Category: FAANG

Posted by AJ Piergiovanni and Anelia Angelova, Research Scientists, Google Research Vision-language foundational models are built on the premise of a single pre-training followed by subsequent adaptation to multiple downstream tasks. Two main and disjoint training scenarios are popular: a CLIP-style contrastive learning and next-token prediction. Contrastive learning trains the model to predict if image-text …

Read more “MaMMUT: A simple vision-encoder text-decoder architecture for multimodal tasks”

The world of artificial intelligence (AI) and machine learning (ML) has been witnessing a paradigm shift with the rise of generative AI models that can create human-like text, images, code, and audio. Compared to classical ML models, generative AI models are significantly bigger and more complex. However, their increasing complexity also comes with high costs …

Read more “Achieve high performance with lowest cost for generative AI inference using AWS Inferentia2 and AWS Trainium on Amazon SageMaker”

Note: This article is written based on the Flutter SDK version 2.10.0. Flutter’s RaisedButton widget has been deprecated since the release of Flutter 2. Material Design guidelines recommend that if you hire Flutter developers, they will use the ElevatedButton widget instead of the deprecated RaisedButton. This article will provide migration instructions for experts who need to …

Read more “RaisedButton Deprecation and Migration Guide With An Example”

Posted by Joanne Truong, Student Researcher, and Wenhao Yu, Research Scientist, Robotics at Google Teaching mobile robots to navigate in complex outdoor environments is critical to real-world applications, such as delivery or search and rescue. However, this is also a challenging problem as the robot needs to perceive its surroundings, and then explore to identify …

Read more “IndoorSim-to-OutdoorReal: Learning to navigate outdoors without any outdoor experience”

Generative AI (GenAI) and large language models (LLMs), such as those available soon via Amazon Bedrock and Amazon Titan are transforming the way developers and enterprises are able to solve traditionally complex challenges related to natural language processing and understanding. Some of the benefits offered by LLMs include the ability to create more capable and …

Read more “Quickly build high-accuracy Generative AI applications on enterprise data using Amazon Kendra, LangChain, and large language models”

One of the most popular models available today is XGBoost. With the ability to solve various problems such as classification and regression, XGBoost has become a popular option that also falls into the category of tree-based models. In this post, we dive deep to see how Amazon SageMaker can serve these models using NVIDIA Triton …

Read more “Hosting ML Models on Amazon SageMaker using Triton: XGBoost, LightGBM, and Treelite Models”