Titanic’s Digital Scan Reveals Never-Before-Seen Details of Wreckage: https://
iotworldtoday.com/robotics/titan
ic-s-digital-scan-reveals-never-before-seen-details-of-wreckage
…
+
Watch the video here: https://
youtube.com/watch?v=YZHd7x
wc4is
…
=
#DigitalTwin
RESEARCH
-

Titanic’s Digital Scan Reveals Never-Before-Seen Wreckage Details
By
–
-

ODSC Europe 2023 Schedule Live with Speaker Topics
By
–
#ODSCEurope’s schedule is now live! See the speakers who will be attending and the topics they’ll be presenting: https://
bit.ly/3MxGk54 by @_odsc ————
#BigData #DataScience #AI #ML #MachineLearning #DeepLearning #Python #NeuralNetworks #LLMs #NLProc #ComputerVision #GenerativeAI -
Cybersecurity Research and AI-Generated Visualization Analysis
By
–
Great research, analysis and writing by @Iasiello_E
. And great graphic of an angry cyber snake by Midjourney! -
Uncovering Value from Generative AI at Big Data World
By
–
Thank you Frankfurt! We had a fantastic time at Big Data World Frankfurt last week discussing how to uncover value from #GenerativeAI and seeing #ValueDrivenAI in action.
-
Collecting evidence and literature results from OntoNotes experiments
By
–
Ah thanks for this! I've been looking for more direct evidence. I want to collect up a little literature of these results I tried to run an experiment on OntoNotes but it was pretty tough (rate limits etc, plus just hard to frame the right prompts for all the entity types).
-

Eleven Multilingual v1: New Speech Synthesis Model Introduced
By
–
Introducing Eleven Multilingual v1: Our New Speech Synthesis Model https://
bit.ly/3Nou3Rr #AI #MachineLearning #LLMs #deeplearning -
Simulants: AI Method Synthesizes Privacy-Preserving Clinical Trial Data
By
–
"Simulants" is a method for synthesizing clinical trial data that maintains subject privacy, facilitating data sharing and innovation in fields like drug safety and bias analysis. Submitted by: Afrah Shafquat @Medidata
-
JoinBoost: SQL-based tree model training library
By
–
"JoinBoost" is a Python library that enables the training of tree models on normalized databases using pure SQL queries, offering portability, scalability, and competitive performance. Submitted by: Zachary Huang @Columbia
-
Data-IQ Framework Stratifies Training Data by Predictive Confidence
By
–
"Data-IQ" is a versatile framework enabling the systematic stratification of training data into outcome-based subgroups using predictive confidence & aleatoric uncertainty, aiding in feature acquisition, dataset selection, & reliable model usage. By: Nabeel Seedat @Cambridge_Uni
-
Minimax Optimal Stability Estimation Under Distribution Shift
By
–
"Minimax Optimal Estimation of Stability Under Distribution Shift" this study proposes an estimator for gauging system stability under environmental changes, providing a method to predict performance deterioration and ensure robustness. Submitted by: Yuanzhe Ma @Columbia