In a recent legal development, two lawyers, Christopher Kachouroff and Jennifer DeMaster, were fined $6,000 by US District Judge Nina Wang for using artificial intelligence (AI) to generate a brief with misquotes and fictional cases. The fine is a stark reminder of the importance of accuracy in legal proceedings.
The statistics tell the story: 30 defective citations were found in the brief, highlighting the need for meticulous attention to detail. Furthermore, the jury’s verdict awarded $2.3 million in damages to Eric Coomer, with Lindell ordered to pay $440,500 in defamation damages. Frankspeech was also held liable, paying out $1,865,500.
These numbers underscore the significance of accurate legal representation and the consequences of errors. The fine serves as a warning to lawyers and AI developers alike: accuracy is paramount in the pursuit of justice.
Nuel Ojeabulu ||CyberHawk
@real_nuelOj
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Jul 7 Today we will be talking about the STATS command in the Splunk Processing language
STATS
This command generates report that displays summary statistics in a tabular format.
Joachim Schork
@JoachimSchork
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Jul 3 Making your data analysis more insightful and informative is effortless with ggstatsplot. This powerful ggplot2 extension in R combines statistical analysis and data visualization in a single workflow, helping you generate plots that include statistical summaries directly on the
Guri Singh
@heygurisingh
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Jul 7 1/ Research Summarizer (w/ bias detection)
Purpose: Quickly skim 50-page papers in 30 seconds
Prompt:
“Summarize this research paper in 5 bullet points. Note any potential bias, funding sources, or study limitations. Use plain English.”
Inquisitive Bird
@Scientific_Bird
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Jun 22 There’s a lack of proper birth registration, death registration, lack of recent censuses, and much more.
This chart illustrates a composite measure of statistical capacity across the world. As is evident, Africa is the region with the lowest average score.
Joachim Schork
@JoachimSchork
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20h Grouped summary statistics are essential because they help us uncover insights and trends within different segments of our data.
Examining an entire variable might miss hidden patterns, but diving into subgroups can reveal pure statistical gold.
The dplyr package in R makes
Sleepy (ML/DL)
@KrishnaNaraKun
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Jul 4 Essential statistics – for machine learning
Complete statistics, Visualised and explained nicely by Prof. Philipp Berens,of University of Tübingen
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