SystemX

In this talk I will present planning and decision-making techniques for safely and efficiently maneuvering autonomous aerospace vehicles during proximity operations, manipulation tasks, and surface locomotion. I will first address the "spacecraft motion planning problem," by discussing its unique aspects and presenting recent results on planning under uncertainty via Monte Carlo sampling. I will then turn the discussion to higher-level decision making; in particular, I will discuss an axiomatic theory of risk and how one can leverage such a theory for a principled and tractable inclusion of risk-awareness in robotic decision making, in the context of Markov decision processes and reinforcement learning. Throughout the talk, I will highlight a variety of space-robotic applications my research group is contributing to (including the Mars 2020 and Hedgehog rovers, and the Astrobee free-flying robot), as well as applications to the automotive and UAV domains.

This work is in collaboration with NASA JPL, NASA Ames, NASA Goddard, and MIT.

This talk will provide a general overview and several examples of powerful robots that can kill people – unintentionally. It will then focus on human-transporting vehicles (self-driving cars). There are numerous significant limitations that will restrict your ability to own a self-driving car. Some of these limitations will be discussed in detail. The areas of discussion will include dynamics, customer needs, failure modes, and legal concerns.

Dorsa Sadigh is an Assistant Professor in CS and EE.

Her work is focused on the design of algorithms for autonomous systems that safely and reliably interact with people.

In the race to launch a product, the concept of "brand" is often an afterthought. Truth is, building a brand is basic to product survival. Good branding communicates quality, credibility and value. It outlives product cycles and inspires customer loyalty. So, how is an effective brand crafted? Diving into a collection of case studies, this talk will explore why design is essential for thinking beyond the hardware to create a brand that fosters an emotional connection between person and product.

1. New Mysteries

• Fast Radio Bursts, FRB's – 1ms pulses, non‐recurring, which strike the earth at a rate of 5000 per day, and are of unknown orgin – more about this
• Gravitational Waves – detected by LIGO but very coarse directions; need radio or optical observations to locate and understand the orgins
• Recent Nature paper on 78 MHz dip in cosmic background ‐ needs confirmation and theoretical explanation

2. Transformational Radio Telescopes – The traditional need for large collecting area and sharp beamwidths needs to be supplemented by telescopes which can find transients from unknown directions in the sky,

• Current example, all the sky, all the time – The Caltech long wavelength array
• DSA, an array to locate and understand the orgins of FRB's
• Next generation affordable array, 2000 x 5m telescopes.

3. Advanced RF Technology for Radio Astronomy and Quantum Computing

• Ultra low noise without cryogenics – 1.4 GHz LNA with 12K noise
• Development of wireless, solar powered, radio telescopes
• LNA requirements for quantum computing – effects of self heating

Rich will provide an overview of the general status of the robotics industry and its impact in various market segments. He will also discuss his experiences in early stage robotics in Silicon Valley and review the landscape of emerging robotics companies. Finally, Rich will discuss his journey with Seismic and share insights on the company strategy and the new category of apparel called Powered Clothing.

TBA

Compute, data, and algorithms have combined to power the recent huge strides in machine intelligence. But there is still plenty of scope for improvement, and hardware is finally coming to the fore. Machine intelligence is the future of computing, so what needs to happen at a hardware level to make it faster and more energy- and cost-efficient?

This talk will outline the key considerations in how to build an efficient processor for machine intelligence both for today's state of the art networks and also to more rapidly and more flexibly support future innovations in algorithms and model structures.

Need for incorporation of security into next generation of microelectronics, improved economics of the platform-based design and advances in high level synthesis make efficient implementation of secure, complex SoCs possible. An opportunity exists to consider new approaches, tools, methodologies and IP that enable semi-automated and automatic approaches to assembly and integration that substantially improve SoC security. One path forward may be to develop a technology where secure, configurable, extensible, application-specific platforms can be used in conjunction with synthesis technology to automatically incorporate original functionality derived from an implementation-independent executable models as either hardware or software. Program concept for addressing this challenge at DARPA will be presented.

A focus on energy efficiency in the late CMOS design era, requires extra careful attention to system reliability and resilience to hardware-sourced errors. At the same time, the emergence of AI (cognitive) applications as a key growth segment is quite obvious. This talk will attempt to address the special challenges that next generation AI (or cognitive) systems pose, with a particular focus on next generation cognitive IoT architectures. We will discuss this primarily from the point of view of providing energy-efficient resilience in environments that are likely to have built-in vulnerability to errors. Such uncertainty stems not just from potentially error-prone (late CMOS) hardware designed for extreme efficiency, but also from algorithmic brittleness of the most prevalent forms of machine learning/deep learning (ML/DL) solution strategies today. In that context, we will briefly examine the promise of the Adaptive Swarm Intelligence (ASI) architectural paradigm that we have recently started investigating at IBM Research. This is a form of distributed or decentralized computing applied to the world of mobile cognitive IoT, backed by resilient support from back-end cloud (server) systems. In addition to examining the promises of inherent system architectural scalability and in-field, continuous learning that ASI offers, we will argue (albeit philosophically!) about why this could open the door to new models of self-aware systems that mimic cooperative and conscious problem solving in a human setting.

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 B03 in the basement of the Gates Computer Science 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.