SIG Governing Board-Executive Committee Motions - FY'02
Motion: Move that the SGB accept the proposal that the SIGs finance the development of the Guide, in exchange for making the Guide free to all and enabling SIG-specific enhancements to the Guide.
That the SGB EC constitute a group to work with HQ and the ACM EC to agree on the details. (11/20/01)
Motion: Move to endorse exception to ACM policy and allow SIGGRAPH to sole source their Web Programming Services. This is a one-time only exception.
Motion: Move to endorse a waiver to current policy and allow a two-year extension to ACM SIGGRAPH's contract with Freeman Decorating. SIGGRAPH leadership is encouraged to exchange this extension for clear benefit to the conference.
Motion: Move to endorse policy modification on the RFP process bringing the threshold to $75,000 for conferences with budgets in excess of $1M.
Motion: Move to endorse a change in policy on the length of contracts for 3 to 5 years for conferences with budgets in excess of $1M.
Motion: The SGB EC approves the budgets of SIGCAPH, SIGDOC, SIGMICRO, SIGSAC and SIGecomm for FY'03. All Chairs for these SIGs will be required to submit an outline by June 1st indicating their plans to bring the SIG out of financial trouble.
Motion: Move that SIGART be converted to a conference SIG as directed by the SIG Operating Rules.
You can use your technical skills for social good and offer volunteer support on software development projects to organizations who could not otherwise afford it. SocialCoder connects volunteer programmers/software developers with registered charities and helps match them to suitable projects based on their skills, experience, and the causes they care about. Learn more about ACM’s new partnership with SocialCoder, and how you can get involved.
ACM Queue’s “Research for Practice” is your number one resource for keeping up with emerging developments in the world of theory and applying them to the challenges you face on a daily basis. In this installment, Dan Crankshaw and Joey Gonzalez provide an overview of machine learning server systems. What happens when we wish to actually deploy a machine learning model to production, and how do we serve predictions with high accuracy and high computational efficiency? Dan and Joey’s curated research selection presents cutting-edge techniques spanning database-level integration, video processing, and prediction middleware. Given the explosion of interest in machine learning and its increasing impact on seemingly every application vertical, it's possible that systems such as these will become as commonplace as relational databases are today.