RESEARCH

→ View original post on X — @mit_csail

MIT Open Courses: Free CS, AI and Algorithms Videos Online

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@mit_csail

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06 February 2023 18h01

Free MIT videos & online materials from more than 2,400 courses, including intro classes in computer science, AI and algorithms. Browse our open CS courses here: https://
bit.ly/39jH8DV (v/
@MITOCW
)

→ View original post on X — @willknight

ChatGPT Search Risks: Why AI Hallucinations Matter

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@willknight

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06 February 2023 17h47

My latest for @WIRED looks at why using ChatGPT for search may be a problem. Microsoft, Baidu, and Google are rushing to incorporate the tech but it is designed to make things up and cannot easily access new info. What could go wrong?

Academic Review Quality Issues in AI Research

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06 February 2023 17h40

Bonus tweet: not all reviews were quite as high quality. Here's one that's basically "LGTM" (
https://
openreview.net/forum?id=x4hmI
sWu7e&noteId=xoY58zHa3X
…). But it was positive, so I'm not complaining! 5/4

TMLR Review Process: 9 Weeks from Submission to Decision

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06 February 2023 17h29

Finally, let me emphasize how good the @TmlrOrg review process was! ~9 weeks from submission to decision. The first review, one of the highest quality I've ever received (
https://
openreview.net/forum?id=x4hmI
sWu7e&noteId=duK2Zgaamy
…), was in ~24 hours from submission! 4/4

New faster attack method developed for AI security

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06 February 2023 17h29

We make a modest step in this direction. We come up with a new attack that is much faster and more effective than previous methods. Still not as effective as I'd like though! I won't write a long thread here since I think we'll have more to say soon, stay tuned 3/n

Why Neural Networks Resist Data Poisoning Attacks Better

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06 February 2023 17h29

It's well known that NNs are very vulnerable to adversarial interventions, e.g., indiscernible test-time attacks. But indiscriminate data poisoning, wherein the attacker modifies a small fraction of the training data to reduce the test accuracy, seems to be much harder! Why? 2/n

Neural Networks Poisoning Attacks Research Paper Accepted

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06 February 2023 17h29

Paper accepted to @TmlrOrg
: "Indiscriminate Data Poisoning Attacks on Neural Networks," led by Yiwei Lu and co-advised with Yaoliang Yu. Neural networks are surprisingly hard to (indiscriminately) poison! We give better attacks. https://
openreview.net/forum?id=x4hmI
sWu7e
… 1/n

→ View original post on X — @katecrawford

Critical Questions and Strategies for ML Dataset Lifecycle Management

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@katecrawford

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06 February 2023 16h58

The guide offers questions, suggestions, strategies, and resources while working with ML datasets at every phase of their lifecycle, and shows the benefits of working critically with them. It gives you the questions that we've found helpful in our work with large ML datasets.

→ View original post on X — @katecrawford

Field Guide to Critical Dataset Navigation and Classification

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@katecrawford

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06 February 2023 16h57

The field guide aims to help you navigate the complexities of datasets, and explore the implications of what you choose, build, and design. It invites you to mess with these messy forms and to approach any logic of classification with a critical eye.