WeAreDevelopers Logo WeAreDevelopers
Sign in
For You LIVE
WeAreDevelopers LIVE • Sep 25, 2024

Data Privacy in LLMs: Challenges and Best Practices

Aditi Godbole

LLMs memorize massive amounts of sensitive data. Are your API keys and user privacy at risk? Discover technical solutions like differential privacy to build secure AI systems.

Pause
Mute Enter Fullscreen
#1 about 2 min

Emerging data privacy challenges in large language models

The growing importance of data privacy as language models become increasingly integrated into digital landscapes.

#2 about 3 min

Capabilities and applications of large language models

How language models understand context, generate humanlike text, and multitask across diverse development use cases.

#3 about 4 min

Fundamental data privacy principles for artificial intelligence models

Core requirements for secure data handling including minimization, purpose limitation, integrity, and storage duration limits.

#4 about 4 min

Unique privacy vulnerabilities in language model architectures

How training data memorization, re-identification risks, and unintended informational disclosures create severe security hurdles.

#5 about 3 min

Real world case studies of model privacy failures

Instances of unintended demographic disclosure and intellectual property exposure within publicly released commercial applications.

#6 about 4 min

Technical approaches for mitigating privacy risks in models

Implementing techniques like differential privacy, federated learning, and secure multi-party computation to shield sensitive inputs.

#7 about 4 min

Best practices for responsible and secure model deployment

Actionable frameworks for integrating privacy by design, comprehensive data governance procedures, and continuous security audits.

#8 about 4 min

Future developments in privacy preserving technologies and regulations

Upcoming technical methods like homomorphic encryption and sweeping regulatory standards including the EU AI Act.

Matching moments

1:59 min

Building culturally aware LLMs for global audiences

Werner Vogels Werner Vogels +1 · World Congress 2026 Europe

17:05 min

Navigating data privacy boundaries and adversarial model reliability

Alexandra Waldherr · LIVE

3:26 min

Personal use cases and data privacy boundaries

Annabella Bassler Annabella Bassler +3 · World Congress 2026 Europe

5:25 min

Addressing core challenges in large language model deployments

Vijay Krishan Gupta +1 · LIVE

5:06 min

Navigating data privacy and leakage in language models

Laurie Voss Laurie Voss +4 · LIVE

1:39 min

Balancing human-centric AI collaboration with environmental sustainability practices

Madalena Costa Madalena Costa · World Congress 2024

More from WeAreDevelopers LIVE

WeAreDevelopers LIVE - Is CSS Catching Up to Flash? thumbnail
1:03:33
11 days ago

WeAreDevelopers LIVE - Is CSS Catching Up to Flash?

Chris Heilmann, Daniel Cranney, Bramus Van Damme

WeAreDevelopers LIVE - Project Chopin: Make Your Team and Agents Play Along thumbnail
1:21:17
18 days ago

WeAreDevelopers LIVE - Project Chopin: Make Your Team and Agents Play Along

Chris Heilmann, Daniel Cranney, Krzysztof Cieślak

Fake or News - AI Toothbrushes, Carrier Pigeon Tech & Life on Mars - Krzysztof Cieślak thumbnail
4:23
19 days ago

Fake or News - AI Toothbrushes, Carrier Pigeon Tech & Life on Mars - Krzysztof Cieślak

Chris Heilmann, Daniel Cranney

WeAreDevelopers LIVE - Open Source Agent Toolkits thumbnail
1:00:38
25 days ago

WeAreDevelopers LIVE - Open Source Agent Toolkits

Chris Heilmann, Daniel Cranney, Eddie Jaoude

Fake or News - AI Music Detectors, Translating Ancient Languages & Tiny Heads in Teslas - Eddie Jaoude thumbnail
6:16
26 days ago

Fake or News - AI Music Detectors, Translating Ancient Languages & Tiny Heads in Teslas - Eddie Jaoude

Chris Heilmann, Daniel Cranney

Fake or News: AI Agents Hire Each Other, Spider-Man Ads in Cars & RAM Thieves - Marc Plogas thumbnail
5:46
about 1 month ago

Fake or News: AI Agents Hire Each Other, Spider-Man Ads in Cars & RAM Thieves - Marc Plogas

Chris Heilmann, Daniel Cranney, Marc Plogas

Related videos

Prompt Injection, Poisoning & More: The Dark Side of LLMs thumbnail
23:24
World Congress 2025 • about 1 year ago

Prompt Injection, Poisoning & More: The Dark Side of LLMs

Keno Dreßel

Beyond the Hype: Building Trustworthy and Reliable LLM Applications with Guardrails thumbnail
29:00
World Congress 2025 • about 1 year ago

Beyond the Hype: Building Trustworthy and Reliable LLM Applications with Guardrails

Alex Soto

Three years of putting LLMs into Software - Lessons learned thumbnail
26:30
World Congress 2025 • about 1 year ago

Three years of putting LLMs into Software - Lessons learned

Simon A.T. Jiménez

How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge thumbnail
42:26
Coffee With Developers • over 1 year ago

How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge

Meta Atamel, Guillaume Laforge

Inside the Mind of an LLM thumbnail
27:11
World Congress 2025 • about 1 year ago

Inside the Mind of an LLM

Emanuele Fabbiani

Self-Hosted LLMs: From Zero to Inference thumbnail
30:04
World Congress 2025 • about 1 year ago

Self-Hosted LLMs: From Zero to Inference

Cedric Clyburn, Roberto Carratalá

Related articles

From learning to earning

Jobs that call for the skills explored in this talk.