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?
RESEARCH
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Academic Review Quality Issues in AI Research
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Bonus tweet: not all reviews were quite as high quality. Here's one that's basically "LGTM" (
https://
openreview.net/forum?id=x4hmI
sWu7e¬eId=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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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¬eId=duK2Zgaamy
…), was in ~24 hours from submission! 4/4 -
Why Neural Networks Resist Data Poisoning Attacks Better
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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
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New faster attack method developed for AI security
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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
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Neural Networks Poisoning Attacks Research Paper Accepted
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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 -
Critical Questions and Strategies for ML Dataset Lifecycle Management
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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.
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Critical Field Guide for Working With Machine Learning Datasets Released
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NEW: Today we release a 'Critical Field Guide for Working With Machine Learning Datasets' by @SarahCiston
. It's a practical guide to navigating datasets. If you're an engineer, designer, journalist artist, or a student who uses datasets, it's here for you. -
Field Guide to Critical Dataset Navigation and Classification
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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.
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Breaking down barriers to education access and resource sharing
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Appreciate it Knut @JagersbergKnut Many thanks indeed, so important to break down barriers to access with learning and sharing resources such as this. Thanks for sharing, much appreciated, S #SDGs #education