Le projet THINK

Bhavya Nagrath in his blog proposes a web application to detect and classify crop diseases from the images of leaves.

Intel Labs and collaborators present two oral presentation papers at the main conference for ACL 2024 on August 11-16

This article demonstrates how to build and develop deep learning workloads using PyTorch and TensorFlow on Intel Tiber Developer Cloud.

These HealthTech startups from the Intel® Liftoff program have developed generative AI tools that showcase how AI can provide groundbreaking solutions, reduce inefficiencies, and eliminate access barriers.

With the help of the Unify LLM router companies can determine easily and cost effective which LLM provides the best outcome for a given prompt, based on the output quality, cost and speed of existing models.  

The two winners from Start Hack 2024 used Intel® Developer Cloud and AI to create new, efficient, and cost-effective communication solutions for businesses.

Compare Fast Inverse Square Root Method to NumPy ufuncs, Numba JIT, and Cython — Which One Wins?

Welcome to our recap of our inaugural Intel® Liftoff Days 2024, a unique virtual hackathon event tailored exclusively for the program members. This week-long immersive tech acceleration experience offered our startup community a distinct opportunity to explore various cutting-edge topics with Intel.

Customer churn is defined as the number of people stopped being customers over a certain time frame. It is a key metric for business and a high customer churn rate indicates that the customer is no longer interested in the company’s products or services.

Researchers at Intel Labs, in collaboration with Xiamen University, have presented LiSA, the first semantic aware AI framework for highly accurate 3D visual localization. LiSA can leverage pre-trained semantic segmentation models to significantly improve state-of-the-art 3D visual localization accuracy, without introducing computational overhead during inference. LiSA was presented at CVPR 2024 as a highlight paper, an award given to the top 3.6% of conference papers.