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AI data privacy: A new product essential

Mind the Product

Read more » The post AI data privacy: A new product essential appeared first on Mind the Product. In the ever-evolving tech landscape, where innovation meets the promise of generative AI, one crucial question looms: Can we truly harness the transformative power of AI while safeguarding sensitive data?

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Privacy by design: flipping the script on privacy in product

Mind the Product

For tech giants like Apple and Google, user privacy has traditionally been seen as something to avoid rather than a selling point for their products. Read more » The post Privacy by design: flipping the script on privacy in product appeared first on Mind the Product.

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Understanding AI's Impact on Customer Privacy and Legal Compliance

Amplitude

Learn how to navigate the intersection of artificial intelligence (AI), privacy, and legal compliance.

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How to Create a Strong Data Privacy and Security Culture

Amplitude

A robust privacy and security culture does more than comply with regulatory standards—it shapes employees' everyday actions and decisions. Learn how to create a strong culture.

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How to Use Customer Feedback for Business Growth

By clicking "Download Now", you agree to receive marketing communications from our partner airfocus and agree to their privacy policy [[link] You may unsubscribe from these communications at any time. Customer feedback by product lifecycle. Common mistakes to avoid when collecting feedback.

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Health Care Product Managers Deal With Privacy Issues

The Accidental Product Manager

Product managers have to deal with patient data privacy laws Image Credit: Stock Catalog. Customers are very aware of the data privacy issues and so they are hesitant to use the health care products that the product managers are providing them with. The Privacy Issue. A great example of this happening in the health care market.

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How we ensure the highest standards of data privacy and compliance within Intercom

Intercom, Inc.

We leave no stone unturned when it comes to data privacy. Before a vendor is procured, our IT, legal, and security teams review their security and data privacy practices in full. We’re constantly on the lookout for ways to bring our data privacy and compliance standards to new heights, and strengthen our data protection policies.

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5 Key Elements for Building a Successful Data-Driven Product

When selecting data providers, companies must ensure they’re tapping into comprehensive, high-quality streams of fresh information which can be easily integrated into their products in a privacy-compliant manner. Read Data Axle’s whitepaper to learn: The 5 key components to consider when licensing data.

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Post-Pandemic eCommerce Growth: Leverage Product Data, Market Research & Shopping Trends

Speaker: Phil Irvine, VP & Director of Audience Intelligence

When you couple that with fluid data privacy changes, this creates an even fuzzier foundation to develop forward-looking marketing strategies. Whether concerned about data privacy and data management, or curious about how businesses can rethink approaches to designing shopping experiences, the answers are here.

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Build Trustworthy AI With MLOps

AI ethics, including privacy, bias and fairness, and explainability. We also look closely at other areas related to trust, including: AI performance, including accuracy, speed, and stability. AI operations, including compliance, security, and governance. How MLOps helps bridge the production gap between systems and teams.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs. Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications.