AWS for Industries

Tag: machine learning

Unlocking the power of data for sustainable water management with AWS

Unlocking the power of data for sustainable water management with AWS

Introduction: Water scarcity is a pressing global challenge with far-reaching consequences. With rising populations, climate change impacts, and increasing urbanization, the demand for fresh water resources continues to outpace supply in many regions. Efficient water management is crucial for long-term sustainability and resilience. The importance of water efficiency: Water is a vital resource that underpins […]

Energy Symposium 2024

Reinventing Energy, Together | AWS Energy Symposium 2024

From the first spark of fire to the harnessing of nuclear power, energy innovation has been the bedrock of human progress. It has illuminated our cities, powered our industries, and propelled us into the space age. Every leap in energy technology has ushered in new eras of possibility, transforming the way we live, work, and […]

Analyzing Remote Communications Infrastructure with Computer Vision

Analyzing Remote Communications Infrastructure with Computer Vision

To plan wireless networks effectively, Communication Service Providers (CSPs) must analyze the viability of potential cell sites. This includes identifying potential facilities, obstructions, sources of interference, etc. Traditionally, capturing this information required a truck roll, which can be expensive, especially at scale. Harnessing the power of Machine Learning (ML) and computer vision to analyze site […]

Accelerating industrialization of Machine Learning feature card

Accelerating industrialization of Machine Learning at BMW Group using the Machine Learning Operations (MLOps) solution

The BMW Group and Amazon Web Services (AWS) announced a strategic collaboration in 2020. The goal of that collaboration is to help further accelerate the BMW Group’s pace of innovation by placing data and analytics at the center of its decision-making. The BMW Group’s Cloud Data Hub (CDH) manages company-wide data and data solutions on […]

Highlights from the AWS Healthcare and Life Sciences Executive Symposium 2023 at re:Invent

As a prelude to re:Invent 2023, AWS hosted the Healthcare and Life Sciences (HCLS) Executive Symposium in Las Vegas on Monday, November 27. The half-day, in-person event, attended by over 300 leaders from 180 organizations, centered around harnessing the power of data, analytics, machine learning (ML), and generative AI to accelerate innovation. This year’s symposium […]

Enhance price capture in energy and commodity trading with AWS machine learning

Enhance price capture in energy and commodity trading with AWS machine learning

In the energy and commodity trading industry, traders negotiate transactions with brokers and counterparties directly. These negotiated transactions are called over-the-counter (OTC) deals. Price discovery for OTC deals is unlike price discovery for common equity, options, and other financial instruments, where pricing information is generally market-efficient and available in near real time. In OTC trades, […]

Top-10 re:Invent 2023 Announcements Important for Healthcare and Life Sciences

Occasionally, new technologies emerge that fundamentally alter how businesses operate. But without the appropriate tools—controls, safeguards, and user experiences—the promise of new technologies can get stuck.  In the past year, many have been captivated by the potential of Generative AI to revolutionize drug discovery, precision medicine, and healthcare delivery. But what tools will turn the […]

How healthcare organizations can improve discharge medication safety

How healthcare organizations can improve discharge medication safety

Medications are integral for preventing and curing illness, yet medication errors can also be a cause of harm. For example, in 1993 over 7000 patients died in the United States as a result of a medication error. As more medications become available for use, the simultaneous use of multiple medications by a single patient is […]

Build an end-to-end framework to store, integrate, and analyze multimodal data using AWS purpose-built Health and Machine Learning services.

Multimodal Data Analysis with AWS Health and Machine Learning Services

In this blog, we show how you can leverage AWS purpose-built health care and life sciences (HCLS), machine learning (ML), and analytics services to simplify storage and analysis across genomic, health records, and medical imaging data for precision health use cases. The included reference architecture is built on AWS HealthOmics, AWS HealthImaging, and AWS HealthLake services which enable you […]

Pfizer boosts bioreactor efficiency with AWS industrial edge services

Pfizer, one of the world’s premier biopharmaceutical companies, uses machine learning (ML) and artificial intelligence (AI) for near-real-time monitoring of mammalian cell culture bioreactors to boost batch yield and reduce the risk of contamination. Using Amazon Web Services (AWS), the company developed Manufacturing Intelligence Edge (MI Edge), a platform that uses AI and ML for […]