Machine Unlearning: Techniques, Challenges, and Future Directions

Update: 2024-05-30

Description

Ken Liu, Ph.D. student in Computer Science at Stanford, is the author of Machine Unlearning in 2024. We explore the concept of machine unlearning, a process of removing specific data points from trained AI models.

Subscribe to the Gradient Flow Newsletter: https://gradientflow.substack.com/

Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon • RSS.

Detailed show notes can be found on The Data Exchange web site.

Comments

Top Podcasts

The Best New Comedy Podcast Right Now – June 2024 The Best News Podcast Right Now – June 2024 The Best New Business Podcast Right Now – June 2024 The Best New Sports Podcast Right Now – June 2024 The Best New True Crime Podcast Right Now – June 2024 The Best New Joe Rogan Experience Podcast Right Now – June 20 The Best New Dan Bongino Show Podcast Right Now – June 20 The Best New Mark Levin Podcast – June 2024

In Channel

AI Unlocked: The Data Bottleneck

2025-01-0925:11

The Data-Centric Shift in AI: Challenges, Opportunities, and Tools

2025-01-0227:43

Monthly Roundup: Semiconductors, Frontier Models, and Practical Innovations

2024-12-2648:51

Breaking the Cloud Barrier: How DBOS Transforms Application Development

2024-12-1936:02

The Essential Guide to AI Guardrails

2024-12-1247:27

Beyond ETL: How Snow Leopard Connects AI, Agents, and Live Data

2024-12-0543:33

2024 Generative AI in Healthcare Survey Results

2024-11-2837:35

Monthly Roundup: BAML, Tencent’s Hunyuan Model, AI & Kubernetes, and the Future of Voice AI

2024-11-2149:22

Building the Future of Finance: Inside AI Valuation Bots

2024-11-1437:45

Unleashing the Power of BAML in LLM Applications

2024-11-0745:45

Cracking the Code: How Enterprises Are Adopting Generative AI

2024-10-3130:09

Monthly Roundup: Ray Compiled Graphs, Llama 3.2 and Multimodal AI, and Structured Data for RAG

2024-10-2452:57

Reimagining Code: The AI-Driven Transformation of Programming and Data Analytics

2024-10-1741:05

The Security Debate: How Safe is Open-Source Software?

2024-10-1051:06

Generative AI in Voice Technology

2024-10-0359:41

Building An Experiment Tracker for Foundation Model Training

2024-09-2637:56

Monthly Roundup: AI Regulations, GenAI for Analysts, Inference Services, and Military Applications

2024-09-1945:49

Unlocking the Power of LLMs with Data Prep Kit

2024-09-1238:15

Advancing AI: Scaling, Data, Agents, Testing, and Ethical Considerations

2024-09-0524:37

Bridging the Hardware-Software Divide in AI

2024-08-2948:27

00:00

Machine Unlearning: Techniques, Challenges, and Future Directions

#box-pro-ellipsis-173693612288548{-webkit-line-clamp:2;}Machine Unlearning: Techniques, Challenges, and Future Directions

Machine Unlearning: Techniques, Challenges, and Future Directions

Ben Lorica

Machine Unlearning: Techniques, Challenges, and Future Directions