We could run out of data to train #AI language programs https://
technologyreview.com/2022/11/24/106
3684/we-could-run-out-of-data-to-train-ai-language-programs/
… @techreview #MachineLearning #DataScience #IoT #serverless #womenwhocode #Robots #100DaysofCode @JAdP @CatherineAdenle @FmFrancoise @Shi4Tech #BigData #Analytics #DigitalTransformation #DeepLearning
MACHINE LEARNING
-
Running Out of Data to Train AI Language Models
By
–
-
Four-Legged Delivery Robot Can Stand Up Like Human
By
–
The four-legged delivery #robot can stand up like a human Robotic Systems Lab v/ @IntEngineering #Robotics #robots #innovation #tech #CES2023 #AI #ML @chboursin @SwissCognitive @ingliguori @sallyeaves @pascal_bornet @ipfconline1 @Exchange5g @wissen_tech @machine_ml
-
MIT Meta Enable Gradient Descent Optimizers Auto-Tune Hyperparameters
By
–
NeurIPS 2022 | MIT & Meta Enable Gradient Descent Optimizers to Automatically Tune Their Own Hyperparameters https://
syncedreview.com/2022/11/25/neu
rips-2022-mit-meta-enable-gradient-descent-optimizers-to-automatically-tune-their-own-hyperparameters/
… -
Artificial Intelligence Advances with Generative AI Progress
By
–
Artificial intelligence continues to impress with generative AI advancement https://
abc.net.au/news/2022-11-2
5/artificial-intelligence-continues-to-impress-with/101698214
… @abcnews #MachineLearning #DeepLearning #AI #Robots #BigData #Analytics #100DaysofCode #IoT #serverless #DEVCommunity #womenwhocode #DigitalTransformation #DataScience -
Dialect-robust Evaluation of Generated Text
By
–
Dialect-robust Evaluation of Generated Text Sun et al.: https://
arxiv.org/abs/2211.00922 #ArtificialIntelligence #DeepLearning #MachineLearning -
Complex Autoencoders Enable Advanced Object Auto-Segmentation in Images
By
–
Fantastic work by @sindy_loewe on complex autoencoders that are able to auto-segment objects in images. https://t.co/RuohaS0WYO
— Max Welling (@wellingmax) 24 novembre 2022Fantastic work by @sindy_loewe on complex autoencoders that are able to auto-segment objects in images.
-
Academic Rankings in AI Research: Beyond Simple Metrics
By
–
I actually don't mind if rankings are there as an option. Like if you want to find out who's "best" by # of ICML papers + 0.5 * # of NeurIPS papers normalized by author, or whatever weird formula, go wild. But that shouldn't be the main point.
-
CSRankings Gaps and ArXiv Collaboration Visualization Tools
By
–
Yes! CSRankings falls short of this goal, since some areas are wholly unrepresented (a student wanted to know who works on learning theory… but COLT isn't there). @RoyRinberg showed me this nice tool he built to visualize arXiv collabs
-
Exploring LAION CLIP Dataset for Keyword Discovery Methods
By
–
is there a way to explore LAION/CLIP so that we can more quickly uncover the key words?
-
AI in Agriculture: Optimizing Irrigation and Increasing Farmer Yields
By
–
We presented the first year of work of the @GPAI #gpai_IandC Project 3 Introducing AI in Agriculture and the data is undeniable: AI is optimising irrigation systems, preserving arable land, obtaining higher yields for farmers, creating new jobs in #AgroTech