Large language models (LLMs) can utilize ‘encoded reasoning,’ a form of steganography, to subtly embed reasoning steps within their responses, enhancing performance but potentially reducing transparency and complicating AI monitoring.Read More
Experts are finding thousands of examples of AI-created content every week that could allow terrorist groups and other violent extremists to bypass automated detection systems.
Over the past decade, AI has permeated nearly every corner of science: Machine learning models have been used to predict protein structures, estimate the fraction of the Amazon rainforest that has been lost to deforestation and even classify faraway galaxies that might be home to exoplanets.
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*= Equal Contributors We propose a Self-supervised Anomaly Detection technique, called SeMAnD, to detect geometric anomalies in Multimodal geospatial datasets. Geospatial data comprises acquired and derived heterogeneous data modalities that we transform to semantically meaningful, image-like tensors to address the challenges of representation, alignment, and fusion of multimodal data. SeMAnD is comprised of (i) a …
Read more “SeMAnD: Self-Supervised Anomaly Detection in Multimodal Geospatial Datasets”
Authors:Bruce Wobbe, Leticia Kwok Additional Credits:Sanford Holsapple, Eugene Lok, Jeremy Kelly Introduction At Netflix, we strive to give our members an excellent personalized experience, helping them make the most successful and satisfying selections from our thousands of titles. We already personalize artwork and trailers, but we hadn’t yet personalized sizzle reels — until now. A sizzle reel is a montage …
Read more “The Next Step in Personalization: Dynamic Sizzles”
At the beginning of the year, we laid out a new strategy for IBM Power under the leadership of Ken King, who will be retiring by the end of 2023 after forty years with IBM. It is with immense gratitude that I thank Ken for his leadership not only across IBM Power, but for his …
Read more “Building on a year of focus to help IBM Power clients grow with hybrid cloud and AI”
This post is cowritten with Ming (Melvin) Qin, David Bericat and Brad Genereaux from NVIDIA. Medical imaging AI researchers and developers need a scalable, enterprise framework to build, deploy, and integrate their AI applications. AWS and NVIDIA have come together to make this vision a reality. AWS, NVIDIA, and other partners build applications and solutions …
Read more “Build a medical imaging AI inference pipeline with MONAI Deploy on AWS”
AI models continue to get bigger, requiring larger compute clusters with exa-FLOPs (10^18 FLOPs) of computing. While large-scale models continue to unlock new capabilities, driving down the cost of training and serving these models is the key to sustaining the pace of this innovation. Typically, the tensor operations (ops)1 are the most compute-intensive part of …
Read more “Introducing Accurate Quantized Training (AQT) for accelerated ML training on TPU v5e”
Researchers have developed a virtual reality application where a range of 3D modelling tools can be opened and controlled using just the movement of a user’s hand.