Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision, large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications. The validation and training datasets that undergird ML technology are …
Today we are excited to announce that the Llama Guard model is now available for customers using Amazon SageMaker JumpStart. Llama Guard provides input and output safeguards in large language model (LLM) deployment. It’s one of the components under Purple Llama, Meta’s initiative featuring open trust and safety tools and evaluations to help developers build …
Read more “Llama Guard is now available in Amazon SageMaker JumpStart”
Posted by Dan Kondratyuk and David Ross, Software Engineers, Google Research A recent wave of video generation models has burst onto the scene, in many cases showcasing stunning picturesque quality. One of the current bottlenecks in video generation is in the ability to produce coherent large motions. In many cases, even the current leading models …
Read more “VideoPoet: A large language model for zero-shot video generation”
By Ruben Stroh, Palantir Deployment Strategist Introduction Since the launch of AIP, Palantir has worked with a wide spectrum of customers to deploy AI-centric process mining & automation workflows that save time, money, and resources. Today we’ll walk through a notional, step-by-step example of how to build this kind of solution with AIP. https://medium.com/media/2dc1cd6e4e6105cb2100362da699324f/href But before …
Read more “Building with Palantir AIP: AI-Powered Process Mining”
As enterprises embrace cloud native and everything as code, the journey from code to production has become a critical aspect of delivering value to customers. This process, often referred to as the “pathway to deploy,” encompasses a series of intricate steps and decisions that can significantly impact an organization’s ability to deliver software efficiently, reliably …
Read more “Accelerate release lifecycle with pathway to deploy: Part 2”
Posted by Dan Kondratyuk and David Ross, Software Engineers, Google Research A recent wave of video generation models has burst onto the scene, in many cases showcasing stunning picturesque quality. One of the current bottlenecks in video generation is in the ability to produce coherent large motions. In many cases, even the current leading models …
Read more “VideoPoet: A large language model for zero-shot video generation”
This post was written in collaboration with Ankur Goyal and Karthikeyan Chokappa from PwC Australia’s Cloud & Digital business. Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production …
*=Equal Contributors Multimodal datasets are a critical component in recent breakthroughs such as Stable Diffusion and GPT-4, yet their design does not receive the same research attention as model architectures or training algorithms. To address this shortcoming in the ML ecosystem, we introduce DataComp, a testbed for dataset experiments centered around a new candidate pool …
Read more “DataComp: In Search of the Next Generation of Multimodal Datasets”
Anycast is a standard, table-stakes feature of every authoritative DNS service. It makes sense: inbound queries should always be routed to the best available servers—usually the ones that are geographically closest. Yet, there is one glaring exception: China. The internet in mainland China is walled off from the rest of the world. Any DNS query that …
Read more “Why you shouldn’t use Global Anycast DNS in China”