An open letter signed by more than 1,300 experts says AI is a "force for good, not a threat to humanity".
RESEARCH
-
One in Three Experimental ML Models Ready for Production
By
–
We looked at how our 9,000+ global customers are applying data science & ML. One key finding? On average, 1 in 3 experimental ML models are a candidate for the real-world Get more findings like this in our 2023 #StateofDataAI report https://
bit.ly/3O5xCM9 -
Self-driving cars in 2023: progress limited to specific geofenced areas
By
–
Back to self-driving — 7 years after these claims were being made (about 2016 technology), 2023 self-driving cars can drive very well within specific geofenced areas (two cities so far). They're not driving "better than humans", because humans drive pretty well anywhere.
-
Challenges and Applications of Large Language Models Overview
By
–
Challenges and Applications of Large Language Models A comprehensive review of the problems that remain unsolved in LLMs arena. The paper also provides a broad overview of application areas of LLMs and highlights some common application architectures across domains. This is
-
General Ability vs Situational Competence in AI Systems
By
–
There's a big difference between possessing a *general* ability vs being able to show the appearance of competence in specific situations. AI has always excelled at the latter, but the value is in the former.
-
Modern Columnar Data Format for ML and LLMs in Rust
By
–
Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. https://
bit.ly/3NwSGek #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Learning Real World Machine Learning Recommended Resource
By
–
Awesome! Recommended to anyone interested in learning how real world ML works!
-
MIT Dataset Enables Precise Semantic Image Captions for Accessibility
By
–
Training ML models w/MIT’s new dataset empowers them to create precise, semantically dense captions, while illustrating data trends & intricate patterns. It could help improve accessibility for those w/visual disabilities: https://
bit.ly/3D6VwQZ -
Likelihood Versus Probability: Key Differences in Data Science
By
–
What is the Difference Between Likelihood and Probability?: Likelihood and probability are interrelated and often confused terms finding common usage in data science and business. Both probabilities are associated with probabilities but differ in… https://
analyticsvidhya.com/blog/2023/06/l
ikelihood-vs-probability/?utm_source=dlvr.it&utm_medium=twitter
… -
Cultivating Curiosity in Medicine: Beyond Efficiency to Patient Care
By
–
"Exercising curiosity at the bedside — which is not
always incompatible with efficiency— is how we cultivate relationships with our patients, how
we diagnose disease, and most important, how we advance the art of medicine." https://
nejm.org/doi/full/10.10
56/NEJMp2304992?query=WB&cid=NEJMWeekendBriefing,July22,2023DM2273275_NEJM_Subscriber&bid=1689454157
…