Carolina State University Ph.D. in Biomedical Informatics from Stanford University Stanford Business Competition winning team member and VC-funded startup co-founder with a successful exit University of Washington data scientist and eScience Institute affiliate Interests: Multi-modal ML, multi-agent systems, knowledge representation, NLP/LLMs, AGI, AI applications and safety
I built with
Anthropic Claudeis under improvement
š¤ Submissions
Congruity - Trustworthy AI
Congruity.AI provides a diverse set of tools and options for business users and consumers alike to interrogate the consistency of content provided by large language models. It does this by first returning a varied sample of responses, utilizing different API parameters as well as prompt variation. We then ingest and analyze the results to present visualizations and other tools for users to investigate the quality and consistency of generated text. These approaches include an ngram census (portrayed on the text), similarity matrices (showing how similar responses are to one another), links to external sources for verification, and a comparison to constitutional rules or values for the language model. Using these complementary tools, users can drill down to identify elements of generated text that are consistent with the facts, with one another, and with corporate or personal values.
