Experts from industry, academia and government share lessons learned and outline a path forward at a Princeton-Stanford workshop Author Kevin Klyman is a researcher at the Stanford Center for Research on Foundation Models and M.A. candidate at Stanford University. Foundation models are the centerpiece of the modern AI ecosystem, leading to rapid innovation, deployment, and […]
Decoding China’s Ambitious Generative AI Regulations
April 16, 2023 by
By Sihao Huang and Justin Curl On April 11th, 2023, China’s top internet regulator proposed new rules for generative AI. The draft builds on previous regulations on deep synthesis technology, which contained detailed provisions on user identity registration, the creation of a database of undesirable inputs, and even the generation of “special objects and scenes” […]
Can ChatGPT—and its successors—go from cool to tool?
March 8, 2023 by
Anyone reading Freedom to Tinker has seen examples of ChatGPT doing cool things. One of my favorites is its amazing answer to this prompt: “write a biblical verse in the style of the King James Bible explaining how to remove a peanut butter sandwich from a VCR.” Based in part on this kind of […]
Toward Trustworthy Machine Learning: An Example in Defending against Adversarial Patch Attacks (2)
July 19, 2022 by
By Chong Xiang and Prateek Mittal In our previous post, we discussed adversarial patch attacks and presented our first defense algorithm PatchGuard. The PatchGuard framework (small receptive field + secure aggregation) has become the most popular defense strategy over the past year, subsuming a long list of defense instances (Clipped BagNet, De-randomized Smoothing, BagCert, Randomized […]
National AI Research Infrastructure Needs to Support Independent Evaluation of Performance Claims
September 2, 2021 by
By Sayash Kapoor, Mihir Kshirsagar, and Arvind Narayanan Our response to the National AI Research Resource RFI highlights the significance of supporting a research infrastructure that is designed to independently test the validity of the claims of AI performance. In particular, we draw attention to the widespread phenomenon of the industry peddling what we call […]
