Podcasts about eecs

Arlindo Oliveira was born in Angola and lived in numerous other countries. He obtained his BSc and MSc degrees in Electrical Engineering and Computer Science (EECS) from Instituto Superior Técnico (IST) and his PhD degree, also in EECS, from the University of California at Berkeley, where he was a Fulbright fellow. He was an invited professor at MIT and a researcher at INESC, CERN, the Electronics Research Laboratory of UC Berkeley, the Berkeley Cadence Laboratories, and the University of Tokyo. He was a member of the National Council for Science Technology and Innovation and of the Advisory Board of the Science and Technology Options Assessment (STOA) Panel of the European Parliament. He is a distinguished professor of IST, president of INESC, distinguished visiting professor at Macau University of Science and Technology, member of the board of Caixa Geral de Depósitos and a researcher at INESC-ID. He authored five books and hundreds of articles in international conferences and journals in the areas of algorithms, artificial intelligence, machine learning, bioinformatics, and computer architecture. He also received several prizes and distinctionsHe has been on the boards of several companies and institutions and is a past president of Instituto Superior Técnico, of INESC-ID and of the Portuguese Association for Artificial Intelligence. He is a member of the Lisbon Academy of Sciences, of the Portuguese Academy of Engineering, of IEEE and of ACM.

"I had to make a decision because I knew that if nothing changed, I was just gonna fail out of EECS. I remember EECS actually sent me a letter where they were like, 'Hey, if your GPA continues this low, you will be kicked out next semester.'" In part one of our conversation with Alfredo Andere, we delve into his journey from Mexico to the prestigious EECS program at UC Berkeley. Alfredo shares his early fascination with technology, the challenges of adapting to a new educational system, and the pivotal moments that shaped his academic and personal growth. Raised in various cities across Mexico, Alfredo's passion for technology was sparked by reading biographies of tech leaders like Steve Jobs and Elon Musk. His entrepreneurial spirit emerged early when he organized a forum that attracted high-profile speakers, including former Mexican presidents, to his all-boys Catholic high school. Despite initial struggles with calculus at Berkeley, Alfredo's determination and commitment to his studies ultimately led to his success in the competitive EECS program.

How do we figure out whether interpretability is doing its job? One way is to see if it helps us prove things about models that we care about knowing. In this episode, I speak with Jason Gross about his agenda to benchmark interpretability in this way, and his exploration of the intersection of proofs and modern machine learning. Patreon: https://www.patreon.com/axrpodcast Ko-fi: https://ko-fi.com/axrpodcast Transcript: https://axrp.net/episode/2025/03/28/episode-40-jason-gross-compact-proofs-interpretability.html   Topics we discuss, and timestamps: 0:00:40 - Why compact proofs 0:07:25 - Compact Proofs of Model Performance via Mechanistic Interpretability 0:14:19 - What compact proofs look like 0:32:43 - Structureless noise, and why proofs 0:48:23 - What we've learned about compact proofs in general 0:59:02 - Generalizing 'symmetry' 1:11:24 - Grading mechanistic interpretability 1:43:34 - What helps compact proofs 1:51:08 - The limits of compact proofs 2:07:33 - Guaranteed safe AI, and AI for guaranteed safety 2:27:44 - Jason and Rajashree's start-up 2:34:19 - Following Jason's work   Links to Jason: Github: https://github.com/jasongross Website: https://jasongross.github.io Alignment Forum: https://www.alignmentforum.org/users/jason-gross   Links to work we discuss: Compact Proofs of Model Performance via Mechanistic Interpretability: https://arxiv.org/abs/2406.11779 Unifying and Verifying Mechanistic Interpretability: A Case Study with Group Operations: https://arxiv.org/abs/2410.07476 Modular addition without black-boxes: Compressing explanations of MLPs that compute numerical integration: https://arxiv.org/abs/2412.03773 Stage-Wise Model Diffing: https://transformer-circuits.pub/2024/model-diffing/index.html Causal Scrubbing: a method for rigorously testing interpretability hypotheses: https://www.lesswrong.com/posts/JvZhhzycHu2Yd57RN/causal-scrubbing-a-method-for-rigorously-testing Interpretability in Parameter Space: Minimizing Mechanistic Description Length with Attribution-based Parameter Decomposition (aka the Apollo paper on APD): https://arxiv.org/abs/2501.14926 Towards Guaranteed Safe AI: https://www2.eecs.berkeley.edu/Pubs/TechRpts/2024/EECS-2024-45.pdf     Episode art by Hamish Doodles: hamishdoodles.com

In this episode, we explore the intricate role of the vagus nerve as a central regulator within the microbiota-gut-brain (MGB) axis, examining its neuroanatomical structure, signaling mechanisms, and interactions with microbial metabolites and immune pathways. We discuss how vagal afferent fibers relay sensory input from the gut to the brain, including signals mediated by short-chain fatty acids (SCFAs) and gut-derived hormones, and how efferent fibers modulate gut motility, intestinal barrier integrity, and inflammation through the cholinergic anti-inflammatory pathway. Finally, we explore vagal dysfunction as well as associated conditions and symptoms, and we touch on just a few potential root causes. Topics: 1. Introduction Focus on the vagus nerve's role in the microbiota-gut-brain (MGB) axis. Bidirectional communication between the brain and microbiota. Overview of communication pathways: neural (e.g., vagus nerve), endocrine (e.g., HPA axis), immune (e.g., cytokines), and metabolic (e.g., SCFAs). 2. Overview of the Nervous System The CNS includes the brain and spinal cord - control centers for the body. The peripheral nervous system extends beyond the CNS The peripheral nervous system is divided into the somatic nervous system and the autonomic nervous system. 3. Autonomic Nervous System (ANS) and Subdivisions Sympathetic Nervous System (SNS) Parasympathetic Nervous System (PNS) Enteric Nervous System (ENS) 4. The Vagus Nerve and Role in the PNS Principal component of the parasympathetic nervous system. Governs "rest-and-digest" activities Contains both afferent (80%) and efferent (20%) fibers. 5. Vagus Nerve Anatomy Fibers originate at the base of the skull and extend into the gut wall. Fibers distributed throughout the mucosa, submucosa, and beyond. Interact indirectly with gut luminal contents via specialized gut cells, including EECs and immune cells. 6. Interaction with Intestinal Cells Enteroendocrine cells (EECs) release gut hormones in response to microbial metabolites. SCFAs, such as butyrate, activate free fatty acid receptors on EECs, stimulating vagal afferents. Immune cells within the gut wall modulate vagal signals during inflammatory responses. 7. Review of Functions Sensory input (afferent fibers): Detects gut-derived signals like microbial metabolites and mechanical stretch. Motor output (efferent fibers): Regulates gut motility, secretion, immune responses, and more. 8. Impact of a Diverse Microbiome on Vagal Activity Enhanced SCFA production boosts vagal activity. SCFAs improve gut barrier integrity, reduce systemic inflammation, and assist in regulating stress responses. 9. Examples: Intestinal Barrier Function Releases acetylcholine (ACh) to modulate inflammatory pathways. Helps enhance tight junction protein expression, preserving gut barrier integrity. Helps prevent the translocation of microbial endotoxins like LPS into systemic circulation. 10. Dysfunction of the Vagus Nerve Reduced vagal tone disrupts gut homeostasis. Conditions such as IBS, IBD, chronic fatigue syndrome, anxiety, depression, and POTS. Chronic stress, infections, and dysbiosis are common contributors. 11. Root Causes 12. Tying Back to the HPA Axis Low vagal tone is associated with increased HPA axis activity. Highlighting the interplay between the gut, brain, and stress response systems. 13. Conclusion Identifying potential root causes. Contributing lifestyle factors. "⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠75 Gut-Healing Strategies & Biohacks⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠" Follow Chloe on Instagram ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@synthesisofwellness⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow Chloe on TikTok @chloe_c_porter Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠synthesisofwellness.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ --- Support this podcast: https://podcasters.spotify.com/pod/show/chloe-porter6/support

Graph learning has gained prominent traction from the academia and industry as a solution to detect complex cyber-attack campaigns. By constructing a graph that connects various network/host entities and modeling the benign/malicious patterns, threat-hunting tasks like data provenance and entity classification can be automated. We term the systems under this theme as Graph-based Security Analytics (GSAs). In this talk, we first provide a cursory view of GSA research in the recent decade, focusing on the academic side. Then, we elaborate a few GSAs developed in our lab, which are designed for edge-level intrusion detection (Argus), subgraph-level attack reconstruction (ProGrapher) and storage reduction (SEAL). In the end of the talk, we will review the progress and pitfalls along the development of GSA research, and highlight some research opportunities. About the speaker: Zhou Li is an Assistant Professor at UC Irvine, EECS department, leading the Data-driven Security and Privacy Lab. Before joining UC Irvine, he worked as Principal Research Scientist at RSA Labs from 2014 to 2018. His research interests include Internet Security, Organizational network security, Privacy Enhancement Technologies, and Security and privacy for machine learning. He received the NSF CAREER award, Amazon Research Award, Microsoft Security AI award and IRTF Applied Networking Research Prize.

All Things TechIE Podcast, Episode 104 where Justin is joined by a special guest, Jack McCauley. Jack designed and built the Oculus DK1 and DK2 virtual reality headsets, prior to the acquisition of the company in 2014 by Facebook for $2 billion. He holds numerous U.S. patents for inventions in software, audio effects, virtual reality, motion control, computer peripherals, and video game hardware and controllers. Jack was awarded a full scholarship to attend University of California, Berkeley where he earned a BSc., EECS in Electrical Engineering and Computer Science in 1986. He currently serves as an Innovator in Residence at Jacobs Institute for Design Innovation at UC Berkeley.

Episode 132I spoke with Manuel and Lenore Blum about:* Their early influences and mentors* The Conscious Turing Machine and what theoretical computer science can tell us about consciousnessEnjoy—and let me know what you think!Manuel is a pioneer in the field of theoretical computer science and the winner of the 1995 Turing Award in recognition of his contributions to the foundations of computational complexity theory and its applications to cryptography and program checking, a mathematical approach to writing programs that check their work. He worked as a professor of computer science at the University of California, Berkeley until 2001. From 2001 to 2018, he was the Bruce Nelson Professor of Computer Science at Carnegie Mellon University.Lenore is a Distinguished Career Professor of Computer Science, Emeritus at Carnegie Mellon University and former Professor-in-Residence in EECS at UC Berkeley. She is president of the Association for Mathematical Consciousness Science and newly elected member of the American Academy of Arts and Sciences. Lenore is internationally recognized for her work in increasing the participation of girls and women in Science, Technology, Engineering, and Math (STEM) fields. She was a founder of the Association for Women in Mathematics, and founding Co-Director (with Nancy Kreinberg) of the Math/Science Network and its Expanding Your Horizons conferences for middle- and high-school girls.Find me on Twitter for updates on new episodes, and reach me at editor@thegradient.pub for feedback, ideas, guest suggestions. I spend a lot of time on this podcast—if you like my work, you can support me on Patreon :) You can also support upkeep for the full Gradient team/project through a paid subscription on Substack!Subscribe to The Gradient Podcast:  Apple Podcasts  | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterOutline:* (00:00) Intro* (03:09) Manuel's interest in consciousness* (05:55) More of the story — from memorization to derivation* (11:15) Warren McCulloch's mentorship* (14:00) McCulloch's anti-Freudianism* (15:57) More on McCulloch's influence* (27:10) On McCulloch and telling stories* (32:35) The Conscious Turing Machine (CTM)* (33:55) A last word on McCulloch* (35:20) Components of the CTM* (39:55) Advantages of the CTM model* (50:20) The problem of free will* (52:20) On pain* (1:01:10) Brainish / CTM's multimodal inner language, language and thinking* (1:13:55) The CTM's lack of a “central executive”* (1:18:10) Empiricism and a self, tournaments in the CTM* (1:26:30) Mental causation* (1:36:20) Expertise and the CTM model, role of TCS* (1:46:30) Dreams and dream experience* (1:50:15) Disentangling components of experience from multimodal language* (1:56:10) CTM Robot, meaning and symbols, embodiment and consciousness* (2:00:35) AGI, CTM and AI processors, capabilities* (2:09:30) CTM implications, potential worries* (2:17:15) Advice for younger (computer) scientists* (2:22:57) OutroLinks:* Manuel's homepage* Lenore's homepage; find Lenore on Twitter (https://x.com/blumlenore) and Linkedin (https://www.linkedin.com/in/lenore-blum-1a47224)* Articles* “The ‘Accidental Activist' Who Changed the Face of Mathematics” — Ben Brubaker's Q&A with Lenore* “How this Turing-Award-winning researcher became a legendary academic advisor” — Sheon Han's profile of Manuel* Papers (Manuel and Lenore)* AI Consciousness is Inevitable: A Theoretical Computer Science Perspective* A Theory of Consciousness from a Theoretical Computer Science Perspective: Insights from the Conscious Turing Machine* A Theoretical Computer Science Perspective on Consciousness and Artificial General Intelligence* References (McCulloch)* Embodiments of Mind* Rebel Genius Get full access to The Gradient at thegradientpub.substack.com/subscribe

Karl Sun is co-founder and chairman at Lucid Software, a leading provider of visual collaboration software. With Lucid's products—Lucidchart, Lucidspark and Lucidscale—teams can turn ideas into reality, clarify complexity, and collaborate visually, no matter where they're located. Prior to Lucid, Karl spent several years at Google, starting and leading business development at Google's China office, opening Google's patent department and setting patent strategy, and leading Google's investments in advanced wind and battery technologies. Karl holds a B.S. and M.S. in EECS from MIT, an M.S. from MIT in Technology and Policy, and a J.D. from Harvard Law School. He has been honored as a Utah Business CEO of the Year and EY Entrepreneur of the Year. Connect with Karl at https://www.linkedin.com/in/karlsun/ This week's episode is brought to you with the support of Netsuite. --- Support this podcast: https://podcasters.spotify.com/pod/show/uncharted1/support

Sramana Mitra is the founder and CEO of One Million by One Million (1Mby1M), the world's first and only global virtual incubator/accelerator. Its goal is to help a million entrepreneurs globally reach a million dollars in annual revenue, build a trillion dollars in global GDP, and create 10 million jobs.Since its founding in 2010, 1Mby1M has become a powerful platform for democratization of entrepreneurship acceleration.Sramana also developed 1Mby1M's Incubator-in-a-Box methodology for Corporate Incubation that is used by enterprises to manage internal and external innovation endeavors.In 2015, LinkedIn named Sramana one of their Top 10 Influencers alongside Bill Gates and Richard Branson.Sramana has been an entrepreneur and a strategy consultant in Silicon Valley since 1994. Her fields of experience span from hardcore technology disciplines like Artificial Intelligence, Cloud Computing and Semiconductors, to sophisticated consumer marketing industries including e-commerce, fashion and education.As an entrepreneur CEO, Sramana founded three companies: Dais (off-shore software services), Intarka (sales lead generation and qualification software using Artificial Intelligence algorithms; VC: NEA) and Uuma (online personalized store for selling clothes using Expert Systems software; VC: Redwood). Two of these were acquired, while the third received an acquisition offer from Ralph Lauren which the company did not accept.As strategy consultant, Sramana has consulted with over 80 companies, including public companies such as SAP, Cadence Design Systems, Webex, KLA-Tencor, Best Buy, MercadoLibre and Tessera among others. Her work has also included numerous startups and VCs.Sramana has a Masters degree in EECS from MIT and a Bachelors degree in Computer Science and Economics from Smith College.From 2000 to 2004, Sramana chaired the MIT Club of Northern California's entrepreneurship program in Silicon Valley.Learn more at www.1Mby1M.com

This episode continues the conversation with Jason Corso - Professor of Robotics and EECS at University of Michigan and Co-Founder/Chief Science Officer at Voxel51 - a Series A AI software company that enables machine learning and computer vision scientists to rapidly curate and experiment with their datasets in order to build higher performing machine learning systems.AI platforms have been a game changer for productivity and mapping, but it's not yet at the level of flexibility that would eliminate most of the grunt work. Eric and Jason speak on how they'd like to see AI platforms collaborate and get to a point where they not only map out your tasks, but also do a lot of the preliminary work - just like an assistant would. Generalized and personalized AI assistants are the next big step that would vastly increase the value that executives get from utilizing AI in their daily workflow. Eric speaks on how he's currently using ChatGPT to some level of success, but also mentions something we've all felt - the need for a system that compartmentalizes workflows, remembers information and draws custom next steps from previously established context.Everyone's excited for what's next for generative AI. Even though closed models are currently performing better than open-source, this situation will most likely change with time as more tools become available. Jason breaks down annotation strategies and speaks on how the idea of just taking data and training your own models might not be the most efficient way to drive innovation as an AI startup. There's a lot of work in understanding how to create good datasets, which is something that most companies are missing.Tune into the full episode to learn more about the potential of AI!HIGHLIGHTS:00:00 Utilizing Microsoft AutoGen04:04 What's next for AI assistant platforms?  09:03 The problem with ChatGPT 12:47 What's the next step in AI tool development?17:31 The problem with questionable datasetsConnect with Jason - https://www.linkedin.com/in/jason-corso/ Check out Voxel51 - https://voxel51.com/ Don't forget to subscribe to the Chaos to Clarity Podcast for more invaluable episodes to help you grow your business and stay ahead of the curve!To reach out to Eric, visit https://chaostoclarity.io/

Today's episode welcomes Jason Corso - Professor of Robotics and EECS at University of Michigan and Co-Founder/Chief Science Officer at Voxel51 - a Series A AI software company that enables machine learning and computer vision scientists to rapidly curate and experiment with their datasets in order to build higher performing machine learning systems.Jason is a builder by nature. During his academic career he started to ask himself - “can I have a bigger impact on the world?”, which led him to meet his co-founder and start Voxel 51. Both of them had a passion for machine learning and an ability to write code - which is how his transition from academia to consulting began. In the early days they received a grant which worked out well and funded them through the process of building their first service. Building a service, however, was never part of the plan. Once they realized that the limitations of the grant won't enable building a product, they sought out venture capital. This venture capital boost allowed them to build out their open-source platform which has more than 2 million downloads as of this episode. Jason speaks on the early success stories of Voxel51. One of their earliest clients took just 1% of their data and in a few hours they were able to look at the data visually, which enabled them to figure out where mistakes were made. Data quality is more important than the sophistication of the system, and Voxel51 enables their clients to find where inefficiencies live.Even with a great system - human input is still needed when it comes to quality control. Jason speaks on how humans filling in the gaps when the system is less certain is highly effective - even though it doesn't scale. Eric speaks on how experienced data scientists develop an almost 6th sense when looking at data and understanding that something is wrong and a change is in order. Check out the full episode to learn more on how to approach utilizing data! HIGHLIGHTS:03:41 Building a service-based business05:21 When do you utilize Voxel51 in the development process?09:52 Quality or quantity - what's more important for your data?15:05 The importance of human pattern recognition 18:03 New applications of AI toolsConnect with Jason - https://www.linkedin.com/in/jason-corso/ Check out Voxel51 - https://voxel51.com/ Don't forget to subscribe to the Chaos to Clarity Podcast for more invaluable episodes to help you grow your business and stay ahead of the curve!To reach out to Eric, visit https://chaostoclarity.io/

In episode 119 of The Gradient Podcast, Daniel Bashir speaks to Professor Michael Sipser.Professor Sipser is the Donner Professor of Mathematics and member of the Computer Science and Artificial Intelligence Laboratory at MIT.He received his PhD from UC Berkeley in 1980 and joined the MIT faculty that same year. He was Chairman of Applied Mathematics from 1998 to 2000 and served as Head of the Mathematics Department 2004-2014. He served as interim Dean of Science 2013-2014 and then as Dean of Science 2014-2020.He was a research staff member at IBM Research in 1980, spent the 1985-86 academic year on the faculty of the EECS department at Berkeley and at MSRI, and was a Lady Davis Fellow at Hebrew University in 1988. His research areas are in algorithms and complexity theory, specifically efficient error correcting codes, interactive proof systems, randomness, quantum computation, and establishing the inherent computational difficulty of problems. He is the author of the widely used textbook, Introduction to the Theory of Computation (Third Edition, Cengage, 2012).Have suggestions for future podcast guests (or other feedback)? Let us know here or reach Daniel at editor@thegradient.pubSubscribe to The Gradient Podcast:  Apple Podcasts  | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterOutline:* (00:00) Intro* (01:40) Professor Sipser's background* (04:35) On interesting questions* (09:00) Different kinds of research problems* (13:00) What makes certain problems difficult* (18:48) Nature of the P vs NP problem* (24:42) Identifying interesting problems* (28:50) Lower bounds on the size of sweeping automata* (29:50) Why sweeping automata + headway to P vs. NP* (36:40) Insights from sweeping automata, infinite analogues to finite automata problems* (40:45) Parity circuits* (43:20) Probabilistic restriction method* (47:20) Relativization and the polynomial time hierarchy* (55:10) P vs. NP* (57:23) The non-connection between GO's polynomial space hardness and AlphaGo* (1:00:40) On handicapping Turing Machines vs. oracle strategies* (1:04:25) The Natural Proofs Barrier and approaches to P vs. NP* (1:11:05) Debates on methods for P vs. NP* (1:15:04) On the possibility of solving P vs. NP* (1:18:20) On academia and its role* (1:27:51) OutroLinks:* Professor Sipser's homepage* Papers discussed/read* Halting space-bounded computations (1978)* Lower bounds on the size of sweeping automata (1979)* GO is Polynomial-Space Hard (1980)* A complexity theoretic approach to randomness (1983)* Parity, circuits, and the polynomial-time hierarchy (1984)* A follow-up to Furst-Saxe-Sipser* The Complexity of Finite Functions (1991) Get full access to The Gradient at thegradientpub.substack.com/subscribe

In this rebroadcast episode of the IJGC podcast, Editor-in-Chief Dr. Pedro Ramirez is joined by Drs. Jenny Mueller and Bill Zammarrelli to discuss molecular classification and risk stratification in endometrial cancer. Jenny Mueller, MD, is a gynecologic oncologist and assistant attending in the department of surgery at Memorial Sloan Kettering Cancer Center. She leads the endometrial cancer research team at MSKCC with an emphasis on prospective, translational, and collaborative efforts within and across institutions. Bill Zammarrelli, MD, currently works as a gynecologic oncology fellow at Memorial Sloan Kettering Cancer Center. He is a commissioned officer in the US Army and completed his residency at Walter Reed National Military Medical Center. His current research focuses on the genetics of endometrial cancer.    Highlights: --PORTEC-1 and GOG-99 risk classifications are discordant for stage I grade 3 endometrioid endometrial carcinoma (EEC). --Stage I grade 3 EECs of CN-high molecular subtype have a worse 3-year progression-free survival compared to non-CN-high molecular subtypes. --Molecular classification in combination with clinicopathologic factors may provide improved prognostic information.

Signs Of Life Radio is Tonight! Hosted by Bob Ginsberg. Special Guest Dr. Christopher Roe TUNE IN TONIGHT! Thursday, November 30th 8:00 PM Eastern (check your time zone) Host: Bob Ginsberg Guest: Dr. Chris Roe Tonight on Signs of Life Radio, Host Bob Ginsberg will be speaking with special guest, Dr. Chris Roe! Chris Roe is professor of psychology at the University of Northampton and director of its Centre for Psychology and Social Sciences, which includes a research group devoted to Exceptional Experience and Consciousness Studies (EECS). Roe's research interests are focused around understanding the nature of anomalous experiences, including the psychology of belief and self-deception. He has utilized experimental approaches to test psi abilities, in particular those involving psychological factors. Most recently, his focus has shifted to investigating unconscious measures of psi and correlating these with behavioral and personality measures.

Anurupa Ganguly is the founder & CEO of Prisms. She founded Prisms to scale a new world teaching model where students learn core math and science concepts spatially, physically and steeped in important real world contexts. Prisms targets bottleneck topics that are often memorized in lieu of deeply understood -- leading to huge gaps and drops offs over time in STEM. Anurupa and her team are transforming math education in the US by rapidly deploying the next generation of spatial computing devices across US K-12 districts, training teachers to integrate problem-driven learning with VR into core curriculum, and working with district leadership to rapidly improve joy, confidence and proficiencies in the modern math and science classrooms. She began her career as a math & physics teacher and later served in leadership roles across the Boston Public Schools, NYC DOE, and Success Academies. She holds degrees in EECS from MIT, and an EdM from BU. Her life's mission is to empower an equitable workforce in STEM.Recommended Resource:Experience on Demand by Jeremy Bailenson

Dr. Vivienne Sze is an associate professor in the EECS department at MIT. Vivienne is recognized for her leading work on energy-efficient computing systems spanning a wide range of domains: from video compression, to machine learning, robotics and digital health. She received the DARPA Young Faculty Award, Edgerton Faculty Award, faculty grants from Google, Facebook and Qualcomm, and a Primetime Engineering Emmy as a member of the team that developed the High-Efficiency Video Coding standard.

Jitendra Malik, Professor of EECS at UC Berkeley discusses with host Pieter Abbeel building AI from the ground-up and sensorimotor before language. Subscribe to the Robot Brains Podcast today | Visit therobotbrains.ai and follow us on YouTube at TheRobotBrainsPodcast and Twitter at @pabbeel. Hosted on Acast. See acast.com/privacy for more information.

In this episode Lauren Hawker Zafer is joined by Dr. Christopher Nguyen Who is Dr. Christopher Nguyen? Dr. Christopher Nguyen, CEO and Cofounder of Aitomatic, has an extensive career in Silicon Valley and global industries. He served as the first engineering director for Gmail at Google and led Global Industrial AI at Panasonic for four years. His current work in Industrial AI is exemplified by the "Industrial Mind," a System-2 AI solution designed for problem-solving in the industrial sector.Dr. Nguyen combines human knowledge with transparent AI, focusing on maximizing Industrial AI's potential for societal impact. He holds a BS in EECS from UC Berkeley, PhD Stanford, and co-founded the Computer Engineering department at HKUST. With his latest company, ⁠Aitomatic⁠, he's hoping to redefine how companies approach AI in the context of life-critical, industrial applications. Why this Episode?

Spotlight Thirteen is a snippet from our upcoming episode: Dr. Christopher Nguyen - Why AI Needs a Human Eye! Listen to the full episode, as soon as it comes out by subscribing to Redefining AI. Who is Dr. Christopher Nguyen? Dr. Christopher Nguyen, CEO and Cofounder of Aitomatic, has an extensive career in Silicon Valley and global industries. He served as the first engineering director for Gmail at Google and led Global Industrial AI at Panasonic for four years. His current work in Industrial AI is exemplified by the "Industrial Mind," a System-2 AI solution designed for problem-solving in the industrial sector. Dr. Nguyen combines human knowledge with transparent AI, focusing on maximizing Industrial AI's potential for societal impact. He holds a BS in EECS from UC Berkeley, PhD Stanford, and co-founded the Computer Engineering department at HKUST. With his latest company, ⁠⁠Aitomatic⁠⁠, he's hoping to redefine how companies approach AI in the context of life-critical, industrial applications. Why this Episode?

00:00 - Intro 00:24 - How did you make a decision about hosting Ukrainian civil society here, in the comittee? What was your opinion about helping Ukrainians from the start of the war? 02:58 - Do you see Ukraine as a member of the #EU? How is the EECS responding to this topic? 03:57 - Do you feel any intensifications of support of Ukrainian civil society? 04:38 - How do European Institutions help Ukrainian people in Brussels? What is the main idea of this help? 06:27 - What is the future of the resolutions in support of Ukraine that were adopted last year? Does it also involve blocked Russian assets? 07:40 - What were your expectations from your presidency? Was it distorted by what was constantly happening around? 09:16 - Has the approach of the European Committee towards citizens changed during the COVID period and what exactly has changed since then? 11:09 - Do the citizens of European Union have enough political power to put pressure on European Institutions for changing their decisions? 12:03 - Looking back at your past experience, would you like to make a difference in the past or even pursue a career other than becoming #EESC President? Is there anything you would do more if you had enough time? 14:12 - Are you traveling to meet other committee members? If not, what are the main reasons for your business trips? Are you doing this to see what the real situation is in other countries? 15:50 - What challenges did you face on your path to leadership? Were there any problems because you are a woman? 17:43 - Do you have any messages or wishes for Ukrainians? Would you like to inspire them for a future? 18:31 - What do you think about citizens involvement into making democracy package legitimate in terms of defending from foreign interference? Should the citizens being empowered for that? 21:23 - Do you plan to visit #Ukraine after the victory? 21:42 - What are your plans for the future as a member of committee?

#oculus #oculusvr #podcast #toctw #virtualreality -OCULUS VR GARAGE TO A GLOBAL PHENOMENON Jack McCauley an Innovator in Residence at Jacobs Institute for Design Innovation at UC Berkeley, a Professor at UC Berkeley, Co-Founder of Oculus, an American engineer, hardware designer, inventor, video game developer, and philanthropist. Jack is best known for designing the guitars and drums for the Guitar Hero video game series, and as a co-founder and former chief engineer at Oculus VR. At Oculus, Jack designed and built the Oculus DK1 and DK2 virtual reality headsets. Oculus was acquired by Facebook for$2 Billion. McCauley holds numerous U.S. patents for inventions in software, audio effects, virtual reality, motion control, computer peripherals, and video game hardware and controllers. Jack was awarded a full scholarship to attend the University of California, Berkeley where he earned a BSc., EECS in Electrical Engineering and Computer Science in 1986. Jack has authored numerous research papers in the field of artificial intelligence (AI) and mathematical modeling of AI-based systems and is currently pursuing new projects at his private R&D facility and hardware incubator in Livermore, California. https://jackmccauley.com/https://www.linkedin.com/in/jack-j-mccauley-9237bb5https://twitter.com/jackmccauley1 Connect & Follow us at: https://in.linkedin.com/in/eddieavil https://in.linkedin.com/company/change-transform-india https://www.facebook.com/changetransformindia/ https://twitter.com/intothechange https://www.instagram.com/changetransformindia/ Listen to the Audio Podcast at: https://anchor.fm/transform-impossible https://podcasts.apple.com/us/podcast/change-i-m-possibleid1497201007?uo=4 https://open.spotify.com/show/56IZXdzH7M0OZUIZDb5mUZ https://www.breaker.audio/change-i-m-possible https://www.google.com/podcasts?feed=aHR0cHM6Ly9hbmNob3IuZm0vcy8xMjg4YzRmMC9wb2RjYXN0L3Jzcw Dont Forget to Subscribe www.youtube.com/ctipodcast

In this week's episode Anna Rose (https://twitter.com/annarrose) and Tarun Chitra (https://twitter.com/tarunchitra) explore the topic of auctions with guests Kshitij Kulkarni (https://twitter.com/ks_kulk), PHD student at Berkeley's EECS department (https://eecs.berkeley.edu/) and Matheus V. X. Ferreira (https://twitter.com/MatheusVXF), Postdoctoral Fellow in Computer Science at Harvard John A. Paulson School of Engineering and Applied Sciences (https://www.seas.harvard.edu/). They discuss the history of auctions, both in the real world and in blockchain, and go on to cover more recent blockchain uses, such as MEV and NFT auctions. They review the incentives of both auction holders and the participants as well as how this incentive design can influence the effectiveness of the auctions themselves. Here are some additional links for this episode: Credibility and Incentives in Gradual Dutch Auctions by Kulkarni, Ferreira and Chitra (https://people.eecs.berkeley.edu/~ksk/files/GDA.pdf) Credible, Optimal Auctions via Blockchains by Kulkarni, Ferreira and Chitra (https://arxiv.org/abs/2301.12532) Optimal Strategic Mining Against Cryptographic Self-Selection in Proof-of-Stake by Kulkarni, Ferreira and Chitra (https://arxiv.org/abs/2207.07996) Credible Auctions: A Trilemma by Akbarpour and Li (https://web.stanford.edu/~mohamwad/Credible.pdf) Credible, Truthful, and Two-Round (Optimal) Auctions via Cryptographic Commitments by Ferreira and Weinberg (https://arxiv.org/abs/2004.01598) Credible, Strategyproof, Optimal, and Bounded Expected-Round Single-Item Auctions for all Distributions by Essaidi, Ferreira and Weinberg (https://arxiv.org/abs/2205.14758) Dynamic Posted-Price Mechanisms for the Blockchain Transaction Fee Market by Ferreira, Moroz, Parkes and Stern (https://arxiv.org/abs/2103.14144) Proof-of-Stake Mining Games with Perfect Randomness by Ferreira and Weinberg (https://arxiv.org/abs/2107.04069) Optimal Strategic Mining Against Cryptographic Self-Selection in Proof-of-Stake by Ferreira, Hahn, Weinberg, Yu (https://arxiv.org/abs/2207.07996) Credible Decentralized Exchange Design via Verifiable Sequencing Rules by Ferreira and Parkes (https://arxiv.org/abs/2209.15569) https://jumpcrypto.com/thepit/zkweek/ (https://jumpcrypto.com/thepit/zkweek/) Find out more about zkSummit9 here: zksummit.com (https://www.zksummit.com/). Apply for ZK Hack Lisbon here: ZK Hack application (https://xng1lsio92y.typeform.com/zkhacklisbon?typeform-source=zkhack.dev) Aleo (https://www.aleo.org/) is a new Layer-1 blockchain that achieves the programmability of Ethereum, the privacy of Zcash, and the scalability of a rollup. Interested in building private applications? Check out Aleo's programming language called Leo by visiting http://developer.aleo.org (https://developer.aleo.org/getting_started/). You can also participate in Aleo's incentivized testnet3 by downloading and running a snarkOS node. No sign-up is necessary to participate. For questions, join their Discord at aleo.org/discord (https://discord.com/invite/aleohq). If you like what we do: * Find all our links here! @ZeroKnowledge | Linktree (https://linktr.ee/zeroknowledge) * Subscribe to our podcast newsletter (https://zeroknowledge.substack.com) * Follow us on Twitter @zeroknowledgefm (https://twitter.com/zeroknowledgefm) * Join us on Telegram (https://zeroknowledge.fm/telegram) * Catch us on YouTube (https://zeroknowledge.fm/)

Sergey Levine, an assistant professor of EECS at UC Berkeley, is one of the pioneers of modern deep reinforcement learning. His research focuses on developing general-purpose algorithms for autonomous agents to learn how to solve any task. In this episode, we talk about the bottlenecks to generalization in reinforcement learning, why simulation is doomed to succeed, and how to pick good research problems.

Anything that's worth it takes time. "My children now as you say, young adults, they've had more than enough of that, with me telling to them, just be patient. For all the progress that we make, the younger generation, whether it be millennials or anything else, they want stuff today." - Rob Neil OBE (Want to read a full written for reading transcript version of this episode? Download it here.) Who is Rob Neil? Rob was born and raised in the London Borough of Brent and began his career in 1983 at Willesden County Court for the Ministry of Justice (MoJ). During his time there, he advanced to Deputy Court Manager before joining the South Eastern I.T. Team. In 1998, he acquired his dream job with MoJ's Corporate HR as a Development Trainer. During his two years of study at the Civil Service College, he earned a Certificate in Training Practice (CTP) and is now a member of CIPD. In 2001, Rob was one of the first people to join the Ministry of Justice's BAME Staff network, referred to as P.R.O.U.D. He then went on to become the first elected Chair of the CSREN (now known as the Civil Service Race Forum) that same year. The Civil Service Race Forum was established then. Rob Neil's legacy in civil service Rob developed his career in the civil service at the MoJ in HR and became a founding member of the Employee Engagement Team. He was in charge of creating the Engagement Champions Network in the year 2008. He was also responsible for the growth of the Employee Engagement Champions across the MoJ, eventually reaching 1000 people in Courts, Tribunals and Legal Aid Agency. He's worked with other Government departments to help them set up their own EECs, including HMRC, DWP, and MoD. In the summer of 2015, Rob was responsible for steering the Diversity & Inclusion Department at the Ministry of Justice. He was instrumental in achieving essential goals, such as the implementation of the Civil Service Talent Action Plan [T.A.P.] and re-negotiating arrangements with all of the Department's Diversity Staff Networks. In April of 2016 Rob was noted as one of the 50 influential figures of BAME (Black Asian Minority Ethnic) background in the public sector, as part of the 'New View 50' You can see the list here. About Krystal Alliance The Krystal Alliance™ team consists of incredibly talented and devoted members who strive to collaborate with committed entities that desire to promote equity in the workplace, encourage and motivate others. The individuals of Krystal Alliance are all specialists in their field, whether devising plans to foster transformation in culture, running interactive sessions to promote inclusive leadership, or imagining ways to build a stronger sense of community. So how did Rob come to get involved with creating this powerhouse team? You'll need to listen to find out! What are you waiting for? Click play, and immerse yourself in another fascinating conversation with another wonderful guest on the Everyday Leadership podcast.   Key leadership learning moments (timestamps)   0:00 - Intro 03:55 - The importance of offering our best 08:47 - Career in policing 16:44 - The power of working alongside others 21:28 - What's good for one... 25:53 - Letting go of the civil service 33:11 - What is 'cultural intelligence'? 37:32 - Linking with people who want to be more inclusive  42:33 - Becoming a granddad  46:55 - Rob's Definition of Leadership Rob's links: LinkedIn Krystal Alliance   Follow the podcast   If you've just stumbled across this podcast episode by chance, please do click here to follow it so you never miss a future episode. If you want to learn more about this podcast, and myself, Sope Agbelusi, you can do so using any of the below links. Connect with Me Website Instagram  LinkedIn  Twitter  Email: hello@mindsetshift.co.uk I am always keen to hear your thoughts and connect with the community of listeners. If you have any comments, feedback or thoughts, please drop me an email at https://mindsetshift.co.uk/#ask-me-anything  

Anything that's worth it takes time. "My children now as you say, young adults, they've had more than enough of that, with me telling to them, just be patient. For all the progress that we make, the younger generation, whether it be millennials or anything else, they want stuff today." - Rob Neil OBE (Want to read a full written for reading transcript version of this episode? Download it here.) Who is Rob Neil? Rob was born and raised in the London Borough of Brent and began his career in 1983 at Willesden County Court for the Ministry of Justice (MoJ). During his time there, he advanced to Deputy Court Manager before joining the South Eastern I.T. Team. In 1998, he acquired his dream job with MoJ's Corporate HR as a Development Trainer. During his two years of study at the Civil Service College, he earned a Certificate in Training Practice (CTP) and is now a member of CIPD. In 2001, Rob was one of the first people to join the Ministry of Justice's BAME Staff network, referred to as P.R.O.U.D. He then went on to become the first elected Chair of the CSREN (now known as the Civil Service Race Forum) that same year. The Civil Service Race Forum was established then. Rob Neil's legacy in civil service Rob developed his career in the civil service at the MoJ in HR and became a founding member of the Employee Engagement Team. He was in charge of creating the Engagement Champions Network in the year 2008. He was also responsible for the growth of the Employee Engagement Champions across the MoJ, eventually reaching 1000 people in Courts, Tribunals and Legal Aid Agency. He's worked with other Government departments to help them set up their own EECs, including HMRC, DWP, and MoD. In the summer of2015, Rob was responsible for steering the Diversity & Inclusion Department at the Ministry of Justice. He was instrumental in achieving essential goals, such as the implementation of the Civil Service Talent Action Plan [T.A.P.] and re-negotiating arrangements with all of the Department's Diversity Staff Networks. In April of2016 Rob was noted as one of the 50 influential figures of BAME (Black Asian Minority Ethnic) background in the public sector, as part of the 'New View 50' You can see the list here. About Krystal Alliance The Krystal Alliance team consists of incredibly talented and devoted members who strive to collaborate with committed entities that desire to promote equity in the workplace, encourage and motivate others. The individuals of Krystal Alliance are all specialists in their field, whether devising plans to foster transformation in culture, running interactive sessions to promote inclusive leadership, or imagining ways to build a stronger sense of community. So how did Rob come to get involved with creating this powerhouse team? You'll need to listen to find out! What are you waiting for? Click play, and immerse yourself in another fascinating conversation with another wonderful guest on the Everyday Leadership podcast. Key leadership learning moments (timestamps) 0:00 - Intro 03:55 - The importance of offering our best 08:47 - Career in policing 16:44 - The power of working alongside others 21:28 - What's good for one... 25:53 - Letting go of the civil service 33:11 - What is 'cultural intelligence'? 37:32 - Linking with people who want to be more inclusive 42:33 - Becoming a granddad 46:55 - Rob's Definition of Leadership Rob's links: LinkedIn Krystal Alliance Follow the podcast If you've just stumbled across this podcast episode by chance, please do click here to follow it so you never miss a future episode. If you want to learn more about this podcast, and myself, Sope Agbelusi, you can do so using any of the below links. Connect with Me Website Instagram LinkedIn Twitter Email: hello@mindsetshift.co.uk I am always keen to hear your thoughts and connect with the community of listeners. If you have any comments, feedback or thoughts, please drop me an email at https://mindsetshift.co.uk/#ask-me-anything

Anything that's worth it takes time. "My children now as you say, young adults, they've had more than enough of that, with me telling to them, just be patient. For all the progress that we make, the younger generation, whether it be millennials or anything else, they want stuff today." - Rob Neil OBE (Want to read a full written for reading transcript version of this episode? Download it here.) Who is Rob Neil? Rob was born and raised in the London Borough of Brent and began his career in 1983 at Willesden County Court for the Ministry of Justice (MoJ). During his time there, he advanced to Deputy Court Manager before joining the South Eastern I.T. Team. In 1998, he acquired his dream job with MoJ's Corporate HR as a Development Trainer. During his two years of study at the Civil Service College, he earned a Certificate in Training Practice (CTP) and is now a member of CIPD. In 2001, Rob was one of the first people to join the Ministry of Justice's BAME Staff network, referred to as P.R.O.U.D. He then went on to become the first elected Chair of the CSREN (now known as the Civil Service Race Forum) that same year. The Civil Service Race Forum was established then. Rob Neil's legacy in civil service Rob developed his career in the civil service at the MoJ in HR and became a founding member of the Employee Engagement Team. He was in charge of creating the Engagement Champions Network in the year 2008. He was also responsible for the growth of the Employee Engagement Champions across the MoJ, eventually reaching 1000 people in Courts, Tribunals and Legal Aid Agency. He's worked with other Government departments to help them set up their own EECs, including HMRC, DWP, and MoD. In the summer of 2015, Rob was responsible for steering the Diversity & Inclusion Department at the Ministry of Justice. He was instrumental in achieving essential goals, such as the implementation of the Civil Service Talent Action Plan [T.A.P.] and re-negotiating arrangements with all of the Department's Diversity Staff Networks. In April of 2016 Rob was noted as one of the 50 influential figures of BAME (Black Asian Minority Ethnic) background in the public sector, as part of the 'New View 50' You can see the list here. About Krystal Alliance The Krystal Alliance™ team consists of incredibly talented and devoted members who strive to collaborate with committed entities that desire to promote equity in the workplace, encourage and motivate others. The individuals of Krystal Alliance are all specialists in their field, whether devising plans to foster transformation in culture, running interactive sessions to promote inclusive leadership, or imagining ways to build a stronger sense of community. So how did Rob come to get involved with creating this powerhouse team? You'll need to listen to find out! What are you waiting for? Click play, and immerse yourself in another fascinating conversation with another wonderful guest on the Everyday Leadership podcast.   Key leadership learning moments (timestamps)   0:00 - Intro 03:55 - The importance of offering our best 08:47 - Career in policing 16:44 - The power of working alongside others 21:28 - What's good for one... 25:53 - Letting go of the civil service 33:11 - What is 'cultural intelligence'? 37:32 - Linking with people who want to be more inclusive  42:33 - Becoming a granddad  46:55 - Rob's Definition of Leadership Rob's links: LinkedIn Krystal Alliance   Follow the podcast   If you've just stumbled across this podcast episode by chance, please do click here to follow it so you never miss a future episode. If you want to learn more about this podcast, and myself, Sope Agbelusi, you can do so using any of the below links. Connect with Me Website Instagram  LinkedIn  Twitter  Email: hello@mindsetshift.co.uk I am always keen to hear your thoughts and connect with the community of listeners. If you have any comments, feedback or thoughts, please drop me an email at https://mindsetshift.co.uk/#ask-me-anything  

Counselling Psychologist & Systemic & Family Practitioner Paula St Ange and Trainee Clinical Psychologist Cassia Keziah Maximen join me in this episode to discuss Emotional Emancipation Circles. Aka as EECs are evidence-informed, psychologically sound, culturally grounded, and community-defined self-help support groups designed to help heal, and end, the trauma caused by the root cause of anti-Black racism. These two women have been group participants and are now trained as EEC group facilitators.  They share how and why these groups were started, the concept is an import from the US which has been adapted to the UK context.  In the early evaluations, EEC participants reported notable improvements in their mental health. Facilitators have been trained in nearly 50 states in the US, Cuba, South Africa and of course the UK. For more information about EECs contact: Malcom_phillip@outlook.com My email is: adosylv@gmail.com Join our Facebook community at: Social Workers MatterSee omnystudio.com/listener for privacy information.

In this episode of the IJGC podcast, Editor-in-Chief Dr. Pedro Ramirez is joined by Drs. Jenny Mueller and Bill Zammarrelli to discuss molecular classification and risk stratification in endometrial cancer. Jenny Mueller, MD, is a gynecologic oncologist and assistant attending in the department of surgery at Memorial Sloan Kettering Cancer Center. She leads the endometrial cancer research team at MSKCC with an emphasis on prospective, translational, and collaborative efforts within and across institutions. Bill Zammarrelli, MD, currently works as a gynecologic oncology fellow at Memorial Sloan Kettering Cancer Center. He is a commissioned officer in the US Army and completed his residency at Walter Reed National Military Medical Center. His current research focuses on the genetics of endometrial cancer. Highlights: - PORTEC-1 and GOG-99 risk classifications are discordant for stage I grade 3 endometrioid endometrial carcinoma (EEC). - Stage I grade 3 EECs of CN-high molecular subtype have a worse 3-year progression-free survival compared to non-CN-high molecular subtypes. - Molecular classification in combination with clinicopathologic factors may provide improved prognostic information.

Tim Barat, CEO & Co-Founder, Gridware, an ex-power pole field worker, named in Forbes' 30 under 30 innovator list for developing a 24/7 monitoring system increasing visibility along power distribution lines - after getting his EECS degree at UC Berkeley.

As we discussed back in Episode 41, business partnerships can be a difficult path to navigate. They are notorious for being massive accelerants to success - or a quick path to failure. Today, we are ecstatic to host Dave Farrow on the podcast. After 23 years in software development and leadership roles, Dave moved into security. Over the past ten years he has founded and run security programs at Barracuda Networks and Veza where he was responsible for GRC, product and corporate security, and incident response. Dave currently serves as VP, CISO at Red Canary. He holds a BS, EECS from UC Berkeley. Dave got started in real estate investing a few years ago through the more unconventional route - private money lending. After getting his feet wet with lending on projects to local, reputable investors, this year he decided he wanted to make the leap on taking a more active role in real estate investing. Throughout the episode, Dave and Scott talk about their most recent flip - breaking down the numbers, their partnership structure, and much more.

Welcome back to Season 2, Episode 181 of the Asian Hustle Network Podcast! We are very excited to have James Vuong on this week's show. We interview Asian entrepreneurs around the world to amplify their voices and empower Asians to pursue their dreams and goals. We believe that each person has a message and a unique story from their entrepreneurial journey that they can share with all of us. Check us out on Anchor, iTunes, Stitcher, Google Play Music, TuneIn, Spotify, and more. If you enjoyed this episode, please subscribe and leave us a positive 5-star review. This is our opportunity to use the voices of the Asian community and share these incredible stories with the world. We release a new episode every Wednesday and Saturday, so stay tuned! James is a serial tech entrepreneur, angel investor, and former VC. He has broad experience ranging from engineering to building products, from investing to founding startups, and from Silicon Valley to SE Asia. James is currently the founder and CEO of Infina.vn, the leading investment and wealth management app in Vietnam, backed by Sequoia, Y Combinator, and many reputable global VCs. Prior to Infina, James was CEO of Lana group, a digital media startup acquired by LINE Corp, the listed Japanese chat app. Prior to that, James was a VC at IDG Ventures, Vietnam's first VC fund with $100M USD. James was a Kauffman Fellow (the first in SE Asia) selected by the Kauffman Foundation in the US in 2008. Prior to coming back to Asia, James held positions as product director and tech lead (in chip logic design) in different companies in Silicon Valley. He received his MBA from Berkeley Haas School of Business in 2006 and BS in EECS at UC Berkeley in 1997. --- Support this podcast: https://anchor.fm/asianhustlenetwork/support

Show Notes(01:35) Ville recalled his education getting degrees in Computer Science from the University of Helsinki in Finland.(04:35) Ville walked over his time working at a startup called Gurusoft that planned to commercialize self-organizing maps, a peculiar artificial neural network.(07:17) Ville reflected on his four years as a researcher at Nokia — working on big data infrastructure, analytics, and ML open-source projects (such as Disco and Ringo).(11:56) Ville shared the story of co-founding a startup that built a novel scriptable data platform called Bitdeli with his brother and not finding a product-market fit.(13:58) Ville walked through AdRoll's acquisition of Bitdeli in June 2013.(15:49) Ville discussed the engineering challenges associated with his work at AdRoll — AdRoll Prospecting and traildb.io.(19:33) Ville mentioned the product and leadership/management lessons during his time being AdRoll's Head of Data and leading various data/ML efforts.(24:43) Ville rationalized his decision to join the ML Infrastructure team at Netflix in 2017.(27:26) Ville discussed the motivation behind the creation of Netflix's human-centric ML infrastructure, Metaflow, later open-sourced in 2019.(30:21) Ville unpacked the key design principles that summarize the philosophy of Metaflow, which is influenced by the unique culture at Netflix.(35:00) Ville talked about his well-known diagram on the data infrastructure's hierarchy of needs.(37:33) Ville examined the technical details behind Metaflow's integration with AWS to make it easy for users to move back and forth between their local and remote modes of development and execution.(40:58) Ville expressed the challenges of finding Metaflow's early adopters internally at Netflix and externally later on at other companies.(45:13) Ville went over the strategy around prioritizing features for Metaflow's future roadmap.(52:22) Ville shared the story behind the founding of Outerbounds, which he co-founded with Savin Goyal and Oleg Avdeev.(55:03) Ville provided his thoughts behind Metaflow's contributors in a way that can generate valuable product feedback for Outerbounds.(58:30) Ville shared valuable hiring lessons to attract the right people who are excited about Outerbounds' mission.(01:01:28) Ville shared upcoming initiatives that he is most excited about for Outerbounds.(01:04:05) Ville walked through his writing process for an upcoming technical book with Manning called “Effective Data Science Infrastructure,” a hands-on guide to assembling infrastructure for data science and machine learning applications.(01:06:34) Ville unpacked his great O'Reilly article that digs deep into the fundamentals of ML as an engineering discipline.(01:11:03) Closing segment.Ville's Contact InfoLinkedInTwitterGitHubOuterboundsWebsite | Twitter | LinkedIn | GitHub | YouTubeMetaflow GitHub | Metaflow DocsSlack CommunityCareersMetaflow Resources for Data ScienceMetaflow Resources for EngineeringMentioned ContentTalksSF Data Mining Meetup: TrailDB — Processing Trillions of Events at AdRoll (July 2016)QConSF 2018: Human-Centric Machine Learning Infrastructure @Netflix (Feb 2019)AWS re:Invent 2019: More Data Science with Less Engineering — ML Infrastructure at Netflix (Dec 2019)Scale By The Bay 2019: Human-Centric ML Infrastructure at Netflix (Jan 2020)AICamp: Metaflow — The ML Infrastructure at Netflix (Aug 2021)ArticlesOpen-Sourcing Metaflow, a Human-Centric Framework for Data Science (Netflix Tech Blog, Dec 2019)Unbundling Data Science Workflows with Metaflow and AWS Step Functions (Netflix Tech Blog, July 2020)MLOps and DevOps: Why Data Makes It Different (O'Reilly, Oct 2021)PeopleMichael Jordan (Distinguished Professor in EECS and Statistics at UC Berkeley)Matthew Honnibal and Ines Montani (Creators of open-source NLP library spaCy)Hadley Wickham (Chief Scientist at RStudio and Adjunct Professor of Statistics at Rice University)Book“The Mom Test” (by Rob Fitzpatrick)NotesMy conversation with Ville was recorded back in October 2021. Since then, many things have happened at Outerbounds. I'd recommend:Visiting Outerbounds' new website with Metaflow resources for Data Science and EngineeringWatching Ville's recent talk at Data Council Austin about the Modern Stack for ML InfrastructureBuying Ville's newly released book “Effective Data Science Infrastructure”About the showDatacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.Datacast is produced and edited by James Le. Get in touch with feedback or guest suggestions by emailing khanhle.1013@gmail.com.Subscribe by searching for Datacast wherever you get podcasts or click one of the links below:Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you're new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

This is an Instagram Live on Sat March 12, 2022 1:30pm EDT (in English) of Professor Mohammad Hajiaghayi with Professor Ming Lin of UMD. We talk about life, US vs Taiwan education, pros and cons of being department chair, hiring process, robotics, Virtual Reality, Virtual Try-On, startup, autonomous driving, and many more. Join future lives if you can at @mhajiaghayi and subscribe at YouTube channel @hajiaghayi.#robotics#autonomousdriving#VirtualReality#VirtualTryOn#startup#Taiwanv.s.US#cs#departmentchair#instagramBio of Prof. Ming C. Lin: She received her B.S., M.S., Ph.D. in EECS from University of California, Berkeley. She is a Distinguished University Professor, Barry Mersky and Capital One Endowed Professor, and former Elizabeth Stevinson Iribe Chair of Computer Science at University of Maryland at College Park, as well as John & Louise Parker Distinguished Professor Emerita at University of North Carolina at Chapel Hill. She is also an Amazon Scholar. She has received several honors and awards, including NSF Young Faculty Career Award, UNC Hettleman Award for Scholarly Achievements, Beverly W. Long Distinguished Term Professor, IEEE VGTC VR Technical Achievement Award, Washington Academy of Sciences Distinguished Career Award and several best paper awards. She is a Fellow of ACM, IEEE, Eurographics, and SIGGRAPH Academy. She is an elected Fellow by the National Academy of Inventors (NAI).

Welcome to the Counter Narrative Podcast, a show designed to change the way we talk, and think, about education. By sharing stories of successes and triumphs, we aim to challenge the dominant narrative that often negatively portrays our disenfranchised populations. I'm your host, Charles Williams. An urban educator for more than 15 years, a current school principal in Chicago, an educational consultant, an equity advocate, and the co-host of Inside The Principal's Office. -- In this episode, I chat with Anurupa Ganguly, the Founder & CEO of Prisms, a VR learning platform that teaches foundational secondary math and science concepts spatially and intuitively, before building up to symbolic notation. She began her career as a math & physics teacher and later served in leadership roles across the Boston Public Schools, NYC DOE, and Success Academies. She holds a BS and MEng in EECS from MIT, and an EdM from BU. During our conversation, Anurupa explained her journey through education and how that inspired her to start a company that allows students to digitally immerse themselves into mathematical concepts through VR. Imagine how impactful and powerful it would be to shift from learning exponential rate of change on worksheets to being involved in a pandemic simulator calculating the spread of an unknown disease. Anurupa also pushed back on the idea that the limited access we often associate with such products is due to budgets and funding (consider the mass amounts of funding schools have received during the past two years) and other excuses that do little more than maintain the gaps that we see in opportunities. This is a powerful conversation that I wish I could have released immediately after recording it so be sure to check out Prisms and see how you can bring this innovative technology to your own space. -- Prisms Website Prisms Twitter Anurupa Twitter Prisms LinkedIn Anurupa LinkedIn -- I want to thank you for listening to The Counter Narrative Podcast. If you like what you are hearing, please be sure to like, subscribe, and of course share it with friends and family. I'd also love to hear your thoughts about the show so please leave a comment or two as well. I'm not sure what platform you're using but the show can be found on Anchor, Google Podcasts, Apple Podcasts, Spotify, and plenty of other platforms. If the show isn't on your preferred site, let me know and I'll be sure to get it up and running. This podcast is also featured on SchoolRubric.com, where you can find educational articles, videos, and interviews with educators from around the globe. Be sure to connect with me and other listeners by following the show on Twitter at @theCNpodcast and joining the show's Facebook Group. --- Support this podcast: https://anchor.fm/thecounternarrative/support

Karl Sun is co-founder and CEO at Lucid Software, a leading provider of visual collaboration software. With Lucid's products—Lucidchart, Lucidspark and Lucidscale—teams can turn ideas into reality, clarify complexity, and collaborate visually, no matter where they're located. Prior to Lucid, Karl spent several years at Google, starting and leading business development at Google's China office, opening Google's patent department and setting patent strategy, and leading Google's investments in advanced wind and battery technologies. Karl holds a B.S. and M.S. in EECS from MIT, an M.S. from MIT in Technology and Policy, and a J.D. from Harvard Law School. He has been honored as a Utah Business CEO of the Year and EY Entrepreneur of the Year. Connect with Karl at https://www.linkedin.com/in/karlsun/ This week's episode is brought to you with the support of Indeed. Grab your special offer at indeed.com/scale --- Support this podcast: https://anchor.fm/uncharted1/support

In Episode One of Season Two, Host Pieter Abbeel is joined by guest (and close collaborator) Sergey Levine, professor at UC Berkeley, EECS. Sergey discusses the early years of his career, how Andrew Ng influenced him to become interested in machine learning, his current projects, and his lab's recent accomplishments.The conversation concludes with Sergey's view on the dangers of machines not being intelligent enough and his advice for students seeking a career in robotic.| SUBSCRIBE TO THE ROBOT BRAINS PODCAST TODAY | Visit therobotbrains.ai and follow us on YouTube TheRobotBrainsPodcast, Twitter @therobotbrains, and Instagram @therobotbrains. | Host: Pieter Abbeel | Executive Producers: Alice Patel & Henry Tobias Jones | Audio Production: Kieron Matthew Banerji | Title Music: Alejandro Del Pozo See acast.com/privacy for privacy and opt-out information.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Jeff Hawkins on neuromorphic AGI within 20 years, published by Steven Byrnes on the LessWrong. I just listened to AI podcast: Jeff Hawkins on the Thousand Brain Theory of Intelligence, and read some of the related papers. Jeff Hawkins is a theoretical neuroscientist; you may have heard of his 2004 book On Intelligence. Earlier, he had an illustrious career in EECS, including inventing the Palm Pilot. He now runs the company Numenta, which is dedicated to understanding how the human brain works (especially the neocortex), and using that knowledge to develop bio-inspired AI algorithms. In no particular order, here are some highlights and commentary from the podcast and associated papers. Every part of the neocortex is running the same algorithm The neocortex is the outermost and most evolutionarily-recent layer of the mammalian brain. In humans, it is about the size and shape of a dinner napkin (maybe 1500cm²×3mm), and constitutes 75% of the entire brain. Jeff wants us to think of it like 150,000 side-by-side "cortical columns", each of which is a little 1mm²×3mm tube, although I don't think we're supposed to the "column" thing too literally (there's no sharp demarcation between neighboring columns). When you look at a diagram of the brain, the neocortex has loads of different parts that do different things—motor, sensory, visual, language, cognition, planning, and more. But Jeff says that all 150,000 of these cortical columns are virtually identical! Not only do they each have the same types of neurons, but they're laid out into the same configuration and wiring and larger-scale structures. In other words, there seems to be "general-purpose neocortical tissue", and if you dump visual information into it, it does visual processing, and if you connect it to motor control pathways, it does motor control, etc. He said that this theory originated with Vernon Mountcastle in the 1970s, and is now widely (but not universally) accepted in neuroscience. The theory is supported both by examining different parts of the brain under the microscope, and also by experiments, e.g. the fact that congenitally blind people can use their visual cortex for non-visual things, and conversely he mentioned in passing some old experiment where a scientist attached the optic nerve of a lemur to a different part of the cortex and it was able to see (or something like that). Anyway, if you accept that premise, then there is one type of computation that the neocortex does, and if we can figure it out, we'll understand everything from how the brain does visual processing to how Einstein's brain invented General Relativity. To me, cortical uniformity seems slightly at odds with the wide variety of instincts we have, like intuitive physics, intuitive biology, language, and so on. Are those not implemented in the neocortex? Are they implemented as connections between (rather than within) cortical columns? Or what? This didn't come up in the podcast. (ETA: I tried to answer this question in my later post, Human instincts, Symbol grounding, and the blank-slate neocortex.) (See also previous LW discussion at: The brain as a universal learning machine, 2015) Grid cells and displacement cells Background: Grid cells for maps in the hippocampus Grid cells, discovered in 2005, help animals build mental maps of physical spaces. (Grid cells are just one piece of a complicated machinery, along with "place cells" and other things, more on which shortly.) Grid cells are not traditionally associated with the neocortex, but rather the entorhinal cortex and hippocampus. But Jeff says that there's some experimental evidence that they're also in the neocortex, and proposes that this is very important. What are grid cells? Numenta has an educational video here. Here's my oversimplified 1D toy example (the modules can als...

Today on Power Lunch Live we talk about collaboration at work and what that means in 2022 and beyond. I have Karl Sun is co-founder and CEO at Lucid Software, a leading provider of visual collaboration software. With Lucid's products—Lucidchart, Lucidspark and Lucidscale—teams can turn ideas into reality, clarify complexity, and collaborate visually, no matter where they're located. Prior to Lucid, Karl spent several years at Google, starting and leading business development at Google's China office, opening Google's patent department and setting patent strategy, and leading Google's investments in advanced wind and battery technologies. Karl holds a B.S. and M.S. in EECS from MIT, an M.S. from MIT in Technology and Policy, and a J.D. from Harvard Law School. He has been honored as a Utah Business CEO of the Year and EY Entrepreneur of the Year. #Lucid #collaboration #futureofwork #powerlunchlive #LinkedInLive www.powerlunch.live

Episode 13: Interview with Jelani Nelson, Professor of EECS at UC Berkeley. Grew up in US Virgin Islands, where an overwhelming majority of population is Black and the educational ethos is very different from the mainland US 50 states. He also created two successful international CS programs for high schoolers: AddisCoder and USVICoder,  in Ethiopia and US Virgin Islands. MIT PhD 2011.  

Enola G. Aird is an activist mother. A former corporate lawyer. She was born in the Republic of Panama, of Caribbean heritage, and attributes much of her vision and passion for the movement for emotional emancipation to stories passed down in her family about her great-grandfather, Samuel Alleyne, a loyal follower of Marcus Garvey. Enola shares the framework of the Emotional Emancipation Circles (EE Circles, EECs) are evidence-informed, psychologically sound, culturally grounded, and community-defined self-help support groups designed to help heal, and end, the trauma caused by the root cause of anti-Black racism: the centuries-old lie of White superiority and Black inferiority. Emotional Emancipation Circles – Community Healing Network Interruptions: Disrupting The Silence | Facebook Interruption Disrupt Silence - YouTube 

The team sits down with  Douglas Mughan - the NSF office head for the convergence accelerator, Chris Sanford -  a program director with the accelerator, and Clea Harrelson -  2021 Knauss Marine policy fellow, to talk about what the National Science Foundation is hoping to achieve with this new program. We also speak with Fadel Adib - Doherty Chair of Ocean Utilization and Associate Professor at the MIT Media Lab and EECS and Seth Zippel - an assistant scientist at the Woods Hole Oceanographic Institution who generated the idea. Letters of intent are due May 5th for this huge opportunity, learn more here.

In this episode, I converse with Bharath Ramsundar, the creator of The DeepChem Project. Bharath received a BA and BS from UC Berkeley in EECS and Mathematics and was valedictorian of his graduating class in mathematics. He went on to finish a PhD in computer science at Stanford University where he studied the application of deep-learning to problems in drug-discovery, and was sponsored by the very prestigious Hertz Fellowship and advised by Prof. Vijay Pande. After his PhD, Bharath co-founded Computable, a startup that built better tools for collaborative dataset management. At Stanford Bharath created The DeepChem Project that seeks to create high quality, open source tools for drug discovery, materials science, quantum chemistry, and biology. We indulge in a fantastic conversation on his early fascination with quantum computing and artificial intelligence that inspired him to embark on his incredible journey in science; starting grad school as the deep learning revolution took off; how both academia and English monarchy are in need of urgent reforms; prescient insights on global manufacturing, geopolitics, and immigration; the revolutionary aspects of technologies like artificial intelligence, quantum computing, and the need to mitigate bias in these systems; and many more things!!

Episode summary introduction: Professor Dutt believes exciting research comes from a combination of serendipity, bright students and good, collaborative relationships. There is more. Professor Nikil Dutt is the Chancellor's Professor of Computer Science, EECS and Cognitive Science at the University of California Irvine. In particular, we discuss the following with him: Pursuing Graduate Programs in the US Joining the Academia The Pursuit of Research UG Students at UC Irvine Advice for Applicants Topics discussed in this episode: Introducing Prof Nikil Dutt, UCI [1:08] Professional Journey so far [3:11] Grad Study at Penn State and UI Urbana-Champaign [6:59] Penn State versus UI Urbana-Champaign [9:14] Research thru Serendipity [11:28] On Choosing Academia [13:24] UC Irvine: Rising thru the Ranks [15:46] On Staying Excited about Research [18:24] UG Students at Irvine [21:32] Research to be Proud of [23:32] Computation Self Awareness Systems [25:25] Tips for Aspiring Students [27:51] UG Students and Research [31:00] Advice for Budding Researchers [34:27] Close: Follow your passion [37:04] Our Guest: Professor Nikil Dutt is the Chancellor's Professor at University of California Irvine with appointments in Computer Science, EECS and Cognitive Science Departments. Professor Dutt is a graduate of Birla Institute of Technology Pilani with a degree in Mechanical Engineering. He then received his MS in Computer Science from Penn State University and a PhD in Computer Science from the University of Illinois at Urbana-Champaign. Memorable Quote: Prof Dutt: “Academia is not for the faint of heart”. Episode Transcript: Please visit Episode's Transcript. Calls-to-action: To Ask the Guest a question, or to comment on this episode, email podcast@almamatters.io. Subscribe or Follow our podcasts at any of these locations:, Apple Podcasts, Google Podcasts, Spotify, RadioPublic, Breaker, Anchor. For Transcripts of all our podcasts, visit almamatters.io/podcasts.

You can find John on Twitter at [twitter.com/jgrahamc](https://twitter.com/jgrahamc).- Babbage overview and the Difference Engine:    https://www.computerhistory.org/babbage/overview/- Difference Engine No. 2 at the London Science Museum:    https://collection.sciencemuseumgroup.org.uk/objects/co526657/difference-engine-no-2-designed-by-charles-babbage-built-by-science-museum-difference-engine- BBC Micro: https://en.wikipedia.org/wiki/BBC_Micro- Sinclair ZX81: https://en.wikipedia.org/wiki/ZX81- BBC Micro Advanced User Guide:    http://stardot.org.uk/mirrors/www.bbcdocs.com/filebase/essentials/BBC%20Microcomputer%20Advanced%20User%20Guide.pdf- Sharp MZ-80K: https://en.wikipedia.org/wiki/Sharp_MZ- John's TED Talk, The greatest machine that never was: https://www.ted.com/talks/john_graham_cumming_the_greatest_machine_that_never_was- Hilbert's Problems: https://mathworld.wolfram.com/HilbertsProblems.html- Gödel's incompleteness theorems: https://plato.stanford.edu/entries/goedel-incompleteness/- The Lovelace–De Morgan mathematical correspondence - A critical re-appraisal: https://www.sciencedirect.com/science/article/pii/S0315086017300319- The mathematical correspondence of Ada Lovelace and Augustus De Morgan:    https://dl.acm.org/doi/10.1145/2867731.2867738- Douglas Engelbart: https://www.britannica.com/biography/Douglas-Engelbart- "Mother of all demos": https://www.youtube.com/watch?v=yJDv-zdhzMY- John's OSCON talk "Turing's Curse": https://www.youtube.com/watch?v=hVZxkFAIziA- Design of the RISC-V Instruction Set Architecture:    https://people.eecs.berkeley.edu/~krste/papers/EECS-2016-1.pdf- Engines of Creation - The Coming Era of Nanotechnology: https://www.amazon.com/Engines-Creation-Nanotechnology-Scientific-Revolution/dp/1872180469/ref=tmm_hrd_swatch_0?_encoding=UTF8&qid=&sr=

Mehdi Maghsoodnia is the CEO of 1health, the leading testing as a service (TaaS) company. He is passionate about personalized healthcare and increasing access to testing in the U.S.  1health launched TaaS earlier this year by bringing to market the first FDA Emergency Use Authorized COVID-19 saliva test, in partnership with IBX (Previously RUCDR). Through these at-home saliva tests, 1health is responsible for the deployment of 1% of COVID-19 testing across the United States.  Instead of asking people to go get tested in laboratories that are often crowded and have delayed results, Mehdi is driving his businesses to bring affordable, simple testing to the people, wherever they are. 1health partners with hospital systems, telehealth companies, corporations and government agencies, school systems, consumer brands, as well as public health departments around the country. Through its lab network, centralized platform, and health partnerships, now more than seven million Americans have access to the 1health COVID-19 saliva test.  Mehdi is on the board of SpineZone and MedCorder, and previously served as CEO of Rafter, BookRenter.com, SVP of products at CafePress, COO at Actiance and SVP at Intellisync. He is also an industry fellow at UC Berkeley, where he teaches innovation and entrepreneurship. He holds a Master’s of Science in EECS from Stanford, and a Bachelor of Science from UC Berkeley. Some of the Topics Covered by Mehdi Maghsoodnia in this Episode What 1health is doing and how it got started Why Mehdi chose to work on this particular problem and get involved in the healthcare industry What the initial product at 1health consisted of How Mehdi funding 1health Mehdi's thoughts around building a team Acquiring customers for 1health and how Mehdi looks at testing different channels How Mehdi thinks about pricing and GTM strategy The competitive landscape 1health is operating in Educating the market when you're creating a whole new market The ideal customer for 1health today Mehdi's experience investing in companies and some of the things he's looking for in companies he invests in How Vitagene came about from 1health What Mehdi's schedule looks like today Learning to say no and how to delegate The magic of exercise to improve your thinking Sign up for The Weekly Grind, for actionable insights and stories from successful entrepreneurs delivered to your inbox once per week: https://www.justgogrind.com/newsletter/ Listen to all episodes of the Just Go Grind Podcast: https://www.justgogrind.com/podcast/ Follow Justin Gordon on Twitter: https://twitter.com/justingordon212 Follow Justin Gordon on Instagram: https://www.instagram.com/justingordon8/

Jitendra Malik is the Arthur J. Chick Professor of EECS at University of California at Berkeley and a Research Scientist at Facebook AI Research (FAIR). Find out more about him on his homepage. Humans of AI: Stories, Not Stats is an interview series with AI researchers to get to know them better as people. We don't talk about AI or their work or the stats of their life like what college they went to. They share what they think about, what they are insecure about, what they get excited about. They share the stories of their day-to-day life. Videos of these interviews are available at humanstories.ai. The host is Devi Parikh, an Associate Professor in the School of Interactive Computing at Georgia Tech and a Research Scientist at Facebook AI Research (FAIR). Find out more about her at her homepage or follow her on Twitter. This interview was recorded on September 22, 2020. --- Send in a voice message: https://anchor.fm/humanstoriesai/message

Sramana Mitra is the founder and CEO of One Million by One Million (1Mby1M), the world’s first and only global virtual incubator/accelerator. Its goal is to help a million entrepreneurs globally reach a million dollars in annual revenue, build a trillion dollars in global GDP, and create 10 million jobs. Since its founding in 2010, 1Mby1M has become a powerful platform for democratization of entrepreneurship acceleration. Sramana also developed 1Mby1M’s Incubator-in-a-Box methodology for Corporate Incubation that is used by enterprises to manage internal and external innovation endeavors. In 2015, LinkedIn named Sramana one of their Top 10 Influencers alongside Bill Gates and Richard Branson. Sramana has been an entrepreneur and a strategy consultant in Silicon Valley since 1994. Her fields of experience span from hardcore technology disciplines like Artificial Intelligence, Cloud Computing and Semiconductors, to sophisticated consumer marketing industries including e-commerce, fashion and education. As an entrepreneur CEO, Sramana founded three companies: Dais (off-shore software services), Intarka (sales lead generation and qualification software using Artificial Intelligence algorithms; VC: NEA) and Uuma (online personalized store for selling clothes using Expert Systems software; VC: Redwood). Two of these were acquired, while the third received an acquisition offer from Ralph Lauren which the company did not accept. As strategy consultant, Sramana has consulted with over 80 companies, including public companies such as SAP, Cadence Design Systems, Webex, KLA-Tencor, Best Buy, MercadoLibre and Tessera among others. Her work has also included numerous startups and VCs. Sramana has a Masters degree in EECS from MIT and a Bachelors degree in Computer Science and Economics from Smith College. From 2000 to 2004, Sramana chaired the MIT Club of Northern California’s entrepreneurship program in Silicon Valley. Learn more at www.1Mby1M.com

Josh Tobin holds a CS PhD from UC Berkeley, which he completed in four years while also working at OpenAI as a research scientist. His focus was on robotic perception and control, and contributed to the famous Rubik's cube robot hand video. He co-organizes the phenomenal Full Stack Deep Learning course and is now working on a new stealth startup. Learn more about Josh: http://josh-tobin.com/ (http://josh-tobin.com/) https://twitter.com/josh_tobin_ (https://twitter.com/josh_tobin_) Want to level-up your skills in machine learning and software engineering? Join the ML Engineered Newsletter: https://mlengineered.ck.page/943aa3fd46 (https://mlengineered.ck.page/943aa3fd46) Comments? Questions? Submit them here: https://charlie266.typeform.com/to/DA2j9Md9 (https://charlie266.typeform.com/to/DA2j9Md9) Follow Charlie on Twitter: https://twitter.com/CharlieYouAI (https://twitter.com/CharlieYouAI) Take the Giving What We Can Pledge: https://www.givingwhatwecan.org/ (https://www.givingwhatwecan.org/) Subscribe to ML Engineered: https://mlengineered.com/listen (https://mlengineered.com/listen) Timestamps: 01:32 Follow Charlie on Twitter (http://twitter.com/charlieyouai (twitter.com/charlieyouai)) 02:43 How Josh got started in CS and ML 11:05 Why Josh worked on ML for robotics 15:03 ML for Robotics research at OpenAI 28:20 Josh's research process 34:56 Why putting ML into production is so difficult 44:46 What Josh thinks the ML Ops landscape will look like 49:49 Common mistakes that production ML teams and companies make 53:11 How ML systems will be built in the future 59:37 The most valuable skills that ML engineers should develop 01:03:50 Rapid Fire Questions Links https://course.fullstackdeeplearning.com/ (Full Stack Deep Learning) https://arxiv.org/abs/1703.06907 (Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World) https://arxiv.org/abs/1710.06425 (Domain Randomization and Generative Models for Robotic Grasping) https://deepmind.com/blog/article/neural-scene-representation-and-rendering (DeepMind Generative Query Network (GQN) paper) https://arxiv.org/abs/1911.04554 (Geometry Aware Neural Rendering) https://www2.eecs.berkeley.edu/Pubs/TechRpts/2019/EECS-2019-104.pdf (Josh's PhD Thesis) https://www.youtube.com/watch?v=x4O8pojMF0w (OpenAI Rubik's Cube Robot Hand video) https://www.wandb.com/podcast/josh-tobin (Weights and Biases interview with Josh) https://www.oreilly.com/library/view/designing-data-intensive-applications/9781491903063/ (Building Data Intensive Applications) http://creativeselection.io/ (Creative Selection)

https://charlesxjyang.github.io/ (Charles Yang) is an EECS masters student at UC Berkeley focusing on AI and dynamical systems. He writes the excellent https://ml4sci.substack.com/ (Machine Learning For Science newsletter) where he showcases a wide range of use cases for machine learning in scientific research and engineering. Learn more about Charles: Website: https://charlesxjyang.github.io/ (https://charlesxjyang.github.io/) Google Scholar: https://scholar.google.com/citations?user=BYOREdwAAAAJ&hl=en (https://scholar.google.com/citations?user=BYOREdwAAAAJ&hl=en) ML4Sci Newsletter (Highly Recommended!): https://ml4sci.substack.com/ (https://ml4sci.substack.com/) Want to level-up your skills in machine learning and software engineering? Subscribe to our newsletter: https://mlengineered.ck.page/943aa3fd46 (https://mlengineered.ck.page/943aa3fd46) Take the Giving What We Can Pledge: https://www.givingwhatwecan.org/ (https://www.givingwhatwecan.org/) Subscribe to ML Engineered: https://www.mlengineered.com/listen (https://www.mlengineered.com/listen) Follow Charlie on Twitter: https://twitter.com/CharlieYouAI (https://twitter.com/CharlieYouAI) Timestamps: (02:08) Getting started in material science and machine learning (08:58) "ImageNet moment" for ML in science (13:20) Model explainability and transparency (17:06) Charles' Current Research (18:40) Embedding existing knowledge into ML models (22:26) "Bilingual Scientists" (24:46) Learning ML as a traditional scientist (28:22) Private vs Public ML Research (32:42) Rise of open-access research (35:22) "SOTA chasing" in ML research (38:10) Scientific ML research processes (44:34) Applying ML knowledge to a scientific problem (48:00) Biggest opportunities for ML in science (51:18) Diversity in the research community (54:24) Writing the ML4Sci newsletter (56:20) Keeping up with new research (01:05:30) Rapid Fire Questions Links: https://ml4sci.substack.com/ (Charles' ML4Sci newsletter) https://ml4sci.substack.com/p/ml4sci-8-defining-the-new-saas-science (Charles' article on AI-powered Science as a Service) https://towardsdatascience.com/deep-learning-in-science-fd614bb3f3ce (Charles' article on Deep Learning in Science) https://ml4sci.substack.com/p/ml4sci-12-thoughts-on-covid-19-scientific (Charles' article on Scientific Gatekeeping) https://ml4sci.substack.com/p/ml4sci-15-news-from-the-world-of (Charles' article on Open Access Research) https://arxiv.org/abs/1912.12132 (Google Weather Forecasting paper) https://ai.googleblog.com/2020/03/a-neural-weather-model-for-eight-hour.html?m=1 (Google 2nd Weather Forecasting paper ) https://deepmind.com/blog/article/AlphaFold-Using-AI-for-scientific-discovery (DeepMind Protein Folding paper) https://www.biorxiv.org/content/10.1101/2020.03.07.982272v1.full.pdf (SalesForce Protein Folding paper) https://www.sciencemag.org/news/2020/02/models-galaxies-atoms-simple-ai-shortcuts-speed-simulations-billions-times (ML speeding up simulations by 9+ orders of magnitude (!)) https://www.anl.gov/ai-for-science-report (Oak Ridge AI for Science Report) https://www.nature.com/articles/s41586-019-1335-8 (Nature paper using word2vec on MatSci papers) https://arxiv.org/abs/2006.11287 (Paper using Graph NNs to find dark matter concentrations) https://www.amazon.com/Power-Broker-Robert-Moses-Fall/dp/0394720245/ (Robert Caro - The Power Broker) https://www.amazon.com/Golden-Gates-Fighting-Housing-America/dp/0525560211/ (Conor Dougherty - Golden Gates)

Today we’re joined by the legendary Michael I. Jordan, Distinguished Professor in the Departments of EECS and Statistics at UC Berkeley.  Michael was gracious enough to connect us all the way from Italy after being named IEEE’s 2020 John von Neumann Medal recipient. In our conversation with Michael, we explore his career path, and how his influence from other fields like philosophy shaped his path.  We spend quite a bit of time discussing his current exploration into the intersection of economics and AI, and how machine learning systems could be used to create value and empowerment across many industries through “markets.” We also touch on the potential of “interacting learning systems” at scale, the valuation of data, the commoditization of human knowledge into computational systems, and much, much more. The complete show notes for this episode can be found at. twimlai.com/go/407.

Bharath created the deepchem.io open-source project to grow the deep drug discovery open source community, co-created the moleculenet.ai benchmark suite to facilitate development of molecular algorithms, and more. Bharath’s graduate education was supported by a Hertz Fellowship, the most selective graduate fellowship in the sciences. Bharath is the lead author of “TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning”, a developer’s introduction to modern machine learning, with O’Reilly Media. Today, Bharath is focused on designing the decentralized protocols that will unlock data and AI to create the next stage of the internet. He received a BA and BS from UC Berkeley in EECS and Mathematics and was valedictorian of his graduating class in mathematics. He did his PhD in computer science at Stanford University where he studied the application of deep-learning to problems in drug-discovery. Follow Bharath on Twitter and Github https://twitter.com/rbhar90 rbharath.github.io Check out some of his projects: https://deepchem.io/ https://moleculenet.ai/ https://scholar.google.com/citations?user=LOdVDNYAAAAJ&hl=en&oi=ao Visit our podcasts homepage for transcripts and more episodes! www.wandb.com/podcast

Welcome to the first podcast of our weekly series! For our first episode we interview soon-to-be EECS legend, Mr. Jake Bringetto.

Isaac Evans is the leader of r2c (https://r2c.dev/), a small startup working on giving security tools directly to developers. Previously, he conducted research into binary exploitation bypasses for techniques like control-flow integrity and novel hardware defenses on new architectures like RISC-V as a researcher at the US Defense Department under a SFS program and at MIT Lincoln Laboratory. Isaac received his BS/MS degrees in EECS from MIT. Other interests include next-generation programming languages, secure-by-design frameworks, software-defined radio, and the intersection of cryptography and public policy.Isaac spoke about semgrem and its capabilities in this episode. - Source code: https://github.com/returntocorp/semgrep- Test in your browser: https://semgrep.live/

Prof. Michael Sung is a technology venture builder and investor, having founded various companies in diverse high-tech industries ranging from AI, blockchain, semiconductor, and new materials industries. In this new interview series, host Dinis Guarda and Michael Sung go through worldwide challenges and opportunities in the Fintech space and how new 4IR technologies like blockchain and AI can be seen as drivers of innovation for the future. Michael Sung also tells us about his CarbonBlue project, a tech-transfer and commercialisation platform that is focused on rapidly commercialising and scaling internationally-sourced high-tech innovation. INTERVIEW FOCUS1. Biography, professional background2. Academic background and research focus as Director of the Fintech Research Center at the Fanhai International School of Finance at Fudan University3. About Fintech: Trends, Challenges and Opportunities4. Dynamics of innovation in the Fintech space5. 4IR Technologies: blockchain - decentralized systems6. 4IR Technologies: blockchain and AI applied to cities and smart city projects7. About CarbonBlue projectBIOGRAPHYProf. Sung is an expert on blockchain and crypto-finance innovation, as founding co-director of the Fintech Research Center at the Fanhai International School of Finance at Fudan University. In addition, Prof. Sung is faculty at the Chinese Institute of Economics and Finance, a national-level think tank focused on developing finance innovation policy for central government. He is also a venture partner for FinNX, cross-border investment bank platform for Fundamental Labs, one of Asia's top blockchain funds.He has a strong background in cross-border technology transfer, strategic industry engagement, commercialisation strategy, business model innovation, and hi-tech entrepreneurship.Prof. Sung has served in numerous advisory roles over the years for the HK, Taiwan, and China governments on international tech transfer, innovation ecosystem building, AI, blockchain, and Fintech policy for various top city and ministry-level officials. Prof. Sung was also the chairman of the steering committee for MIT Tech Review's Emtech HK Conference. He has received various awards for technology entrepreneurship, including MIT Enterprise Forum's Most Visionary Technology Award and Google's Solve for X Prize. Prof. Sung received his Ph.D. in EECS at the MIT Media Lab/Computer Science and Artificial Intelligence Laboratory as well as a graduate financial engineering degree from MIT Sloan Business School. https://www.citiesabc.com/https://twitter.com/citiesabc_https://www.instagram.com/citiesabc/

Today we’re joined by Joseph Gonzalez, Assistant Professor in the EECS department at UC Berkeley.  Our main focus in the conversation is Joseph’s paper “Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers,” which explores compute-efficient training strategies, based on model size. We discuss the two main problems being solved; 1) How can we rapidly iterate on variations in architecture? And 2) If we make models bigger, is it really improving any efficiency? We also discuss the parallels between computer vision and NLP tasks, how he characterizes both “larger” and “faster” in the paper. Check out the complete show notes for this episode at twimlai.com/talk/378.

Pedro Pachuca, an ambitious entrepreneur passionately intentioned towards making an impact. Since the age of 11, Pedro has been enamored by Computer Science. His curiosity and willingness to learn has driven him to explore new opportunities. Not only is Pedro an exceptional learner, but also a teacher, and startup business leader. At just the age of 19, Pedro's body of work is already quite extensive. There is a substantial good list of challenges Pedro has already accomplished. As a member apart of the exclusive M.E.T. program at UC Berkeley, Pedro strongly believes the program has exceptionally facilitated him with strong interpersonal relationships with influential enterprises and influential people in the Silicon Valley. You can check out more information about Pedro Pachuca on LinkedIn.

On this episode of Silicon Valley Insider, Keith Koo's special guest is Silicon Valley native Aparna Dhinkaran, Co-Founder and Chief Product Officer of Arizen AI, a company focused on bringing infrastructure tooling to Artificial Intelligence (A.I.) and Machine Learning (ML). Aparna discusses her rise in the tech world having graduated in EECS at UC Berkeley and then on to start her PhD program at Cornell before pausing everything to start her previous company MonitorML a Y Combinator backed company. After MonitorMl was acquired, Aparna talks about joining forces with her co-founder to start Arize.ai On this week's Cyber-tip, Keith discusses gives another warning on scams related to the Coronavirus. Tune in to hear more! www.svin.biz Listen Saturdays 10-11am 860 KTRB Silicon Valley | San Francisco Listen and subscribe to the "Silicon Valley Insider" Podcast ahead of time to make sure you don't miss this show. Download the podcast at 11:00am on Saturdays. For questions or comments, email: info@svin.biz Be sure to subscribe and listen to the podcast. You can also listen to past podcasts here: Castbox: https://castbox.fm/channel/The-Silicon-Valley-Insider-Show-with-Keith-Koo-id1100209?country=us iTunes: https://itunes.apple.com/us/podcast/the-silicon-valley-insider-show/id1282637717?mt=2 Android, Spotify (and iTunes): https://omny.fm/shows/the-silicon-valley-insider-show Email us at info@svin.biz or find us here: www.svin.biz Artificial Intelligence, AI, Blockchain, Big Data, Data Analytics, Cyberrisk, Information security, VC, Venture Capital, Angel Investments, Fundraising, Capital Raising, Investor, Human Rights, Technology for Good, UN SDGs, Emerging Technology, #Patreon

Liwei Wang is a professor in the Department of Computer Science and Technology, School of EECS at Peking University. In this episode, Professor Wang highlighted his research papers accepted at NeurIPS 2019, shared his perspectives on data privacy, and the differences in the trends and challenges of AI research between China and the US. Learn more at Robin.ly: http://bit.ly/2wzlCgu Prof. Wang’s main research interest is machine learning theory and has published more than 100 papers on top conferences including NeurIPS. He was the first Asian researcher who was named among “AI’s 10 to Watch”. He served as the Area Chair of NeurIPS and the Associate Editor of PAMI.

Tragedy tomorrow (or at least next week). Comedy tonight! But first you might want to know what to expect because Old Comedy has some things that we don't really see in modern theatre. To join the discussion, visit the blog at Triumvir Clio's School of Classical Civilization. References Cartwright, Mark. "Ancient Greek Comedy." Ancient History Encyclopedia. Ancient History Encyclopedia, 25 Mar 2013. Web. 12 Dec 2019. MacLennan, Bruce. "Typical Structure Of A Greek Play". Web.Eecs.Utk.Edu, 1999, http://web.eecs.utk.edu/~bmaclenn/Classes/US210/Greek-play.html. --- Send in a voice message: https://anchor.fm/bethany-banner/message Support this podcast: https://anchor.fm/bethany-banner/support

In this episode of the Data Exchange I speak with Nir Shavit, Professor of EECS at MIT, and cofounder and CEO of Neural Magic, a startup that is creating software to enable deep neural networks to run on commodity CPUs (at GPU speeds or faster). Their initial products are focused on model inference, but they are also working on similar software for model training.Our conversation spanned many topics, including:Neurobiology, in particular the combination of Nir's research areas of multicore software and connectomics – a branch of neurobiology.Why he believes the combination of the right software and CPUs will prove capable of handling many deep learning tasks.Speed is not the only factor: the “unlimited memory” of CPUs are able to unlock larger problems and architectures.Neural Magic's initial offering is in inference, model training using CPUs is also on the horizon.Detailed show notes can be found on The Data Exchange web site.

Vikash Gilja is an assistant professor at UCSD, where he researchers brain-machine interfaces. Dr. Gilja is an advisor to Paradromics. He holds a Ph.D. in computer science from Stanford University, an M.Eng and B.S. in EECS from MIT, and a...

------------------Support the channel------------ Patreon: https://www.patreon.com/thedissenter SubscribeStar: https://www.subscribestar.com/the-dissenter PayPal: paypal.me/thedissenter PayPal Subscription 1 Dollar: https://tinyurl.com/yb3acuuy PayPal Subscription 3 Dollars: https://tinyurl.com/ybn6bg9l PayPal Subscription 5 Dollars: https://tinyurl.com/ycmr9gpz PayPal Subscription 10 Dollars: https://tinyurl.com/y9r3fc9m PayPal Subscription 20 Dollars: https://tinyurl.com/y95uvkao ------------------Follow me on--------------------- Facebook: https://www.facebook.com/thedissenteryt/ Twitter: https://twitter.com/TheDissenterYT Anchor (podcast): https://anchor.fm/thedissenter O Dr. Arlindo Oliveira é Presidente do Instituto Superior Técnico e Professor do Departamento de Engenharia Informática, onde tem desenvolvido trabalho no contexto de sistemas digitais, síntese lógica, algoritmia, aprendizagem automática e bioinformática. Doutorou-se em Engenharia Electrotécnica e Ciências da Computação (EECS) pela Universidade da Califórnia em Berkeley, em 1994. É um dos maiores especialistas portugueses em Inteligência Artificial, e publicou em 2017 o livro “The Digital Mind: How Science Is Redefining Humanity”, pela MIT Press, existindo também a sua versão em português, pela IST Press. Neste episódio, focamo-nos em alguns dos principais tópicos do livro “The Digital Mind” (ou “Mentes Digitais”, na versão em português). Falamos sobre sistemas de inteligência artificial (IA) especializados e gerais e a forma como a ciência cognitiva e a inteligência artificial se informam uma à outra. Depois, abordamos as várias maneiras possíveis de reproduzir um cérebro humano artificialmente, e da possibilidade de atingir a imortalidade. Também falamos sobre a relação entre mente e cérebro, o que é uma mente, o teste de Turing, as diferenças entre mentes naturais e mentes digitais, e vários tipos de tecnologia ao nosso dispor para tentar desenvolver sistemas de inteligência artificial mais avançados e melhorar/superar a condição humana. Finalmente, discutimos a ética por detrás de IA, tanto em relação à maneira como os devemos tratar como à maneira como eles nos devem tratar a nós. -- Sigam o trabalho do Dr. Arlindo Oliveira: Website (IST): https://bit.ly/2VpdDcD Blogue Digital Minds: https://bit.ly/30lsgkY Livro “The Digital Mind”: https://bit.ly/2Q0yJNF “Mentes Digitais” (livro em português): https://bit.ly/2E9mlGp Livro “Inteligência Artificial”: https://bit.ly/2WRlKjG Artificial Intelligence Podcast (podcast do MIT): https://bit.ly/2UbbDFa -- A HUGE THANK YOU TO MY PATRONS: KARIN LIETZCKE, ANN BLANCHETTE, SCIMED, PER HELGE HAAKSTD LARSEN, LAU GUERREIRO, RUI BELEZA, MIGUEL ESTRADA, ANTÓNIO CUNHA, CHANTEL GELINAS, JIM FRANK, JERRY MULLER, FRANCIS FORD, HANS FREDRIK SUNDE, BRIAN RIVERA, ADRIANO ANDRADE, YEVHEN BODRENKO, SERGIU CODREANU, ADAM BJERRE, ŁUKASZ STAFINIAK, AIRES ALMEIDA, BERNARDO SEIXAS, AND HERBERT GINTIS! A SPECIAL THANKS TO MY PRODUCERS, YZAR WEHBE and ROSEY!

This week, Jon Foust and Michelle Casbon bring you another fascinating interview from our time at Next! Michelle and special guest Amanda were able to catch up with Paco Nathan of Derwen AI to talk about his experience at Next and learn what Derwen is doing to advance AI. Paco and Derwen have been working extensively on ways developer relations can be enhanced by machine learning. Along with O’Reilly Media, Derwen just completed three surveys, called ABC (AI, Big Data, and Cloud), to look at the adoption of AI and the cloud around the world. The particular interest in these studies is a comparison between countries who have been using AI, Big Data, and Cloud for years and countries who are just beginning to get involved. One of the most interesting things they learned is how much budget companies are allocating to machine learning projects. They also noticed that more and more large enterprises are moving, at least partially, to the cloud. One of the challenges Paco noticed was the difference between machine learning projects in testing versus how they act once they go live. Here, developers come across bias, ethical, and safety issues. Good data governance polices can help minimize these problems. Developing good data governance policies is complex, especially with security issues, but it’s an important conversation to have. In the process of computing the survey data, Paco discovered many big companies spend a lot of time with this issue and even employ checklists of requirements before projects can be made live. In his research, Paco also discovered that about 54% of companies are non-starters. Usually, their problems stem from tech debt and issues with company personnel who do not recognize the need for machine learning. The companies working toward integrating machine learning tend to have issues finding good staff. Berkeley is working to solve this problem by requiring data science classes of all students. But as Paco says, data science is a team sport that works well with a team of people from different disciplines. Paco is an advocate of mentoring, to help the next generation of data scientists learn and grow, and of unbundling corporate decision making to help advance AI. Amanda, Michelle, and Paco wrap up their discussion with a look toward how to change ML biases. People tend to blame ML for bias outcomes, but models are subject to data we feed in. Humans have to make decisions to work around that by looking at things from a different perspective and taking steps to avoid as much bias as we can. ML and humans can work together to find these biases and help remove them. Paco Nathan Paco Nathan is the Managing Parter at Derwen. He has 35+ years tech industry experience, ranging from Bell Labs to early-stage start-ups. Paco is also the Co-chair Rev. Advisor for Amplify Partners, Recognai, Primer AI, and Data Spartan. He was formerly the Director of Community Evangelism for Databricks and Apache Spark. Cool things of the week CERN recreated the Higgs discovery on GCP video To discover the Higgs yourself, check out the CERN open data portal site Fun facts from Michelle’s visit: Seven total, four main experiments ATLAS (largest, general-purpose) site CMS (prettiest, general-purpose) site ALICE (heavy-ion) site LHCb (interactions of b-hadrons, matter/antimatter asymmetry) site The French/Swiss border runs across the CERN property Streetview of CERN control center site CERN is the birthplace of the web Where the protons come from site Watch Particle Fever movie Interview Derwen, Inc. site Derwen, Inc. Blog blog Cloud Programming Simplified: A Berkeley View on Serverless Computing paper Apache Spark site Google Cloud Storage site Datastore site Kubeflow site Quicksilver site O’Reilly Media site Google Knowledge Graph site Jupyter site JupyterCon site The Economics of Artificial Intelligence site “Why Do Businesses Fail At Machine Learning?” by Cassie Kozyrkov video The Gutenberg Galaxy site Programmed Inequality site Question of the week Stadia Connect occurred last Thursday. What are some of the biggest announcements that came out of it? Where can you find us next? Jon is in New York for Games for Change. Michelle and Mark Mirchandani are back in San Francisco. Brian & Aja are at home in Seattle. Gabi is in Brazil. Sound Effect Attribution “Crowd laugh.wav” by tom_woysky of Freesound.org

Today we’re joined by Genevera Allen, associate professor of statistics in the EECS Department at Rice University, Founder and Director of the Rice Center for Transforming Data to Knowledge and Investigator with the Neurological Research Institute with the Baylor College of Medicine. Genevera caused quite the stir at the American Association for the Advancement of Science meeting earlier this year with her presentation “Can We Trust Data-Driven Discoveries?" In our conversation we cover: • The goal of Genevera's talk, and what was lost in translation. • Use cases outlining the shortcomings of current machine learning techniques. • Reproducibility, including inference vs discovery, and the lack of terminology for many of the various reproducibility issues, & much more! The complete show notes for this episode can be found at twimlai.com/talk/266.  

How can the humble zebrafish teach us about the human microbiome? John Rawls discusses the benefits of using animal models Take the MTM Listener Survey  Julie’s Biggest Takeaways:   Zebrafish and other model animals provide opportunities to understand host-microbe interactions. Zebrafish are particularly useful for imaging studies, due to their translucent skin and the ease of in vivo microscopy. This allows zebrafish to be used to in studies of spatial architecture or longitudinal studies (imaging the same fish specimen over time) in ways that other model organisms can’t be.   Zebrafish get their first microbes from their mother, just like mammals! The chorion, a protective coating that surrounds the zebrafish embryo, is seeded with microbes from passing through the cloaca of the female zebrafish. Surface-sterilizing this chorion allows researchers to generate germ-free animals that are very useful for microbiome studies.   A gut epithelial transcription factor is regulated by a signal from the gut microbiota, and this signaling interaction is conserved among all vertebrates. The transcription factor itself, HNF4, is found in both complex and simple animals, like the sea sponge, and may serve a long-conserved function in regulating interactions between animals and their microbiota.   Enteroendocrine cells release hormones based on specific chemical cues, but they can also interact with the nervous system. This makes them an important part of the gut-brain system, and the power of in vivo imaging has made zebrafish a great model for better understanding their function. Specific members of the microbiome specifically stimulate these EECs, sending signals up the vagus nerve to the brain.   Featured Quotes:   “We know that the zebrafish functionality of its intestine is very similar to what one encounters in the mouse or human intestine and we and others have been able to translate our findings from zebrafish studies into human biology.”   On genomic studies that have found similar transcription profiles in zebrafish, stickleback fish, mice, and humans: “This suggested that there is a core transcriptome that gut epithelial cell use in different vertebrate species that haven’t shared an ancestor in 420 million years!”   Comparing fish and mouse: “Genes regulated by microbiota in these respective hosts display a lot of overlap. Many of the same signaling pathways and metabolic processes are affected by microbiotas in different hosts in similar ways.”   “There’s been a lot of interesting research documenting the role of the intestinal microbiome in promoting harvest of dietary nutrients we consume. Much of that literature has been focused on the events that occur in the distal intestine, in the colon, where recalcitrant carbohydrates and proteins that make it that far, many of which we are unable to digest, are made available to the colonic microbiome, members of which are able to digest and degrade them to things such as short chain fatty acids, which we can consume.”   “Eventually, we’ll have some strong candidates in terms of specific bacterial strains or communities or factors or pharmacologic agents that could be used to affect dietary fat absorption or metabolism. We’re still a long ways away from that.”   “One of the fascinating things about developmental biology is that the only way you get a viable animal is if the different tissues and the different cells within the body are coordinating amongst themselves for energy, for nutrients, for oxygen, et cetera. As you’re building an animal and as you’re sustaining an animal, the different tissues have to cooperate. When that doesn’t happen, when tissues or cells become selfish or don’t play by the rules, you get things like cancer and other diseases as well...when I began learning about the field of microbiome science and some of the work that was coming out from that field, it sounded to me like the microbiome was going to be a really important part of that. Not only can we think of the microbiome as a ‘microbial organ,’ as it is sometimes called, and therefore worthy of consideration within the context of developmental biology, but also the influence of the microbiome on any one tissue is going to modify its need and its ability to cooperate within the integrated system.”   Links for this Episode:   John Rawls’ lab website More amazing zebrafish images from the Rawls lab Duke University Microbiome Center Genome Research article on HNF4 regulation Cell Host and Microbe article on microbial influence on fatty acid absorption  

State of the Art Podcast was invited to attend and speak with participants in CODAME's Art + Tech Festival, ARTOBOTS at The Midway earlier this month. Part 1 features one-on-one on-site conversations with artists Alexander Reben and Meredith Tromble on art and AI. We conclude the episode with a fascinating conversation with UC Berkeley artist and professor, Ken Goldberg, on the "uncanny valley."Thank you CODAME for inviting us to cover this awesome event, and a special shoutout to Vanessa Chang, CODAME curator, for personally extending the invitation to us. You can listen to our interview with Vanessa Chang here.-About Alexander Reben-Alexander Reben is an artist and roboticist who explores humanity through the lens of art and technology. His work probes the inherently human nature of the artificial. Using tools such as artificial philosophy, synthetic psychology, perceptual manipulation and technological magic, he brings to light our inseparable evolutionary entanglement to invention which has unarguably shaped our way of being. This is done to not only help understand who we are, but to consider who we will become in our continued codevelopment with our artificial creations.Projects referred to in this episode: Boxie, Headgasmatron, and Pulse MachineLearn more at http://areben.com/-About Meredith Tromble-Meredith Tromble is a multimedia artist, writer, performer, and teacher at the San Francisco Art Institute. Learn more about Meredith at http://meredithtromble.net/-About Ken Goldberg-Ken Goldberg is an artist, inventor, and UC Berkeley Professor focusing on robotics. He was appointed the William S. Floyd Jr Distinguished Chair in Engineering and serves as Chair of the Industrial Engineering and Operations Research Department. He has secondary appointments in EECS, Art Practice, the School of Information, and Radiation Oncology at the UCSF Medical School. Ken is Director of the CITRIS "People and Robots" Initiative and the UC Berkeley AUTOLAB where he and his students pursue research in machine learning for robotics and automation in warehouses, homes, and operating rooms. Ken developed the first provably complete algorithms for part feeding and part fixturing and the first robot on the Internet. Despite agonizingly slow progress, he persists in trying to make robots less clumsy. He has over 250 peer-reviewed publications and 8 U.S. Patents. He co-founded and served as Editor-in-Chief of the IEEE Transactions on Automation Science and Engineering. Ken's artwork has appeared in 70 exhibits including the Whitney Biennial and films he has co-written have been selected for Sundance and nominated for an Emmy Award. Ken was awarded the NSF PECASE (Presidential Faculty Fellowship) from President Bill Clinton in 1995, elected IEEE Fellow in 2005 and selected by the IEEE Robotics and Automation Society for the George Saridis Leadership Award in 2016. He lives in the Bay Area and is madly in love with his wife, filmmaker and Webby Awards founder Tiffany Shlain, and their two daughters. Tweet him @Ken_Goldberg-About CODAME-Sparked by the network of creative coders, designers, and artists that Bruno Fonzi and Jordan Gray knew from around the world, CODAME was founded to celebrate their passion for art and technology. The CODAME brand of immersive, engaging, and out of the ordinary experiences was coined at the inaugural CODAME ART+TECH Festival in 2010 on a foggy rooftop in downtown San Francisco. CODAME builds ART+TECH projects and nonprofit events to inspire through experience.Follow them @codameTweet them @codameLearn more here-About ARTOBOTS-June 4-7, 2018 @ The Midway, San FranciscoThe annual CODAME ART+TECH Festival is a four-day conference with workshops, talks and nightlife events with immersive, engaging, out of the ordinary experiences. The festival features gallery installations, screenings, and performances.This year’s ART+TECH Festival, codenamed #ARTOBOTS, examines the sphere of robotics, automation, and artificial intelligence. Through art, discussion, play and performance, CODAME probes these potentials.

On today’s show I chat with Song Han, assistant professor in MIT’s EECS department, about his research on Deep Gradient Compression. In our conversation, we explore the challenge of distributed training for deep neural networks and the idea of compressing the gradient exchange to allow it to be done more efficiently. Song details the evolution of distributed training systems based on this idea, and provides a few examples of centralized and decentralized distributed training architectures such as Uber’s Horovod, as well as the approaches native to Pytorch and Tensorflow. Song also addresses potential issues that arise when considering distributed training, such as loss of accuracy and generalizability, and much more. The notes for this show can be found at twimlai.com/talk/146.

In this episode, I’m joined by Ian Goodfellow, Staff Research Scientist at Google Brain and Sandy Huang, Phd Student in the EECS department at UC Berkeley, to discuss their work on the paper Adversarial Attacks on Neural Network Policies. If you’re a regular listener here you’ve probably heard of adversarial attacks, and have seen examples of deep learning based object detectors that can be fooled into thinking that, for example, a giraffe is actually a school bus, by injecting some imperceptible noise into the image. Well, Sandy and Ian’s paper sits at the intersection of adversarial attacks and reinforcement learning, another area we’ve discussed quite a bit on the podcast. In their paper, they describe how adversarial attacks can also be effective at targeting neural network policies in reinforcement learning. Sandy gives us an overview of the paper, including how changing a single pixel value can throw off performance of a model trained to play Atari games. We also cover a lot of interesting topics relating to adversarial attacks and RL individually, and some related areas such as hierarchical reward functions and transfer learning. This was a great conversation that I’m really excited to bring to you! For complete show notes, head over to twimlai.com/talk/119

In this episode of the Data Show, I spoke with Kristian Hammond, chief scientist of Narrative Science and professor of EECS at Northwestern University. He has been at the forefront of helping companies understand the power, limitations, and disruptive potential of AI technologies and tools. In a previous post on machine learning, I listed types […]

Arlindo Oliveira é presidente do Instituto Superior Técnico e autor do livro The Digital Mind, lançado este ano e cuja edição em português, com o título Mentes Digitais, foi lançada na semana passada. Foi uma conversa cheia, em que falámos de vários temas ligados ao futuro da Inteligência Artificial, ou, nas palavras do convidado, ao surgimento das 'mentes digitais'. Ao usar esta palavra - 'mente' - Arlindo Oliveira transporta deliberadamente a discussão da Inteligência Artificial actual, independentemente dos seus avanços inegáveis, para um futuro mais ou menos longínquo, em que poderemos ter Inteligência Artificial equivalente - e, portanto, superior - à humana Algumas das questões de que falámos são, naturalmente, técnicas, outras - em maior número do que poderia parecer à partida - são mais filosóficas, levando-nos a questionar o que é ser Humano e como pode vir a ser o convívio com estas 'mentes digitais'. Arlindo Oliveira é um dos maiores especialistas portugueses em Inteligência Artificial e alguém numa posição privilegiada para prever o futuro neste campo, uma vez que junta interesse e formação académica em computação e neurologia.  Doutorou-se em Engenharia Electrotécnica e Ciências da Computação (EECS) pela Universidade da Califórnia em Berkeley, em 1994. Desde então, é Professor do Departamento de Engenharia Informática do Instituto Superior Técnico, onde tem desenvolvido trabalho no contexto de sistemas digitais, síntese lógica, algoritmia, aprendizagem automática e bioinformática. O livro 'The Digital Mind' foi lançado este ano pela prestigiada MIT Press. A tradução em português, editada pela IST Press, acaba de ser lançada no mercado nacional. (sonoplastia com a colaboração de Luís Ferreira) Clip do filme Maria Papoila retirado de: https://youtu.be/Mn90o038ZLE

Margaret Burnett is a professor of Computer Science in the School of EECS at Oregon State University. She is a pioneer woman in computer science whose work has been honoured with numerous awards, including ACM Distinguished Scientist. Her passion is to change the world by designing more gender-inclusive software. In this conversation, she shares experiences being the first woman software developer at Proctor & Gamble Ivorydale in the 1970s, and creating two start-ups as well as a women’s business network in the 1980s. She also talks about her work in academia, in particular about her GenderMag project, as well as practical experiences including mentoring and management using dove-tailing strategies as well as managing family life by drawing fences. She also tries to do one thing every day to make the world a better place. An inspirational person in so many ways! See http://www.changingacademiclife.com/blog/ 2017/7/5/margaret-burnett for a time-stamped overview of the conversation and related links.

Meeting for 6.172 industry mentors. Description of mentorship role, expectations, overview of course and how it fits into EECS curriculum.

Klothoiden sind Kurven, die 1794 von Jakob I. Bernoulli zuerst beschrieben wurden. Er hatte die Form eines Metallstreifens untersucht, der von einem Gewicht an einem Ende verbogen wird, während das andere Ende eingespannt ist. Als Resultat des elastischen Verhaltens ist dann die Krümmung proportional zur Kurvenlänge. Viele weitere Eigenschaften von Kurven mit dIeser Eigenschaft wurden dann von Leonhard Euler über den Rahmen des Gedankenexperiments von Bernoulli hinaus bewiesen , wie zum Beispiel die Position der asymptotischen Endpunkte. Im Straßen- und Schienenbau sind Klothoiden ausgezeichnete Übergangsbögen zwischen geraden Strecken und Kurven, da diese Kurve die Krümmung zwischen den beiden Abschnitten gleichmäßig anpasst. Bei der Planung von Schienentrassen wurde diese Eigenschaft vor etwa 100 Jahren schon ausgenutzt. Eine aktuelle wichtige Anwendung ist die Abbildung der Straßen in Fahrassistenzsystemen, wo passend parametrisierte Klothoiden große Vorteile gegenüber Splines besitzen, wie Gotami Heller im Gespräch mit Gudrun Thäter erklärt. Um Klothoiden tatsächlich im Computermodell benutzen zu können, muss eine möglichst adäquate Approximation gesucht und implementiert werden, die die nötige Glattheit in der Kurve erhält. Literatur und Zusatzinformationen M. Bäumker: Rechenverfahren der Ingenieurvermessung http://www.eecs.berkeley.edu/Pubs/TechRpts/2008/EECS-2008-111.pdf: R. Levien: The Euler spiral, a mathematical history, Technical Report University of Carlifornia at Berkeley, UCB/EECS-2008-111, 2008. D. Khosla: Accurate estimation of forward path geometry using two-clothoid road model, Intelligent Vehicle Symposium, 2002. IEEE. Vol. 1. IEEE, 2002.

The desire to compute on sensitive data without revealing it has led to several decades of research in the area of secure multi-party computation. Today, cloud computing serves as a major motivation for the development of secure data processing techniques suitable for use in outsourced environments for computing with private or sensitive data. Despite much attention, most of the available techniques focused on a rather narrow domain of integer arithmetic. In this talk, we describe our work on other types of computation and algorithms suitable for secure computation and outsourcing with the goal of enabling secure and efficient distributed implementation of a general-purpose program. This, in particular, includes a compiler that transforms a program written in C extension, where variables to be protected are marked as private, into its secure distributed implementation suitable for execution in the cloud. About the speaker: Marina Blanton is an assistant professor in the Department of ComputerScience and Engineering at the University of Notre Dame. She received her MS in EECS from Ohio University in 2002, MS in CS from Purdue University in2004, and PhD in CS from Purdue University in 2007. Dr. Blanton's researchinterests are centrally in information security, privacy, and appliedcryptography. Recent projects span across areas such as secure computationand outsourcing, integrity of outsourced computation and storage, privatebiometric and genomic computation, privacy-preserving systems for medicaland social networks, authentication, anonymity, and key management. Dr.Blanton has served on technical program committees for top conferences andworkshops and journal editorial boards. Her research is supported by NSF,AFOSR, and AFRL.

Lada Adamic is a visiting scholar at the UC Berkeley School of Information and an associate professor at the University of Michigan School of Information and Center for the Study of Complex Systems. She is also affiliated with EECS. Her research interests center on information dynamics in networks: how information diffuses, how it can be found, and how it influences the evolution of a network's structure. Her projects have included identifying expertise in online question and answer forums, studying the dynamics of viral marketing, and characterizing the structure in blogs and other online communities. She has received an NSF CAREER award, and best paper awards from Hypertext'08, ICWSM'10 and '11, and the most influential paper of the decade award from Web Intelligence'11.

Paul Birkmeyer, EECS at UC Berkeley, talks about his work in the Biomimetic Millisystems Lab designing and building robots. The Lab seeks to harness features of locomotion, actuation, mechanics, and control strategies to improve millirobot capabilities.TranscriptSpeaker 1: [inaudible] [inaudible]. Welcome to spectrum Speaker 2: the science and technology show [00:00:30] on k a l x Berkeley, a biweekly 30 minute program with interviews featuring bay area scientists and technologists, a calendar of local events and news. My name is Brad swift and I'm the host of today's show. Today's interview is with Paul Burke Meyer, a phd candidate in the electrical engineering and computer science department known as Ekes. He is working with Professor Ron fearing in his biomimetic millis systems lab building six legged crawling and climbing robots. [00:01:00] The goal of the biomimetic Miller systems lab is to harness features of animal manipulations, locomotion, sensing actuation, mechanics, dynamics and control strategies to radically improve Miller robot capabilities. Miller robots are small robots. For instance, the robot Paul Burke Meyer has built named dash is 10 centimeters long, five centimeters wide and weighs 15 grams. This interview [00:01:30] is prerecorded and edited. Welcome to spectrum Paul Burke. Myer, thanks for coming. Speaker 3: Yeah. Thank you for having me. It's a pleasure to be here. Where are you situated at cal? What's your current status there? I am pursuing my phd here. I'm entering into my fifth year actually. Uh, and I'm studying Ekes specifically electrical engineering and I'm working on robotics in the w department. So Speaker 2: are you in a specific group with any x or is [00:02:00] it just a general study thing? No, it's gotta be something more specific for a Ph d Speaker 3: it is. So, uh, I've been working with Professor Ron fearing since I arrived and he runs the biomimetic Milly systems lab. And within that he has a few different projects, but specifically I'm working on a sort of six legged crawling and climbing robots. Describe for us the robots you're building that my goal for my phd when I first came and still true is to make [00:02:30] a robot that can dynamically climb up a any sort of surface that it's presented with. So the contribution I'm trying to make is how do you make a robot that's minimally actuated? So class uses only a single actuator right now, single motor to drive all the legs. How do you create something that is passively stable? So the structure itself makes it stable when it's climbing. So you don't actually have to spend extra computation and have extra motors on there to keep you from either [00:03:00] falling off the wall or turning and things like that. Speaker 3: Um, how can you climb dynamically, not this sort of slow plodding climbing. How can you climb dynamically, rapidly up a surface and do it stable and do it with very little effort. And what does the foot look like that allows you to make a robot like that. So what does your foot need to do in order to be able to engage and disengage rapidly and without any actuation? So that's [00:03:30] sort of what my phd will say in the end, hopefully. And maybe a year and a half or two years. How did you go about building that kind of a robot? Speaker 3: So the design was long and hard. Um, so when I first came to the biomimetic Mullin systems lab, they were already using what they're calling the smart composite manufacturing process, if you want to describe it. Yeah. So the original process was taking [00:04:00] two pieces of carbon fiber and cutting mirrored slits in both. You cut a bunch of slits on the one piece and you mere it across to the other, and then you take a piece of thin Palmer thin plastic sheet and then you take those two mirrored pieces and put them together and make a sandwich structure. And so you have carbon fiber with one pattern polymer, and then the other piece of carbon fiber with the same pattern that now aligns with the other one, it [00:04:30] bends. Now it's flexible at those polymer hinges at those where those slits were originally. So if each slit is a joint, it doesn't cost you anything to cut more joints out. Speaker 3: Whereas if you're making sort of traditional machined robot out of say aluminum and ball-bearings and things, each new joint does a new bearing, which has some costs, has extra weight. So you can add many, many joints. For example, Dash I think has 75 or more joints in [00:05:00] the robot. Um, many of them are fixed, so they're used just to fold up the final structure and then you glue them in place. Each hip has six moving joints. So each hip has six moving joints. They're six hips. So Justin, the hips alone, they're already 36 moving joints. Um, whereas if you were to do this with ball-bearings, you quickly get something very big and very heavy. So this actually started off as a prototyping process. [00:05:30] Before they would use the carbon fiber process to make their robots. At the time they were making very small robotic flies and you have to assemble these flies under microscopes and it's very tedious. Speaker 3: And if you, if you mess up, so in your design process, you didn't account for something or something doesn't quite align. You've lost a couple of days just working under a microscope, your back hurts, your eyes are tired and it's very frustrating. They realize, hey, this is just a geometric [00:06:00] pattern. So if we make it very small, little fold up the exact same way as if we make it very big, the pattern is the same, the folds are the same. So they take cardboard and make the pattern just bigger and then assemble it by hand without a microscope within a few hours. And exactly, they can tell it's gonna move in the way I want. So this started off as a prototyping process designed by, uh, Aaron Hoover, who's now a professor at Olin and he just graduated. So I actually took this process and started to make [00:06:30] robot designs and realized, Hey, these are actually very functional. Speaker 3: They don't have to be prototypes necessarily. They're actually functional robots at the end. And uh, the cardboard was used, it's cheap cuts very quickly on a laser and you can go through designs very quickly. So instead of having one design that takes two days to build, you can build one in an hour or two. And so you can sort of explore that design space very quickly. So coming into the lab, they were using this manufacturing process where you design everything flat and you cut it out with the laser and you have to fold [00:07:00] it up into something that is functional and moves in the way that you want. And at the time, and still true, we don't have any good way of mapping what a 2d pattern is in the laser cutter, what that map looks like. And what you'll get out when you fold it up into three dimensions. Speaker 3: Keeping in mind that these joints can't spin 360 degrees like a ball bearing. They're limited to at most 180 [00:07:30] degrees before they hit the link on the other side. So you have to in your in your head or on paper draw these structures. Say I started with hips, how can I get a nice leg motion out? And so I designed the hips and then like extrapolated that to six hips and sort of as you go you have to sort of mentally unfold these hips and figure out what that pattern looks like and then you put six hips and then you have to make sure that it can all fit on a flat piece and that when you unfolded [00:08:00] they don't have pieces that are unfolded on top of each other. As you go. Say you'll make a pattern and the first one you make, you fold it up and you realize that some part has to go through another part because the way you designed it actually you didn't realize this part was going to fold into the other cause you have to go back and redesign it. Speaker 3: A lot of trial and error, a lot of trial and error and it took more than 50, maybe, maybe less than a hundred different design iterations for the dash that is [00:08:30] published now from where I started. And even then there were some designs I did with just a single hip just to see what a good hip design was. And it took a lot of time just to get familiar with this folding and unfolding process and laying out parts in two dimensions. And that took me six months just to get familiar with that when I first came. So, so dash is made out of this paper composite. Um, but I've made Balsa wood versions, [00:09:00] I've made fiberglass versions. I actually have not made carbon fiber just because our laser that we use to cut carbon fiber, the bed is not quite big enough so you can't cut pieces quite big enough to make dash. But now we have actually a new laser that I, I will probably pursue carbon fiber if only for the novelty. Um, so it was a, it was a long process. Speaker 4: [inaudible] you are listening to spectrum [00:09:30] line a l x Berkeley. You're talking with Paul Burke Meyer about designing and building small six legged crawling and climbing robots. Speaker 2: The robot that you've built and published a paper about is called Dash. What does that stand for? Dash stands for the dynamic autonomous sprawled hexapod. Once you'd spent a lot of time with Dash, you then wanted [00:10:00] to create an x generation. What was it out of dash that you wanted to explore with clash? Speaker 3: So the things I liked about dash were the fact that it was still fairly small, 10 centimeters long, only 15 grams and very powerful. So if I kept it attached to a wall so it couldn't fall backwards off the wall, it had a lot of power. Could accelerate to full speed within a few hundred milliseconds. I mean it was very, very powerful. So that was nice. But its failure [00:10:30] was in the fact that in order to run it has these two plates basically that move up and down and forward and back relative to each other to drive the legs. That's basically the body is the transmission and it's true, the transmission is moving up and down. And so that's actually the problem is that it's pushing itself off the wall and it does this. So that was the, the main thing I wanted to address, but I liked the way the legs moved. Speaker 3: They call it alternating tripod gait where you have three legs in contact of any one time, so you have this [00:11:00] sort of tripod of support. So I knew what I had generally that worked and I knew sort of what didn't work. And so with clash it was how do I get rid of this up and down motion? And I'd spent enough years doing this smart composite manufacturing that the transition from dash to an entirely new design was only a couple iterations before I got something that actually climbed rather than multiple 50 or so iterations. So that was a lot smoother. The hips are essentially the same, but though the way that they're driven is a little bit different. [00:11:30] And now instead of moving up and down, it's sort of moving side to side and forward and back. So it's not pushing itself off the wall. Speaker 2: Can you describe the control systems you use for your robots? So the, the Speaker 3: interesting thing with the robots that we're making in our lab is that we're trying to reduce the amount of controls necessary as much as possible. Traditional robots, heavy computational power, um, so that they can control each limb and very precisely so in, in, or wants, they don't fall over. [00:12:00] Basically the biggest problem is not falling over for, for legged robots and maintaining stability at least traditionally. So what we're trying to do is to minimize the amount of overhead you have to have, just to be functional. So we've worked with biologists here at Berkeley. They've sort of found these really interesting properties and cockroaches where if they're running over smooth terrain, if you measure their, uh, leg muscle activity, it follows some very repeatable pattern [00:12:30] over smooth terrain, meaning that they're, they're activating the legs the same and then they give them this very rough, varied terrain with bumps, maybe two or three times the height of the cockroach. Speaker 3: They're very significant and they measure the leg activity and it looks almost exactly the same as when it's running on flat terrain. So what that that said to them was the roach is basically saying run and it doesn't care what the terrain is. They've decided that there's this [00:13:00] mechanical complexity and compliance. So the legs basically act as shock absorbers. They're just running and the legs sort of compensate for any roughness in the terrain. What we're trying to do is basically have a robot that does that where you just tell the robot to run and it doesn't care what it hits or what it's running over. It just basically runs and the legs are soft enough and bend enough to sort of compensate forever variation. There isn't the terrain. So the first design of dash that actually [00:13:30] put a motor in the motor actually came from a radio shack toy and I just took the electronics from that toy because it was remote controlled. Speaker 3: Since then, the electronics have been swapped for custom electronics. A couple other students in our lab have designed really small lightweight electronics with an accelerometer and a gyroscope, even a port for uh, integrating a cell phone camera and there students who are using that cell phone camera to sort of [00:14:00] guide the robot from my end. I'm basically doing the robot design and I put these electronics on and I have two commands, three really run. And I tell it how fast and turn left or turn right. And that's it. The nice thing is you don't have to do anything more than that because it, it, it runs well and it can go over a different terrain. It can climb obstacles and dash climb obstacles as tall as itself and it doesn't really care. And so that was what that lets you do is get really [00:14:30] small CPS, really small computers that basically you put on these robots and they take very little power. But now for control, all of all they have to say is go or turn when they can use the rest of their computational time to say, read information from the camera and decide which way do I want to go? What's my objective? So from a stability controls point, it's couldn't be easier. Um, and now we're using these whatever extra [00:15:00] CPU cycles in our small board to do sort of more complicated behavior, but that's sort of another person's project. Speaker 2: What sort of applications do you see this robot having? I know that you would want to use it as a vehicle, right? To have payloads on it. Right? And it also then goes into these strange places or if it can climb walls that's astounding. Right. On its own. Right. And then how do you then utilize it? Speaker 3: The original goal was to have a robot that you could deploy [00:15:30] in search and rescue operations. So, um, say in an earthquake where you have claps buildings or claps minds, um, you can send in very small robots, uh, through the cracks, through the crevices down to find survivors. And you can have thousands of these really cheap and small robots and you don't care if 99% of the robots fail to find anyone or fail to even make it down as long as some small fraction finds a survivor, then you have, [00:16:00] technically you've succeeded. So the goal is to make lots of these small, inexpensive robots that can climb through the cracks, have sensors on them that can detect if someone's alive and then little radios to communicate with each other and communicate with the outside world to say, this is where someone is. Even if it's with some high probability that there's someone here, you know, it's worth spending your time digging in this exact location rather than having to uncover the entire building. Speaker 2: I would imagine there are lots of uses in that realm of, of sensing [00:16:30] environments just in general, whether it's a collapse, building, a search and rescue, but you're just a hazardous place to monitor. And to have these things patrolling. So there's the, the whole idea is numbers and inexpensive, right? Manufacturer, Speaker 3: right. So, so there are also proposals for environmental sensing. So deploying these robots, especially these nice mobile robots and say agricultural areas where you want to track how a crop dusters pesticides [00:17:00] travel across the countryside. You could have robots that sort of move and they can respond to say changing winds so that it can sort of get into the line of you know, the the path of these plumes of pesticides and sort of track how they're progressing across the country if they're affecting, you know, downwind communities. Also we have visions of putting these on bridges to do, checking for signs of stress on bridges and or say the nuclear power plants [00:17:30] in Japan. You could deploy these and have them run around and find you know, leaks or just have a nice mesh sort of deployed sensor network and sort of get readings from lots of different spaces and sort of try to understand how the radiation is moving. Oh Speaker 4: you are listening to spectrum line k a l x Berkeley. We are talking with Paul Burke Meyer about designing and building small six legged crawling [00:18:00] and climbing robots. Speaker 2: So Paul, how did you become interested in engineering? Speaker 3: For me it was pretty clear from the beginning. So when I was younger, um, I was really interested in, well like most people in engineering right now. I built a lot of things out of Legos and connects and things and was really interested in electronics. I actually had [00:18:30] an elderly neighbor next door to me who I would go over and visit and uh, he would give me all of his popular mechanics magazines and popular science magazines when he was done reading them. And I think that was really the hook that got me because I was reading these magazines, seeing all these cool things and thinking like, how can I end up in this magazine? What can I do to be in this magazine because these are all really, really neat things. I think that was the, the original hook. Then, uh, it sort of blossomed [00:19:00] in high school. Speaker 3: We had, uh, an advanced physics class. It was the first time it was offered and it was really sort of undefined. The curriculum wasn't really well formed and uh, as a result we had some freedom that you might not normally have in a high school course to do different projects that we wanted. Uh, the teacher at the time approached me maybe two thirds of the way into the year and said, hey, I have this, uh, this little programming board that they use at MIT for basic robotics things and I just have one of them and [00:19:30] you're doing well in the class. You want to see if you can maybe make a something and we can try to define a project for you using this board. The project ended up being making a robot that could drive through a maze and pop a balloon at the end. And he actually let me pick a partner to work with me. And I actually chose my girlfriend at the time who is now my wife. Um, and so we worked on this project for a long time and had a lot of fun. We made the whole, like the car system programmed the robot [00:20:00] and it was a spectacular failure, but it really was a lot of fun. And I think that was sort of what really cemented engineering for me. Speaker 2: So you mentioned in, in talking about getting started in robotics and engineering, the the aspect of having a lot of fun with it and are you able to maintain that sense of fun and play in your work? For me Speaker 3: this is, it's all fun. It's, I feel like I'm making toys all day [00:20:30] and I don't have to work at it to keep it fun because I love making these things and I think it's really exciting to come up with new structures and sort of understand why things aren't working, what you can do to change them. So for me it's, I mean adjust the, the project itself is so I think, I think it can be fun for other people when you have a like I can make this project fun for other people by actually making something that works and [00:21:00] sharing it with people and having this cool little robot that they can play with that can run up walls and things like that. But I think, I think it's true for lots of people in their careers. I think if you find the one you like, it's fun no matter what you do as long as, as long as you get to do it. So Speaker 2: well thanks very much Paul for coming in and talking. Speaker 3: Came with us was great. You're welcome. There was a lot of fun. Speaker 4: The [00:21:30] video of dash on Youtube, search for dash resilient, high speed 16 gram x and pedal robot regular feature of spectrum is to mention a few of the science and technology events happening locally over the next few weeks. [inaudible]. Speaker 2: The Science at Cau lecture series for July will be presented by professor Romanian Kezar Rooney [00:22:00] and will be entitled Exoskeleton Systems for medical applications. Dr Casa Rooney is a professor in the Mechanical Engineering Department at the University of California, Berkeley and director of the Berkeley Robotics and human engineering laboratory is one of the world's leading experts in robotic human augmentation. The date of the lecture is Saturday, July 16th at 11:00 AM in the genetics and plant biology building room 100 which is on the northwest corner of the UC Berkeley campus. [00:22:30] The East Bay Science cafe is held the first Wednesday of every month that the cafe of Valparaiso at La Pena Cultural Center, 31 oh five Shattuck avenue in Berkeley from 7:00 PM to 9:00 PM the cost of admittance is the purchase of a beverage or food item of your choice. Wednesday, July 6th our crystal Cha graduate student and National Science Foundation Graduate Research Fellow in the Department of integrative biology at UC Berkeley will present. [00:23:00] Her topic is titled Spiders, Crustaceans, and sells omi. A story of how animals use cells to put themselves together. Speaker 2: UC Berkeley. Professor Gordon. Frankie will present a discussion on native bee populations in the bay area at the Peralta community garden. This event is free and open to the public. It will be held Saturday, July 9th at noon in the Peralta community garden. The garden address is 1400 Peralta [00:23:30] AV in Berkeley. Since today's show is at the beginning of the month, let me remind you of the free admittance days for some of the local institutions that normally charge admission. The exploratorium in San Francisco is the first Wednesday of each month. The UC botanical garden in Strawberry Canyon. Berkeley is the first Thursday of each month. The Tech Museum in San Jose is the second Sunday of each month. The Cal Academy of Science in San Francisco is the third Wednesday of each month. [00:24:00] Now several news stories from the UC Berkeley News Center. The story about a new public website providing access to extensive climate change research being conducted at California universities and research centers. Speaker 2: The website. cal-adapt.org has a variety of features tailored for different types of users, including members of the general public, concerned about their neighborhood or region decision-makers such as city planners and resource managers [00:24:30] and experts who want to examine data. The information on the website comes from peer reviewed climate change research funded by the California Energy Commission's public interest energy research program. The site displays the research data in a variety of climate change related scenarios and in map format modeling various projections such as changes in snowpack, wildfire, danger and temperature throughout the end of the century. The cal dash adapt website was developed by the [00:25:00] geospatial innovation facility at UC Berkeley's College of natural resources. Speaker 2: The journal Science gives out a monthly prize called spore. Spore stands for science prize for online resources in education. The June award was given to the molecular work bench software developed by the Concord consortium. The molecular workbench is a free open source software tool that helps learners overcome challenges and understanding the science of atoms [00:25:30] and molecules. This software simulates atomic scale phenomenon, permits users to interact with them. It can model electrons, atoms, and molecules, which makes it exceptable across physics, chemistry, biology, and engineering. Students from grades five through college can use the software to experiment with atomic scale systems. The software includes an author ing tool that enables educators to create complete learning activities with simulations, [00:26:00] text, images, graphs, navigation links and embedded assessments. Hundreds of these activities have been created and tested in classrooms. Educators are free to download and use completed activities or simulations or create their own. Speaker 2: The website is mw.concorde.org/modeler/in an earlier show, we carried a story [00:26:30] about research into toxic flame retardant chemicals in clothing and furniture which pose health hazards for babies and young children. A companion study on the efficacy of the flame retardants was released in June in a peer study presented at the 10th annual symposium on fire safety science at the University of Maryland on June 21st scientists found that California's furniture flammability standard technical bulletin one one seven does not provide measurable fire safety [00:27:00] benefits. The standard has led to the unnecessary use of flame retardant chemicals at high levels and baby products and furniture, widespread human and animal exposure, and the potential to harm human health and the environment. While there are no proven fire safety benefits to technical bulletin one one seven the chemicals used to meet it leak from furniture into house dust, which is ingested by people in pets. Speaker 2: Humans studies have shown associations [00:27:30] between increased flame retardant body levels and reduced IQ in children reduced fertility and to Krinn and thyroid disruption changes in male hormone levels, adverse birth outcomes and impaired development. Flame retardants have been found in the bodies of nearly all north Americans tested with the highest human levels in young children and Californians. Dogs have retardant [00:28:00] levels up to 10 times higher than humans and cats because of their grooming behavior have levels up to 100 times higher. The California standard established by technical bulletin one one seven has become a de facto national standard legislation to allow an alternative fabric flammability standard that would provide equal or greater fire safety without the use of chemical flame retardants failed last month with strong opposition [00:28:30] from lobbyists for Kim Torah, Alber Marley and Israeli chemicals limited. For more information and the complete study, go to the website, green science policy.org Speaker 5: [inaudible] [inaudible]. Speaker 4: The abuse occurred during the show is by Listonic Donna David from his album folk and acoustic made [00:29:00] available by a creative Commons attribution only licensed 3.0 editing assistance was provided by Judith White Marceline and Gretchen Sanders. Thank you for listening to spectrum. If you have any comments about the show, please send them to us via email. Our email address is spectrum dot k a l x@yahoo.com join us in two weeks [00:29:30] at the same time. Speaker 5: [inaudible]. See acast.com/privacy for privacy and opt-out information.

Paul Birkmeyer, EECS at UC Berkeley, talks about his work in the Biomimetic Millisystems Lab designing and building robots. The Lab seeks to harness features of locomotion, actuation, mechanics, and control strategies to improve millirobot capabilities.TranscriptSpeaker 1: [inaudible] [inaudible]. Welcome to spectrum Speaker 2: the science and technology show [00:00:30] on k a l x Berkeley, a biweekly 30 minute program with interviews featuring bay area scientists and technologists, a calendar of local events and news. My name is Brad swift and I'm the host of today's show. Today's interview is with Paul Burke Meyer, a phd candidate in the electrical engineering and computer science department known as Ekes. He is working with Professor Ron fearing in his biomimetic millis systems lab building six legged crawling and climbing robots. [00:01:00] The goal of the biomimetic Miller systems lab is to harness features of animal manipulations, locomotion, sensing actuation, mechanics, dynamics and control strategies to radically improve Miller robot capabilities. Miller robots are small robots. For instance, the robot Paul Burke Meyer has built named dash is 10 centimeters long, five centimeters wide and weighs 15 grams. This interview [00:01:30] is prerecorded and edited. Welcome to spectrum Paul Burke. Myer, thanks for coming. Speaker 3: Yeah. Thank you for having me. It's a pleasure to be here. Where are you situated at cal? What's your current status there? I am pursuing my phd here. I'm entering into my fifth year actually. Uh, and I'm studying Ekes specifically electrical engineering and I'm working on robotics in the w department. So Speaker 2: are you in a specific group with any x or is [00:02:00] it just a general study thing? No, it's gotta be something more specific for a Ph d Speaker 3: it is. So, uh, I've been working with Professor Ron fearing since I arrived and he runs the biomimetic Milly systems lab. And within that he has a few different projects, but specifically I'm working on a sort of six legged crawling and climbing robots. Describe for us the robots you're building that my goal for my phd when I first came and still true is to make [00:02:30] a robot that can dynamically climb up a any sort of surface that it's presented with. So the contribution I'm trying to make is how do you make a robot that's minimally actuated? So class uses only a single actuator right now, single motor to drive all the legs. How do you create something that is passively stable? So the structure itself makes it stable when it's climbing. So you don't actually have to spend extra computation and have extra motors on there to keep you from either [00:03:00] falling off the wall or turning and things like that. Speaker 3: Um, how can you climb dynamically, not this sort of slow plodding climbing. How can you climb dynamically, rapidly up a surface and do it stable and do it with very little effort. And what does the foot look like that allows you to make a robot like that. So what does your foot need to do in order to be able to engage and disengage rapidly and without any actuation? So that's [00:03:30] sort of what my phd will say in the end, hopefully. And maybe a year and a half or two years. How did you go about building that kind of a robot? Speaker 3: So the design was long and hard. Um, so when I first came to the biomimetic Mullin systems lab, they were already using what they're calling the smart composite manufacturing process, if you want to describe it. Yeah. So the original process was taking [00:04:00] two pieces of carbon fiber and cutting mirrored slits in both. You cut a bunch of slits on the one piece and you mere it across to the other, and then you take a piece of thin Palmer thin plastic sheet and then you take those two mirrored pieces and put them together and make a sandwich structure. And so you have carbon fiber with one pattern polymer, and then the other piece of carbon fiber with the same pattern that now aligns with the other one, it [00:04:30] bends. Now it's flexible at those polymer hinges at those where those slits were originally. So if each slit is a joint, it doesn't cost you anything to cut more joints out. Speaker 3: Whereas if you're making sort of traditional machined robot out of say aluminum and ball-bearings and things, each new joint does a new bearing, which has some costs, has extra weight. So you can add many, many joints. For example, Dash I think has 75 or more joints in [00:05:00] the robot. Um, many of them are fixed, so they're used just to fold up the final structure and then you glue them in place. Each hip has six moving joints. So each hip has six moving joints. They're six hips. So Justin, the hips alone, they're already 36 moving joints. Um, whereas if you were to do this with ball-bearings, you quickly get something very big and very heavy. So this actually started off as a prototyping process. [00:05:30] Before they would use the carbon fiber process to make their robots. At the time they were making very small robotic flies and you have to assemble these flies under microscopes and it's very tedious. Speaker 3: And if you, if you mess up, so in your design process, you didn't account for something or something doesn't quite align. You've lost a couple of days just working under a microscope, your back hurts, your eyes are tired and it's very frustrating. They realize, hey, this is just a geometric [00:06:00] pattern. So if we make it very small, little fold up the exact same way as if we make it very big, the pattern is the same, the folds are the same. So they take cardboard and make the pattern just bigger and then assemble it by hand without a microscope within a few hours. And exactly, they can tell it's gonna move in the way I want. So this started off as a prototyping process designed by, uh, Aaron Hoover, who's now a professor at Olin and he just graduated. So I actually took this process and started to make [00:06:30] robot designs and realized, Hey, these are actually very functional. Speaker 3: They don't have to be prototypes necessarily. They're actually functional robots at the end. And uh, the cardboard was used, it's cheap cuts very quickly on a laser and you can go through designs very quickly. So instead of having one design that takes two days to build, you can build one in an hour or two. And so you can sort of explore that design space very quickly. So coming into the lab, they were using this manufacturing process where you design everything flat and you cut it out with the laser and you have to fold [00:07:00] it up into something that is functional and moves in the way that you want. And at the time, and still true, we don't have any good way of mapping what a 2d pattern is in the laser cutter, what that map looks like. And what you'll get out when you fold it up into three dimensions. Speaker 3: Keeping in mind that these joints can't spin 360 degrees like a ball bearing. They're limited to at most 180 [00:07:30] degrees before they hit the link on the other side. So you have to in your in your head or on paper draw these structures. Say I started with hips, how can I get a nice leg motion out? And so I designed the hips and then like extrapolated that to six hips and sort of as you go you have to sort of mentally unfold these hips and figure out what that pattern looks like and then you put six hips and then you have to make sure that it can all fit on a flat piece and that when you unfolded [00:08:00] they don't have pieces that are unfolded on top of each other. As you go. Say you'll make a pattern and the first one you make, you fold it up and you realize that some part has to go through another part because the way you designed it actually you didn't realize this part was going to fold into the other cause you have to go back and redesign it. Speaker 3: A lot of trial and error, a lot of trial and error and it took more than 50, maybe, maybe less than a hundred different design iterations for the dash that is [00:08:30] published now from where I started. And even then there were some designs I did with just a single hip just to see what a good hip design was. And it took a lot of time just to get familiar with this folding and unfolding process and laying out parts in two dimensions. And that took me six months just to get familiar with that when I first came. So, so dash is made out of this paper composite. Um, but I've made Balsa wood versions, [00:09:00] I've made fiberglass versions. I actually have not made carbon fiber just because our laser that we use to cut carbon fiber, the bed is not quite big enough so you can't cut pieces quite big enough to make dash. But now we have actually a new laser that I, I will probably pursue carbon fiber if only for the novelty. Um, so it was a, it was a long process. Speaker 4: [inaudible] you are listening to spectrum [00:09:30] line a l x Berkeley. You're talking with Paul Burke Meyer about designing and building small six legged crawling and climbing robots. Speaker 2: The robot that you've built and published a paper about is called Dash. What does that stand for? Dash stands for the dynamic autonomous sprawled hexapod. Once you'd spent a lot of time with Dash, you then wanted [00:10:00] to create an x generation. What was it out of dash that you wanted to explore with clash? Speaker 3: So the things I liked about dash were the fact that it was still fairly small, 10 centimeters long, only 15 grams and very powerful. So if I kept it attached to a wall so it couldn't fall backwards off the wall, it had a lot of power. Could accelerate to full speed within a few hundred milliseconds. I mean it was very, very powerful. So that was nice. But its failure [00:10:30] was in the fact that in order to run it has these two plates basically that move up and down and forward and back relative to each other to drive the legs. That's basically the body is the transmission and it's true, the transmission is moving up and down. And so that's actually the problem is that it's pushing itself off the wall and it does this. So that was the, the main thing I wanted to address, but I liked the way the legs moved. Speaker 3: They call it alternating tripod gait where you have three legs in contact of any one time, so you have this [00:11:00] sort of tripod of support. So I knew what I had generally that worked and I knew sort of what didn't work. And so with clash it was how do I get rid of this up and down motion? And I'd spent enough years doing this smart composite manufacturing that the transition from dash to an entirely new design was only a couple iterations before I got something that actually climbed rather than multiple 50 or so iterations. So that was a lot smoother. The hips are essentially the same, but though the way that they're driven is a little bit different. [00:11:30] And now instead of moving up and down, it's sort of moving side to side and forward and back. So it's not pushing itself off the wall. Speaker 2: Can you describe the control systems you use for your robots? So the, the Speaker 3: interesting thing with the robots that we're making in our lab is that we're trying to reduce the amount of controls necessary as much as possible. Traditional robots, heavy computational power, um, so that they can control each limb and very precisely so in, in, or wants, they don't fall over. [00:12:00] Basically the biggest problem is not falling over for, for legged robots and maintaining stability at least traditionally. So what we're trying to do is to minimize the amount of overhead you have to have, just to be functional. So we've worked with biologists here at Berkeley. They've sort of found these really interesting properties and cockroaches where if they're running over smooth terrain, if you measure their, uh, leg muscle activity, it follows some very repeatable pattern [00:12:30] over smooth terrain, meaning that they're, they're activating the legs the same and then they give them this very rough, varied terrain with bumps, maybe two or three times the height of the cockroach. Speaker 3: They're very significant and they measure the leg activity and it looks almost exactly the same as when it's running on flat terrain. So what that that said to them was the roach is basically saying run and it doesn't care what the terrain is. They've decided that there's this [00:13:00] mechanical complexity and compliance. So the legs basically act as shock absorbers. They're just running and the legs sort of compensate for any roughness in the terrain. What we're trying to do is basically have a robot that does that where you just tell the robot to run and it doesn't care what it hits or what it's running over. It just basically runs and the legs are soft enough and bend enough to sort of compensate forever variation. There isn't the terrain. So the first design of dash that actually [00:13:30] put a motor in the motor actually came from a radio shack toy and I just took the electronics from that toy because it was remote controlled. Speaker 3: Since then, the electronics have been swapped for custom electronics. A couple other students in our lab have designed really small lightweight electronics with an accelerometer and a gyroscope, even a port for uh, integrating a cell phone camera and there students who are using that cell phone camera to sort of [00:14:00] guide the robot from my end. I'm basically doing the robot design and I put these electronics on and I have two commands, three really run. And I tell it how fast and turn left or turn right. And that's it. The nice thing is you don't have to do anything more than that because it, it, it runs well and it can go over a different terrain. It can climb obstacles and dash climb obstacles as tall as itself and it doesn't really care. And so that was what that lets you do is get really [00:14:30] small CPS, really small computers that basically you put on these robots and they take very little power. But now for control, all of all they have to say is go or turn when they can use the rest of their computational time to say, read information from the camera and decide which way do I want to go? What's my objective? So from a stability controls point, it's couldn't be easier. Um, and now we're using these whatever extra [00:15:00] CPU cycles in our small board to do sort of more complicated behavior, but that's sort of another person's project. Speaker 2: What sort of applications do you see this robot having? I know that you would want to use it as a vehicle, right? To have payloads on it. Right? And it also then goes into these strange places or if it can climb walls that's astounding. Right. On its own. Right. And then how do you then utilize it? Speaker 3: The original goal was to have a robot that you could deploy [00:15:30] in search and rescue operations. So, um, say in an earthquake where you have claps buildings or claps minds, um, you can send in very small robots, uh, through the cracks, through the crevices down to find survivors. And you can have thousands of these really cheap and small robots and you don't care if 99% of the robots fail to find anyone or fail to even make it down as long as some small fraction finds a survivor, then you have, [00:16:00] technically you've succeeded. So the goal is to make lots of these small, inexpensive robots that can climb through the cracks, have sensors on them that can detect if someone's alive and then little radios to communicate with each other and communicate with the outside world to say, this is where someone is. Even if it's with some high probability that there's someone here, you know, it's worth spending your time digging in this exact location rather than having to uncover the entire building. Speaker 2: I would imagine there are lots of uses in that realm of, of sensing [00:16:30] environments just in general, whether it's a collapse, building, a search and rescue, but you're just a hazardous place to monitor. And to have these things patrolling. So there's the, the whole idea is numbers and inexpensive, right? Manufacturer, Speaker 3: right. So, so there are also proposals for environmental sensing. So deploying these robots, especially these nice mobile robots and say agricultural areas where you want to track how a crop dusters pesticides [00:17:00] travel across the countryside. You could have robots that sort of move and they can respond to say changing winds so that it can sort of get into the line of you know, the the path of these plumes of pesticides and sort of track how they're progressing across the country if they're affecting, you know, downwind communities. Also we have visions of putting these on bridges to do, checking for signs of stress on bridges and or say the nuclear power plants [00:17:30] in Japan. You could deploy these and have them run around and find you know, leaks or just have a nice mesh sort of deployed sensor network and sort of get readings from lots of different spaces and sort of try to understand how the radiation is moving. Oh Speaker 4: you are listening to spectrum line k a l x Berkeley. We are talking with Paul Burke Meyer about designing and building small six legged crawling [00:18:00] and climbing robots. Speaker 2: So Paul, how did you become interested in engineering? Speaker 3: For me it was pretty clear from the beginning. So when I was younger, um, I was really interested in, well like most people in engineering right now. I built a lot of things out of Legos and connects and things and was really interested in electronics. I actually had [00:18:30] an elderly neighbor next door to me who I would go over and visit and uh, he would give me all of his popular mechanics magazines and popular science magazines when he was done reading them. And I think that was really the hook that got me because I was reading these magazines, seeing all these cool things and thinking like, how can I end up in this magazine? What can I do to be in this magazine because these are all really, really neat things. I think that was the, the original hook. Then, uh, it sort of blossomed [00:19:00] in high school. Speaker 3: We had, uh, an advanced physics class. It was the first time it was offered and it was really sort of undefined. The curriculum wasn't really well formed and uh, as a result we had some freedom that you might not normally have in a high school course to do different projects that we wanted. Uh, the teacher at the time approached me maybe two thirds of the way into the year and said, hey, I have this, uh, this little programming board that they use at MIT for basic robotics things and I just have one of them and [00:19:30] you're doing well in the class. You want to see if you can maybe make a something and we can try to define a project for you using this board. The project ended up being making a robot that could drive through a maze and pop a balloon at the end. And he actually let me pick a partner to work with me. And I actually chose my girlfriend at the time who is now my wife. Um, and so we worked on this project for a long time and had a lot of fun. We made the whole, like the car system programmed the robot [00:20:00] and it was a spectacular failure, but it really was a lot of fun. And I think that was sort of what really cemented engineering for me. Speaker 2: So you mentioned in, in talking about getting started in robotics and engineering, the the aspect of having a lot of fun with it and are you able to maintain that sense of fun and play in your work? For me Speaker 3: this is, it's all fun. It's, I feel like I'm making toys all day [00:20:30] and I don't have to work at it to keep it fun because I love making these things and I think it's really exciting to come up with new structures and sort of understand why things aren't working, what you can do to change them. So for me it's, I mean adjust the, the project itself is so I think, I think it can be fun for other people when you have a like I can make this project fun for other people by actually making something that works and [00:21:00] sharing it with people and having this cool little robot that they can play with that can run up walls and things like that. But I think, I think it's true for lots of people in their careers. I think if you find the one you like, it's fun no matter what you do as long as, as long as you get to do it. So Speaker 2: well thanks very much Paul for coming in and talking. Speaker 3: Came with us was great. You're welcome. There was a lot of fun. Speaker 4: The [00:21:30] video of dash on Youtube, search for dash resilient, high speed 16 gram x and pedal robot regular feature of spectrum is to mention a few of the science and technology events happening locally over the next few weeks. [inaudible]. Speaker 2: The Science at Cau lecture series for July will be presented by professor Romanian Kezar Rooney [00:22:00] and will be entitled Exoskeleton Systems for medical applications. Dr Casa Rooney is a professor in the Mechanical Engineering Department at the University of California, Berkeley and director of the Berkeley Robotics and human engineering laboratory is one of the world's leading experts in robotic human augmentation. The date of the lecture is Saturday, July 16th at 11:00 AM in the genetics and plant biology building room 100 which is on the northwest corner of the UC Berkeley campus. [00:22:30] The East Bay Science cafe is held the first Wednesday of every month that the cafe of Valparaiso at La Pena Cultural Center, 31 oh five Shattuck avenue in Berkeley from 7:00 PM to 9:00 PM the cost of admittance is the purchase of a beverage or food item of your choice. Wednesday, July 6th our crystal Cha graduate student and National Science Foundation Graduate Research Fellow in the Department of integrative biology at UC Berkeley will present. [00:23:00] Her topic is titled Spiders, Crustaceans, and sells omi. A story of how animals use cells to put themselves together. Speaker 2: UC Berkeley. Professor Gordon. Frankie will present a discussion on native bee populations in the bay area at the Peralta community garden. This event is free and open to the public. It will be held Saturday, July 9th at noon in the Peralta community garden. The garden address is 1400 Peralta [00:23:30] AV in Berkeley. Since today's show is at the beginning of the month, let me remind you of the free admittance days for some of the local institutions that normally charge admission. The exploratorium in San Francisco is the first Wednesday of each month. The UC botanical garden in Strawberry Canyon. Berkeley is the first Thursday of each month. The Tech Museum in San Jose is the second Sunday of each month. The Cal Academy of Science in San Francisco is the third Wednesday of each month. [00:24:00] Now several news stories from the UC Berkeley News Center. The story about a new public website providing access to extensive climate change research being conducted at California universities and research centers. Speaker 2: The website. cal-adapt.org has a variety of features tailored for different types of users, including members of the general public, concerned about their neighborhood or region decision-makers such as city planners and resource managers [00:24:30] and experts who want to examine data. The information on the website comes from peer reviewed climate change research funded by the California Energy Commission's public interest energy research program. The site displays the research data in a variety of climate change related scenarios and in map format modeling various projections such as changes in snowpack, wildfire, danger and temperature throughout the end of the century. The cal dash adapt website was developed by the [00:25:00] geospatial innovation facility at UC Berkeley's College of natural resources. Speaker 2: The journal Science gives out a monthly prize called spore. Spore stands for science prize for online resources in education. The June award was given to the molecular work bench software developed by the Concord consortium. The molecular workbench is a free open source software tool that helps learners overcome challenges and understanding the science of atoms [00:25:30] and molecules. This software simulates atomic scale phenomenon, permits users to interact with them. It can model electrons, atoms, and molecules, which makes it exceptable across physics, chemistry, biology, and engineering. Students from grades five through college can use the software to experiment with atomic scale systems. The software includes an author ing tool that enables educators to create complete learning activities with simulations, [00:26:00] text, images, graphs, navigation links and embedded assessments. Hundreds of these activities have been created and tested in classrooms. Educators are free to download and use completed activities or simulations or create their own. Speaker 2: The website is mw.concorde.org/modeler/in an earlier show, we carried a story [00:26:30] about research into toxic flame retardant chemicals in clothing and furniture which pose health hazards for babies and young children. A companion study on the efficacy of the flame retardants was released in June in a peer study presented at the 10th annual symposium on fire safety science at the University of Maryland on June 21st scientists found that California's furniture flammability standard technical bulletin one one seven does not provide measurable fire safety [00:27:00] benefits. The standard has led to the unnecessary use of flame retardant chemicals at high levels and baby products and furniture, widespread human and animal exposure, and the potential to harm human health and the environment. While there are no proven fire safety benefits to technical bulletin one one seven the chemicals used to meet it leak from furniture into house dust, which is ingested by people in pets. Speaker 2: Humans studies have shown associations [00:27:30] between increased flame retardant body levels and reduced IQ in children reduced fertility and to Krinn and thyroid disruption changes in male hormone levels, adverse birth outcomes and impaired development. Flame retardants have been found in the bodies of nearly all north Americans tested with the highest human levels in young children and Californians. Dogs have retardant [00:28:00] levels up to 10 times higher than humans and cats because of their grooming behavior have levels up to 100 times higher. The California standard established by technical bulletin one one seven has become a de facto national standard legislation to allow an alternative fabric flammability standard that would provide equal or greater fire safety without the use of chemical flame retardants failed last month with strong opposition [00:28:30] from lobbyists for Kim Torah, Alber Marley and Israeli chemicals limited. For more information and the complete study, go to the website, green science policy.org Speaker 5: [inaudible] [inaudible]. Speaker 4: The abuse occurred during the show is by Listonic Donna David from his album folk and acoustic made [00:29:00] available by a creative Commons attribution only licensed 3.0 editing assistance was provided by Judith White Marceline and Gretchen Sanders. Thank you for listening to spectrum. If you have any comments about the show, please send them to us via email. Our email address is spectrum dot k a l x@yahoo.com join us in two weeks [00:29:30] at the same time. Speaker 5: [inaudible]. Hosted on Acast. See acast.com/privacy for more information.

Douglas Engelbart (M.S.'53, Ph.D.'55 EECS) At Stanford Resarch International, Engelbart pioneered such firsts in computer technology as the mouse, display editing, windows, cross-file editing, idea/outline processing, hypermedia, and groupware. Awarded the National Medal of Technology, the highest honor given to America's innovators by the U.S. President.

Douglas Engelbart (M.S.'53, Ph.D.'55 EECS) At Stanford Resarch International, Engelbart pioneered such firsts in computer technology as the mouse, display editing, windows, cross-file editing, idea/outline processing, hypermedia, and groupware. Awarded the National Medal of Technology, the highest honor given to America's innovators by the U.S. President.

Hierarchies arise in the context of access control whenever the set of users can be modeled as a set of partially ordered classes (i.e., represented as a directed graph). In such systems, a user that belongs to a particular class inherits privileges of all of its descendant classes. The problem of key management for an access hierarchy then consists in assigning a key to each class in the hierarchy so that keys for descendant classes can be obtained via an efficient key derivation process. We propose an efficient solution to this problem with a number of important properties, some of which are: a single key per class, local handling of changes to the hierachy, and provable security against collusion. Whereas many previous schemes had some of these properties, ours is the first that satisfies all of them. In addition, we give techniques to exponentially lower key derivation time for trees with only a contant increase in the space to store the hierarchy. About the speaker: Marina Blanton is a PhD candidate at Purdue University. She received her MS in CS from Purdue University in 2004 and MS in EECS from Ohio University in 2002. Her research interests lie in the areas of access control, applied cryptography, and privacy. More information is available at http://www.cs.purdue.edu/homes/mbykova.