Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
ACM TechTalks
ACM members and non-members alike are welcome to attend our popular series of free TechTalks by expert industry professionals, distinguished ACM award laureates, and visionary researchers from industry and academia. Focused on keeping our global audience of busy practitioners at the forefront of technical trends, professional development, and emerging technologies, the TechTalks are also popular with students and educators. Recent talks have covered topics in Artificial Intelligence and Machine Learning, Big Data and Data Science, Blockchain, Computer Vision, Deep Learning, JavaScript, Microservices, Python, Quantum Computing, and more. Registration is free and the TechTalks can be attended both live and on-demand, on desktop and mobile devices. Check this page frequently for upcoming events as well as our on-demand archive. To subscribe to our TechTalk announcements, email learning@acm.org.
View Our Recent TechTalk
Quantum Computational Supremacy with Scott Aaronson
In fall 2019, a team at Google made the first-ever claim of "quantum computational supremacy"—that is, a clear quantum speedup over a classical computer for some task—using a 53-qubit programmable superconducting chip called Sycamore. Since then, a group at USTC in China has made additional claims of quantum supremacy, using both superconducting qubits and "Boson Sampling" (a proposal by me and Alex Arkhipov from 2011) with ~70 photons in an optical network. In addition to engineering, these experiments built on a decade of research in quantum complexity theory. This talk will discuss questions like: what exactly were the contrived computational problems that were solved? How does one verify the outputs using a classical computer? And crucially, how confident can we be that the problems are really classically hard?
ACM Learning Center TechTalk Archive
ACM award winners, leading researchers, industry veterans, thought leaders, and innovators address today and tomorrow's hottest topics and issues in computing for busy practitioners, as well as educators, students, and researchers. Check out our archive of these ACM TechTalks, free for members and non-members alike.
TechTalks on Artificial Intelligence & Machine Learning
Talks from some of the leading visionaries and bleeding-edge researchers in AI/ML: Fei-Fei Li on visual intelligence in computers and ImageNet; Eric Horvitz on AI solutions in the open world; and Tom Mitchell on using ML to study how the brain creates and represents language.
Running Linux Apps on Windows: How and Why?
View the recent ACM TechTalk, "Running Linux Apps on Windows: How and Why?" presented by Scott Hanselman, blogger and web developer at Microsoft, where he works on Open Source on ASP.NET and the Azure Cloud, host of the Hanselminutes Podcast (http://hanselminutes.com), and member of the ACM Practitioner Board. Bradley K. Jensen, Principal Data Scientist and Architect in the Data and Analytics Division at Centric Consulting and member of the ACM Professional Development Committee (PDC), moderated the questions and answers session following the talk. Continue the discussion on ACM's Discourse Page.
Learning Symbolic Equations with Deep Learning
View the recent ACM TechTalk, "Learning Symbolic Equations with Deep Learning," presented by Shirley Ho, Acting Director of the Center for Computational Astrophysics (CCA) at the Flatiron Institute, where she leads the Cosmology X Data Science Group. Her research interests have ranged from fundamental cosmological measurements to exoplanet statistics to using machine learning to estimate how much dark matter is in the universe. Continue the discussion on ACM's Discourse Page.
