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”
Posted by Xin Wang, Software Engineer, and Nishanth Dikkala, Research Scientist, Google Research Contemporary deep learning models have been remarkably successful in many domains, ranging from natural language to computer vision. Transformer neural networks (transformers) are a popular deep learning architecture that today comprise the foundation for most tasks in natural language processing and also …
We live in an era of unprecedented technology breakthroughs and opportunities. Recent advances in areas like AI and quantum computing offer transformative potential for businesses, but may also bring new risks and security challenges. IBM is working to address these challenges and evolving threats by helping organizations support highly secure, resilient and durable storage through …
Read more “Putting data storage at the forefront of cloud security”
Posted by Xin Wang, Software Engineer, and Nishanth Dikkala, Research Scientist, Google Research Contemporary deep learning models have been remarkably successful in many domains, ranging from natural language to computer vision. Transformer neural networks (transformers) are a popular deep learning architecture that today comprise the foundation for most tasks in natural language processing and also …
Large language models (LLMs) with their broad knowledge, can generate human-like text on almost any topic. However, their training on massive datasets also limits their usefulness for specialized tasks. Without continued learning, these models remain oblivious to new data and trends that emerge after their initial training. Furthermore, the cost to train new LLMs can …
Google Cloud Speech-to-Text is a fully managed service that converts speech to text in real time. It can be used to transcribe audio and video files, create subtitles for videos, and build voice-activated applications. The service supports a wide range of audio formats, including WAV, MP3, and AAC. It can also transcribe audio in a …
The home of the first industrial revolution just made a massive investment in the next one. The U.K. government has announced it will spend £225 million ($273 million) to build one of the world’s fastest AI supercomputers. Called Isambard-AI, it’s the latest in a series of systems named after a legendary 19th century British engineer …
Read more “Turing’s Mill: AI Supercomputer Revs UK’s Economic Engine”
You can now create custom versions of ChatGPT that combine instructions, extra knowledge, and any combination of skills.