article thumbnail

Stability AI backs effort to bring machine learning to biomed

TechCrunch

Called OpenBioML , the endeavor’s first projects will focus on machine learning-based approaches to DNA sequencing, protein folding and computational biochemistry. Stability AI’s ethically questionable decisions to date aside, machine learning in medicine is a minefield. Predicting protein structures.

article thumbnail

Governance for responsible AI: The easy things and the hard ones

CIO

Companies developing and deploying AI solutions need robust governance to ensure they’re used responsibly. Based on a recent DataStax panel discussion, “ Enterprise Governance in a Responsible AI World ,” there are a few hard and easy things organizations should pay attention to when designing governance to ensure the responsible use of AI.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

What is data governance? Best practices for managing data assets

CIO

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. Data governance framework Data governance may best be thought of as a function that supports an organization’s overarching data management strategy.

article thumbnail

Machine Learning Project Checklist

DataRobot

Download the Machine Learning Project Checklist. Planning Machine Learning Projects. Machine learning and AI empower organizations to analyze data, discover insights, and drive decision making from troves of data. More organizations are investing in machine learning than ever before.

article thumbnail

Build Trustworthy AI With MLOps

In our eBook, Building Trustworthy AI with MLOps, we look at how machine learning operations (MLOps) helps companies deliver machine learning applications in production at scale. AI operations, including compliance, security, and governance. AI ethics, including privacy, bias and fairness, and explainability.

article thumbnail

How automation enables better data governance

CIO

Companies from all industries worldwide continue to increase investments in BPM/Workflow, Robotic Process Automation (RPA), machine learning (ML), and artificial intelligence (AI), and accelerate operational transformations to automate and make data governance more agile to keep up with the exponential growth of incoming information.

article thumbnail

Secure cloud fabric: Enhancing data management and AI development for the federal government

CIO

In recent years, government agencies have increasingly turned to cloud computing to manage vast amounts of data and streamline operations. Current challenges with cloud data The US government generates and collects a massive amount of data each year – everything from census information to intelligence gathering.

article thumbnail

The Business Value of MLOps

As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models.

article thumbnail

10 Keys to AI Success in 2021

The importance of governance in ensuring consistency in the modeling process. How MLOps streamlines machine learning from data to value. AI storytelling in communicating value to your organization. Trusted AI and how vital it is to your AI projects.

article thumbnail

Resilient Machine Learning with MLOps

To prevent deployment delays and deliver resilient, accountable, and trusted AI systems, many organizations invest in MLOps to monitor and manage models while ensuring appropriate governance. Download today to find out more!