Hackerman Hall B-17
Virtual assistants, providing a voice interface to web services and IoTs, can potentially develop into monopolistic platforms that threaten consumer privacy and open competition. This talk presents Almond as an open-source alternative.
Unlike existing commercial assistants, Almond can be programmed in natural language to perform new tasks. It lets users control who, what, when, where, and how their data are to be shared, all without disclosure to a third party.
Almond has a Write-Once-Run-Anywhere (WORA) skill platform: skills need to be written only once and can run automatically on other assistants. This helps level the playing field for new assistants.
Finally, Almond’s open-source technologies enable non-ML experts to develop natural language capabilities in their domains of interest. Through open-world collaboration, Almond can become the smartest virtual assistant.
Monica Lam is a Professor in the Computer Science Department at Stanford University since 1988. She received a B.Sc. from University of British Columbia in 1980 and a Ph.D. in Computer Science from Carnegie Mellon University in 1987. Monica is a Member of the National Academy of Engineering and Association of Computing Machinery (ACM) Fellow. She is a co-author of the popular text Compilers, Principles, Techniques, and Tools (2nd Edition), also known as Dragon book. She is the PI of the NSF Research Award “Autonomy and Privacy with Open Federated Virtual Assistants”. This project combines machine learning, natural language processing, programming systems, distributed systems, human-computer interaction, blockchain technology to create an open-source assistant that promotes consumer privacy and open competition. Her Almond research project is the first virtual assistant that lets users share their digital assets easily in natural language, without disclosing any information to a third party.
Hackerman Hall B-17
Our ability to collect, manipulate, analyze, and act on vast amounts of data is having a profound impact on all aspects of society. Much of this data is heterogeneous in nature and interlinked in a myriad of complex ways. From information integration to scientific discovery to computational social science, we need machine learning methods that are able to exploit both the inherent uncertainty and the innate structure in a domain. Statistical relational learning (SRL) is a subfield that builds on principles from probability theory and statistics to address uncertainty while incorporating tools from knowledge representation and logic to represent structure. In this talk, I will give a brief introduction to SRL, present templates for common structured prediction problems, and describe modeling approaches that mix logic, probabilistic inference and latent variables. I’ll overview our recent work on probabilistic soft logic (PSL), a SRL framework for large-scale collective, probabilistic reasoning in relational domains. I’ll close by highlighting emerging opportunities (and challenges!!) in realizing the effectiveness of data and structure for knowledge discovery.
Lise Getoor is a professor in the Computer Science Department at the University of California, Santa Cruz and director of the Data, Discovery and Decisions Research Center at UC Santa Cruz. Her research areas include machine learning, data integration and reasoning under uncertainty, with an emphasis on graph and network data. She has over 250 publications and extensive experience with machine learning and probabilistic modeling methods for graph and network data. She is a Fellow of the Association for Artificial Intelligence, an elected board member of the International Machine Learning Society, serves on the board of the Computing Research Association (CRA), and was co-chair for ICML 2011. She is a recipient of an NSF Career Award and thirteen best paper and best student paper awards. She received her PhD from Stanford University in 2001, her MS from UC Berkeley, and her BS from UC Santa Barbara, and was a professor in the Computer Science Department at the University of Maryland, College Park from 2001-2013.
Hackerman Hall B-17
An exploration of the research on “Grit”, interleaved with the story of writing Practical Object-Oriented Design in Ruby, and the tale of a horrendous bike ride. This talk will convince you that you can accomplish anything.
Sandi Metz, author of Practical Object-Oriented Design in Ruby and 99 Bottles of OOP, believes in simple code and straightforward explanations. She prefers working software, practical solutions and lengthy bicycle trips (not necessarily in that order) and writes, consults, and teaches about object-oriented design
Hackerman Hall B-17
A recent New York Times article boldly stated that the Golden Age of Design is upon us. Our society is certainly in the midst of a great shift in how we view the world. In the past century, we have moved from the Age of Craft to the Industrial Age; we are currently on the cusp of the Age of Information. In the 20th century, innovations including the personal computer, the internet, smart phones, cloud computing, wearable computers and 3D and CNC printing have helped to radically change our conception of what we design. Today, designers no longer create products; they instead create platforms for open innovation.
This talk will reflect my walk through the discipline of design’s many eras and shifts, in order to understand this movement from designing products to designing platforms. The eras of user-centered design, experience design, service design, and systems design will be explored to better understand this migration. An alternative framing, product-service ecologies, will be introduced to stress a systemic and ecological view as a design approach to designing the products, services, environments, and platforms of today. A systemic view ensures that the designer can identify a need and understand the implications of designing something to impact the ecology in a positive way. A systemic view helps move the designer from problem solving to problem seeking, from modeling to understanding relationships, and from prototyping to perturbing the system to understand outcomes. It also ensures that designers are creating pragmatic and purposeful systems that will improve the state of today’s world.
Jodi Forlizzi is the Geschke Director and a Professor of Human-Computer Interaction in the School of Computer Science at Carnegie Mellon University. She is responsible for establishing design research as a legitimate form of research in HCI that is different from, but equally as important as, scientific and human science research. For the past 20 years, Jodi has advocated for design research in all forms, mentoring peers, colleagues, and students in its structure and execution, and today it is an important part of the CHI community.
Jodi’s current research interests include designing educational games that are engaging and effective, designing robots, AVs, and other technology services that use AI and ML to adapt to people’s needs, and designing for healthcare. Jodi is a member of the ACM CHI Academy and has been honored by the Walter Reed Army Medical Center for excellence in HRI design research. Jodi has consulted with Disney and General Motors to create innovative product-service systems.