[reader] read, analyze, comment

Finally, after years of disorientation, computer scientists have  started
to understand the role and importance of KR in AI and everything, in
particular, in understanding complexity, systemic dysfunction etc etc etc.

I would say the mission of the CG is being accomplished, that is, make the
case of KR in ML and to technology in general

Sorry I don't have time to comment, I do not necessarily agree with
everything the articles I share say. Just noting the issues

PDM


This AI Paper Presents A Comprehensive Study of *Knowledge* Editing for
Large Language Models
<https://www.marktechpost.com/2024/01/06/this-ai-paper-presents-a-comprehensive-study-of-knowledge-editing-for-large-language-models/&ct=ga&cd=CAEYACoTMTk4NzgzNjkwNDEzMzUwMDQ1MzIdN2U2MjMwOWEzY2EwOGM3YTpjb20udHc6ZW46VFc&usg=AOvVaw0lfs90GqGEID8qFSJlb09w>
MarkTechPost
Researchers have discovered the ability of LLMs to learn *representations*
that reflect perceptual and symbolic notions and track subjects' boolean ...





Constructing a finer-grained *representation* of clinical trial results
from ClinicalTrials.gov
<https://www.google.comhttps://www.nature.com/articles/s41597-023-02869-7&ct=ga&cd=CAEYASoTMTk4NzgzNjkwNDEzMzUwMDQ1MzIdN2U2MjMwOWEzY2EwOGM3YTpjb20udHc6ZW46VFc&usg=AOvVaw09utdxeSNweIrPj42ZUARS>
Nature
The standardization of metadata and use of *knowledge* graph contributed to
the obstacles to the reuse of study metadata in clinical trials ...







<https://www.google.com/alerts/feeds/09670693557036673178/11785560971845998616>

<https://www.google.com.tw/alerts?source=alertsmail&hl=en&gl=TW&msgid=MTk4NzgzNjkwNDEzMzUwMDQ1Mw&s=AB2Xq4gHlwAYS0ae1sl8OFgIo12YrBwtnY1i1cA&ffu=>