EE380 Computer Systems Colloquium

TBA

The Stanford EE Computer Systems Colloquium (EE380) meets on Wednesdays 4:30-5:45 throughout the academic year. Talks are given before a live audience in Room 104 of the Shriram Building on the Stanford Campus. The live talks (and the videos hosted at Stanford and on YouTube) are open to the public.

Stanford students may enroll in EE380 to take the Colloquium as a one unit S/NC class. Enrolled students are required to keep and electronic notebook or journal and to write a short, pithy comment about each of the ten lectures and a short free form evaluation of the class in order to receive credit. Assignments are due at the end of the quarter, on the last day of examinations.

EE380 is a video class. Live attendance is encouraged but not required. We (the organizers) feel that watching the video is not a substitute for being present in the classroom. Questions are encouraged.

Many past EE380 talks are available on YouTube, see the EE380 Playlist.

TBA

The Stanford EE Computer Systems Colloquium (EE380) meets on Wednesdays 4:30-5:45 throughout the academic year. Talks are given before a live audience in Room 104 of the Shriram Building on the Stanford Campus. The live talks (and the videos hosted at Stanford and on YouTube) are open to the public.

Stanford students may enroll in EE380 to take the Colloquium as a one unit S/NC class. Enrolled students are required to keep and electronic notebook or journal and to write a short, pithy comment about each of the ten lectures and a short free form evaluation of the class in order to receive credit. Assignments are due at the end of the quarter, on the last day of examinations.

EE380 is a video class. Live attendance is encouraged but not required. We (the organizers) feel that watching the video is not a substitute for being present in the classroom. Questions are encouraged.

Many past EE380 talks are available on YouTube, see the EE380 Playlist.

TBA

The Stanford EE Computer Systems Colloquium (EE380) meets on Wednesdays 4:30-5:45 throughout the academic year. Talks are given before a live audience in Room 104 of the Shriram Building on the Stanford Campus. The live talks (and the videos hosted at Stanford and on YouTube) are open to the public.

Stanford students may enroll in EE380 to take the Colloquium as a one unit S/NC class. Enrolled students are required to keep and electronic notebook or journal and to write a short, pithy comment about each of the ten lectures and a short free form evaluation of the class in order to receive credit. Assignments are due at the end of the quarter, on the last day of examinations.

EE380 is a video class. Live attendance is encouraged but not required. We (the organizers) feel that watching the video is not a substitute for being present in the classroom. Questions are encouraged.

Many past EE380 talks are available on YouTube, see the EE380 Playlist.

TBA

The Stanford EE Computer Systems Colloquium (EE380) meets on Wednesdays 4:30-5:45 throughout the academic year. Talks are given before a live audience in Room 104 of the Shriram Building on the Stanford Campus. The live talks (and the videos hosted at Stanford and on YouTube) are open to the public.

Stanford students may enroll in EE380 to take the Colloquium as a one unit S/NC class. Enrolled students are required to keep and electronic notebook or journal and to write a short, pithy comment about each of the ten lectures and a short free form evaluation of the class in order to receive credit. Assignments are due at the end of the quarter, on the last day of examinations.

EE380 is a video class. Live attendance is encouraged but not required. We (the organizers) feel that watching the video is not a substitute for being present in the classroom. Questions are encouraged.

Many past EE380 talks are available on YouTube, see the EE380 Playlist.

Electronic Design Automation (EDA) enables the design of semiconductors comprised of tens of billions of devices. EDA consists of design software incorporating cutting-edge optimization and analysis algorithms, as well as pre-designed blocks known as "Intellectual Property" (IP). This talk reviews trends in the EDA industry in the context of the Semiconductor industry, highlighting new developments such as the rise of IP to become the largest segment in EDA, the increased use of system-level tools, and the resurgence of chip design particularly in the area of artificial intelligence. The talk ends with a brief mention of two related activities: The Stanford class "EDA and Machine Learning Hardware", in which students learn the inner workings of (some) EDA tools and how to use them effectively to design digital hardware, e.g. a convolutional neural network for image recognition implemented in an FPGA; and Silicon Catalyst, an innovative local incubator focused on accelerating solutions in Silicon.

The next stage of human-computer evolution, Scalable Intelligent Systems, integrates people, communications, and computers into a unified cooperative environment. Think of it as moving beyond Google, Facebook, Instagram, and the other social networks. Scalable Intelligent Systems can be actualized by 2025 and are likely to include the following characteristics:

• Interactively acquire and present information from video, web pages, hologlasses, online data bases, sensors, articles, human speech and gestures, etc.
• Real-time integration of massive, pervasively inconsistent information
• Close human collaboration using hologlasses for secure mobile interaction.
• Organizations of people and IoT devices (Citadels) for trustworthiness, resilience, and performance with no single point of failure
• Scalability in all important dimensions including no hard barriers to continual improvement in the above areas.

There is no computer-only solution that can implement the above by 2025. Consequently, people are fundamental to a Scalable Intelligent System.

Scalable Intelligent Systems, as envisioned, will be the most complex software that has ever been created. Every advanced country in the world has recently introduced its own development plan. The development of Scalable Intelligent Systems will create enormous social and policy challenges.

For example, Scalable Intelligent Systems can be of enormous value in Pain Management. Pain management requires much more than just prescribing opioids and other pain killers, which are often critical for short-term and less often longer-term use. Organizational aspects play an important role in pain management. Scalable Intelligent Systems can help users with appliances, entertainment, exercise, hypnosis, medication, meditation, physical therapy, and collaboration with medical helpers.

Building and deploying a Scalable Intelligent Technology stack is possible by 2025. The rewards are high but the amount of effort required is substantial. We have to get to work.

Since the rise of deep learning in 2012, much progress has been made in deep-learning-based AI tasks such as image/video understanding and natural language understanding, as well as GPU/accelerator architectures that greatly improve the training and inference speed for neural-network models. As the industry players race to develop ambitious applications such as self-driving vehicles, cashier-less supermarkets, human-level interactive robot systems, and human intelligence augmentation, major research challenges remain in computational methods as well as hardware/software infrastructures required for these applications to be effective, robust, responsive, accountable and cost-effective. Innovations in scalable iterative solvers and graph algorithms will be needed to achieve these application-level goals but will also impose much higher-level of data storage capacity, access latency, energy efficiency, and processing throughput. In this talk, I will present our recent progress in building highly performant AI task libraries, creating full AI applications, providing AI application development tools, and prototyping the Erudite system at the IBM-Illinois C3SR.

In this presentation, I would like to discuss with you how to establish a sustainable and smart society through the internet of energy for connecting at any time and any place. I suspect that you have heard the phrase, "Internet of Energy" less often. The meaning of this phrase is simple. Because of a ubiquitous energy transmission system, you do not need to worry about a shortage of electric power. One of the most important items for establishing a sustainable society is [...]

"Inaugural Linvill Distinguished Seminar on Electronic Systems Technology," EE News, July 2018

Leela is a semantic artificially intelligent agent modeled on the theories of Jean Piaget. She builds increasingly abstract semantic models of the world from her experiences of exploration, play, and experimentation. As an agent she is able to formulate, execute, and explain her own plans.

This talk will provide an introduction to Leela's background and design and will show her in action.

How do we choose and remember our secure access codes? So far biometrics, password managers, and systems like Facebook connect have not been able to guarantee the security we need. Remembering dozens of different passwords becomes a usability nightmare. 25+ years into online experience, each of us have many hard-to-remember or easy-to-guess passwords, with all the risks and frustration they imply.

We describe experiments showing how to make easy to remember codes and passwords and the system to make them, called Cue-Pin-Select. It can generate (and regenerate) passwords on the go using only the user's brain for computation. It has the advantage of creating memorable passwords, not requiring any external storage or computing device, and can be executed in less than a minute to create a new password.

This talk will summarize recent usable security work done with Ted Selker. It will start with the Cue-Pin-Select algorithm, cover an improvement we found that applies to all passphrase-based security systems, and explain some of the work currently underway to have better tools to study password schemes and human computation.