Building Trust in AI Means Building Trust in Data
Confluent
MAY 10, 2024
Discover how to build trust in AI by strengthening data and people layers. Learn about risk frameworks, data streaming, and more for effective solutions.
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Confluent
MAY 10, 2024
Discover how to build trust in AI by strengthening data and people layers. Learn about risk frameworks, data streaming, and more for effective solutions.
Cloudera
DECEMBER 1, 2023
It focuses on five key pillars: investing in research and development; unleashing government AI resources; setting standards and policy; building the AI workforce; and advancing trust and security. The post Building Trust in Public Sector AI Starts with Trusting Your Data appeared first on Cloudera Blog.
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databricks
MAY 6, 2024
Introduction Organizations aiming to become AI and data-driven often need to provide their internal teams with high-quality and trusted data products. Building.
Cloudera
JANUARY 30, 2024
The universal industrial data challenge Data — as the foundation of trusted AI — can lead the way to transform business processes and help manufacturers innovate, define new business models, and establish new revenue streams. Trusted AI begins with trusted data What resolves the data challenge and fuels data-driven AI in manufacturing?
Cloudera
OCTOBER 24, 2023
But to truly drive transformation telcos must ensure AI models are driven by accurate, high-quality, trusted data, and determine how to manage and govern massive volume at scale. This is the essence of “Trusted AI Everywhere.” Trusted AI Everywhere” explained Trusted AI poses significant challenges.
LinkedIn Engineering
MARCH 16, 2023
Avery's career in military IT took an unexpected turn when he caught wind of a LinkedIn Trust & Safety (QA) manager opportunity in his hometown of Omaha, Nebraska. LinkedIn’s Trust & Safety team At LinkedIn, I'm part of Trust & Safety’s Abuse & Content Enforcement (ACE) group, leading a group of six analysts and agents.
databricks
JANUARY 24, 2024
Reliable, accurate and trusted data is the most critical requirement for any data application in an enterprise. As Databricks customers increasingly rely on.
Cloudera
JUNE 7, 2023
By now, almost everyone across the tech landscape has heard of the Zero Trust (ZT) security model, which assumes that every device, application, or user attempting to access a network is not to be trusted (see NIST definitions below). The post How Cloudera Supports Zero Trust for Data appeared first on Cloudera Blog.
Precisely
MAY 18, 2023
The annual Precisely Data Integrity Summit , Trust ’23, was another amazing success that virtually brought together thousands of data professionals worldwide. Zahid Kamal from Central Insurance shares how integrated data quality metrics build trust and enhance data governance programs.
Confluent
MARCH 2, 2023
Perhaps the largest challenge for modern data teams is gaining and retaining trust. Insights without truth are worthless, so trustworthy results must come first.
Precisely
MAY 9, 2023
Author’s note: this article about industry trends and trusted data has been adapted from an article originally published in Solutions Review. But to achieve true transformation, your processes and strategic decisions need to be powered by trusted data. Learn more 1. I look forward to seeing you there.
Data Engineering Podcast
FEBRUARY 3, 2020
Data trusts are a legal framework for allowing businesses to collaboratively pool their data. This allows the members of the trust to increase the value of their individual repositories and gain new insights which would otherwise require substantial effort in duplicating the data owned by their peers.
Monte Carlo
DECEMBER 22, 2023
At IMPACT 2023, I had the pleasure of sitting down with Annie Duke , former professional poker player, professional decision strategist to discuss how to make smarter decisions from limited data, how teams can establish better decision-making processes, and when to know if that “gut feeling” is worth trusting. And at the root of consensus?
Monte Carlo
DECEMBER 22, 2023
At IMPACT 2023, I had the pleasure of sitting down with Annie Duke , former professional poker player, professional decision strategist to discuss how to make smarter decisions from limited data, how teams can establish better decision-making processes, and when to know if that “gut feeling” is worth trusting. And at the root of consensus?
Data Engineering Podcast
AUGUST 10, 2021
Summary All of the fancy data platform tools and shiny dashboards that you use are pointless if the consumers of your analysis don’t have trust in the answers. Go to dataengineeringpodcast.com/census today to get a free 14-day trial. Interview Introduction Can you describe what Stemma is and the story behind it?
Precisely
JULY 10, 2023
Did you join us for Trust ’23: the Precisely Data Integrity Summit? Trust ’23 was chock-full of content for everyone – whatever your industry or data integrity area of focus may be. Read our eBook Top Takeaways from Trust ’23 If you were not able to join us live for our Precisely Data Integrity Summit? Want to learn more?
Monte Carlo
SEPTEMBER 27, 2023
When it comes to building data and AI products you can trust, Monte Carlo, the leader of the data observability category, and Alation, the data intelligence leader, are better together. Can I trust the data feeding this model? Enter: data observability and data intelligence platforms , the solution to data trust.
Monte Carlo
JANUARY 16, 2024
And with targeted Monte Carlo alerts for stakeholders in Slack and Teams, stakeholders always know exactly when a dataset is—and is not—safe to use, developing trust in the data team along the way. “We And standards create the framework for data trust. We want them involved in data governance too.”
Precisely
JULY 31, 2023
The 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, delivers groundbreaking insights into the importance of trusted data. The post From Data Quality to Data Integrity: The Path to Trusted Data appeared first on Precisely. One key finding?
Monte Carlo
AUGUST 10, 2022
My Painful Data Trust Experience Many years ago, an exec approached me after a contentious meeting and asked, “Shane, so is the data trustworthy?” Data trust is everything. Unfortunately, data trust is also often a lagging indicator of quality and reliability. Perhaps you can relate. And damage can be done.
Teradata
OCTOBER 13, 2020
The most frequently asked question of Finance departments today is, ‘whose data do we trust’? Here’s how to ensure Finance always has the correct answer.
KDnuggets
AUGUST 2, 2022
Many machine learning models fail to deliver. Sadly, it’s often due to a lack of focus on data quality.
Precisely
JULY 27, 2023
The 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, delivers groundbreaking insights into the importance of trusted data. For the report, more than 450 data and analytics professionals worldwide were surveyed about the state of their data programs.
KDnuggets
OCTOBER 2, 2023
This article explores strategies for evaluating the reliability of labels generated by Large Language Models (LLMs). It discusses the effectiveness of different approaches and offers practical insights for various applications.
KDnuggets
MARCH 24, 2020
In this article, we’ll talk about calibration in graph machine learning, and how it can help to build trust in these powerful new models.
Precisely
JUNE 2, 2023
Data enrichment using trusted third-party sources adds a valuable perspective that can lead to breakthrough insights. The post Ensure Success with Trusted Data When Moving To The Cloud appeared first on Precisely. Despite these common threads, every organization will find its own unique path to achieving high levels of data integrity.
Confluent
APRIL 19, 2023
Storyblocks, the world’s first stock media subscription service, trusts Confluent over Kafka, enabling Storyblocks to prioritize innovation and mission critical use cases.
KDnuggets
DECEMBER 2, 2019
What are trust and safety? What is the role of trust and security in the modern world? Read this overview of 7 data science application use cases in the realm of trust and security.
KDnuggets
MAY 3, 2023
ChatGPT has created a flurry of discussion in the educational community. Will it encourage people to cheat or become lazy? What helpful uses exist? Learn more here.
U-Next
SEPTEMBER 29, 2022
If you’re trusted, they’ll buy from you.” A mere 5% increase in customer retention can result in a 95 % increase in profit , which shows that the rewards of customer trust are significant. Customers who trust a business are 83% more likely to recommend it to others than those who do not. ” .
Monte Carlo
DECEMBER 5, 2022
Data observability at PayJoy To understand the quality of their data and improve data trust across teams, Trish’s team turned to data observability through Monte Carlo. Monte Carlo is a very good way for us to understand our data quality at scale,” said Trish. So, what’s next for data at PayJoy?
Confluent
MAY 10, 2023
Confluent manages 30,000+ Kafka clusters, produces over 3 trillion messages, and does durability checks on over 80 trillion Kafka messages per day while offering 99.99% uptime. Check out our cool stats!
KDnuggets
OCTOBER 27, 2022
Learn how data-centric AI can improve your model's overall performance.
databricks
SEPTEMBER 15, 2023
Special thanks to our partners at Immuta, Alation, and Anomalo for their collaboration on the content and technical assets from this article.
databricks
MARCH 27, 2023
The importance and impact of data in healthcare is greater than it has ever been, with access to truly large-scale datasets and powerful.
KDnuggets
OCTOBER 8, 2019
As so many more organizations now rely on AI to deliver services and consumer experiences, establishing a public trust in the AI is crucial as these systems begin to make harder decisions that impact customers.
Cloudera
DECEMBER 3, 2021
The post In AI we trust? Cloudera’s Fast Forward Labs provides readers with comprehensive and accessible guides to emerging data and machine learning-enabled trends, and working prototypes. Find out more at Cloudera’s Fast Forward Labs. . Why we Need to Talk About Ethics and Governance (part 2 of 2) appeared first on Cloudera Blog.
Cloudera
NOVEMBER 25, 2021
The post In AI we Trust? More information on emerging data and machine learning-enabled trends, and working prototypes are available at Cloudera’s Fast Forward Labs. Get more comprehensive and accessible guides at Cloudera’s Fast Forward Labs. . Why we Need to Talk about Ethics and Governance (part 1 of 2) appeared first on Cloudera Blog.
Teradata
DECEMBER 19, 2022
As 2022 nears to a close, members of Teradata’s C-suite and executive leadership team give us their predictions for 2023, on topics ranging from health-tech and AI to marketing and HR.
Yelp Engineering
MARCH 26, 2024
One of Yelp’s top priorities is the trust and safety of our users. Yelp’s platform is most well-known for its reviews, and its moderation practices have been recognised in academic research for mitigating misinformation and building consumer trust.
Confluent
APRIL 12, 2022
Streaming data has become critical to the success of modern businesses. Leveraging real-time data enables companies to deliver the rich, digital experiences and data-driven backend operations that delight customers. For […].
Cloudera
APRIL 18, 2024
What we’ve seen is that more businesses are looking at the potential of those tools through the lens of trust—specifically, do I trust these open models with my data? Do I trust my data to be ready for use in AI? Do I trust the models to give me useful insights?
Monte Carlo
AUGUST 17, 2021
The rise of data downtime In 2021, it’s simply not enough to use data to drive accurate decision making and power digital products — you need to trust it, too. Once trust is lost, it’s hard to gain back. With Monte Carlo, my team can understand what data is important for the business, as well as whether or not this data can be trusted.
KDnuggets
JULY 31, 2019
We put an AutoML tool to the test on a real-world problem, and the results are surprising. Even with automatic machine learning, you still need expert data scientists.
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