Starting in 1974, Kenneth Bowles – who at the time directed UC San Diego’s Computing Center – began to adapt the computer language Pascal for use on so-called “microcomputers,” precursors of today’s PCs. His primary interest at the time was a programming language that would allow students to work individually on projects without waiting their turn to do batch processing on the mainframe. But Bowles also foresaw the value of portable software that would allow programmers to write something once and run it anywhere. His solution was pseudo-code – p-code for short – an intermediate language to run on each machine and serve as a uniform translator.
Since most of his fellow computer-science faculty members were involved in more theoretical research, Bowles turned instead to students to fulfill his dream. He recruited one graduate student, Mark Overgaard, and a handful of undergraduates. At one point or another, more than 70 students were involved in the UCSD Pascal project, doing everything from writing code to shipping floppy disks to research centers around the world (for a token $15 royalty fee). In the early 1980s, the University of California sold rights to the technology to SofTech Systems, which tried but failed to convince IBM to adopt UCSD Pascal as the core operating system of its first personal computers. (Bill Gates’ MS-DOS won the IBM contract.)
Bowles gained world renown for initiating and leading this project that culminated in UCSD Pascal influencing many aspects of computing that are now ubiquitous, including modern PCs and Macs as well as Sun Microsystem’s Java language, which incorporates p-code.
Mark Overgaard and other alumni who worked on the ground-breaking language for what would later be called the personal computer gathered in recently to mark the 30th anniversary of the computer language and reminisce about the influence and legacy that Kenneth Bowles had on computing, teaching, and their lives and careers.
Watch — UCSD Pascal: Celebrating the Life and Work of Kenneth Bowles
Our planet is experiencing worldwide growth in energy consumption and CO2 emission and is experiencing temperature rise and climate change at an accelerating rate. A new series from the Institute of Energy Efficiency at UC Santa Barbara describes a path to reducing our energy consumption and CO2 emission.
The series kicks off with John Bowers, Director of the Institute of Energy Efficiency and Professor of Electrical and Computer Engineering and Materials, discussing the evolution of photonics and what the future holds for more efficient, higher capacity data centers, which are important for machine learning and data processing.
Fiber optics has transformed our work and, indeed, our lives, by enabling the Internet through low-cost, high-capacity fiber optic transmission. In data centers, fiber optics is replacing electrical cables, thereby allowing for higher and more economical performance.
Watch — A New Focus for Energy Efficiency
Explore the immensity of the human brain, its billions of neurons and trillions of connections, and the research that is helping us understand more about this complex and amazing organ.
Lawrence Livermore National Laboratory’s popular lecture series returns with four new episodes each relating to the brain. The lectures are aimed at a middle and high school level and presented by LLNL scientists in collaboration with high school science teachers. This is a great opportunity to get a look at the cutting-edge science in a friendly and understandable way. Explore the immensity of the human brain, its billions of neurons and trillions of connections, and the research that is helping understand more about this amazing organ.
Browse more programs in Field Trip at the Lab: Science on Saturday.
We use recommender system all the time. A website will recommend something to you based on what you’ve watched, listened to, bought or who you’ve friended on Facebook. These systems attempt to predict your preferences based on past interactions.
The systems range from simple statistical approaches like Amazon’s people who bought X also bought Y links, to complex Artificial Intelligence-based approaches that drive feed ranking on sites like Facebook.
Julian McAuley, UC San Diego Computer Science and Engineering, explores the modeling techniques behind personalized recommendation technology on the web and the different systems that we encounter.
He reminds us that we often find these recommendations a bit “creepy,” but that actually the recommender system has no human intelligence; it’s really a simple statistical process. They focus on short-term predictions but could they be adapted to make long-term predictions or estimate more subjective qualities? Would that be bad?
Watch How Do Websites Personalize Recommendations for Me? – Exploring Ethics
With the vast amount of data available in digital form, the field of Artificial Intelligence (AI) is evolving rapidly.
If you’ve even been caught on a phone tree with a computer that doesn’t understand what you are saying, you’ll appreciate that scientists are trying to figure out how to teach machines to understand, to communicate and even be empathetic.
William Wang, Director of the Natural Language Processing Group at UCSB, summarizes the stunning achievements of Artificial Intelligence for the past decade and talks about the intersection of AI and language. He’s trying to build an empathetic conversational agent that can understand and generate human sentences with rich emotions.
Wang also looks at the challenges facing AI in the future and the work ahead of these researchers as they strive to keep improving AI and making it better for everyone.
William Wang is the Director of UCSB’s Natural Language Processing Group, and an Assistant Professor in the Department of Computer Science at UCSB. He received his PhD from School of Computer Science, Carnegie Mellon University. He has broad interests in Artificial Intelligence, Machine Learning, and Natural Language Processing. He is the recipient of a DARPA Young Faculty Award, an IBM Faculty Award, a Facebook Research Award, and an Adobe Research Award. He is an alumnus of Columbia University, and he also worked at Yahoo! Labs, Microsoft Research Redmond, and University of Southern California. His work and opinions appear at major tech media outlets such as Wired, VICE, Fast Company, The Next Web, and Mental Floss.
Watch Artificial Intelligence: What’s Next?