Trained on an enormous corpus of publicly available data from a broad range of topics, large language models (LLMs) are powerful in many ways but can be improved in other areas. Due to the size of the training data, it can be resource-intensive to train them frequently. As a result, they may not have the …
Read more “Build enterprise gen AI apps with Google Cloud databases”
Hip disorders, comprising some of the world’s most common joint diseases, are especially prevalent among adolescents and young adults, causing stiffness, pain or a limp. But they can be hard to diagnose using solely 2D medical imaging. Helping to treat these disorders, the Boston Children’s Hospital’s (BCH’s) Adolescent and Young Adult Hip Preservation Program is …
Posted by Manish Gupta, Staff Software Engineer, Google Research AI-driven technologies are weaving themselves into the fabric of our daily routines, with the potential to enhance our access to knowledge and boost our overall productivity. The backbone of these applications lies in large language models (LLMs). LLMs are memory-intensive and typically require specialized hardware accelerators …
Read more “Mixed-input matrix multiplication performance optimizations”
Machine learning (ML) models are fundamentally shaped by data, and building inclusive ML systems requires significant considerations around how to design representative datasets. Yet, few novice-oriented ML modeling tools are designed to foster hands-on learning of dataset design practices, including how to design for data diversity and inspect for data quality. To this end, we …
Recent years have witnessed an explosion in the proliferation of self-storage units. These large, warehouse units have sprung up nationally as a booming industry because of one reason—the average person now has more possessions than they know what to do with. The same basic situation also plagues the world of IT. We’re in the midst …
When deploying a large language model (LLM), machine learning (ML) practitioners typically care about two measurements for model serving performance: latency, defined by the time it takes to generate a single token, and throughput, defined by the number of tokens generated per second. Although a single request to the deployed endpoint would exhibit a throughput …
Read more “Benchmark and optimize endpoint deployment in Amazon SageMaker JumpStart “
A New Paradigm for Computer Vision Workflows Massive investments are being made across the DoD to develop and field Machine Learning (ML) based capabilities for intelligence and operational data sources. In particular, the application of Computer Vision (CV) models on top of overhead aerial imagery has become a key focus area for teams looking to …
Telecommunications industry, a cornerstone of global connectivity, has been going through a technological renaissance for some time, driven by innovations such as 5G, IoT, cloud computing and AI. As a result, networks have become increasingly hard to manage. There is a need for automation to handle routine tasks, monitor network health and respond to issues in …
Read more “Networks unchained: the shift toward intent-based autonomous operations”
Posted by Manish Gupta, Staff Software Engineer, Google Research AI-driven technologies are weaving themselves into the fabric of our daily routines, with the potential to enhance our access to knowledge and boost our overall productivity. The backbone of these applications lies in large language models (LLMs). LLMs are memory-intensive and typically require specialized hardware accelerators …
Read more “Mixed-input matrix multiplication performance optimizations”