8/ CodeT5+ – supports a wide range of code understanding and generation tasks and different training methods to improve efficacy and computing efficiency; achieves SoTA on tasks like code completion, math programming, and text-to-code retrieval tasks.
INNOVATION
-
Symbol Tuning Boosts Language Models In-Context Learning Performance
By
–
9/ Symbol Tuning – an approach to finetune LMs on in-context input-label pairs where natural language labels are replaced by arbitrary symbols; boosts performance on unseen in-context learning tasks and algorithmic reasoning tasks.
-
DoReMi: Domain-Weighted Resampling for Efficient Model Training
By
–
7/ DoReMi – trains a small proxy model over domains to produce domain weights without knowledge of downstream tasks; it resamples a dataset with the domain weights which allows using a 280M proxy model to train an 8B model (30x larger) more efficiently.
-
Drag Your GAN: Interactive Point-Based Image Control Method
By
–
1/ Drag Your GAN – an approach for controlling GANs that allows dragging points of the image to precisely reach target points in a user-interactive manner.https://t.co/Nbhtle5VRG
— DAIR.AI (@dair_ai) 21 mai 20231/ Drag Your GAN – an approach for controlling GANs that allows dragging points of the image to precisely reach target points in a user-interactive manner.
-
Top ML Papers of the Week: DragGAN, CodeT5+, Med-PaLM 2
By
–
Top ML Papers of the Week (May 15 – 21): – DragGAN
– CodeT5+
– StructGPT
– Med-PaLM 2
– Symbol Tuning
– Evidence of Meaning in LLMs
… -
AI-Generated Song ‘Heart on My Sleeve’ Goes Viral Online
By
–
AI-Generated Song Goes Viral: In a striking example of the capability of artificial intelligence to mimic real-life experiences, an AI-generated song titled “Heart on My Sleeve” has taken the internet by storm. Featuring what appears to be the voices of… https://
analyticsvidhya.com/blog/2023/04/a
i-generated-song-goes-viral/?utm_source=dlvr.it&utm_medium=twitter
… -
ML on Graphs: Solving Problems Traditional Methods Failed
By
–
That's a wrap! I build maps for a living, we have used ML on graphs to solve problems where traditional methods failed. Sharing these resources based on my experience!! Find me → @akshay_pachaar Everyday, I share tutorials around ML! Check one of my older threads
-
GNNs Fundamentals: YouTube Playlist and Expert Talks
By
–
GNNs by AI Overloards A fantastic YouTube playlist for grasping the fundamentals! Also featuring invited talks by industry experts using ML on Graphs. Check this out https://
youtube.com/playlist?list=
PLSgGvve8UweGx4_6hhrF3n4wpHf_RV76_
… -
Graph Neural Networks Foundations: Message Passing and Node Embedding
By
–
Foundations of Graph Neural Networks By @PetarV_93 (Scientist at DeepMind) The perfect starting point! What you'll learn:
– GNNs from first principles
– Message passing on graphs
– Node Embedding
– Geometric Deep Learning Check this -
AI Unlocks Deeper Oil Extraction Through Advanced Analytics
By
–
Artificial Intelligence Is Wading Into the Deep to Unlock More Oil – The Motley Fool Read more here: https://
ift.tt/4PTmC2O #ArtificialIntelligence #AI #DataScience #100DaysOfCode #Python #MachineLearning #BigData #DeepLearning #NLP #Robots #IoT