Carlini (photo: Kore Chan/Daily Cal)

AI training may leak secrets to canny thieves

A paper released on arXiv last week by a team of researchers including Prof. Dawn Song and Ph.D. student Nicholas Carlini (B.A. CS/Math '13), reveals just how vulnerable deep learning is to information leakage.  The researchers labelled the problem “unintended memorization” and explained it happens if miscreants can access to the model’s code and apply a variety of search algorithms. That's not an unrealistic scenario considering the code for many models are available online, and it means that text messages, location histories, emails or medical data can be leaked.  The team doesn't “really know why neural networks memorize these secrets right now, ” Carlini says.  “At least in part, it is a direct response to the fact that we train neural networks by repeatedly showing them the same training inputs over and over and asking them to remember these facts."   The best way to avoid all problems is to never feed secrets as training data. But if it’s unavoidable then developers will have to apply differentially private learning mechanisms, to bolster security, Carlini concluded.

How Flight Simulation Tech Can Help Turn Robots Into Surgeons

Robotics researchers from Berkeley's AUTOLab, led by IEOR and EECS professor Ken Goldberg, have built a heaving robotic platform — mimicking the motion of a breathing, heart-beating human patient — to help develop algorithms that robotic surgical assistants can use to guide their cutting.  This research is the subject of an article in Wired magazine titled "How Flight Simulation Tech Can Help Turn Robots Into Surgeons."  During surgery, when the chest heaves or blood pumps, the surgeon has to compensate for that movement.  The researchers took the data from watching the surgeon's movements and developed algorithms that could mimic his strategy for cutting along a line. This new robot, which is a kind of a Stewart platform, mimics that movement.  Stewart platforms are normally hefty pneumatic devices that power things like immersive flight simulators. But for this study, the researchers took the concept and shrunk it down to a 6-inch-wide device, opting for servo motors instead of pneumatic power. The machine costs just $250.

Retraining the brain’s vision center to take action

Neuroscience researchers, including Prof. Jose Carmena, have demonstrated the astounding flexibility of the brain by training neurons that normally process input from the eyes to develop new skills, in this case, to control a computer-generated tone.  Carmena, the senior author of a paper about the development that appeared in the journal Neuron, explains that “to gain a reward, the rats learned to produce arbitrary patterns of neural activity unrelated to visual input in order to control a BMI, highlighting the power of neuroplasticity and the flexibility of the brain.”   “These findings suggest that the striatum has a broader role in shaping cortical activity based on ongoing experience and behavioral outcomes than previously acknowledged, and have wide implications for the neuroscience of thought and action and brain-machine interfaces,” said Carmena.

RISELab's AI research wins $10M NSF award

The RISELab, led by Prof. Ion Stoica, has received an Expeditions in Computing award from the National Science Foundation (NSF), providing $10 million in funding over five years to enable game-changing advances in real-time decision making technologies.  The award is presented to research teams pursuing large-scale, far-reaching and potentially transformative research in computer and information science and engineering.   RISELab’s award will be used to develop technology for an era in which AI systems will make decisions that will play an increasingly central role in people’s lives in areas such as healthcare, transportation and business.

Richard Nixon (photo: Lotfi Zadeh)

Subjects natural, rational, and transcendental: the photos of Lotfi Zadeh

Prof. Lotfi Zadeh, who passed away in 2017, was an avid photographer who grew up in a multicultural environment, surrounded himself with a cosmopolitan crowd, and always kept his mind open to new ideas.   In the 1960s and 70s, he enjoyed capturing the people around him in a series of black and white portraits.  His burgeoning career gave him access to a number of artists, academics, and dignitaries who, along with his colleagues, friends, and family, proved a great source of inspiration for him.   Some of Zadeh's portraits can be viewed in the EECS Newsletter courtesy of Prof. David Attwood.

Security for data analytics – gaining a grip on the two-edged sword

Prof. Dawn Song and graduate student Noah Johnson are taking a new approach to enable organizations to follow tight data security and privacy policies while enabling flexible data analysis, as well as machine learning for analysts.  Working with Uber, they tested their system using a dataset of 8 million queries written by the company’s data analysts. The system is currently being integrated into Uber’s internal data analytics platform.  With help from the Signatures Innovation Fellows program, they are advancing the system to provide the same level of security and flexibility for a broad range of data analysis and machine learning, whether needed in basic and medical research or business analytics.

Small robots with smart bodies can safely bump into obstacles

Prof. Ron Fearing's team have modified a palm-size robot with a soft, roach-like exoskeleton and six legs, called the Dynamic Autonomous Sprawled Hexapod (DASH), to use the momentum of a head-on crash to tip itself upward to climb a wall.  Kaushik Jayaram (Ph.D. Robotics/Biology '14, advisor: Robert Full) discovered how cockroaches use the energy from collisions to propel themselves up and over obstacles.  “Their bodies are doing the computing, not their brains or complex sensors,” explains Jayaram. DASH can now scurry up an incline, if equipped with gecko toes – sticky pads that Full and Fearing has also investigated and adapted for robots – they may one day become as nimble as a cockroach. The work “shows that small robots can be built with simple, robust, smart bodies to safely bump into obstacles instead of using complex and expensive sensing and control systems," says Full. 

Anca Dragan and Raluca Popa

Anca Dragan and Raluca Popa win Sloan Research Fellowships

Assistant Profs. Anca Dragan and Raluca Ada Popa have been awarded 2018 Alfred P. Sloan Research Fellowships.  They are among 126 early-career scholars who represent the most promising scientific researchers working today. Their achievements and potential place them among the next generation of scientific leaders in the U.S. and Canada. Winners receive $65,000, which may be spent over a two-year term on any expense supportive of their research.  Popa and Dragan were both selected in the Compter Science category.   Popa is a co-founder of the RISELab where she is trying to develop a learning and analytics framework that can run on encrypted data.  Dragan runs the InterACT lab and is a PI for the Center for Human-Compatible AI.  Her goal is to enable robots to work with, around and in support of people, autonomously generating behavior in a way that formally accounts for their interactions with humans. “The Sloan Research Fellows represent the very best science has to offer,” said foundation president Adam Falk. “The brightest minds, tackling the hardest problems, and succeeding brilliantly – fellows are quite literally the future of 21st century science.”

Computer Vision to Protect Patients — and Budgets

Prof. Alexandre Bayen and PhD student Pulkit Agrawal developed a computer vision-based system to help memory care centers monitor patient falls and to reduce them where possible.  State regulations require an MRI of the head any time a patient suffers an unwitnessed fall, and about a fourth of all Alzheimer’s-related hospital visits are triggered by a fall. With five million Americans currently living with Alzheimer’s, the task of preventing, tracking and treating fall-related injuries has become daunting and costly, with more than a $5 billion annual cost to medicare--and the number of people with Alzheimer’s is expected to double in the next 15 years.   A system capable of detecting falls by autonomously monitoring patients and sending therapists video clips could improve the monitoring process immensely  “There are no effective drugs yet to treat Alzheimer’s,” Agarwal says. “Until we have them, we have to help patients where they are. Developing computer vision systems to detect falls and fall vulnerability seemed like a good way to improve healthcare for a growing patient population.”

Edward Lee awarded Berkeley Citation

Prof. Edward Lee is a 2018 recipient of the Berkeley Citation, which was awarded at the 2018 Berkeley Annual Research Symposium (BEARS).  The Berkeley Citation is awarded to distinguished individuals whose contributions to UC Berkeley go beyond the call of duty and whose achievements exceed the standards of excellence in their fields.  Lee, who is the Robert S. Pepper Distinguished Professor in EECS, has been on the faculty since 1986.  He was the EE division and EECS department Chair from 2005-2008, the director of the nine-university TerraSwarm Research Center, a director of the Berkeley Industrial Cyber-Physical Systems Research Center, and the director of the Berkeley Ptolemy project.  He recently published Plato and the Nerd - The Creative Partnership of Humans and Technology (MIT Press, 2017).