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Posted by Dustin Zelle, Software Engineer, Google Research, and Arno Eigenwillig, Software Engineer, CoreML Objects and their relationships are ubiquitous in the world around us, and relationships can be as important to understanding an object as its own attributes viewed in isolation — take for example transportation networks, production networks, knowledge graphs, or social networks. …
This post is co-written with Ilan Geller, Shuyu Yang and Richa Gupta from Accenture. Bringing innovative new pharmaceuticals drugs to market is a long and stringent process. Companies face complex regulations and extensive approval requirements from governing bodies like the US Food and Drug Administration (FDA). A key part of the submission process is authoring …
In today’s fast-paced AI landscape, developers face numerous challenges when it comes to building applications that use large language models (LLMs). In particular, the scarcity of GPUs, which are traditionally required for running LLMs, poses a significant hurdle. In this post, we introduce you to a novel solution that allows developers to harness the power …
Read more “No GPU? No problem. localllm lets you develop gen AI apps on local CPUs”
I’m thrilled to invite you to embark on an enlightening journey with me on StefanSpeaks. As we stand at the forefront of a technological revolution, it’s time to explore and understand the profound impact of Artificial Intelligence on our future, our humanity, and the boundless opportunities it presents. In 2016, I stepped into the world …
Across the globe, financial institutions are rapidly modernizing to deliver secure, seamless payment experiences that meet the demands of digital-first consumers. Financial institutions face the challenge of enabling digital payments while simultaneously managing existing payment capabilities like checks. Although check usage is decreasing worldwide, in the US, checks remain the popular payment option for rent …
Read more “Modernizing payments without disrupting legacy checks systems”
Launched in 2021, Amazon SageMaker Canvas is a visual, point-and-click service for building and deploying machine learning (ML) models without the need to write any code. Ready-to-use Foundation Models (FMs) available in SageMaker Canvas enable customers to use generative AI for tasks such as content generation and summarization. We are thrilled to announce the latest …
A new study underscores the potential of AI and accelerated computing to deliver energy efficiency and combat climate change, efforts in which NVIDIA has long been deeply engaged. The study, called “Rethinking Concerns About AI’s Energy Use,” provides a well-researched examination into how AI can — and in many cases already does — play a …
Read more “New Study Cites AI as Strategic Tool to Combat Climate Change”
Posted by Rajat Sen and Yichen Zhou, Google Research Time-series forecasting is ubiquitous in various domains, such as retail, finance, manufacturing, healthcare and natural sciences. In retail use cases, for example, it has been observed that improving demand forecasting accuracy can meaningfully reduce inventory costs and increase revenue. Deep learning (DL) models have emerged as …
Read more “A decoder-only foundation model for time-series forecasting”
Almost a year ago, IBM encountered a data validation issue during one of our time-sensitive mergers and acquisitions data flows. We faced several challenges as we worked to resolve the issue, including troubleshooting, identifying the problem, fixing the data flow, making changes to downstream data pipelines and performing an ad hoc run of an automated …
Read more “IBM Databand: Self-learning for anomaly detection”
Posted by Rajat Sen and Yichen Zhou, Google Research Time-series forecasting is ubiquitous in various domains, such as retail, finance, manufacturing, healthcare and natural sciences. In retail use cases, for example, it has been observed that improving demand forecasting accuracy can meaningfully reduce inventory costs and increase revenue. Deep learning (DL) models have emerged as …
Read more “A decoder-only foundation model for time-series forecasting”