Unbox your creativity in 2024 you prepare for #SASHackathon. In partnership with @intel
, we're bringing an engaging board game to local SAS offices sure to spark hacking cool innovation. Can't wait to see what you bring to the (game) table! http://
2.sas.com/6014Rp5Hk
COMPUTING
-
SAS Intel Hackathon 2024: Unbox Your Creative Innovation
By
–
-
Feedback Transformer: Angela Fan’s Expensive AI Architecture
By
–
the most similar thing i know of is the Feedback Transfomer from Angela Fan: https://
arxiv.org/abs/2002.09402 it's so expensive to run though -
Gemini: Highly Capable Multimodal Models Family
By
–
Gemini: A Family of Highly Capable Multimodal Models Anil et al.: https://
arxiv.org/abs/2312.11805 #ArtificialIntelligence #DeepLearning #MachineLearning -
AI is not science fiction: it’s transforming our world
By
–
AI's not sci-fi. Look around. It's transforming our world.
-
Ultimate AI Inference Webinar Series: Development to Production
By
–
Don't miss out on the ultimate AI inference webinar series! Watch our expert-led talks on-demand, exploring #AI use cases from development to production with full-stack AI inferencing. Register here > https://
nvda.ws/474m1Do #inference #financialservices -
Data Science Core: Data and Science Fundamentals
By
–
Yeah, I have this radical idea that the *core* of Data Science is about two things: 1. Data
2. Science -
Small Language Models: Accessible Training and Deployment Solutions
By
–
Training large language models is a very technically demanding and resource intensive task. Many such models also require lots of specialized compute to use. Fortunately, we have recently been blessed by public releases of several "small" LLMs 1/4
-
PyTorch Uses Own Tensor Engine, Not NumPy
By
–
Actually, PyTorch does not build on NumPy.
It uses its own tensor engine with GPU support, compilation, etc.
The only dependencies on NumPy is to provide some interoperability between NumPy arrays and Torch tensors. -
Di Wang Wins SODA 2024 Best Paper Award Minimum Cut
By
–
Congrats to Di Wang & coauthors for co-winning the SODA 2024 Best Paper Award for "Deterministic Near-Linear Time Minimum Cut in Weighted Graphs", which is a significant development since Karger's famous randomized algorithm for this problem. Learn more→ https://
goo.gle/48mXpqr -
Neural Network Resilience Through Summation and Dense Connectivity
By
–
I follow the summations and network connectivity to understand resilience to information loss.
When each output is the sum over a large set of input computations, which themselves densely cross-connect in previous layers — I just expect information to be really resilient to