Podcasts about computer architecture

Professor Fred Chong is the Seymour Goodman Professor of Computer Architecture and is also a fellow of the Institute of Electrical and Electronics Engineers. In this episode of the Course, Professor Chong shares how he witnessed the evolution of computers and A.I., while finding a niche, quantum computing and computer architecture, for himself to dive into as a research pathway.  As a faculty member at the University of Chicago, he finds joy, meaning and impact in teaching and guiding students. Tune in to listen to Professor's career story.

MAKE HISTORY WITH US THIS SUMMER:https://demystifysci.com/demysticon-2025PATREON https://www.patreon.com/c/demystifysciPARADIGM DRIFThttps://demystifysci.com/paradigm-drift-showPATREON: get episodes early + join our weekly Patron Chat https://bit.ly/3lcAasBMERCH: Rock some DemystifySci gear : https://demystifysci.myspreadshop.com/allAMAZON: Do your shopping through this link: https://amzn.to/3YyoT98SUBSTACK: https://substack.com/@UCqV4_7i9h1_V7hY48eZZSLw@demystifysciJim Keller is on of the all-time great computer architects who has shaped the tech revolution during his tenure at Digital Equipment Corporation, AMD, Tesla, Intel, AMD and Apple. In addition to being a crack engineer, Keller is also deeply curious about the inner workings of nature on all scales, and is the patron for our upcoming Beyond the Big Bang meeting in Portugal. Keller is a big proponent of what philosopher Paul Feyerabend called “scientific anarchy,” where progress requires us to abandon a prescriptive approach to what counts as “science,” because many contradictory theories can be “true” at once. We build on our previous conversation about the nature of institutions to unpack why the Big Bang is about to fall apart, what it takes to build a new theory, and how to create a lasting impact without striving explicitly for immortality. (00:00) Go! (00:04:07) Skepticism in Scientific Models and the Role of Physical Intuition(00:11:26) The Evolution of Physics and Cognitive Sciences(00:18:07) Challenges in Conventional Cosmic and Solar Models(00:22:10 )Evolution of Computer Architecture(00:24:02) The Utilitarian Approach of Engineers(00:28:12) Debugging in Engineering(00:30:32) Reevaluating Scientific Paradigms(00:34:00) Collaborative Dynamics in Science and Engineering(00:37:13) The Influence of Paradigms on Scientific Discourse(00:44:42) Musician's Journey and Archetypes(00:45:37) Belief Systems and Shared Realities(00:49:59) The Bible and Mythology(01:00:17) Sci-Fi, Technology, and Societal Impact(01:02:31) Religious Beliefs and Cultural Diversity(01:07:53) Cultural Beliefs and Alignment(01:10:50) Alignment vs. Experimentation(01:13:23) Decentralization and Experimentation(01:15:00) Individual Experience in Religion(01:18:10) Mythology and Technology(01:21:14) Scarcity and Human Behavior(01:23:04) Complexity in Human Systems(01:33:47) Human Collaboration and Motivation(01:36:16) Public Speaking and Leadership Dynamics(01:39:51) Stability and Change in Systems(01:43:52) Paradigm Drifts (01:49:02) Geopolitical Structures and Exploration(01:53:37) Political Power Dynamics(01:57:05) Critique of Power Structures(02:08:45) Paradigm Shifts(02:14:44) Mission-Driven Success(02:18:04) Authenticity in Art#TechVisionary, #AIInnovation, #TechnologyLeader, #TechVisionary, #TechGuru, #astrophysics, #engineeringlife, #cosmos, #innovations, #technews, #codinglife , #programminglife , #techindustry , #engineeringlife, #philosophypodcast, #sciencepodcast, #longformpodcastCheck our short-films channel, @DemystifySci: https://www.youtube.com/c/DemystifyingScience AND our material science investigations of atomics, @MaterialAtomics https://www.youtube.com/@MaterialAtomicsJoin our mailing list https://bit.ly/3v3kz2S PODCAST INFO: Anastasia completed her PhD studying bioelectricity at Columbia University. When not talking to brilliant people or making movies, she spends her time painting, reading, and guiding backcountry excursions. Shilo also did his PhD at Columbia studying the elastic properties of molecular water. When he's not in the film studio, he's exploring sound in music. They are both freelance professors at various universities. SOCIAL: - Discord: https://discord.gg/MJzKT8CQub- Facebook: https://www.facebook.com/groups/DemystifySci- Instagram: https://www.instagram.com/DemystifySci/- Twitter: https://twitter.com/DemystifySciMUSIC: -Shilo Delay: https://g.co/kgs/oty671

Joeita interviews Darryl Adams, Director of Accessibility at Intel, about his journey with accessible technology and his predictions about AI as a vehicle for disability inclusion. Highlights:Disability, Access & Technology - Opening Remarks (00:00)Darryl Adams, Director of Accessibility at Intel (01:13)Computer Architecture, Hardware & Accessibility (01:29)Darryl's Journey with Intel and Access Tech (02:37)Embracing Technology in a Different Way (04:27)Challenges Pursuing Accessibility (06:17)Artificial Intelligence, Accessibility & Intel (09:11)Generative AI (12:28)Privacy Concerns Surrounding AI (13:36)Intel's New Indoor Wayfinding Initiative (15:23)Wayfinding Tech Demo at Paris Olympics (17:30)Keeping Wayfinding Maps Up to Date (18:45)Darryl's Vision for the Future of Access Tech (21:17)Closing Remarks (22:54)It All Started in the CafeteriaDarryl Adams' mission to make a more accessible PC started with an epiphany in the Intel cafeteria in 2007. Adams was meeting his colleague, to discuss a new passion project: a device that would scan printed text and read it out loud for people with severe dyslexia, like his colleague, or visual impairment, like Adams.Fast forward to today, Darryl Adams is the Director of the Intel Accessibility Office.Darryl Adams Opinion piece:  “Intel's Commitment to Building an Inclusive and Accessible World" Accessibility at Intel Follow Darryl Adams online: LinkedIn, X / Twitter  About The PulseOn The Pulse, host Joeita Gupta brings us closer to issues impacting the disability community across Canada.Joeita Gupta has nurtured a life-long dream to work in radio! She's blind, moved to Toronto in 2004 and got her start in radio at CKLN, 88.1 FM in Toronto. A former co-host of AMI-audio's Live from Studio 5, Joeita also works full-time at a nonprofit in Toronto, specializing in housing/tenant rights. Find Joeita on X / Twitter: https://twitter.com/JoeitaGupta The Pulse airs weekly on AMI-audio. For more information, visit https://www.ami.ca/ThePulse/ About AMIAMI is a not-for-profit media company that entertains, informs and empowers Canadians who are blind or partially sighted. Operating three broadcast services, AMI-tv and AMI-audio in English and AMI-télé in French, AMI's vision is to establish and support a voice for Canadians with disabilities, representing their interests, concerns and values through inclusion, representation, accessible media, reflection, representation and portrayal. Learn more at AMI.caConnect on Twitter @AccessibleMediaOn Instagram @accessiblemediaincOn Facebook at @AccessibleMediaIncOn TikTok @accessiblemediaincEmail feedback@ami.ca

This is a special episode to commemorate the 50th anniversary of the International Symposium on Computer Architecture (ISCA) in June 2023. We have three leaders from our community who have served as SIGARCH chairs -- Dr. David Patterson, Dr. Norm Jouppi and Dr. Natalie Entright-Jerger -- reflect on the evolution of the computer architecture field as well as our community over half a century, and share their perspectives on opportunities and exciting times ahead. David Patterson is a professor emeritus at ​​UC Berkeley, a distinguished engineer at Google, and recipient of the Turing Award. Norm Jouppi, a VP and Engineering Fellow at Google, where he is the chief architect for Google's Tensor Processing Units (TPUs), and a recipient of the Eckert-Mauchly award. Natalie Enright-Jerger is a professor at the University of Toronto, where she is the Canada Research Chair in Computer Architecture, and is a recipient of the Alfred P. Sloan Research Fellowship, and distinguished member of ACM and IEEE.

Associate Professor Diana Franklin from the Department of Computer Science explains how a lifelong desire to teach led her to develop new tools and programs to teach kids about quantum computing. From being a computer architect to a computer science educationist, Prof. Franklin continues her journey to bettering the STEM education environment with zombie games and lots of research. 

Professor Mengjia Yan shares insights into her cybersecurity research. A full transcript of this podcast will be available at cap.csail.mit.edu

listen to Founders: https://www.listennotes.com/podcasts/founders/124-softwar-an-intimate-UrgGJSAiaY2/ 40mins in

Part two of Khari Douglas' interview with Dr. Mark D. Hill, the Gene M. Amdahl and John P. Morgridge Professor Emeritus of Computer Sciences at the University of Wisconsin-Madison and the Chair Emeritus of the CCC Council. This episode was recorded prior to Dr. Hill joining Microsoft as a Partner Hardware Architect with Azure. His research interests include parallel computer system design, memory system design, computer simulation, deterministic replay and transactional memory. In this episode, Mark discusses the importance of hardware security, the impact of AI on hardware, and working in academia vs industry. Timestamps to jump to certain topics: Hardware Security & Vulnerabilities - (1:01) Mark's Involvement with CCC/CRA - (5:58) AI and the Future of Hardware - (10:38) Simulation of Computer Hardware - (14:00) Thoughts on Running Successful A Successful Organization - (18:11) Academia Versus Industry - (23:53) Future of Computing Research - (28:24) Outro - (30:56)

Khari Douglas interviews Dr. Mark D. Hill, the Gene M. Amdahl and John P. Morgridge Professor Emeritus of Computer Sciences at the University of Wisconsin-Madison and the Chair Emeritus of the CCC Council. This episode was recorded prior to Dr. Hill joining Microsoft as a Partner Hardware Architect with Azure. His research interests include parallel computer system design, memory system design, computer simulation, deterministic replay and transactional memory. In this episode Hill discusses the importance of computer architecture, the 3C model of cache behavior, and overcoming the end of Moore's law. Timestamps to jump to certain topics: What is Computer Architecture? - (1:01) Three C Model of Cache Behavior - (5:40) Log-based Transactional Memory - (9:58) End of Moore's Law - (16:36) Hardware accelerators - (20:40) The Gables Model - (29:41) Three Other Models of Computer System Performance - (32:24) Outro - (36:15)

Mark Gilbreath, Founder and CEO of LiquidSpace, joins Bold Founder, Caleb Parker, to discuss why he believes we've reached peak portfolio. Mark says “infinite workplace” enables work from anywhere to proliferate, and as a result 80% of enterprise customers in the US will significantly reduce their leased office portfolios.  We learn about the new LiquidSpace Enterprise solution, and hear stories of their early days with enterprise customers, as well as a new big partnership with Comfy, which provides tens of thousands of workspace options to hundreds of thousands of employees. Mark says landlords need to recognise that flexible use of space must be a principal asset management strategy. Traditional real estate leasing practices do not solve for delivering thousands of workplace options at scale for employees today. The two also discuss how Workplace Brand is going to become a fundamental part of commercial real estate.  Connect with Mark on Twitter Connect with Caleb on Twitter If you have any questions or feedback on this episode, email podcast@workbold.co Value Bombs Real estate will become more liquid going forward Mindsets are shifting profoundly in regards to fixed real estate portfolios We're no longer having a binary debate between working from the office or home. The challenge for enterprise companies is how to provide tools that enable flexibility and workplace choice while maintaining duty of care and ensuring the overall financial objectives of the company are met. Workplace will be a continuum Traditional real estate leasing practices do not solve for delivering thousands of workplace options at scale for employees We are at Peak Portfolio 80%+ of US enterprises will significantly contract their lease office portfolios Infinite workplace enables work from anywhere to proliferate Digital online and mobile transactions have potential to break the broker commission fee model Office landlords must become more liberal in their thinking Landlords need to recognise that flexible use of space must be a principal asset management strategy The 10 year lease and bond-like structure will not be the only asset strategy  Flexible asset strategies complement traditional asset strategies Flexibility has value - the economic activity of an asset with flexibility can be higher than those just deploying traditional leases Occupiers need the ability to easily tap into the thousands of workspace options globally. Workplace Brand is going to become a fundamental part of commercial real estate Workplace is becoming a consumerized experience, and that will scale as employees come back from the pandemic with workplace choice and autonomy We're going to see people choosing their workplace based on trust, and that's where brand becomes important Brand creates trust in the experience that will be delivered Landlords who aren't conscious of the brand experience delivered across their portfolios will see a lag in their economic performance   About Mark Gilbreath Mark is the Founder and CEO of LiquidSpace, which he founded in 2010 and has raised $34.5m from investors, including Reid Hoffman of Greylock partners, Mike maples Jr. of gateway Fund, Roth capital partners, Shasta ventures, CBRE, Steelcase, and the GPT group. He holds a BSEE in Computer Architecture from the University of Virginia. His motto: More happy people working in fewer buildings, the planet smiles.  LiquidSpace invented real-time real estate and disrupted the traditional office industry. Its digital marketplace enables professionals, companies and real estate leaders to fluidly discover, transact, and manage workplaces on flexible terms and puts the commercial real estate buyer in control. The platform provides access to real-time office inventory on flexible terms with over 20,000 venue partners around the world. Sponsors Fortune Favours the Bold Bold merges property management & Space-as-a-Service to drive asset value and help office customers grow faster. Now part of NewFlex (www.workbold.co) Future Proof Your Portfolio with NewFlex NewFlex delivers and manages a range of branded solutions for every type of building, in every type of location, for every type of occupier. Including the flexibility to develop your own brand. All enabled by flexible management contracts where we are invested in making money for you. (www.newflex.com)   Launch Your Own Podcast A Podcast Company is the leading podcast production company for brands, organizations, institutions, individuals, and entrepreneurs. Our team sets you up with the right equipment, training, and guidance to ensure you sound amazing. (https://www.apodcastcompany.com and www.podcastsyndicator.com)   Subscribe to the #WorkBold Podcast Apple | Spotify | Google | Stitcher | Podbean

Episode 007 | December 22, 2020 One of Microsoft Research India’s goals is to help strengthen the research ecosystem and encourage young students to look at research as a career. But it is not always easy for students to understand what research is all about and how to figure out if research is the right career for them. The Research Fellow program at Microsoft Research India enables bright young students to work on real-world research problems with top notch researchers across the research lifecycle, including ideation, implementation, evaluation, and deployment. Many of the students who have been part of the program have gone on to become researchers, engineers and entrepreneurs. Today, we speak to Shruti Rijhwani, a graduate of MSR India’s Research Fellow program who is currently doing her PhD at the Carnegie Mellon University, and joining us is Dr. Vivek Seshadri, a researcher at MSR India who also heads the Research Fellow program at the lab. Shruti was a research fellow at MSR India in 2016, working on natural language processing models for code-switched text. She is currently PhD student at the Language Technologies Institute at Carnegie Mellon University. Stemming from her work at MSR India, she has continued research in multilingual NLP, with a focus on low-resource and endangered languages. Vivek primarily works with the Technology for Emerging Markets group at Microsoft Research India. He received his bachelor’s degree in Computer Science from IIT Madras, and a Ph.D. in Computer Science from Carnegie Mellon University where he worked on problems related to Computer Architecture and Systems. After his Ph.D., Vivek decided to work on problems that directly impact people, particularly in developing economies like India. Vivek is also the Director for the Research Fellow program at MSR India. For more information about the Research Fellow program, click here. Related Microsoft Research India Podcast: More podcasts from MSR India iTunes: Subscribe and listen to new podcasts on iTunes Android RSS Feed Spotify Google Podcasts Email Transcript Shruti Rijhwani: I think I credit my whole graduate school decision-making process, the application process, and even the way I do research in grad school to my experience as a Research Fellow in MSR India. Of course, the first thing was that I wasn't even sure whether I wanted to go to grad school, but after going through the Research Fellow program and with my amazing mentors and collaborators at MSR India, I took the decision to apply to grad school. [Music] Sridhar Vedantham: Welcome to the Microsoft Research India podcast, where we explore cutting-edge research that’s impacting technology and society. I’m your host, Sridhar Vedantham. [Music] One of Microsoft Research India’s goals is to help strengthen the research ecosystem and encourage young students to look at research as a career. But it is not always easy for students to understand what research is all about and how to figure out if research is the right career for them. The Research Fellow program at Microsoft Research India enables bright young students to work on real-world research problems with top notch researchers across the research lifecycle, including ideation, implementation, evaluation, and deployment. Many of the students who have been part of the program have gone on to become researchers, engineers and entrepreneurs. Today, we speak to Shruti Rijhwani, a graduate of MSR India’s Research Fellow program who is currently doing her PhD at the Carnegie Mellon University, and joining us is Dr. Vivek Seshadri, a researcher at MSR India who also heads the Research Fellow program at the lab. [Music] Sridhar Vedantham: OK, so I'm looking forward to this podcast because it's going to be a little different from what we've done in the past, in the sense that this is not a podcast about research projects or technologies, but it's something much more human, and we're going to be talking about the Research Fellow program that we have at MSR India. And I'd like to welcome a special guest- Shruti, who used to be a Research Fellow at the lab and also Vivek Seshadri, who is a researcher at the lab and whom we've had on the podcast earlier in a different capacity. But today he's wearing the hat of the czar or the director of the Research Fellow program here. So welcome, Shruti and Vivek. Vivek Seshadri: Good evening, Sridhar, and very good morning Shruti. Shruti Rijhwani: Hi Sridhar and Vivek, it’s great to be here and great to be back to interacting with people from MSR India. It's been about four years since I left the RF program, so I'm really looking forward to talking about it and remembering some of my experiences. Sridhar Vedantham: Excellent, so let's lay a little bit of a groundwork before we jump into the whole thing. Vivek can you give us a bit of an overview of what the Research Fellow program is. Vivek Seshadri: Sridhar, the Research Fellow program has been around ever since the organization Microsoft Research India started itself. I think initially it was called the Assistant Researcher program and then it was called the Research Assistant Program and right now we're calling it the Research Fellow program. But the core of the program has been to enable recent undergraduate and Master’s students to spend one or two years at MSR India and get a taste for what research in computer science looks like, especially in an industrial setting. Sridhar Vedantham: So has the program evolved over time, or have there been any substantive changes or it's still the same at its core and its essence? Vivek Seshadri: I think the only thing that has changed significantly is the number of research fellows that we have had. I think in the program started in its first year, I think we had had three assistant researchers, and today as we speak, we have over 50 Research Fellows in the lab working on various projects. So, in that sense, the program has definitely grown in size along with the lab, but I think the core goal of the program has not changed at all. It is still to give Research Fellows a taste of what research looks like in computer science and enable them to build their profile and prepare them for a career in computer science research and engineering. Sridhar Vedantham: Right, so one thing that I've seen personally is that the Research Fellows add a huge amount of energy and life to the lab. And on that note, Shruti, what motivated you to come into MSR India to join the Research Fellow program? Shruti Rijhwani: That's a great question and something that I think my experience is probably what a lot of Research Fellows who apply and join the program actually go through before deciding to join the program. So, I did an undergrad degree in computer science from BITS PILANI and during those four years I took classes on machine learning, information retrieval and so on, and also did two internships where I got a taste of like how machine learning applications can be applied to products in the real world. But both of those internships were kind of focused on the engineering side and I was really interested in what a career in doing machine learning research or using machine learning for research-based applications would look like. And I knew that if I wanted to pursue a career in this field, I would probably have to go to graduate school to get a Master’s and a PhD, but I wasn't entirely sure whether this is what I wanted to do, so it was kind of like an exploratory phase for me to be in the Research Fellow program. I wanted to get some research experience, I wanted to see what established researchers in computer science do on a daily basis, and what the research process kind of is like when you're working in machine learning, and more specifically in natural language processing, which is what I was interested in. Sridhar Vedantham: Right, so, Vivek, what I'm getting from Shruti is that, uh, the Research Fellow program is something that she is looking at to form a base or a basis for a longer career in research itself. So do you have any specific insights or inputs into about what the program actually offers in a structured manner to the Research Fellows that we have? Vivek Seshadri: Yeah, so Microsoft Research now at its core is a research organization. All researchers at MSR do research in computer science and they're working on a variety of projects spanning all areas of computer science, you know, from theory, artificial Intelligence, machine learning, systems, security and MSR India also is known for its Technology for Emerging Markets (TEM) Group where we look at, you know, problems specifically affecting developing countries like India. So, essentially, Research Fellows join one of these projects and work with world class researchers on multiple phases of research, including ideations, building solutions, prototyping those solutions, deploying them in the field, working with large real industrial datasets to test out their solutions. So that experience essentially gives the perfect taste of what modern computer science research looks like for Research Fellows, and just like Shruti most of our Research Fellows after their stint at MSR India apply for grad school and you know, go to one of the top grad schools across the world, but there are others who decide, you know, research is not for them. Many of them join Microsoft and continue to work at Microsoft in some, you know some other role. And a few of them actually, you know, have taken the entrepreneurial route. You know, we have had CEOs of many, many big companies, including Ola and some of our own projects which have been converted to startups like Digital Green and Everwell. So, you know, some of them take that route as well. But primarily it's that experience of what computer science research looks like today. I think that’s the essence of what the research program offers students. Sridhar Vedantham: Great and uh, in terms of numbers, how many Research Fellows do you think would have graduated so far from MSR India over the years? Vivek Seshadri: Like I said, you know, in the initial years it was handful of Research Fellows that we have So overall, if you look at the numbers, it's around 150 Research Fellows in a period of 15 years. But if you look at our run rate in the most recent years, we have been graduating close to 30 Research Fellows every year, and that number is just increasing. Sridhar Vedantham: Great, so this is another contribution of MSR to the research field, I guess. Vivek Seshadri: Absolutely, yeah. And you know these guys hit the ground running. You know, if they do choose to do a PhD, they hit the ground running. They know how research works. They know the different phases of, you know, research projects, how to go about tackling these problems. So, in that sense I'm assuming all the advisors of past Research Fellows are extremely happy advisors- little less work for them in actually guiding their students. Sridhar Vedantham: [Laughing] OK, I think we need to speak to some of the advisors privately to validate that. Vivek Seshadri: Yes. Sridhar Vedantham: So Vivek, another question for you. You know MSR India has also got this very large internship program. What's the fundamental difference between an internship at MSR and a Research Fellow position? Vivek Seshadri: MSR used to have a very vibrant three-month summer internship program and I think over the years what we have realized is that for any stint at MSR to benefit both the student and the research projects at MSR, you need that reasonable amount of time. So, if you see even the internship program, you know we have almost faded out three-month internships. We only offer six-month internships these days. So in that sense, the main difference between the traditional internship program and the Research Fellow program is that duration. You know when a Research Fellow comes in, we know that they're going to spend at least one year with us. In most cases, they are going to spend two years with us, which means the researcher, with confidence, can set a really big goal for the Research Fellow and you know, really have that long shot instead of, a short internship where to have any meaningful output, you know, you cannot have a really large vision or a large goal. So in that sense, if you actually see the contributions that Research Fellows have made to some of our projects, they are extremely substantial, solving some fundamental problems in computer science, impacting, projects in major ways within Microsoft and also having impact on society. These contributions would not be possible in a six-month internship program. [Music] Sridhar Vedantham: Shruti, when you were doing your Research Fellowship at MSR India, what is the kind of work you were doing and who were your mentors out here? Shruti Rijhwani: Right, so as I said, I was really interested in machine learning applications, more specifically as applied to natural language processing problems. So when I was a Research Fellow at MSR India, I was mentored by Monojit Choudhury and also worked closely with Kalika Bali on natural language processing problems. We were focusing on the problem of code switching, which is basically when multilingual people mix languages when they're speaking. we were basically trying to create natural language processing tools to automatically understand such code-mixed language. Sridhar Vedantham: And how do you think that helped you? I mean you are at CMU now, which is one of the top tier PhD schools in the world. But how do you think the time that you spent here in MSR India actually helped you get to where you are? Shruti Rijhwani: I think I credit my whole graduate school decision-making process, the application process, and even the way I do research in grad school to my experience as a Research Fellow in MSR India. Of course, the first thing was that I wasn't even sure whether I wanted to go to grad school, but after going through the Research Fellow program and with my amazing mentors and collaborators at MSR India, I took the decision to apply to grad school. And as I said, I was working on problems in multilingual natural language processing. And although I focused on code switching at MSR India, it kind of made me very interested in continuing in this field of just trying to be able to automatically process many, many languages at the same time and through my Masters and now my PhD, all of my research has been focused on doing multilingual NLP. So, in a way my experience at MSR sort of shaped my view of NLP research and taught me important research and technical skills, going all the way from like doing a literature survey to collecting data, doing experiments, and finally writing publications. I went through that process for the first time at MSR India, and it's like really helped me go through graduate school as well. Sridhar Vedantham: Great, so it sounds like you really worked hard while you were at MSR. Did you actually have some time to do something other than work, to kind of go out, have fun and enjoy yourself? Shruti Rijhwani: Yeah, I tried to keep a great work life balance at MSR India and in fact I think MSR and the Research Fellow program in general quite encourages that. We had a strong community of Research Fellows. We were all really good friends and it kind of makes sense because all of us were in the same exploratory phase of doing research for the first time, for most of us. So there's a lot we had in common, and all of us were good friends, enjoyed ourselves outside of work as well. So yeah, I really enjoyed my time at MSR. Sridhar Vedantham: I believe MSR India's also got this fantastic annual offsite which is a great deal of fun. Shruti Rijhwani: Definitely. I was a Research Fellow for one year and the offsite that year was really good fun. It's good to interact with people outside of work as well and learn about the people you collaborate with as people, not just colleagues. So I really enjoyed the MSR offsite and as Research Fellows, we also would often have our own outings like we would go out in the city and explore the city and so on. So it was - really fun. I really appreciated the community of Research Fellows that we had. Sridhar Vedantham: Super. Vivek, a question for you. What does the Research Fellow selection process look like? How do you actually go about it, and is there any particular way in which you look at matching candidates to mentors? Vivek Seshadri: Absolutely. I think in in many ways the Research Fellow selection process is similar to how grad school applications work. how universities select PhD students and there are multiple projects going on inside MSR India in different areas. Applicants have specific interests. You know, these days, even in the four years of undergrad that they go through, people develop interest in various areas, so they come in with their own interests. So our goal is to essentially identify the best candidates for each project. And like I mentioned, you know, it's not only the case that the number of Research Fellows slots have increased over the years from three in the first year to something close to 40 to 50 right now. It's also that the number of applicants has increased significantly. We receive close to 1000 applications and in some sense you know it’s a long review process where we ensure that each applicant at least gets one pair of eyes looking at the application and then determining whether there are projects within MSR India that suit that candidate, . we come up with extensive rankings and finally researchers go through that pool of applicants that we have ranked and figure out who the best candidate for their project is. Sridhar Vedantham: So, Shruti, if I were to ask you what the main takeaway is for you from the Research Fellow program, what would you say? Shruti Rijhwani: Well, there are a whole bunch, I really gained so much from this program. As I already said, you know it shaped my view of research and really gave me a good footing to start my journey through Graduate School with my Master’s and now my PhD. I would really recommend this program to anyone who is looking to get a little bit of experience in computer science research and if anyone wants to kind of explore this as a career option, I think this is a really good first step. Particularly because there are researchers in MSR India working on such broad fields in computer science. And just attending talks and having conversations about their research can really expand your view on computer science research and give you a really strong place to set your own career off in whatever field you're interested in. So I think that's my main takeaway. I really enjoy the community feeling in MSR India among the RFs as well as with the senior researchers in the lab. And just the fact that it helped me so much in Graduate School. I definitely recommend the program to anyone who has an inkling of interest in computer science research. Sridhar Vedantham: That's fantastic and I know for a fact that the people who are involved with the Research Fellow program and in general people at the lab really feel proud when, you know, people like you go through the program and then join some of the top organizations in the world. So Vivek, how do students apply for an RF position? And what's the kind of exposure that they can look at? I mean, I know we've been speaking to Shruti, who you know, kind of was focusing on one particular area, but in a more general sense, can you talk a bit about what students can expect when they come for a Research Fellow position here? Vivek Seshadri: Sridhar, if you look at computer science as a field in the past few years, it has become increasingly interdisciplinary. And Microsoft Research India being a flat organization, enables researchers for experts in different areas to sort of collaborate with each other and, you know, solve big problems that require such collaboration. In fact, in the past few years, if you have noticed we have had major impact in multiple problems where researchers from machine learning, systems, compilers and HCI have come together and offered big solutions to important problems. So in that sense, given where computer science is today and where it is going, I think MSR India is sort of an ideal place for new budding researchers to come and gain experience in what that interdisciplinary research looks like. In fact, as an RF, if I mean just like Shruti mentioned, even though they are working on a specific problem in a specific area, they will often not only have the opportunity to listen to people working in other areas through talks and lectures and whatnot, they may also have to actively collaborate with other Research Fellows working in these other areas. So that experience of interdisciplinary research is sort of essential for any budding scientists in computer science. So I think that's one of the main reasons why I feel MSR India is a great place for students to come and test what research in computer science looks like today. Sridhar Vedantham: And what's the process for somebody applying for the RF position? Vivek Seshadri: Yeah, like I mentioned, the application process is very similar to, you know, a grad school application. You know we do require students to upload their resume and a statement of purpose. There's a portal. People can just search for the Research Fellow program at MSR. In the Internet it will lead them directly to our page from where they can apply. There's a single deadline this time on January 15th (2021), which is right after you know grad school applications. So if students are applying to grad school, they already have all the material to apply for the Research Fellow program. Sridhar Vedantham: Great, so what I'll do is add links to the Research Fellow program. Will attach it to the podcast so that the listeners can actually go and check it out and see what the Research Fellow program offers. And Shruti and Vivek. Thank you so much for your time. I know that we're doing this in multiple time zones, so thank you so much for being accommodative. And it's been a great conversation. Vivek Seshadri: Likewise, Sridhar, thanks a lot. Shruti Rijhwani: Thanks, I had a great time. Sridhar Vedantham: Thank you, stay safe everybody.

Moore's Law, effect of Moore's Law, Intel 8080(first gen microprocessor), techniques to build contemporary microprocessors, performance balances and approaches of achieving increased speed performance. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app

Originally published November 7, 2018 An instruction set defines a low level programming language for moving information throughout a computer. In the early 1970’s, the prevalent instruction set language used a large vocabulary of different instructions. One justification for a large instruction set was that it would give a programmer more freedom to express the The post Computer Architecture with Dave Patterson Holiday Repeat appeared first on Software Engineering Daily.

Originally published November 7, 2018An instruction set defines a low level programming language for moving information throughout a computer. In the early 1970's, the prevalent instruction set language used a large vocabulary of different instructions. One justification for a large instruction set was that it would give a programmer more freedom to express the logic of their programs.Many of these instructions were rarely used. Think of your favorite programming language (or your favorite human language). What percentage of words in the vocabulary do you need to communicate effectively? We sometimes call these language features “syntactic sugar”. They add expressivity to a language, but may not improve functionality or efficiency.These extra language features can have a cost.Dave Patterson and John Hennessy created the RISC architecture: Reduced Instruction Set Compiler architecture. RISC proposed reducing the size of the instruction set so that the important instructions could be optimized for. Programs would become more efficient, easier to analyze, and easier to debug.Dave Patterson's first paper on RISC was rejected. He continued to research the architecture and advocate for it. Eventually RISC became widely accepted, and Dave won a Turing Award together with John Hennessy.Dave joins the show to talk about his work on RISC and his continued work in computer science research to the present. He is involved in the Berkeley RISELab and works at Google on the Tensor Processing Unit.Machine learning is an ocean of new scientific breakthroughs and applications that will change our lives. It was inspiring to hear Dave talk about the changing nature of computing, from cloud computing to security to hardware design.

Originally published November 7, 2018 An instruction set defines a low level programming language for moving information throughout a computer. In the early 1970’s, the prevalent instruction set language used a large vocabulary of different instructions. One justification for a large instruction set was that it would give a programmer more freedom to express the The post Computer Architecture with Dave Patterson Holiday Repeat appeared first on Software Engineering Daily.

Originally published November 7, 2018 An instruction set defines a low level programming language for moving information throughout a computer. In the early 1970’s, the prevalent instruction set language used a large vocabulary of different instructions. One justification for a large instruction set was that it would give a programmer more freedom to express the The post Computer Architecture with Dave Patterson Holiday Repeat appeared first on Software Engineering Daily.

The cloud: to come the full circle of computing, DcNet: A Data Center Network Architecture that supports live VM migration, and towards disaggregating the Software-defined networking (SDN) Control Plane. Prof. Douglas Comer is a Professor of Computer Science at Purdue University. He was the chair of DARPA's Distributed Systems Architecture Board. Prof. Comer has written a series of best-selling technical books on the Internet and Computer Networks, Operating Systems, and Computer Architecture. He is also a member of the Internet Hall of Fame. --- Send in a voice message: https://anchor.fm/scientificsense/message Support this podcast: https://anchor.fm/scientificsense/support

In the August 2020 edition of Communications of the ACM, West Linn, OR, USA-based author and journalist, Samuel Greengard wrote Neuromorphic Chips Take Shape. The available data Greengard had is the claim that a Caltech (California Institute of Technology) professor invented this technology, neuromorphic chips. In this Podcast, I discussed the efficacy of this research. On BitJetKit.com, Search 'Neuromorphic Chips' on the top-right search link. Image by FunkyFocus from Pixabay --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app Support this podcast: https://anchor.fm/bitjetkit/support

Welcome to the 19th episode of The CEO Story Podcast! With weekly podcasts releasing, "The CEO Story" takes a deep dive into the success (and sometimes pitfalls) of being your own boss! We encourage each and every individual to candidly share their stories to help other entrepreneurs understand the highs and lows that come with the journey.As always be sure to check out more of our podcast episodes:Podcast Website - https://ceostory.buzzsprout.comYoutube - https://www.youtube.com/channel/UCasaMQttGpdFnIMeWXER1SQWebsite - https://www.togethercfo.com/Give us a Like on Facebook - https://www.facebook.com/TogetherCFO/Like our LinkedIn Page - https://www.linkedin.com/company/together-cfoGive us a Follow on Instagram - @TogethercfoIn this episode, I had the pleasure of interviewing Ike Kavas. Ike is the CEO and Founder of Ephesoft. The company focuses on solving global process automation and data accessibility challenges.Ike Kavas has over 20 years of document capture, document management, workflow and systems engineer experience. His focus is to guide, innovate and expand the company's mission of turning the world's unstructured content into actionable data.His previous role was Chief Technology Officer at Ephesoft and he holds a patent on supervised machine learning for document classification and extraction. He achieved the CDIA+ certification and has been involved with hundreds of projects using products from EMC-Captiva, Kofax, Readsoft, TIS, OpenText, Microsoft and Xerox.He is a serial entrepreneur with three ventures and successful exits. He has not only the technical background by implementing several multi-million dollar projects for Fortune 100 companies but also has solid sales/business experience as he has achieved repeated financial and operational goals in his career.Ike earned his BS degree in Electrical and Electronics Engineering and studied Computer Architecture at Anatolia UniversityStay up to date with Ike:LinkedIn - https://www.linkedin.com/in/ikavas/Ephesoft Website - https://ephesoft.com/Ephesoft LinkedIn - https://www.linkedin.com/company/ephesoft-inc/Ephesoft Facebook - https://www.facebook.com/ephesoftEphesoft Twitter - https://twitter.com/ephesoft

David Patterson is a Turing award winner and professor of computer science at Berkeley. He is known for pioneering contributions to RISC processor architecture used by 99% of new chips today and for co-creating RAID storage. The impact that these two lines of research and development have had on our world is immeasurable. He is also one of the great educators of computer science in the world. His book with John Hennessy “Computer Architecture: A Quantitative Approach” is how I first learned about and was humbled by the inner workings of machines at the lowest level. Support this podcast by

  Episode 002 | March 20, 2020 Enabling Rural Communities to Participate in Crowdsourcing, with Dr. Vivek Seshadri Crowdsourcing platforms and the gig economy have been around for a while. But are they equally accessible to all communities? Dr. Vivek Seshadri, a researcher at Microsoft Research India, doesn’t think so, and is trying to change this. On this podcast, Vivek talks about what motivated him to focus on research that can help underserved communities, and in particular, about Project Karya, a new platform to provide digital work to rural communities. The word “Karya” literally means “work” in a number of India languages. Vivek primarily works with the Technology for Emerging Markets group at Microsoft Research India. He received his bachelor's degree in Computer Science from IIT Madras, and a Ph.D. in Computer Science from Carnegie Mellon University where he worked on problems related to Computer Architecture and Systems. After his Ph.D., Vivek decided to work on problems that directly impact people, particularly in developing economies like India. Related · Microsoft Research India Podcast: More podcasts from MSR India · iTunes: Subscribe and listen to new podcasts on iTunes · Android · RSS Feed · Spotify · Google Podcasts · Email Transcript Vivek Seshadri: If you look at crowdsourcing platforms today, there are a number of challenges that actually prevent them from being accessible to people from rural communities. The first one is, most of these platforms contain tasks only in English. And all their task descriptions, everything, is in English which is completely inaccessible to rural communities. Secondly, if you go to rural India today, the notion of digital work is completely alien to them. And finally, there is a logistical challenge here. Most crowdsourcing platforms will assume that the end-user has a computer and constant access to internet. This is actually a luxury in many rural communities in India even today. (Music plays) Host: Welcome to the Microsoft Research India podcast, where we explore cutting-edge research that’s impacting technology and society. I’m your host, Sridhar Vedantham. Crowdsourcing platforms and the gig economy have been around for a while. But are they equally accessible to all communities? Dr. Vivek Seshadri, a researcher at Microsoft Research India, doesn’t think so, and is trying to change this. On this podcast, Vivek talks about what motivated him to focus on research that can help underserved communities, and in particular, about Project Karya, a new platform to provide digital work to rural communities. The word “Karya” literally means “work” in a number of India languages. Vivek primarily works with the Technology for Emerging Markets group at Microsoft Research India. He received his bachelor's degree in Computer Science from IIT Madras, and a Ph.D. in Computer Science from Carnegie Mellon University where he worked on problems related to Computer Architecture and Systems. After his Ph.D., Vivek decided to work on problems that directly impact people, particularly in developing economies like India. (Music plays) HOST: Vivek, welcome to the podcast. Vivek: Thanks, Sridhar. This is the first time I am doing anything like this, so I am really excited and a little bit nervous. Host: Oh, I don't think there's anything to be nervous about really here. You guys are used to speaking in public all the time. So, I'm sure it'll be fine. Vivek, you are a computer scientist and you did your PhD in Computer Science in Systems, right? What made you gravitate towards research that helps underserved communities, typically the kind of research that one associates with the ICTD space? Vivek: So, Sridhar, when I finished my PhD in 2016, I sort of had two decisions to make- should I stay in the US or should I move back to India? Should I stay in the same area that I am doing research in or should I move to a different field? Both these questions were sort of answered when I visited MSR and had interactions with people like Bill Thies. The kind of research that they were doing impressed me and also influenced me to make the decision to come back to India and work on similar problems that directly impact people. Host: That's interesting. So this is something that was brought upon by meeting people in the lab here rather than something that was there in your mind all along. Vivek: Absolutely. Actually, when I started my PhD, I wanted to come back and become professor in places like IIT or IISc. And when I moved back, I was actually introduced to MSR by one of my friends who actually visited MSR before me. And I just thought I'll pay a visit. And the conversations that I had with people here, sort of made my decision absolutely easy. Host: And the rest is history, as they say. Vivek: Absolutely. It’s been three years since I moved here and I couldn't be happier. Host: Great. So Vivek, walk us through this project called Karya, which I know you have been associated with for quite a while. What exactly is project Karya and what are your goals with that project? Vivek: So, there are two trends that enables or motivates the need for a project like Karya. The first trend is that there is a digital revolution in the world today, where improvements in technologies like Machine Learning are allowing people to interact with devices using natural language. The second trend is specific to India where we are trying to push towards a digital future which is creating a lot of tasks like audio transcription, document digitization, etc. Both these trends are going to result in a huge amount of what we call digital work. And the goal for project Karya is to take this digital work and make it accessible to people from rural communities who typically have very low incomes today and are predominantly stuck with physical labor. We believe completing these digital tasks and getting paid for them will be a valuable source of supplemental income for people from rural communities. Host: Crowdsourcing and crowdsourcing platforms have been around for quite a while now. And they are also well-established methods of gig work. So what's the need for another approach or a different framework like Karya? Vivek: That's a great question. If you look at crowdsourcing platforms today, there are a number of challenges that actually prevent them from being accessible to people from rural communities. Specifically, let me describe to you three challenges. The first one is, most of these platforms contain tasks only in English. And all their task descriptions, everything, is in English which is completely inaccessible to rural communities. Secondly, if you go to rural India today, the notion of digital work is completely alien to them. In fact, when we went to rural communities in our first visit and told them we will actually pay some money for completing some set of digital tasks, they looked at us in disbelief. Like they actually didn't believe that we are going to pay them until we actually did. So, there is this huge issue of awareness. And finally, there is a logistical challenge here. Most crowdsourcing platforms will assume that the end-user has a computer and constant access to internet. This is actually a luxury in many rural communities in India even today. Host: So, does Karya enable people to use their existing skillsets and knowledge to earn supplemental or extra income? Vivek: So, Sridhar, like I mentioned, there are two sources of digital work that we are looking at currently. One is creating label data sets for models like automatic speech recognition, and other language-based machine learning models. The second source of digital work that we are looking at is things like speech transcription or document digitization, which the government is very extremely interested in. Now depending on what type of task we are going to do, people may have to be able to read in their regional language or type in their regional language. Now, when it comes to reading, we find that most people from rural communities are adept at reading in their regional language. When it comes to typing, as you can imagine there are not many good keyboards that will allow you to type in your local language. This is something that most people in rural communities have never done before. In fact, even though, most people in rural communities are not familiar with English, they actually use a very crude form of transliteration to actually communicate in their regional languages. That's what we observed- most people used WhatsApp and when communicating with each other they actually use transliteration in English and not type in their native language. Host: So, you are saying that there is a large number of people who are actually typing in the English script, but the language that they are representing is their own vernacular. Vivek: Exactly. And the transliteration is very crude. They know what sounds each English alphabet corresponds to and they just put together a bunch of characters next to each other and it's almost like they have created a whole new script for their local language. Host: Right. Vivek: But something like that wouldn't actually be useful for us. We would want them to type in their local language. For instance, let’s take an example of document digitization. The idea there is, the government has a whole of government records which contain hand-written words in their local language. It could be names of people, it could be addresses, etc. When I want to digitize these documents, I may actually want someone to type out the names that they see in the document in the local language. Now, there, I would actually want them to use the native script. And not, some crude form of transliteration. Host: Sure. Vivek: So, in this particular case, we actually used a keyboard that was developed by IIT Bombay called Swarachakra. And our users actually learnt to use that keyboard within a very short span of time and they were able to perform extremely well in the task that we had assigned them. Host: So, it sounds like there is a lot of work that is readily available. What is required is to actually deliver it and make it possible for people to leverage that work in order to earn extra income. Vivek: Absolutely. Actually, the government of India has its own crowdsourcing platform, where they outsource text digitization like I mentioned to anyone in India who wants to do it. Unfortunately, even that platform is not accessible to rural communities. If I go to rural India and ask anyone about that platform, they wouldn't know anything about it. So, in some sense, there is work that is readily available, but there is this huge gap in access. Host: And the gap in access is because these platforms work on their traditional paradigm of needing a desktop computer with an internet connection? Vivek: Exactly. In fact, the platform that the Government of India has, it’s a website that you have to access and you need internet connection to receive tasks and complete tasks. And our goal is to sort of eliminate that requirement. In fact, the goal of project Karya is to enable anyone with just a smartphone to be able to perform digital tasks on their phone. (Music plays) Host: I know you've already conducted some experiments with Karya. And you've also published a paper in Chi in 2019. Can you walk us through some of the results of the experiments that you've conducted? Vivek: So, one of the biggest challenges in creating a platform like Karya is the perceived lack of trust in rural labor. When we actually spoke to many potential work providers on whether they would be willing to outsource their work to rural workers, one of the first questions that they ask is if they can trust the quality of labor that we get from rural workers. So, in the Chi paper, what we wanted to sort of evaluate was the accuracy and effectiveness with which workers from rural India can actually complete a specific type of digital task. So, in that particular paper, we actually looked at text digitization, where the task is as simple as the user is shown an image of an hand-written text and all they had to do was type out whatever word they see in the particular image. And of course, they will be given thousands of images that they have to digitize over a period of two weeks. And what we actually found in the paper was that workers from rural India actually did fantastically well. In fact, in a crowdsource setting, they outperformed a professional transcription firm to which we gave the same data set. So, that was very interesting for us. Host: That’s really interesting. Do you have any insights into why that might have happened or, how this community of people that you engaged with were able to outperform professional services? Vivek: So, with respect to the performance of the transcription firm itself, we could only guess, because it was a black box for us. We just gave them the data set and asked them to provide the results and the results that we got were not that good. But we can definitely guess why workers from rural communities did so well. First of all, the additional income that workers from rural communities are getting out of completing these tasks is significant. So, for them there is actually a fear that they may not get paid if they don’t complete the tasks accurately. So, from that point of view, most users paid extreme attention to completing the tasks accurately. And these workers also found it a lot of fun. Like I mentioned before, most of their current work is typically physical labor, be it farming, many of them are actually unemployed. So, for them, this is actually a fun activity that they can do together with their friends where they also get some money. So, from their point of view, it was both fun and it gave them very very valuable supplemental income. I think both these were significant factors in the rural workers performing really well in the task that we gave them. Host: Your Chi paper was based on text digitization by members of rural communities. But have you looked at other types of tasks that can be completed through Karya? Vivek: Yes. Actually, as we were working on the platform, we realized that there is a real need for speech data sets in various languages in India. In fact, in our very lab, Kalika Bali, who is a researcher, is working on this project called Ellora, whose goal it is, is to create voice technologies for all the languages in India. One of the fundamental bottlenecks in achieving this is labeled speech data sets. A labeled speech data set is essentially a data set that contains various audio recordings, and the transcripts that correspond to those recordings. We actually found a mechanism to use Karya to collect such a data set for various languages. In fact, we have an ongoing study where we are collecting hundreds of hours of speech data for languages for which there is almost no data today. Host: So, when you give out these speech collection tasks, what is the actual process, how does it actually work? Vivek: So, at the lowest level, the task is essentially for the user to read out, record themselves reading out a sentence. However, to make the task more fun, we actually made them read out stories. Some empowering stories, some stories about history of our country, some stories about popular figures like Buddha, and users really liked reading out stories as opposed to reading out random bits of sentences. Host: So, we've been talking about Karya as a project in which we are helping or building a new paradigm in crowdsourcing. What are the actual components that go into Karya as a system? Vivek: So, Sridhar, if you look at any crowdsourcing platform that is out there today there are two major components. One is the server that actually contains all the tasks that have to be completed, that is the component that work providers interact with to submit the task that they want to get completed. The second component is actually the client that the workers will use to actually complete the tasks. In a typical crowdsourcing platform where internet connection is assumed, the client will directly talk to the server, get the tasks and the responses are also directly submitted to the server. Host: Right. Vivek: Now, like I mentioned, most rural communities in India do not have internet connectivity. In fact, two of the three locations that we have worked with have absolutely no connectivity. Which means a platform that assumes internet connectivity is going to exclude those people from participating in the platform and get paid for completing valuable tasks. Host: So, how do you bridge that? Vivek: So, the way we bridge this gap is by introducing this third component that we are calling a Karya Box. Now, the Karya Box is essentially a device that we will place in the village where we want to work with people. And you can think of the box as a local crowdsourcing server for that particular village. Host: Okay. Vivek: So, the Karya Box will essentially act as a local crowdsourcing server in the village where we have placed it. Users in the village can directly interact with the box through the Wi-Fi access point that the box will expose. So, anyone with a smartphone can just connect to the Karya box Wi-Fi and then interact with the box to get tasks and submit their responses as well. Now the question is, how does the box communicate with our server? Host: Yeah. Vivek: So, in most villages which do not have connectivity what we observe is there are definitely people who go to nearby cities for work or even to get digital content that they can get back to the village. What we need to do is to employ someone like that who can carry the box to a location where is internet connectivity, periodically, maybe once a day or even once a week. And at that instant, when the box gets connectivity to the server it can exchange, both the responses that have been submitted already by the rural workers and also get any new tasks for the village, if any. Host: That seems to be a smart and inexpensive way to get around the lack of connectivity issue. Vivek: Absolutely. Actually, I can tell you a story around this. Host: Oh, please, we love stories. Vivek: When we did our recent study, we actually deployed the box in the village. That village actually has really good connectivity. So, we were actually expecting the box to be in regular contact with our server. But due to various reasons, there was an internet shutdown in the village for the first one week after we deployed the box. But there you go. Our system actually worked because it does not assume that the box regularly talks to the server. Host: I am assuming and correct me if I'm wrong, that a lot of the people who are interacting with the system, the Karya app especially on the phone, right, they'd be doing something of this nature for the first time. How did people typically find working with the Karya app and were there significant hurdles, were there issues in the communities that you went and did your experiments with? Vivek: So, like I mentioned before, most people actually found doing this kind of an activity a lot of fun. So, from that point of view, there was not much boredom even though the tasks were extremely repetitive. Now imagine, looking at words screen after screen and typing them out or sentences screen after screen and reading them out. This is probably a very mundane task for people in urban communities. But for people in rural communities, where they don't get to do this kind of thing very often or even interact with a smartphone very often, they actually found it a lot of fun. In fact, many people actually found some sense of pride in actually completing tasks in their local language. (Music plays) Host: It seems like this kind of digital work has the potential over time to provide people with livelihoods and enhance existing incomes. Do you think there is a potential downside to digital work or a potential downside to the online gig economy? Vivek: Definitely, there is a limitation, similar to any other gig economy, like your, cab-hailing services where it's a physical gig work that you are doing, or delivering food, it's again a physical gig economy. As more people join the platform, the amount of work that is going to be available for every individual person is going to go down. So in that sense, one should not think of even the digital gig economy as a sustainable source of livelihood. So from that point of view, one of the limitations is the excitement that workers in rural communities have for such kinds of tasks. These tasks are much easier to complete than the task that they are involved in right now. And they also pay much higher than the task that they are doing right now. So there is definitely the possibility that some of them may think this is a much more lucrative job that will provide a full-time income for them. But we have to warn them in advance, saying, this is not the case. Host: So expectation setting is going to be key. Vivek: Expectation setting is, in fact, a huge part of what we need to do when we actually scale out the platform. In fact, even for the small studies that we conducted in these villages where studies were for a period of two weeks, during which time people may earn let's say 3000 rupees, their question at the end of the study is, "When are you going to come back?" Right? So, that sort of enthusiasm is both encouraging and scary. Because, if you don't have a sustainable source of work that you can provide to these villagers, it can end up in disappointment. Host: Was there anything that surprised you when you were working with and when you were talking to various communities during the experiments with Karya? Vivek: Yes. Actually, two things stood out for us. The first thing is, how inclusive the notion of digital work can be when it comes to employing people from diverse backgrounds. What we observed was, women who were typically not allowed to get out of their house in rural communities for various reasons were able to participate on our platform and actually earn income for the first time in their lives. People with physical disabilities were able to participate on our platform. Host: That must have felt extremely empowering for them. Vivek: Absolutely. And the second thing that we observed is like I mentioned before, this sense of pride that they had when they were completing tasks in their local language. Like I mentioned before, this is not something that they get to do often. In fact, in one of our studies where the task involved was recording themselves reading out stories, many people actually went over and did the tasks all over again, just so that they can read the stories to their kids or to the community. This is something that was completely surprising to us. Now imagine if someone in an urban community would actually be willing to do that. Host: Yeah. That's good food for thought. So it certainly seems like your experiments with Karya show that it's got a huge amount of promise and potential. Over time, where to you see or where do you hope to see Karya? Vivek: So Sridhar, like I mentioned, as language technologies keep improving the need for creating these technologies for various Indian languages is only going to increase. There are going to be many startups which would want data sets for creating the models that they want in local languages. We believe, with our insights and solutions that we have built for creating a crowdsourcing platform for rural communities, Karya can be the platform that these organizations, both private startups or even the government, can come to, to get their valuable task competed. Host: Vivek, this has been an extremely interesting conversation. Thank you for your time. Vivek: Thanks a lot, Sridhar for giving me this opportunity to both talk about the project and also do my first podcast. Host: My pleasure. To learn more about Dr. Vivek Seshadri, the Technology for Emerging Markets Group, visit Microsoft Research India.  

In this ep, we catch you guys up with what's been going on with us ever since we did not upload for a few weeks and then uploaded an old episode, including going to New York and stuff. We also talk about octaves, computer architecture, reveal how knowledgeable we are, and became god. We also talk about Filthy Frank/Joji so you guys gotta listen to the whole thing to know what we're talking about. -Arta

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An instruction set defines a low level programming language for moving information throughout a computer. In the early 1970’s, the prevalent instruction set language used a large vocabulary of different instructions. One justification for a large instruction set was that it would give a programmer more freedom to express the logic of their programs. Many The post Computer Architecture with Dave Patterson appeared first on Software Engineering Daily.

An instruction set defines a low level programming language for moving information throughout a computer. In the early 1970’s, the prevalent instruction set language used a large vocabulary of different instructions. One justification for a large instruction set was that it would give a programmer more freedom to express the logic of their programs. Many The post Computer Architecture with Dave Patterson appeared first on Software Engineering Daily.

Dr. Witty earned a PHD in Computer Science from the Illinois Institute of Technology and is an Associate Professor at the University of Nebraska-Lincoln and prior to that was a researcher at Iowa State University. Dr. Witty grew up in Thailand and has had many jobs prior to becoming a professor, he worked in restaurants, as a mechanic, and as a translator and speaks Thai and English. One of Dr. Witty’s core strengths is always being curious on how things works. His undergraduate degree is in Philosophy and after buying a $3000 computer in 1994, he decided he wanted to learn how they worked so he took a class in Computer Architecture, specifically for what he wanted to know and that got him hooked. He had no real background in programming languages and was difficult and challenging. He received a lot of mentorship and guidance from Dr. Morris Chang, a professor at the University of South Florida. One of the main reasons Dr. Witty got his PHD is that he likes to educate people. What really has Dr. Witty fired up is AI and now having compute power to really implement the dreams of AI. Many time students come into college with one idea and then end up changing, college allows you to change. Many students lack clarity on what they want, but don’t quit college because there are classes you don’t like it helps to build who you are. If you decide to get your masters, one thing that is different is all the students there tend to be very smart and one of the main differences between grad students is some have perseverance and grit and major challenges do not get them down, and that is a critical trait to be successful. Dr. Witty’s best advice is to have clarity in what you do and a personal habit for success is being detailed orientated. His favorite phone app is YouTube and the book he recommends is Outliers by Malcom Gladwell You can get a free book from Audible at www.stemonfirebook.com and can cancel within 30 days and keep the book of your choice with no cost. Free Audio Book from Audible.

The 1990s were when computers really entered the mainstream of architecture. The rise of personal computing, with wider access to inexpensive machines, the world wide web, advances in software and hardware, all took place against the background of global political transformation that at the time was theorised as the End of History, the breakup of the Soviet Union, democratisation, and the apparent rise of a single, global, liberal capitalist world order. But the exploration of CAD, rendering, generative design and CNC manufacture would all be theorised through a pre-existing set of ideas and agendas, drawing heavily on ‘French theory’ — Derrida, (and particularly) Deleuze — and a partially pre-digested blend of complexity mathematics. We find ourselves — among the blobs, deformed surfaces, landscapes and evolutionary forms — in a world of ‘affective singularities’, ‘the Fold’, pliancy, Catastrophe Theory… We talk technology, key actors, and attempt a glossary of key concepts… Under discussion —  — Frank Gehry’s fish sculpture — Revit / BIM — The F117 and B2 defense projects — Peter Eisenman — John Frazer — MIT Computer Lab — the Bilbao Guggenheim — Cardiff opera house — Yokohama ferry terminal — NOX’s Freshwater and Saltwater pavilions — The Affective — Catastrophe Theory — D’Arcy Thompson — The Fold — Singularity — Max Reinhardt Haus — Phallogocentrism & Helene Cixous Recordings are from Peter Eisenman’s Lecture ‘Architecture in the Age of Electronic Media’ (1993) (AA archive)[https://www.aaschool.ac.uk//VIDEO/lecture.php?ID=737] Music — Lee Rosevere ‘Quizitive’ Lee Rosevere ‘Curiosity’ Lee Rosevere ‘Thoughtful’ all from (Free Music Archive)[freemusicarchive.org] Clips of —  Awesome 3 ‘Don’t Go’ (1992) Liquid ‘Sweet Harmony’ (1992) 2 Bad Mice ‘Bombscare’ (1992) M.A.N.I.C ‘I’m Coming Hardcore’ (Original Mix) (1991) *Support the show on Patreon to receive bonus content for every show. *Follow us on twitter // instagram // facebookWe’re on the web at aboutbuildingsandcities.orgThis podcast is powered by Pinecast.

Hajime Morita さんをゲストに迎えて、ドキュメント、キーボード、CPU、自作言語処理系などについて話しました。 スポンサー: Ergodox EZ Show Notes Perl Toolchain Summit 2018 – Tatsuhiko Miyagawa’s Blog Essential Admits the Essential Phone Has a Bad Camera Misreading Chat – Nonsensical CS Paper Talk by Morrita and Mukai Anchor Jeff Bezos makes Amazon execs read 6-page memos in meetings ErgoDox EZ: An Incredible Mechanical Ergonomic Keyboard ★ Community Blog - 握力王 vs 日本男児 ヘルシーすぎるプログラマ対談 Tesla Autopilot Chief Jim Keller Leaves for Job at Intel Computer Architecture, Sixth Edition XLA Overview TensorFlow Tensor Comprehensions Swift for TensorFlow project home page The Julia Language PyTorch Why Swift For TensorFlow KotlinConf 2017 - My Life as a Tech Transfer Monad by Erik Meijer 巨象も踊る Papers We Love 10 Key Points of Ruby Development

Today's emerging neural computing substrates have their origins in either biology (spiking neural networks, like IBM's TrueNorth), or machine learning (deep convolutional networks, like Google's TPU). There are glaring gaps between these two approaches, since they differ dramatically in terms of architecture, efficiency, usability, and practical applicability to real-world tasks. Deep neural networks, which are based on the nonlinear perceptron neuron model, have recently emerged as a very powerful tool for classifying spatial inputs, such as complex, real-world image data. DNNs re-evaluate the entire network at every time step, performing either convolutions or matrix-vector multiplications for each layer, requiring massive amounts of compute time and memory to train and process, since there can be millions of parameters that need to be learned and retained for the networks to achieve high rates of accuracy. In contrast, spiking neural networks can be very energy efficient, because they are fundamentally event driven, leading to an efficiency gap between these approaches.However, spiking networks suffer from a dearth of effective approaches for configuring and/or training these networks to perform tasks with practical value. The semantic limitations of simplified hardware spiking neurons chip can make deployment of applications with a biological inspiration challenging, leading to a semantic gap. Similarly, numerical applications require many ad hoc changes to map to such substrates, leading to an algorithmic gap. Finally, emerging technology may provide a much more efficient substrate for these algorithms, creating a technology gap.

David Schaffer is a world-class researcher in Computer Architecture. He received his Ph.D. from Stanford and then moved to Sweden with his family. He is currently a senior researcher in the Uppsala Architecture Research Team working among a group of curious minds from around the world. Recently, David started the Scalable Learning Project, a platform to "flip the classroom", making teaching and learning interactive. Students not only love it, they also perform much better. ----- Do you enjoy this podcast?  If so, please leave your comment and share the podcast with your family and friends. Your support will keep us on track and bring many other sung and unsung heroes to this podcast. Feisworld Podcast is now available on all major channels including iTunes, Google Play, SoundCloud, Stitcher. An honest podcast review will help us tremendously. Please consider providing yours on iTunes.   Like us on Facebook  Follow us on Twitter --- Send in a voice message: https://anchor.fm/feisworld/message Support this podcast: https://anchor.fm/feisworld/support

Overview of computer architecture, profiling a program, and a set of example programs. Student performance on project 1 is also discussed.

Eugene provokes us to question some assumptions related to computer architecture, the definitions of security, and how best to build trusted systems. Are current methods of defining security appropriate? How might we better design a system to be secured? A great deal of the trust we think we can place (or not) in our computing systems is based on experience with the ones we commonly use. However, those computing systems continue to be victimized by a variety of failures and attacks. Perhaps some of the 'common knowledge' on which we base our designs is itself faulty? Perhaps we are employing concepts that should be re-examined? In this talk, Eugene provokes the audience to question some assumptions related to computer architecture, the definitions of security, and how best to build trusted systems. In particular, we should question if the current methods of defining security are appropriate, how we might better design a system to be secured, and whether we understand the appropriate tradeoffs when paying for heightened trust. Professor Eugene H. Spafford is one of the most senior and recognized leaders in the field of computing. He has an on-going record of accomplishment as a senior advisor and consultant on issues of security and intelligence, education, cybercrime and computing policy to a number of major companies, law enforcement organizations, academic and government agencies. This talk is a Keynote from the TRUST 2009 Conference (University of Oxford, April 2009) which focused on trusted and trustworthy computing, both from technical and social perspectives.

How do we build trustworthy hardware, and how can we use that to increase the trustworthiness of broader distributed computation? Sean presents some things he's learned, some things he wishes he had done differently, and some things he'd still like to do. How do we build trustworthy hardware, and how can we use that to increase the trustworthiness of broader distributed computation? These questions have followed Sean through a variety of venues in his career so far: academia, government, start-up, large industry, and academia again. In this talk, Sean presents some things he's learned, some things he wishes he had done differently, and some things he'd still like to do. Professor Sean Smith has been working in information security - attacks and defenses, for industry and government - since before there was a Web. His current work, as PI of the Dartmouth PKI Lab, investigates how to build trustworthy systems in the real world. This talk is a Keynote from the TRUST 2009 Conference (University of Oxford, April 2009) which focused on trusted and trustworthy computing, both from technical and social perspectives.

Eugene provokes us to question some assumptions related to computer architecture, the definitions of security, and how best to build trusted systems. Are current methods of defining security appropriate? How might we better design a system to be secured? A great deal of the trust we think we can place (or not) in our computing systems is based on experience with the ones we commonly use. However, those computing systems continue to be victimized by a variety of failures and attacks. Perhaps some of the 'common knowledge' on which we base our designs is itself faulty? Perhaps we are employing concepts that should be re-examined? In this talk, Eugene provokes the audience to question some assumptions related to computer architecture, the definitions of security, and how best to build trusted systems. In particular, we should question if the current methods of defining security are appropriate, how we might better design a system to be secured, and whether we understand the appropriate tradeoffs when paying for heightened trust. Professor Eugene H. Spafford is one of the most senior and recognized leaders in the field of computing. He has an on-going record of accomplishment as a senior advisor and consultant on issues of security and intelligence, education, cybercrime and computing policy to a number of major companies, law enforcement organizations, academic and government agencies. This talk is a Keynote from the TRUST 2009 Conference (University of Oxford, April 2009) which focused on trusted and trustworthy computing, both from technical and social perspectives.

How do we build trustworthy hardware, and how can we use that to increase the trustworthiness of broader distributed computation? Sean presents some things he's learned, some things he wishes he had done differently, and some things he'd still like to do. How do we build trustworthy hardware, and how can we use that to increase the trustworthiness of broader distributed computation? These questions have followed Sean through a variety of venues in his career so far: academia, government, start-up, large industry, and academia again. In this talk, Sean presents some things he's learned, some things he wishes he had done differently, and some things he'd still like to do. Professor Sean Smith has been working in information security - attacks and defenses, for industry and government - since before there was a Web. His current work, as PI of the Dartmouth PKI Lab, investigates how to build trustworthy systems in the real world. This talk is a Keynote from the TRUST 2009 Conference (University of Oxford, April 2009) which focused on trusted and trustworthy computing, both from technical and social perspectives.

Now that the IT industry is urgently facing perhaps its greatest challenge in 50 years, and computer architecture is a necessary but not sufficient component to any solution, this talk declares that computer architecture is interesting once again.