Podcasts about anna university

Anna University sexual assault sparks political slugfest. BJP's Annamalai whips himself in protest

Vikatan Imperfect Show is a unique political satire program that tackles local, national, and international current affairs in an engaging and witty manner. Through sharp humour and insightful commentary, the show presents a satirical take on the latest news and political events, making complex issues more accessible and entertaining for the audience. With its clever blend of humour and thought-provoking analysis, the show has gained a massive following on YouTube, attracting viewers who appreciate its distinctive approach to current affairs. Whether it's breaking news, political controversies, or global happenings, Vikatan Imperfect Show brings a fresh perspective, using satire as a tool to provoke thought and encourage meaningful discussions. Its ability to simplify and entertain has made it a go-to show for many who seek both entertainment and a deeper understanding of the world around them.

This is the Catchup on 3 Things by The Indian Express and I'm Flora Swain.Today is the 26th of December and here are the headlines.A roadside biryani vendor, Gnanasekaran, was arrested in Chennai for allegedly sexually assaulting a student at Anna University's campus on Monday night. The arrest led to a political uproar, with BJP and AIADMK accusing Tamil Nadu's ruling DMK of ties to the accused. However, the DMK denies any association. The attack reportedly occurred around 8 pm when the student was in a secluded area of the 180-acre campus, chatting with a friend. Authorities are investigating the case while the political parties continue their accusations.At a Patna event commemorating the life of former Prime Minister Atal Bihari Vajpayee, a protest erupted when folk singer Devi performed the line "Ishwar Allah tero naam" from the bhajan "Raghupati Raghav Raja Ram." Protesters interrupted the performance, claiming it was inappropriate. BJP leader Shahnawaz Hussain condemned the disruption, calling it "the height of intolerance." The song, which has been closely associated with Mahatma Gandhi, was being sung as part of a tribute to Vajpayee, leading to tensions during the event.Aam Aadmi Party (AAP) national convener Arvind Kejriwal expressed frustration with Congress over complaints filed against AAP leading up to Delhi's 2025 elections. Kejriwal criticized Congress for alleging AAP was anti-national despite seeking its help during campaigning. Delhi CM Atishi questioned why Congress formed an alliance with AAP if they had such doubts. She accused Congress leaders in Delhi of aiding BJP in the upcoming polls and possibly making secret pacts to harm AAP's electoral prospects.Telangana Chief Minister A Revanth Reddy met with major figures from the Telugu film industry on Thursday, rejecting their demand for increased movie ticket prices. Reddy stressed the importance of respecting the law and not offering any more concessions for film screenings. He also urged industry leaders to support government campaigns against drugs, promote women's safety, and help with ecotourism and temple tourism initiatives. The meeting followed concerns over a stampede during the premiere of "Pushpa 2," which tragically killed a woman.In Gaza, five Palestinian journalists were killed in an Israeli airstrike on Thursday, according to local authorities. However, the Israeli military stated that the airstrike targeted a vehicle carrying Islamic Jihad militants. The journalists were reportedly in a broadcast vehicle outside Al-Awda Hospital in the Al-Nuseirat refugee camp when the attack occurred. The Palestinian Journalists Union confirmed their deaths, which were part of a series of airstrikes that also killed at least 16 others. This violence comes as ceasefire talks remain stalled after months of fighting.This was the Catch Up on 3 Things by The Indian Express.

Vikatan Imperfect Show is a unique political satire program that tackles local, national, and international current affairs in an engaging and witty manner. Through sharp humour and insightful commentary, the show presents a satirical take on the latest news and political events, making complex issues more accessible and entertaining for the audience. With its clever blend of humour and thought-provoking analysis, the show has gained a massive following on YouTube, attracting viewers who appreciate its distinctive approach to current affairs. Whether it's breaking news, political controversies, or global happenings, Vikatan Imperfect Show brings a fresh perspective, using satire as a tool to provoke thought and encourage meaningful discussions. Its ability to simplify and entertain has made it a go-to show for many who seek both entertainment and a deeper understanding of the world around them.

Abhilash Kantamneni (Abhi) is an Efficiency Canada research manager specializing in energy poverty and low-income energy efficiency. His community-based approach to energy efficiency, civic engagement and capacity building has earned him wide recognition including being named a ‘40 Under 40 Energy Leader' by the Midwest Energy News and a Canada Storyteller Award by SSHRC-CRSH. Abhi has a Master of Science in Physics, and in Computer Science from Michigan Tech, and a Bachelor of Engineering in Electrical Engineering from Anna University. Resource list. https://canoefm.com/wp-content/uploads/2024/03/PH-Resource-List-for-Energy-Poverty-and-the-Climate-Emergency-Final-Mar-14-2024.pdf

Do you like to consider yourself a values-driven leader? Do you wonder how to assess how you're doing?My guest today on The Courage of a Leader podcast is Raj Echambadi. We delved into how he thinks about and practically demonstrates values that inspire and engage others.Raj is the President of Illinois Institute of Technology and has a principle-driven vision for the institute and he shares with us how he thinks about and practically demonstrates values that inspire and engage others.You'll enjoy, be impressed and be inspired by what Raj has to say and how he says it.This is not an episode to miss!About the Guest:Raj Echambadi became the 10th president of Illinois Institute of Technology in August 2021. Echambadi's vision for Illinois Tech is centered on a new path to preeminence driven by four principles: first, honoring and strengthening the university's role as an engine of opportunity and a national leader in economic mobility; second, pursuing growth through reimagining education to serve learners at all stages of life; third, fueling future innovation by empowering students; and fourth, exemplifying purpose-driven citizenship in service of the Bronzeville neighborhood, Chicago, and the world.Previously, Echambadi served as the dean of D'Amore-McKim School of Business at Northeastern University. Before joining Northeastern, Echambadi served in various roles, including as senior associate dean of strategic innovation, at Gies College of Business at the University of Illinois at Urbana-Champaign, where he was a driving force behind a scaled online M.B.A. (iMBA) program that was lauded as one of the best educational innovations in the past decade. Echambadi received his bachelor's degree in mechanical engineering from Anna University in India and a doctorate in marketing from the University of Houston. His academic research focuses on strategic innovation within organizations and how firms should balance current and future opportunities. He has won numerous teaching and research accolades including the prestigious Academy of Management Journal Best Paper Award for his work on employee entrepreneurship. About the Host:Amy L. Riley is an internationally renowned speaker, author and consultant. She has over 2 decades of experience developing leaders at all levels. Her clients include Cisco Systems, Deloitte and Barclays.As a trusted leadership coach and consultant, Amy has worked with hundreds of leaders one-on-one, and thousands more as part of a group, to fully step into their leadership, create amazing teams and achieve extraordinary results. Amy's most popular keynote speeches are:The Courage of a Leader: The Power of a Leadership LegacyThe Courage of a Leader: Create a Competitive Advantage with Sustainable, Results-Producing Cross-System CollaborationThe Courage of a Leader: Accelerate Trust with Your Team, Customers and CommunityThe Courage of a Leader: How to Build a Happy and Successful Hybrid Team Her new book is a #1 international best-seller and is entitled, The Courage of a Leader: How to Inspire, Engage and Get Extraordinary Results.www.courageofaleader.comhttps://www.linkedin.com/in/amyshoopriley/ Link mentioned in the podcastThe Inspire Your Team assessment (the courage assessment): https://courageofaleader.com/inspireyourteam/ Thanks for listening!Thanks so much for listening to The Courage of a Leader podcast! If you got inspired and/or got valuable...

Dr. T S Subbaraman holds a doctorate in Physics and was a former Head of the Physics department at Anna University, Chennai. Though his specialisation is Physics, his heart favours Tamil. He had been passionate about Tamil theatre. He has performed on stage from the age of nine. He has also performed in various TV and radio dramas. He has the credit of making the science show "Maanudam ventradu," which was aired in All India Radio for three continuous years. In recognition of Dr. Subbaraman's passion for Tamil, Anna University appointed him as the first Director of the Centre for Development of Tamil in Engineering and Technology in 2001. - Dr.T. S. சுப்பராமன் இயற்பியலில் முனைவர் பட்டம் பெற்றவர், சென்னை அண்ணா பல்கலைக்கழகத்தில் இயற்பியல் துறை முன்னாள் தலைவராக இருந்தவர். இது அவரது ஒரு பக்கம். அவரது சிறப்பு இயற்பியலாக இருக்கலாம், ஆனால் அவரது ஆர்வம் தமிழ் மொழி மீது தான். டாக்டர் சுப்பராமன் ஒன்பது வயதிலிருந்து தமிழ் நாடகங்களில் நடித்துள்ளார், பல்வேறு தொலைக்காட்சி மற்றும் வானொலி நாடகங்களில் நடித்துள்ளார். அவரது அறிவியல் நாடகம் மூன்று ஆண்டுகள் தொடர்ச்சியாக ஆல் இந்தியா ரேடியோவில் ஒலிபரப்பப்பட்டது. இவரது தமிழ் ஆர்வத்தை உணர்ந்த அண்ணா பல்கலைக்கழகத்தினர், 2001 ஆம் ஆண்டு பொறியியல் மற்றும் தொழில்நுட்ப தமிழ் வளர்ச்சி மையம் நிறுவப்பட்டபோது அதன் முதல் இயக்குனராக நியமித்தனர்.

Kumar Gajmer is the Product Manager and the Technical Lead for the Bhutan National Digital Identity (NDI) Project. He started his career in IT in 2008 as a Software Engineer. After completion of his high school in Bhutan, he did his bachelor's in Information Technology from Anna University, India. Pallavi Sharma leads Marketing and Communications for the Bhutan National Digital Identity (NDI) Project. As part of the role, she drives media, public relations, and education campaigns to accelerate adoption of the Bhutan NDI digital wallet. She also works in close liaison with national and international stakeholders for enhanced product positioning and visibility. About Podcast Episode Read more about the episode by heading to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://northernblock.io/podcasts/bhutan-national-digital-identity-ndi-what-it-takes-for-a-nationwide-launch⁠⁠⁠⁠⁠⁠ The full list of topics discussed between Kumar, Pallavi and Mathieu in this podcast episode include, Project Goals and Context - What were the overall goals of the Bhutan NDI project, and how do they relate to the specific context and needs of Bhutan? Financial Inclusion and Digital Identity - How does focusing on financial inclusion as a starting point influence the approach to digital identity in Bhutan? Decentralized Architecture Decision - What research and considerations led to the choice of a decentralized architecture for Bhutan's digital identity program? Legal Framework and Privacy - How is privacy integrated into Bhutan's legislation, and what legal adjustments were made to accommodate digital identity? Legislative Process Duration and Challenges - What was the timeline and were there any significant challenges in developing the National Digital Identity Act? Governance and Public-Private Partnership - What does the governance body for the NDI look like, and how does the public-private partnership model function? Business Strategy and Ecosystem Growth - How were use cases developed, and what strategies were employed to grow the ecosystem and foster public-private partnerships? Voluntary Participation - Is participation in the digital ID system optional for Bhutanese citizens? Use Case Categorization - How are use cases categorized and prioritized within the digital identity framework? Foundational Identity Credential - What does the foundational identity credential look like, and what government records form its basis? Private Sector Collaboration - What challenges were faced in educating and gaining buy-in from the private sector for the new digital identity infrastructure? Private Sector as Credential Issuers - Are there concerns from the private sector about the risks associated with becoming credential issuers? Technology and Wallet Infrastructure - Why was a decision made to develop a specific wallet for Bhutan's NDI instead of using existing wallet infrastructures like Apple or Google Wallet? International Standards and Compatibility - How were international standards considered in the development of Bhutan's digital identity infrastructure to accommodate foreigners? Where to find Kumar? LinkedIn: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/kategio/⁠ X/Twitter: ⁠⁠⁠⁠⁠⁠⁠https://twitter.com/KateGiovacchini⁠ Where to find Pallavi? LinkedIn: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/andrew-johnson-web-dev/⁠ X/Twitter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/Andere_Andrew⁠ Follow Mathieu Glaude X/Twitter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/mathieu_glaude⁠⁠ LinkedIn:⁠⁠ ⁠⁠⁠⁠https://www.linkedin.com/in/mathieuglaude/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Website:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://northernblock.io/

This episode of "40 Under 40 Global Change Leaders" features the incredible Mythili Sarathy. An IIM Bangalore alumna and Anna University graduate, Mythili boasts a stellar track record in transportation, oil & energy, telecom, and IT. Leading business strategy, marketing, IT, and HR, she drives growth through diversification, brand building, and change management. Mythili excels in coaching, talent management, Pre-sales, and more.  In this episode, Mythili imparts invaluable insights on the significance of inspiring and influencing as essential leadership qualities during times of change, as well as the art of taking risks.

    Sengavi Thirupathy  is the Senior Decarbonization Analyst responsible for managing project progress and deadlines, facilitating team meetings, and assisting the Associate Director of the Decarbonization team. Additionally, she serves as the QA QC lead for Energy Modeling scopes, the energy modeling training lead for the Decarbonization department, and Decarbonization lead participating in the VIM initiative. Sengavi graduated from Anna University, Chennai, India in May 2016 with a Bachelor of Technology in Chemical Engineering and completed her Master's in engineering in Energy Systems from the University of Illinois, Urbana-Champaign. Previously, Sengavi has worked on over 10 Net zero energy building design and modeling and 3 Net zero carbon projects. Sengavi has worked on various sectors such as medical office buildings, schools, and animal houses, semiconductor manufacturing units, multifamily residential buildings, automobile manufacturing buildings, data centers and office buildings. Sengavi has worked on Energy Audits, Utility incentive program management and grid carbon assessments as well.   Show Highlights A senior decarbonization analyst shares everything you need to know about decarbonization energy modeling, high performance buildings, and so much more. Working with the mandates surrounding energy efficiency and energy modeling for green building.  How to successfully shift your majors to work with your passion.  Sengavi shares her successful shift from chemical engineering into complete energy systems in the civil and architecture test side. High level tips on what really affects an energy model.  Useful tools like IES, Energy Plus, Energy Pro and eQuest to learn the ecosystem is an open source to use for energy modeling. Include passive strategies in your design, construction or existing buildings to reduce the need to bring in energy. Adaptability and grid harmonization will drive all of the design in the future.  Understanding the challenges with existing buildings vs new construction in energy modeling.   “I feel like buildings need to adapt to all of the things that nature is throwing at us right now. Adaptability and grid harmonization is what is going to drive all of the design in the future. The grid is becoming cleaner, and so how is your building going to adapt to it?” -Sengavi Thirupathy      Show Resource and Information Connect with Charlie Cichetti and GBES   GBES is excited our membership community is growing. Consider joining our membership community as members are given access to some of the guests on the podcasts that you can ask project questions. If you are preparing for an exam, there will be more assurance that you will pass your next exam, you will be given cliff notes if you are a member, and so much more. Go to to learn more about the 4 different levels of access to this one-of-a-kind career-advancing green building community!   If you truly enjoyed the show, don't forget to leave a positive rating and review on .  We have prepared more episodes for the upcoming weeks, so come by again next week! Thank you for tuning in to the !   Copyright © 2023 GBES

#nvidia #omniverse #digitaltwin #industrial #metaverse #xrom #podcast Mukundan Govindraj is the principal solutions architect at NVIDIA-Omniverse & he has over 14 years of experience in immersive technologies industrial metaverse, digital twins, computer vision algorithms, and real-time 3D solutions, he has built & led 500+ digital twin and metaverse experiences with a strong foundation in game engines, design principles, UI/UX, web technologies and Computer-generated imagery pipeline. Having built and led 500+ digital twin and metaverse experiences in the field of aerospace, architecture, energy, education, healthcare, media and entertainment, manufacturing, military, industrial, law enforcement, media, retail sector and ++. Have conceptualized and led the complete design, development and deployment of large-scale metaverse platforms both on-prem and on-cloud. His areas of research around Metaverse: AI in Metaverse, AR-based assembly line explorations, Crime Scene investigation in VR, Diagnostic, and rehabilitation VR system for low vision syndrome, Generative AI for 3D assets, NERF, Photogrammetry, R&D in MR-assisted liver surgery, Spherical dome projection Member of the syllabus committee board of Anna University. Tech Speaker at several respected forums and universities on the topic of AI and Metaverse around the world. NVIDIA Omniverse- is a scalable, multi-GPU real-time reference development platform for building and operating metaverse applications and based on Pixar's Universal Scene Description and NVIDIA RTX™ technology. https://in.linkedin.com/in/gmukundan https://twitter.com/elixir_bash https://www.nvidia.com/en-us/omniverse/ https://developer.nvidia.com/nvidia-omniverse-platform https://www.linkedin.com/posts/gmukundan_omniverse-metaverse-immersiveleaks-activity-6894946132103966720-6ptY XROM- Home of Extended Reality India's 1st AR/VR Focussed Podcast Kindly subscribe to our youtube channel www.youtube.com/xrompodcast Music Credit: Adam Avil Track Title: Shiv

Usually when you hear about meat's connection to methane, it's about all the methane that cows are emitting into the atmosphere, accelerating climate change. What if, however, you could capture methane before it goes into the atmosphere, and feed it to microbes which in turn convert it into protein-packed ingredients to make alt-meat? Sounds like magic, but it's not magic, it's science! And it's a science that Dr. Ezhil Subbian and her team at String Bio are advancing right now. The India-based company in 2022 closed its $20 million Series B round and is now scaling up to commercialize its microbial protein ingredients. In this interview, Dr. Subbian and I talk about how she started the company, why she moved it from Silicon Valley to Bangalore, India, where they get the methane to feed their microbes, and much more. It's a fun conversation with someone passionate about fermentation and seeking to scale it in a part of the world where it's desperately needed—where meat demand is rising the fastest: Asia. So enjoy this conversation with a real pioneer in the microbial fermentation space as she tells you her story of going from biotech researcher to startup CEO. Discussed in this episode Our past episode with Zero Acre Farms. Ezhil recommends Meditations by Marcus Aurelius  Paul's favorite quote from Meditations: “Everything that happens is either endurable or not. If it's endurable, then endure it. Stop complaining. If it's unendurable … then stop complaining. Your destruction will mean its end as well.” Ezhil recommends The Gene: An Intimate History by Siddhartha Mukherjee  Finally, Ezhil recommends Good to Great by Jim Collins More about Ezhil Subbian, PhD Ezhil is a scientist, innovator, thinker, hiking enthusiast and a citizen of the world. Ezhil is driven by a passion to leverage the power of biology to deliver sustainable and cost-effective solutions. Her experience in biobased product development over the last 20 years helps her bring deep technical expertise to the work at String. Ezhil's work was most recently recognized with the Women Transforming India Award 2018 from United Nations/NITI Aayog. Ezhil completed her degree in Industrial and Biotech engineering from Anna University, Chennai, and then went on to do a PhD in Molecular Biology and Biochemistry at Oregon Health and Science University in Portland. She then worked for over 12 years in Silicon Valley's Bay area as part of the biotechnology industry. She worked as a scientist and technical lead across multiple companies before becoming a consultant and then starting up. Ezhil is a scientist, innovator, thinker, hiking enthusiast and a citizen of the world. Ezhil is driven by a passion to leverage the power of biology to deliver sustainable and cost-effective solutions. Her experience in biobased product development over the last 20 years helps her bring deep technical expertise to the work at String. Ezhil's work was most recently recognized with the Women Transforming India Award 2018 from United Nations/NITI Aayog.

LISTEN NOW!! Sivasankaran “Soma” Somasundaram is President and Chief Executive Officer of ChampionX and serves on the Company's Board of Directors. Soma has led the Company in these roles since its spin-off from Dover Corporation (“Dover”) in 2018 and through its transformational merger in 2020 when the Company added Chemical Technologies to its portfolio and changed its name to ChampionX Corporation. He received a bachelor's degree in mechanical engineering from Anna University and a master's degree in industrial engineering from the University of Oklahoma. Born in India, Soma shares with us the origin of his name and how he became “Soma” once he arrived in Oklahoma for University. He reflects back on his life growing up as the son of a teacher and the influence his father had. We learn that his father taught him how to enable others to do great work, which became an important part of Somas Story and success. Soma tells us about the approach he uses to create a positive and collaborative culture. It starts with experiences, to create the belief system that people need, in order to shape the culture. Soma talks about the open email line where employees can reach out directly. These emails are a critical part in ensuring employees have an outlet to express what they are experiencing, good and bad. Feeling a sense of belonging is important to Soma. We talk about why representation matters and how ChampionX is approaching diversity, specifically on overcoming unconscious bias. Soma talks about the process of continuous improvement and creating positive experiences. He is conscious of the fact that your work life has an impact on who you are at home.Soma shares how to handle failure. He talks about your first reaction to failure is to think about what it means to you. When you should first not think about yourself, instead focus on how you will solve the problem. Come hang out with us:Download on Apple Podcast——>> ClickDownload on Spotify———>>ClickConnect with Maisy and Jamie:Connect with Massiel Diez: Instagram | LinkedInConnect with Jamie Elrod: Instagram | LinkedInFollow FTB on Instagram | LinkedInJoin FTB NationIf your interested in working with us, please contact : flippingthebarrel@gmail.com To find out more about our mid-roll audio sponsor TechnipFMC please visit: TechnipFMCTo find out more about our pre-roll audio sponsor Varel Energy Solutions please visit: Varel EnergyTo find out more about website sponsor Nextier Energy Solutions please visit: Nextier Oilfield Solutions

Speaking Podcast Social Media / Coaching My Other Podcasts + Donations https://bio.link/podcaster ==================== Bio of Ananda: Ananda Soundhararajan believes in continuous learning and lives by the principle that every single day counts. An engineering leader who has been developing and delivering software for about two decades. Expert in Restful APIs and specialized in Micro Service design and API Gateway technologies, and a big advocate of Cloud and DevOps transformation. Author of “Machine Learning – Getting Started” book, a highly rated content to launch yourself into machine learning. Ananda holds a Bachelor of Engineering in Computer Science from SSN College of Engineering, Anna University, Chennai, India. An active marathon runner and promotes physical and mental health as the number.1 priority. Toastmaster since 2018 and holds an officer role (VP of Membership) at Lake County Toastmasters. Volunteer of Girl scouts of Greater Chicago and Northwest Indiana. Ananda spends his free time with family, gardening, and walking in nature trails. What we Discussed: - How to Start with Machine Learning - Will it remove jobs - Ai Advantages and Disadvantages - What can we expect from it in the future - His Toastmasters Journey - His Book Machine Learning and more How to Contact Ananda: https://www.linkedin.com/in/ananda-soundhararajan YouTube channel: https://www.youtube.com/channel/UCxxGU_Q6A-8aJlSGP19FYUA Don't forget to visit www.lakecountytoastmasters.com if you have the appetite to work on your public speaking and leadership skills. =============== Speaking Podcast Social Media / Coaching My Other Podcasts + Donations https://bio.link/podcaster --- Send in a voice message: https://anchor.fm/roy-coughlan/message

Latha Ravi and her husband Ravi Somasundaram co-own The Flying Locksmiths South Atlanta. They have lived in the South Atlanta area for over 15 years. Ms. Latha Ravi graduated with an MS in Computer Science and Engineering from Oakland University, MI, and a BE in Electronics and Telecommunication Engineering from Anna University, India. She is an entrepreneur and has 25+ years of experience in technology and customer service with American businesses of varying sizes, from startups to corporate Fortune 500 companies. As an owner, Latha work to anticipate and understand the needs of their customers by building long-term relationships and quickly offering the best solutions to keep you, your loved ones, and your business safe and secure. They started this franchise location together to offer locksmith and security solutions you can trust and rely on with the power of a great name brand brought to you with family values and professionalism. https://flyinglocksmiths.com/south-atlanta/ --- Send in a voice message: https://anchor.fm/drycleaningconnection/message

Patrick's guest is Professor Ranga Ramanujam from Vanderbilt University Owen Graduate School of Management. Ranga's research, consulting, and teaching focus on organizational errors, reliability, and operational failures. Numerous former students and current colleagues of Ranga's kept telling Patrick to put Ranga on the podcast. As Patrick puts it, "They were 100% right. Ranga is insightful, humble, and engaging!" The discussion follows the lessons Ranga learned as a young 'accidental manager' until his time at Vanderbilt where he teaches MBA students about the importance of leading themselves and others. Ranga's formal education began at Anna University in Chennai, India, and finished with his earning a Ph.D. at Carnegie Mellon University in the United States. That said, listeners will quickly realize that Ranga believes that we never stop learning.

In this episode, Sujani sits down with Bhargav Krishna to discuss his experiences pursuing higher education all around the world. Bhargav gives tips on choosing between programs, considerations that need to be made when choosing programs, and shares his experience with Harvard's Doctor of Public Health (DrPH) program. You'll LearnWhy Bhargav decided to pursue a DrPH and how he decided on a DrPH over a PhD What made Bhargav choose to pursue Harvard's DrPH program Tips on choosing the right DrPH programA brief summary of what you might expect from Harvard's DrPH program Bhargav's biggest learnings from the DrPH program and how he has changed as a professional sinceHow Bhargav is using skills from the DrPH in his current workThe diverse career paths that other graduates from the program are onAdvice for anyone considering pursuing a DrPH Today's GuestBhargav Krishna is a Fellow at the Centre for Policy Research. His research interests span areas of health policy, environmental policy, and environmental epidemiology, with a focus on the impact of air quality and climate change on health. Previously, Bhargav set up and managed the Centre for Environmental Health at the Public Health Foundation of India (PHFI), where he led work on air quality, climate, and health. In this capacity, he served on Union and State government expert committees on air pollution, biomedical waste, and critically polluted areas. He has also carried out work on health systems and sustainable development across several states. Bhargav holds a Doctorate in Public Health (DrPH) from the Harvard T. H. Chan School of Public Health, a Master's degree in Global Environmental Change from Kings College London and an undergraduate degree from Anna University, Chennai. He is Adjunct Faculty at PHFI and Visiting Faculty at Azim Premji University where he teaches environmental health and health policy respectively. He is also co-founder of Care for Air, a Delhi-based non-profit working to raise awareness of air pollution among school children.ResourcesBhargav Krishna's LinkedIn Learn more about Harvard's DrPH programAn alumni spotlight article on BhargavOther PH SPOT resources:Share ideas for the podcast: Fill out this formNever heard of a podcast before? Read this guide we put together to help you get set up.Be notified when new episodes come out, and receive hand-picked public health opportunities every week by joining the PH SPOT community.Contribute to the public health career blog: www.phspot.ca/contributeUpcoming course on infographics: phspot.ca/infographicsLearn more about the PH Spot 6-week training programSupport the show (http://www.phspot.ca/signup)

Future of Work Sherpa Dan Smolen discovers Raj Subrameyer's immigrant's future work story. Raj arrived in the United States for graduate study. He was an introverted Southern Indian student who pursued the lofty career goals that others expected him to follow. Astonishingly, he applied for over 1,200 jobs and got but a handful of interviews. That's when he decided to focus on his own happiness; he began a process of discovery which got him unstuck to start his own business. Now, through his brand ChaiLatte Consulting, Raj helps tech careerists get unstuck for the future of work. Full interview starts at 2:55 In a wide-ranging discussion, Raj: Provides the unique value proposition of ChaiLatte Consulting, his own name-change, and the importance of having an “immigrant mindset.” Starts at 4:40 Recalls how he tapped his “inner extrovert” to help careerists. Starts at 8:32 Pushes against the [Southern Indian] cultural tenet of not questioning things. Starts at 13:25 Delves into the WHY of personal (career) branding. Starts at 26:27 Describes how immigrants to the US can overcome their disadvantages. Starts at 31:22 Offers his take on future of work opportunities. Starts at 39:01 Raj also describes his motivation to help others achieve career success: “I wanted to help underdogs like me, who had the skill-sets, but were looking for guidance.” With great cheer, Raj Subrameyer lives a rewarding immigrant's future work story. Full interview starts at 2:55 About our guest: Raj Subrameyer earned a Bachelor of Science in Information Technology from Anna University and a Masters of Science in Software Engineering from the Rochester Institute of Technology. Raj is the author of the book, Skyrocket Your Career. He lives and works in Chicago, Illinois. EPISODE DATE: November 26, 2021 Social media: – Facebook – LinkedIn – Twitter – TEDx Talk (NEW!) – YouTube Please Subscribe to The Dan Smolen Podcast on: – Apple Podcast – Android – Google Podcasts – Pandora – Spotify – Stitcher – TuneIn …or wherever you get your podcasts. You may also click HERE to receive our podcast episodes by email. Image credits: Lady Liberty, Choreograph for iStock Photo; Raj Subrameyer, The Dan Smolen Experience; Podcast button, J. Brandt Studio for The Dan Smolen Experience.

Vish Narendra, CIO of Graphic Packaging International, is no stranger to technology or its capabilities. Today, we will be discussing where he sees technology as the key to the future of doing good, what he enjoys most about being involved with TechBridge, and where he hopes to see TechBridge go.   --- Vish attended Anna University, where he graduated with a degree in Electrical Engineering, and the Illinois Institute of Technology, where achieved his MBA in Information Management. This degree and experience launched him into a career in IT and software roles at companies like GE and, now, Graphic Packaging International. Vish Narendra is an experienced technology and business executive with global experience in IT, business strategy, acquisition integration and digital business transformation with domain experience in consulting, software development, manufacturing and supply chain. In addition to his involvement with TechBridge as a board member and the sitting Board Chair, he also serves on the advisory boards for Georgia CIO and Greylock Partners. Vish has been involved with TechBridge since 2014, and he has been an integral part of the TechBridge community from the start. Vish has won many awards and earned many honors, one of which being the 2017 Georgia CIO of the Year ORBIE Award Winner | Global Category. We are honored to have him on our board and as a friend of TechBridge! 

In this episode Ramesh shares his experience and perspectives related toHis interest in software and programming that was fueled by an IIT professor teaching programmingOne of the very few who did a software project as part of his degree and then joining Tata Burroughs from campus, as the first batchGetting back to academics to get his Master's degreeHow his extra learning at IISc and the work experience in the first couple of years helped him skip a few courses and jump into more advanced topics during the Masters'Joining HCL in their Singapore venture, Far East Computers LimitedHow his experience with facing customers helped in the assignment of setting up a QA environment at Oracle headquartersMoving to management roles in engineering managementJumping at the opportunity to start a development center in India from scratchThinking that he could do that for a year and then get back to the USAHow he had to take on various responsibilities of not just delivering, but also establishing processes, building networks for recruitment etcRealizing the need to take innovative approaches to attract the right talent, when competing with other companies that would hire in large numbersTaking up a teaching role at Anna University How that gave him an opportunity to observe the students over a semester, and not having to learn by interacting for 20 minutes in an interviewExtending this learning through internships Starting to love teachingThe trigger for his getting into writing [and authoring books], some of which are standard curriculum recommendations in about 50 universities across the world“Transferring knowledge to others will have a bigger impact on Society as a whole”Enjoying the role of a teacher at various institutionsHow some interests popped up by necessity, Slicing time every day for work, education and family - to make time for all Taking risks knowing that all options may not progress as desiredSome tips that would help selecting the right candidatesHow everyone should feel comfortable to disagree, but not be disagreeablehow , as a technical guy, you can have all the answers, but as a leader, you should have all the questionsHis career advice:Being passionate about what one doesDo not undervalue the importance of keeping your skills up to dateWhy you should become useless for your jobPlease bear with some audio distractions in the background in patches. You will love this story..Gopalaswamy Ramesh is an independent consultant, eminent author and has served as visiting / adjunct professor in several reputed universities and an acknowledged thought leader in the areas of global software project management, software testing and related areas as well as on soft skills. He has over three decades of experience in industry, consulting and teaching. He played a key role in establishing Oracle's India Development Center and grew it from zero to close to 500 people. His contributions to this phenomenal growth were acknowledged in Oracle International magazine When he left Oracle in 2002, he was their Senior Director, heading the engineering team at Bangalore.Before returning to India in 1994 to set up Oracle IDC, Ramesh worked in Oracle Headquarters in Redwood Shores, California, holding several technical and management positions. He also headed pre-sales and post-sales support of Oracle products in the ASEAN countries while working at Far East Computers, Singapore from 1982 till 1988. During this stint, he actively participated in launching and supporting Oracle in several countries in the region.Since 2002, Ramesh has been an independent consultant, offering consultancy services in the areas of global software project management, software testing and soft skills in India and abroad. His passion for teaching and sharing his vast knowledge and rich experience have resulted in his writing eight books have become best sellers and two of them being also translated to Chinese language. His books have been widely read and used as prescribed or reference books in a number of universities in India and abroad. The book Managing Global Software Projects won the National Award for the Best Book.As a thought leader, Ramesh has been an active invited participant in several well known conferences and workshops. He has played the roles of Program Chair, Technical Review Committee Head as well as an invited keynote presenter in several international conferences.Passionate about interacting with students and imparting relevant practical knowledge and training to students, Ramesh has been an Adjunct Professor in several leading universities and has taught in a number of very reputed institutions like IIIT-Bangalore, IIT Madras, Anna University, Chennai and Amrita School of Business. He was part of the Academic Advisory Board of Project Management Institute, India from 2009 to 2014, during which time he was the Technical Committee Chair for first two Research and Academic Conferences (RAC) on Project Management in India.Ramesh is passionate about inculcating the right value systems in school children and about people with special needs. He has also written books on moral education நிச்சயம் வெல்லலாம் நேரான பாதையில் in Tamil and Virtuous and Victorious – Always in English for school children. He has translated from English to Tamil the best-selling book GIFTED about the achievements of fifteen differently abled people. He and his wife, Lakshmi Ramesh who is a trained special educator are active participants in initiatives on people with special needs.Ramesh holds a B E Degree in Electronics and Communication Engineering from Indian Institute of Science, Bangalore, a M S Degree in Computer Science from Indian Institute of Technology, Madras (the thesis on Automatic Programming won the National Gold medal) and M S Degree in Engineering Management from Stanford University, California.Ramesh may be reached at gopalaswamy_ramesh@yahoo.com

Episode 010 | September 28, 2021Artificial intelligence, Machine Learning, Deep Learning, and Deep Neural Networks are today critical to the success of many industries. But they are also extremely compute intensive and expensive to run in terms of both time and cost, and resource constraints can even slow down the pace of innovation. Join us as we speak to Muthian Sivathanu, Partner Research Manager at Microsoft Research India, about the work he and his colleagues are doing to enable optimal utilization of existing infrastructure to significantly reduce the cost of AI.Muthian's interests lie broadly in the space of large-scale distributed systems, storage, and systems for deep learning, blockchains, and information retrieval.Prior to joining Microsoft Research, he worked at Google for about 10 years, with a large part of the work focused on building key infrastructure powering Google web search — in particular, the query engine for web search. Muthian obtained his Ph.D from University of Wisconsin Madison in 2005 in the area of file and storage systems, and a B.E. from CEG, Anna University, in 2000.For more information about the Microsoft Research India click here.RelatedMicrosoft Research India Podcast: More podcasts from MSR IndiaiTunes: Subscribe and listen to new podcasts on iTunesAndroidRSS FeedSpotifyGoogle PodcastsEmail TranscriptMuthian Sivathanu: Continued innovation in systems and efficiency and costs are going to be crucial to drive the next generation of AI advances, right. And the last 10 years have been huge for deep learning and AI and primary reason for that has been the significant advance in both hardware in terms of emergence of GPUs and so on, as well as software infrastructure to actually parallelize jobs, run large distributed jobs efficiently and so on. And if you think about the theory of deep learning, people knew about backpropagation about neural networks 25 years ago. And we largely use very similar techniques today. But why have they really taken off in the last 10 years? The main catalyst has been sort of advancement in systems. And if you look at the trajectory of current deep learning models, the rate at which they are growing larger and larger, systems innovation will continue to be the bottleneck in sort of determining the next generation of advancement in AI.[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]Sridhar Vedantham: Artificial intelligence, Machine Learning, Deep Learning, and Deep Neural Networks are today critical to the success of many industries. But they are also extremely compute intensive and expensive to run in terms of both time and cost, and resource constraints can even slow down the pace of innovation. Join us as we speak to Muthian Sivathanu, Partner Research Manager at Microsoft Research India, about the work he and his colleagues are doing to enable optimal utilization of existing infrastructure to significantly reduce the cost of AI.[Music]Sridhar Vedantham: So Muthian, welcome to the podcast and thanks for making the time for this.Muthian Sivathanu: Thanks Sridhar, pleasure to be here.Sridhar Vedantham: And what I'm really looking forward to, given that we seem to be in some kind of final stages of the pandemic, is to actually be able to meet you face to face again after a long time. Unfortunately, we've had to again do a remote podcast which isn't all that much fun.Muthian Sivathanu: Right, right. Yeah, I'm looking forward to the time when we can actually do this again in office.Sridhar Vedantham: Yeah. Ok, so let me jump right into this. You know we keep hearing about things like AI and deep learning and deep neural networks and so on and so forth. What's very interesting in all of this is that we kind of tend to hear about the end product of all this, which is kind of, you know, what actually impacts businesses, what impacts consumers, what impacts the health care industry, for example, right, in terms of AI. It's a little bit of a mystery, I think to a lot of people as to how all this works, because... what goes on behind the scenes to actually make AI work is generally not talked about. Muthian Sivathanu: Yeah.Sridhar Vedantham: So, before we get into the meat of the podcast you just want to speak a little bit about what goes on in the background.Muthian Sivathanu: Sure. So, machine learning, Sridhar, as you know, and deep learning in particular, is essentially about learning patterns from data, right, and deep learning system is fed a lot of training examples, examples of input and output, and then it automatically learns a model that fits that data, right. And this is typically called the training phase. So, training phase is where it takes data builds a model how to fit. Now what is interesting is, once this model is built, which was really meant to fit the training data, the model is really good at answering queries on data that it had never seen before, and this is where it becomes useful. These models are built in various domains. It could be for recognizing an image for converting speech to text, and so on, right. And what has in particular happened over the last 10 or so years is that there has been significant advancement both on the theory side of machine learning, which is, new algorithms, new model structures that do a better job at fitting the input data to a generalizable model as well as rapid innovation in systems infrastructure which actually enable the model to sort of do its work, which is very compute intensive, in a way that's actually scalable that's actually feasible economically, cost effective and so on.Sridhar Vedantham: OK, Muthian, so it sounds like there's a lot of compute actually required to make things like AI and ML happen. Can you give me a sense of what kind of resources or how intensive the resource requirement is?Muthian Sivathanu: Yeah. So the resource usage in a machine learning model is a direct function of how many parameters it has, so the more complex the data set, the larger the model gets, and correspondingly requires more compute resources, right. To give you an idea, the early machine learning models which perform simple tasks like recognizing digits and so on, they could run on a single server machine in a few hours, but models now, just over the last two years, for example, the size of the largest model that's useful that state of the art, that achieves state of the art accuracy has grown by nearly three orders of magnitude, right. And what that means is today to train these models you need thousands and thousands of servers and that's infeasible. Also, accelerators or GPUs have really taken over the last 6-7 years and GPUs. A single V-100 GPU today, a Volta GPU from NVIDIA can run about 140 trillion operations per second. And you need several hundreds of them to actually train a model like this. And they run for months together to train a 175 billion model, which is called GPT 3 recently, you need on the order of thousands of such GPUs and it still takes a month.Sridhar Vedantham: A month, that's sounds like a humongous amount of time. Muthian Sivathanu: Exactly, right? So that's why I think just as I told you how the advance in the theory of machine learning in terms of new algorithms, new model structures, and so on have been crucial to the recent advance in the relevance in practical utility of deep learning.Equally important has been this advancement in systems, right, because given this huge explosion of compute demands that these workloads place, we need fundamental innovation in systems to actually keep pace, to actually make sure that you can train them in reasonable time, you can actually do that with reasonable cost.Sridhar Vedantham: Right. Ok, so you know for a long time, I was generally under the impression that if you wanted to run bigger and bigger models and bigger jobs, essentially you had to throw more hardware at it because at one point hardware was cheap. But I guess that kind of applies only to the CPU kind of scenario, whereas the GPU scenario tends to become really expensive, right?Muthian Sivathanu: Yep, yeah.Sridhar Vedantham: Ok, so in which case, when there is basically some kind of a limit being imposed because of the cost of GPUs, how does one actually go about tackling this problem of scale?Muthian Sivathanu: Yeah, so the high-level problem ends up being, you have limited resources, so let's say you can view this in two perspectives, right. One is from the perspective of a machine learning developer or a machine learning researcher, who wants to build a model to accomplish a particular task right. So, from the perspective of the user, there are two things you need. A, you want to iterate really fast, right, because deep learning, incidentally, is this special category of machine learning, where the exploration is largely by trial and error. So, if you want to know which model actually works which parameters, or which hyperparameter set actually gives you the best accuracy, the only way to really know for sure is to train the model to completion, measure accuracy, and then you would know which model is better, right. So, as you can see, the iteration time, the time to train a model to run inference on it directly impacts the rate of progress you can achieve. The second aspect that the machine learning researcher cares about is cost. You want to do it without spending a lot of dollar cost.Sridhar Vedantham: Right.Muthian Sivathanu: Now from the perspective of let's say a cloud provider who runs this, huge farm of GPUs and then offers this as a service for researchers, for users to run machine learning models, their objective function is cost, right. So, to support a given workload you need to support it with as minimal GPUs as possible. Or in other words, if you have a certain amount of GPU capacity, you want to maximize the utilization, the throughput you can get out of those GPUs, and that's where a lot of the work we've been doing at MSR has focused on. How do you sort of multiplex lots and lots of jobs onto a finite set of GPUs, while maximizing the throughput that you can get from them?Sridhar Vedantham: Right, so I know you and your team have been working on this problem for a while now. Do you want to share with us some of the key insights and some of the results that you've achieved so far, because it is interesting, right? Schedulers have been around for a while. It's not that there aren't schedulers, but essentially what you're saying is that the schedulers that exist do not really cut it, given the, intensity of the compute requirements as well as the jobs, as the size of the jobs and models that are being run today in terms of deep learning or even machine learning models, right?Muthian Sivathanu: That's right.Sridhar Vedantham: So, what are your, key insights and what are some of the results that you guys have achieved?Muthian Sivathanu: So, you raise a good point. I mean, schedulers for distributed systems have been around for decades, right. But what makes deep learning somewhat special is that it turns out, in contrast to traditional schedulers, which have to view a job as a black box, because they're meant to run arbitrary jobs. There is a limit to how efficient they can be. Whereas in deep learning, first of all because deep learning is such high impact area with lots, and I mean from an economic perspective, there are billions of dollars spent in these GPUs and so on. So, there is enough economic incentive to extract the last bit of performance out of these expensive GPUs, right. And that lends itself into this realm of- what if we co-design? What if we custom design a scheduler for the specific case of deep learning, right. And that's what we did in the Gandiva project which we published at OSDI in 2018. What we said was, instead of viewing a deep learning job as just another distributed job which is opaque to us, let's actually exploit some key characteristics that are unique to deep learning jobs, right? And one of those characteristics, is that although, as I said, a single deep learning training job can run for days or even months, right, deep within it is actually composed of millions and millions of these what are called mini batches. So, what is a mini batch? A mini batch is an iteration in the training where it reads one set of input training examples, runs it through the model, and then back propagates the loss, and essentially, changes the parameters to fit that input. And this sequence this mini batch repeats over and over again across millions and millions of mini batches. And what makes it particularly interesting and relevant from a systems optimization viewpoint is that from a resource usage perspective and from a performance perspective, mini batches are identical. They may be operating on different data in each mini batch, but the computation they do is pretty much identical. And what that means is we can look at the job for a few mini batches and we can know what exactly is going to do for the rest of its life time, right. And that allows us to, for example, do things like, we can automatically decide which hardware generation is the best fit for this job, because you can just measure it in a whole bunch of hardware configurations. Or when you're distributing the job, you can compare it across a whole bunch of parallelism configurations, and you can automatically figure out, this is the right configuration, right hardware assignment for this particular job, which you couldn't do in an arbitrary job with a distributed scheduler because the job could be doing different things at different times. Like a MapReduce job for example, it would keep fluctuating across how we'd use a CPU, network, storage, and so on, right. Whereas with deep learning there is this remarkable repeatability and predictability, right. What it also allows us to do is, we can then look within a mini batch what happens, and it turns out, one of the things that happens is, if you look at the memory usage, how much GPU memory the training loop itself is consuming, somewhere at the middle of a mini batch, the memory peaks to almost fill the entire GPU memory, right. And then by the time the mini batch ends, the memory usage drops down by like a factor of anywhere between 10 to 50x. Right, and so there is this sawtooth pattern in the memory usage, and so one of the things we did in Gandiva was proposed this mechanism of transparently migrating a job, so you should be able to, on demand checkpoint a job. The scheduler should be able to do it and just move it to a different machine, maybe even essentially different GPU, different machine, and so on, right. And this is very powerful from load balancing. Lots of scheduling things become easy if you do this. Now, when you're doing that, when you are actually moving a job from one machine to another, it helps if the amount of state you need to move is small, right. And so that's where this awareness of mini batch boundaries and so on helps us, because now you can choose when exactly to move it so that you move 50x, smaller amount of state.Sridhar Vedantham: Right. Very interesting, and another part of this whole thing about resources and compute and all that is, I think, the demands on storage itself, right?Muthian Sivathanu: Yeah.Sridhar Vedantham: Because if the models are that big, that you need some really high-powered GPUs to compute, how do you manage the storage requirements?Muthian Sivathanu: Right, right. So, it turns out the biggest requirement from storage that deep learning poses is on the throughput that you need from storage, right. So, as I mentioned, because GPUs are the most expensive resource in this whole infrastructure stack, the single most important objective is to keep GPUs busy all the time, right. You don't want them idling, at all. What that means is the input training data that the model needs in order to run its mini batches, that is to be fed to it at a rate that is sufficient to keep the GPUs busy. And GPUs process, I mean the amount of data that the GPU can process from a compute perspective has been growing at a very rapid pace, right. And so, what that means is, you know, when between Volta series and an Ampere series, for example, of GPUs there is like 3X improvement in compute speed, right. Now that means the storage bandwidth should keep up with that pace, otherwise faster GPU doesn't help. It will be stalling on IO. So, in that context one of the systems we built was the system called Quiver, where we say a traditional remote storage system like the standard model for running this training is...the datasets are large- I mean the data sets can be in terabytes, so, you place it on some remote cloud storage system, like Azure blob or something like that, and you read it remotely from whichever machine does the training, right. And that bandwidth simply doesn't cut it because it goes through network backbone switches and so on, and it becomes insanely expensive to sustain that level of bandwidth from a traditional cloud storage system, right. So what we need, to achieve here is hyper locality. So, ideally the data should reside on the exact machine that runs the training, then it's a local read and it has to reside on SSD and so on, right. So, you need several gigabytes per second read bandwidth.Sridhar Vedantham: And this is to reduce network latency?Muthian Sivathanu: Yes, this is to reduce network latency and congestion, like when it goes through lots of back end, like T1 switches, T2 switches etc. The end-to-end throughput that you get across the network is not as much as what you can get locally, right?Sridhar Vedantham: Right.Muthian Sivathanu: So, ideally you want to keep the data local in the same machine, but as I said, for some of these models, the data set can be in tens of terabytes. So, what we really need is a distributed cache, so to speak, right, but a cache that is locality aware. So, what we have is a mechanism by which, within each locality domain like a rack for example, we have a copy of the entire training data, so, a rack could comprise maybe 20 or 30 machines, so across them you can still fit the training data and then you do peer to peer across machines in the rack for the access to the cache. And within a rack, network bandwidth is not a limitation. You can get nearly the same performance as you could from local SSD, so that's what we did in Quiver and there are a bunch of challenges here, because if every model wants the entire training data to be local to be within the rack, then there is just no cache space for keeping all of that.Sridhar Vedantham: Right.Muthian Sivathanu: Right. So we have this mechanism by which we can transparently share the cache across multiple jobs, or even multiple users without compromising security, right. And we do that by sort of intelligent content addressing of the cache entries so that even though two users may be accessing different copies of the same data internally in the cache, they will refer to the same instance.Sridhar Vedantham: Right, I was actually just going to ask you that question about how do you maintain security of data, given that you're talking about distributed caching, right? Because it's very possible that multiuser jobs will be running simultaneously, but that's good, you answered it yourself. So, you know I've heard you speak a lot about things like micro design and so on. How do you bring those principles to bear in these kind of projects here?Muthian Sivathanu: Right, right. So, I alluded to this a little bit in one of my earlier points, which is the interface, I mean, if you look at a traditional scheduler which we use the job as a black box, right. That is an example of traditional philosophy to system design, where you build each layer independent of the layer above or below it, right, so that, there are good reasons to do it because you know, like multiple use cases can use the same underlying infrastructure, like if you look at an operating system, it's built to run any process, whether it is Office or a browser or whatever, right.Sridhar Vedantham: Right.Muthian Sivathanu: But, in workloads like deep learning, which place particularly high demands on compute and that are super expensive and so on, there is benefit to sort of relaxing this tight layering to some extent, right. So that's the philosophy we take in Gandiva, for example, where we say the scheduler no longer needs to think of it as a black box, it can make use of internal knowledge. It can know what mini batch boundaries are. It can know that mini batch times are repeatable and stuff like that, right. So, co-design is a philosophy that has been gaining traction over the last several years, and people typically refer to hardware, software co-design for example. What we do in micro co-design is sort of take a more pragmatic view to co-design where we say look, it's not always possible to rebuild entire software layers from scratch to make them more tightly coupled, but the reality is in existing large systems we have these software stacks, infrastructure stacks, and what can we do without rocking the ship, without essentially throwing away everything in building everything from a clean slate. So, what we do is very surgical, carefully thought through interface changes, that allow us to expose more information from one layer to another, and then we also introduce some control points which allow one layer to control. For example, the scheduler can have a control point to ask a job to suspend. And it turns out by opening up those carefully thought through interface points, you leave the bulk of the infrastructure unchanged, but yet achieve these efficiencies that result from richer information and richer control, right. So, micro co-design is something we have been adopting, not only in Gandiva and Quiver, but in several other projects in MSR. And MICRO stands for Minimally Invasive Cheap and Retrofittable Co-design. So, it's a more pragmatic view to co-design in the context of large cloud infrastructures.Sridhar Vedantham: Right, where you can do the co-design with the minimum disruption to the existing systems.Muthian Sivathanu: That's right. Sridhar Vedantham: Excellent. [Music]Sridhar Vedantham: We have spoken a lot about the work that you've been doing and it's quite impressive. Do you have some numbers in terms of you know, how jobs will run faster or savings of any nature, do you have any numbers that you can share with us? Muthian Sivathanu: Yeah, sure. So the numbers, as always depend on the workload and several aspects. But I can give you some examples. So, in the Gandiva work that we did. We, introduce this ability to time slice jobs, right. So, the idea is, today when you launch a job in a GPU machine, that job essentially holds on to that machine until it completes, and until that time it has exclusive possession of that GPU, no other job can use it, right. And this is not ideal in several scenarios. You know, one classic example is hyperparameter tuning, where you have a model and you need to decide what exact hyperparameter values like learning rate, etc. actually are the best fit and give the best accuracy for this model. So, people typically do what is called the hyperparameter search where you run maybe 100 instances of the model, see how it's doing, maybe kill some instances spawn of new instances, and so on, right. And hyperparameter exploration really benefits from parallelism. You want to run all these instances at the same time so that you have an apples-to-apples comparison of how they are doing. And if you want to run like 100 configurations and you have only 10 GPUs, that significantly slows down hyperparameter exploration- it serializes it, right. What Gandiva has is an ability to perform fine grained time slicing of the same GPU across multiple jobs, just like how an operating system time slices multiple processes, multiple programs on the same CPU, we do the same in GPU context, right. And because we make use of mini batch boundaries and so on, we can do this very efficiently. And with that we showed that for typical hyperparameter tuning, we can sort of speed up the end-to-end time to accuracy by nearly 5-6x, right. Uh, and so this is one example of how time slicing can help. We also saw that from a cluster wide utilization perspective, some of the techniques that Gandiva adopted can improve overall cluster utilization by 20-30%. Right, and this directly translates to cost incurred to the cloud provider running those GPS because it means with the same GPU capacity, I can serve 30% more workload or vice versa, right, for a given workload I only need 30% lesser number of GPUs.Sridhar Vedantham: Yeah, I mean those savings sound huge and I think you're also therefore talking about reducing the cost of AI making the process of AI itself more efficient. Muthian Sivathanu: That's correct, that's correct. So, the more we are able to extract performance out of the same infrastructure, the cost per model or the cost per user goes down and so the cost of AI reduces and for large companies like Microsoft or Google, which have first party products that require deep learning, like search and office and so on, it reduces the capital expenditure running such clusters to support those workloads.Sridhar VedanthamRight.Muthian Sivathanu: And we've also been thinking about areas such as, today there is this limitation that large models need to run in really tightly coupled hyperclusters which are connected via InfiniBand and so on. And that brings up another dimension of cost escalation to the equation, because these are sparse, the networking itself is expensive, there is fragmentation across hyperclusters and so on. What we showed in some recent work is how can you actually run training of large models in just commodity VMs-these are just commodity GPU VMs- but without any requirement on them being part of the same InfiniBand cluster or hypercluster, but just they can be scattered anywhere in the data center, and more interestingly, we can actually run these off of spot VMs. So Azure, AWS, all cloud providers provide these bursty VMs or low priority VMs, which is away essentially for them to sell spare capacity, right. So, you get them at a significant discount. Maybe 5-10x cheaper price. And the disadvantage, I mean the downside of that is they can go away at any time. They can be preempted when real demand shows up. So, what we showed is it's possible to train such massive models at the same performance, despite these being on spot VMs and spread over a commodity network without custom InfiniBand and so on. So that's another example how you can bring down the cost of AI by reducing constraints on what hardware you need.Sridhar Vedantham: Muthian, we're kind of reaching the end of the podcast, and is there anything that you want to leave the listeners with, based on your insights and learning from the work that you've been doing? Muthian Sivathanu: Yeah, so taking a step back, right? I think continued innovation in systems and efficiency and costs are going to be crucial to drive the next generation of AI advances, right. And the last 10 years have been huge for deep learning and AI and primary reason for that has been the significant advance in both hardware in terms of emergence of GPUs and so on, as well as software infrastructure to actually parallelize jobs, run large distributed jobs efficiently and so on. And if you think about the theory of deep learning, people knew about backpropagation about neural networks 25 years ago. And we largely use very similar techniques today. But why have they really taken off in the last 10 years? The main catalyst has been sort of advancement in systems. And if you look at the trajectory of current deep learning models, the rate at which they are growing larger and larger, systems innovation will continue to be the bottleneck in sort of determining the next generation of advancement in AI.Sridhar Vedantham: Ok Muthian, I know that we're kind of running out of time now but thank you so much. This has been a fascinating conversation.Muthian Sivathanu: Thanks Sridhar, it was a pleasure.Sridhar Vedantham: Thank you

Future of Work Sherpa Dan Smolen meets a tech career strategist who helps people get unstuck for the future of work. Raj Subrameyer arrived in the US for graduate study. He was an introverted South Indian student who pursued the lofty career goals that others expected him to follow. Raj says he applied for over 1,200 jobs and got but a handful of interviews. That's when he decided to focus on his own happiness; he began a process of discovery which got him unstuck to start his own business. Now, through his brand ChaiLatte Consulting, Raj helps tech careerists get unstuck for the future of work. Full interview starts at 3:05 In a wide-ranging discussion, Raj: Provides the unique value proposition of ChaiLatte Consulting, his own name-change, and the importance of having an "immigrant mindset." Starts at 4:28 Recalls how he tapped his "inner extrovert" to help careerists. Starts at 8:20 Pushes against the [Southern Indian] cultural tenet of not questioning things. Starts at 13:13 Delves into the WHY of personal (career) branding. Starts at 26:15 Describes how immigrants to the US can overcome their disadvantages. Starts at 31:11 Offers his take on future of work opportunities. Starts at 38:49 Raj also describes his motivation to help others achieve career success: "I wanted to help underdogs like me, who had the skill-sets, but were looking for guidance." With great cheer, Raj Subrameyer helps careerists get unstuck for the future of work. Full interview starts at 3:05 About our guest: Raj Subrameyer earned a Bachelor of Science in Information Technology from Anna University and a Masters of Science in Software Engineering from the Rochester Institute of Technology. Raj is the author of the book, Skyrocket Your Career. He lives and works in Chicago, Illinois. EPISODE DATE: September 10, 2021 Social media: – Facebook – LinkedIn – Twitter – YouTube Link to Raj's Ted Talk (coming soon)! Please Subscribe to The Dan Smolen Podcast on: – Apple Podcast – Android – Google Podcasts – Pandora – Spotify – Stitcher – TuneIn …or wherever you get your podcasts. You may also click HERE to receive our podcast episodes by email. Image credits: Shoe stuck to chewing gum, Sergey Spritnyuk for iStock Photo; Raj Subrameyer, The Dan Smolen Experience; Podcast button, J. Brandt Studio for The Dan Smolen Experience.

Salil is a System Performance Engineer at T-Mobile. He currently lives in Urbana Champaign, IL. His work related Interests include wireless telecommunication and data analytics. Salil did his bachelors in Electronics and Communications Engineering at Anna University, India and did his Master's in Electrical Engineering at the University of Florida. He has 8 years of work experience in the telecom industry.  Salil loves aviation and spends his weekends playing flight simulators. The Beechcraft King Air B200 is his favorite airplane to fly. He enjoy playing the guitar and is an avid listener of rock music from the 80s and 90s. He also developed an interesting in reading (both fiction and non-fiction alike) and is also learning to mountain bike in his spare time. --- Support this podcast: https://anchor.fm/stuttertime/support

The Greater Chennai Corporation on Saturday started using drones, on an experimental basis, to spray larvicide along the waterbodies to control the mosquito menace. The civic body was collaborating with Dr. Kalam Advanced UAV Research Centre on the MIT campus of Anna University for this activity. Corporation Commissioner Gagandeep Singh Bedi and other senior officials monitored the spraying through drones along the Cooum near Langs Garden Road on Saturday. With the help of drones, he said that spraying of the anti-larval oil can be done in a faster and safer manner. K. Senthil Kumar, Director, Dr. Kalam Advanced UAV Research Centre, said such drones were first used by Agriculture Department for spraying pesticides, when Mr. Bedi was the secretary. --- Send in a voice message: https://anchor.fm/gmbwithkay/message

This conversation between Mohan Panchapikesan, CEO and Director at Medexpert Software Solutions, shares his stories about - Mohan started his career after completing his engineering in Anna University and IIT Kharagpur and talks about being a self made person but stays as a small town boy from Trichy Mohan shares being inherently curious and how his firm looks at not only the hospital management software but also the Ecosystem that drives it including insurance, pharma and the equipment sourcing and the entire supply chainMohan talks about the growth and fixed mindset and its application being the CEO. Being in a position of authority, having an understanding of people's fears and ambiguity enables in bringing cohesion towards the goals of the firm by motivationMohan talks about Elon Musks' motivation of moving to Mars due to the explosion of population and take that as an opportunity He refers Ford, Starbucks, McDonalds and Microsoft stories to talk about being bigger is better and democratising everything you doTalking about evolution and democratising the reach of services between the 1990s and 2020s has expanded the voice of individuals & takes the example of this podcast being in existence because of the forces that are in playStaying curious is the only way to sustain your learnings Perform or perish in corporate world has seeped into the personal world as Adopt or Die Discoverability is the key in the age of plethora of choices and technologists become the match makers of the world. Best match makers are those that have the horoscopes of all the open source software out thereFrom interoperability to intelligently make those inter connectionsIntelligence in integration and ecosystem is evolving. Unless we as mankind evolve with it, we will become artificial or redundant in the ecosystemOne has to be attuned with what is happening around us social or technology wise Mohan started his career in software in SA Software working as an RDBMS specialist. He later honed his data and software skills working in Walmart as a program manager. Mohan worked in Cognizant in various leadership roles by scaling people, technology and solutions to provide the right type of integration to the clients. Mohan became an entrepreneur serendipitously through a mutual friend. He's now CEO of Medexpert software solutions that's focused on reducing inefficiencies in the Medical ecosystem and driving innovations.Mohan can be reached at https://www.linkedin.com/in/mpjaya/

Anvesh is a Managing Director at MassMutual Ventures (MMV) and co-heads MMV's investment efforts in Asia. Prior to MMV, Anvesh was a Director and Head of Investments at Openspace Ventures, where he was part of the founding team. He started his career at Citi in the TMT Investment Banking team, during which he spent around 8 years in Hong Kong and Mumbai on M&A and financial advisory work with clients in the APAC region. Anvesh holds a BE in electronics and communications engineering from Anna University and an MBA from T.A. Pai Management Institute.Anvesh currently serves as a Director on the Boards of Biofourmis, Lynk, See-Mode, Milieu Insight and Qapita.In this episode, we will cover:1. Has the second wave of Covid in India impacted MMV's investment thesis? (2:00)2. Learnings from interactions with portfolio founders during covid (3:50)3. The rise of the enterprise tech ecosystem in Asia (8:00)4. Leaving investment banking for venture capital, what did the landscape look like back then vs where it is now (14:37)5. What is it like looking into different South East Asian marketing from a VC lens? (17:49)6. How do VCs help frame regulatory structures in frontier markets? (24:01)7. What does the LP appetite for Asia today look like? (28:54)8. Where and how does the the fund fit into MassMutual's macro ambitions? (32:10)9. What could the future thesis for MMV look like? (37:18)10. How does MMV look at the healthcare landscape across SEA? (44:04)11. Which is a better bet – a startup in a developing or establish market? (50:05)12 Role of regulatory framework in fostering customer loyalty (53:09)13. Evaluating similar business models across multiple geographies (56:45)14. What startups don't understand about SEA markets (58:39)

Founded in December 2016 and bagging many awards from Central Ministry, Webboombaa was co-founded by Mr. Durairaju, who faced multiple failures in his college life, but a winner of Top 30 under 30 award from Impact Weekly Magazine, and his co-founders and friends, Sarath Ravikumar and Varun Kumar. Mr. Durai is also one of the few founders who has taken an exit from his startup. Mr. Durairaju is an Engineering Graduate from Anna University, Marketing and Operations Graduate (MBA) from Sri Sairam Group of Institutions, Artificial Intelligence Powered Marketing Graduate from IIM, Calcutta and also learnt Product Growth and Marketing from GrowthX. He was a Business development Student Ambassador in Uniq Technologies, Co-Founder and CEO of Astute Fanfare, and now is also the Co-Founder of Brandinfluencerz. His startup Astutue Fanfare was started while he was a college student. Want to learn more about a Startup, founded by a Marketing executive and his friends? Tap the Play Button! Curious to know who's behind Tamilpreneur ? Listen to the intro of S5E1 - https://open.spotify.com/show/5f59gJfY5VIqP3NkPJwi3d Follow us on our Instagram : https://www.instagram.com/tamilpreneur/ Checkout our Youtube channel : https://www.youtube.com/watch?v=fOCHKQxZv7Y&t=1s&ab_channel=Tamilpreneur. If you are listening on Spotify, Google podcast - please Subscribe :) If you are listening on iTunes make sure to Rate and Review the podcast. Yes, It really helps !! Tamilpreneur - 1 Lakh Tamil entrepreneurs by 2025

Heard of Contactless Facemask Dispenser? If you haven't, you are at the right place to get great insights. If you have, let's add more information to your knowledge. Having already created a prototype in 2018 and officially collaborating with a co-working space to launch it in March 2020, the SARS CoV-2 Virus brought the project to a halt. The prototype is of an Automatic Tender Coconut water Dispenser called InstaCoco. Now, with the lockdown in place and launch of the first project under the radar atleast temporarily, what was the next plan to go about? The serial entrepreneurs used the time they got in the lockdown to brainstorm for a new idea and came up a new device using all scrap they could find at home - a Contactless Facemask Dispenser, INSTAMASK!  Bootstrapping the startup, InstaGood Technology Solutions (iGoTS), and incubating it with Anna University, the couple founders Vijayaragavan Visuvamithiran and Krishnna Priyadarshini are here with Tamilpreneur for a mind blowing interview session.  1. How did they convince their parents to quit their jobs to pursue entrepreneurship?   2. What qualities do they think wannapreneurs should have?  3. How did they grow the company?  4. What was their problem statement? And how did they find their solution? 5. What extraordinary questions did the aspiring entrepreneurs ask Vijay and Krishnna in the AMA session? And what did they learn from the founders?  Tune in to know the answers to your inquisition! Curious to know who's behind Tamilpreneur ? Listen to the intro in this episode :) Follow us on our Instagram  : https://www.instagram.com/tamilpreneur/ Checkout our Youtube channel : https://www.youtube.com/watch?v=fOCHKQxZv7Y&t=1s&ab_channel=Tamilpreneur. If you are listening on Spotify, Google podcast - please Subscribe :) If you are listening on iTunes make sure to Rate and Review the podcast. Yes, It really helps !!

In this episode #84, the hosts Naveen Samala & Sudhakar Nagandla interacted with another guest Partha Partha Gopalakrishna heads the SAP competency for strategic industry verticals in North America for Tech Mahindra. He has over 20+ years of SAP consulting experience and has been with Tech Mahindra for the last 3+ years.   He holds a Master's degree in Business administration from Virginia commonwealth university and a bachelor's degree in Mechanical engineering from College of Engineering Guindy, Anna University.  Partha was hired by TCS as a part of their campus recruitment drive, during the IT boom in 1997. He started his IT career as a developer. He got trained in SAP by SAP India in the year 2000 and since then he has been associated with the SAP technologies working in various functional, technical, program management, sales, and practice leadership roles.  He has worked across multiple industry verticals – Retail/CPG, transportation, discrete/process manufacturing, life sciences, automotive, etc.   Over the years, he has led various successful large SAP transformation programs at many Fortune 500 companies.  He has been actively involved in developing ERP transformation roadmaps for various customers.   is a regular speaker in various SAP forums and often writes/posts/blogs on the SAP topic on his social media?  He strongly believes that teamwork, networking, and out-of-the-box thinking are key to a successful IT career  He lives in Richmond, Virginia with his wife and two kids. Partha's Insights: Partha's Career Journey & Rising up in Corporate Ladder Day in a life of a SAP Practice Leader Key Industry and IT trends in the post COVID-19 world Global Trends impacting the SAP market and product portfolio Intelligent enterprise in layman terms How SAP technologies help companies become intelligent enterprise? How to build career in SAP Tips for those aspiring to MAKE BIG in their CAREER Enjoy the episode! Partha's LinkedIn Profile: https://www.linkedin.com/in/gpartha/ Dear #TGV Audience…Here is a chance to broadcast yourself

Anna University Soorappa | Is he Honest? | சூரப்பா சுத்தமானவரா? சூப்பர் சங்கியா? | சகாயம், சந்தோஷ் பாபு | JagadheesPaarvai

AICTI send mail to the Anna University. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app Support this podcast: https://anchor.fm/m-a51/support

**Pricing Strategies, deconstructing a sales pitch, making your entertainment profitable, sustaining a business, building an idea. when to seek investors ** This is the part 2 of our conversation. In part 1 Santhosh Palavesh and I discuss about building startups, busting myths, financial prudence, delegating decisions, energy suckers and much more! **About Santhosh Palavesh Santhosh Palavesh is a serial entrepreneur, marketer, digital expert, blockchain enthusiast, growth hacker, video-gamer, and a Tony Stark Addict! He is the CEO of UMM digital and The Chief Digital & Innovations Officer of Belfrics, One of fastest-growing Blockchain Fintech firm with a presence in over 12 countries. At present, he is responsible for developing blockchain-based solutions at Belfrics for Indian conglomerates, Banks as well as state governments. Santhosh has successfully completed his Bachelors in Mechanical Engineering as well as his Masters in Business Administration from Anna University in Chennai. He has an overall work experience of 10+ years in Fintech as well as Digital Transformation. Connect with Santhosh : FB :https://www.facebook.com/santhosh.palavesh In:https://www.linkedin.com/in/santhoshpalavesh/

Santhosh Palavesh and I discuss about building startups, busting myths, financial prudence, delegating decisions, energy suckers and much more! **This is the part 1 of our conversation. Stay tuned for part 2. About Santhosh Palavesh Santhosh Palavesh is a serial entrepreneur, marketer, digital expert, blockchain enthusiast, growth hacker, video-gamer, and a Tony Stark Addict! He is the CEO of UMM digital and The Chief Digital & Innovations Officer of Belfrics, One of fastest-growing Blockchain Fintech firm with a presence in over 12 countries. At present, he is responsible for developing blockchain-based solutions at Belfrics for Indian conglomerates, Banks as well as state governments. Santhosh has successfully completed his Bachelors in Mechanical Engineering as well as his Masters in Business Administration from Anna University in Chennai. He has an overall work experience of 10+ years in Fintech as well as Digital Transformation. 

With the advent of cloud computing, our view of cryptographic protocols has changed dramatically. In this talk, I will give an overview of some of the newer challenges that we face in cloud cryptography and outline some of the techniques used to solve these problems. In particular, a few questions that I will address are:1) How can we store sensitive data in the cloud, in an encrypted manner, and yet allow controlled access to certain portions of this data?2) How can we ensure reliability of data across cloud servers that may be connected by only a low-degree communication network, even when some of the servers may become corrupted?3) How can users authenticate themselves to the cloud in a user-friendly way?This talk will assume no prior knowledge of cryptography and is based on works that appear at TCC 2012, ICALP 2010 and STOC 2010. About the speaker: Nishanth Chandran is a post-doctoral researcher in the Cryptography group at Microsoft Research, Redmond. His research interests are in the area of cryptography, security and distributed algorithms. Nishanth has published several papers in top theory and cryptography conferences such as STOC, FOCS, Crypto, Eurocrypt, TCC and so on. He received his PhD in Computer Science from UCLA in 2011, his Masters in Computer Science from UCLA in 2007, and his Bachelors in Computer Science and Engineering from Anna University, India in 2005. Nishanth received the Dissertation Year Fellowship from UCLA and the Chorafas International Award for exceptional achievements in research in 2010. He is also a professional Indian classical violinist.