Podcasts about Computational linguistics

Our guest today is Dr. Ken Forbus, the Walter P. Murphy Professor of Computer Science and a Professor of Education at Northwestern University. Joining Dr. Ken Ford to co-host today's interview is Dr. James Allen, who was IHMC's associate director until he retired a few years ago. James is a founding fellow of the American Association for Artificial Intelligence and a perfect fit for today's discussion with Dr. Forbus, who, like James, is an AI pioneer.  Back in 2022, James was named a fellow by the Association for Computational Linguistics, an organization that studies computational language processing, another field he helped pioneer. Dr. Forbus also is a Fellow of the Association for the Advancement of Artificial Intelligence and was the inaugural winner of the Herbet A. Simon Prize for Advances in Cognitive Systems. He is well-known for his development of the Structure Mapping Engine. In artificial intelligence and cognitive science, the Structure Mapping Engine is a computer simulation of analogy and similarity comparisons that helped pave the way for computers to reason more like humans. Show Notes: [00:03:07] Ken opens the interview with Dr. Forbus by asking if it is true that he had an unusual hobby for a nerdy kid growing up. [00:04:18] James mentions that Dr. Forbus' family moved often when he was younger and asks how that affected him. [00:05:18] Ken mentions that when Dr. Forbus was in high school, he filled his free time reading about psychology and cognition before eventually coming across some articles on AI. Ken asks Dr. Forbus to talk about this experience and what happened next. [00:07:49] James asks Dr. Forbus if he remembers the first computer he owned. [00:09:17] Ken asks Dr. Forbus if there was anything, other than its reputation, that led him to attend MIT. [00:10:09] James mentions that for the past few decades, Dr. Forbus has been working on developing “human like” AI systems. While much of AI research and development has been focused on meeting the standard of the Turing test, James asks Dr. Forbus why he is not a fan of the Turing test. [00:12:24] Ken mentions that Dr. Forbus received his Ph.D. from MIT in 1984, the same year that Apple released the first Macintosh, which was rolled out with a famous Super Bowl ad. This computer was the first successful mouse driven personal computer with a graphical interface. Ken asks Dr. Forbus what he remembers about that ad, and what his reaction to it was at the time. [00:13:22] James mentions that 1984 was also the year that Dr. Forbus made his first splash in the AI world with his paper on qualitative process theory. James goes on to explain that at the time, qualitative reasoning regarding quantities was a major problem for AI. In his paper, Dr. Forbus proposed qualitative process theory as a representational framework for common sense physical reasoning, arguing that understanding common sense physical reasoning first required understanding of processes and their effects and limits. James asks Dr. Forbus to give an overview of this paper and its significance. [00:18:10] Ken asks Dr. Forbus how it was that he ended up marrying one of his collaborators on the Structure Mapping Engine project, Dedre Gentner. [00:19:14] James explains that Dedre's Structure Mapping Theory explains how people understand and reason about relationships between different situations, which is central to human cognition. James asks Dr. Forbus how Dedre's theory was foundational for the Structure Mapping Engine (SME). [00:25:19] Ken mentions how SME has gone through a number of changes and improvements over the years, as documented in Dr. Forbus' 2016 paper “Extending SME to handle large scale cognitive modeling.” Ken asks, as a cognitive model, what evidence Dr. Forbus has used to argue for the psychological and cognitive plausibility of SME. [00:30:00] Ken explains that many AI systems rely on deep learning,

Is AI Becoming Conscious? The Hidden Evolution No One is Talking About | Prof. De Kai  (Part 2)

Are We Raising AI… or Is AI Raising Us? | Professor De Kai on The Dov Baron Show

Michael Keller is a prominent pastor with a distinguished career intertwining academia and theology. Having spent his formative years in New York City and obtaining degrees in History and Psychology from Vanderbilt University, Michael pursued theological studies at Gordon Conwell Theological Seminary, earning both M.Div and THM degrees. He has served in various pastoral roles across London and Boston and most notably, Michael holds a Ph.D. in Computational Linguistics applied to the sermons of Jonathan Edwards from the Free University in Amsterdam. He currently pastors in Manhattan where he engages with a diverse community, addressing contemporary Christian challenges.Rebecca and Michael Keller explore the complexities of faith in urban environments and explore the changing landscape of spiritual conversations in cities like New York and Boston, addressing questions around Christianity's relevance and goodness in modern society.Sign up for weekly emails at RebeccaMcLaughlin.org/SubscribeFollow Confronting Christianity:Instagram | XPurchase Rebecca's Books:Confronting Christianity: 12 Hard Questions for the World's Largest ReligionDoes the Bible Affirm Same-Sex Relationships?: Examining 10 Claims about Scripture and Sexuality10 Questions Every Teen Should Ask (and Answer) about ChristianityJesus though the Eyes of Women: How the First Female Disciples Help Us Know and Love the LordNo Greater Love: A Biblical Vision for FriendshipConfronting Jesus: 9 Encounters with the Hero of the GospelsAmazon affiliate links are used where appropriate. As an Amazon Associate we earn from qualifying purchases, thank you for supporting!Produced by ⁠⁠⁠⁠The Good Podcast Co.⁠⁠⁠⁠

Guest: Dr. Christian Hempelmann, Professor of Computational Linguistics in the Department of Literature and Languages at East Texas A&M University Learn more about your ad choices. Visit megaphone.fm/adchoices

-Why is mental health in BC getting worse? Guest: Jonny Morris, CEO of the Canadian Mental Health Association of BC -What's driving up BC's liveable wage? Guest: Iglika Ivanova, Senior Economist at the Canadian Center for Policy Alternatives' BC Branch and Lead Author of the Study -What caused the laughter epidemic of 1962? Guest: Dr. Christian Hempelmann, Professor of Computational Linguistics in the Department of Literature and Languages at East Texas A&M University -Why should we all become experts at something? Guest: Hannah Poikonen, Neuroscientist and Researcher at ETH Zurich (public university in Zurich) Learn more about your ad choices. Visit megaphone.fm/adchoices

The Cognitive Crucible is a forum that presents different perspectives and emerging thought leadership related to the information environment. The opinions expressed by guests are their own, and do not necessarily reflect the views of or endorsement by the Information Professionals Association. During this episode, Remi Whiteside discusses his Ph.D. research and dissertation which is entitled: Peering into US Army Media, Information, and Data Literacy Fundamentals against Malign Information in the Open Information Environment: A Qualitative Case Study. According to Remi Whiteside, the US Army currently has no institutionalized program-of-record for educational development, uniquely designed for its population of uniformed Information Professionals in training to detect, analyze, and scrutinize malign information in the Open Information Environment. Unlike its peer services, the US Army does not perceive malign information, a reimagined tool of ideological subversion, as a high-caliber threat so far as to invest the time, money, or resources into critical, foundational metaliteracy competencies needed for its Information Professionals for the Open Information Environment.  Recording Date: 1 Aug 2024 Research Question: Remi Whiteside suggests an interested student ask–in relation to media and information—how do narratives derived from the Open Information Environment shape servicemembers' metanarratives and do these metanarratives conflict with military identity? Resources: Peering into US Army Media, Information, and Data Literacy Fundamentals against Malign Information in the Open Information Environment: A Qualitative Case Study Syntactic Structures by Noam Chomsky Rhet Ops: Rhetoric and Information Warfare (Composition, Literacy, and Culture) by Jim Ridolfo and William Hart-Davidson NOEMA Magazine Link to full show notes and resources Guest Bio: Remington Whiteside is an active-duty Chief Warrant Officer in the US Army, career education, and academic researcher into MIDLE (media, information, and data literacy education) and M2DP (malinformation, misinformation, disinformation, propaganda). He started his career as an enlisted Cryptologic Linguist, with work in strategic, SOF, and training environments. He metamorphosed to Signals Intelligence Warrant Officer, specializing in tactical SIGINT, COMINT, OSINT, PAI, OPSEC, and Intelligence Support to Cyber and Electromagnetic Warfare (EW) training as an Observer-Coach-Trainer at Fort Johnson, Louisiana at the Joint Readiness Training Center. Remi holds an undergraduate degree in Middle Eastern studies, a graduate degree in Applied Linguistics with a focus on Computational Linguistics, and a Doctor of Philosophy degree in Education. He is lovingly supported by his wife Sara and his three children: Evolette, Torben, and Soren. About: The Information Professionals Association (IPA) is a non-profit organization dedicated to exploring the role of information activities, such as influence and cognitive security, within the national security sector and helping to bridge the divide between operations and research. Its goal is to increase interdisciplinary collaboration between scholars and practitioners and policymakers with an interest in this domain. For more information, please contact us at communications@information-professionals.org. Or, connect directly with The Cognitive Crucible podcast host, John Bicknell, on LinkedIn. Disclosure: As an Amazon Associate, 1) IPA earns from qualifying purchases, 2) IPA gets commissions for purchases made through links in this post.

Peoples & Things host, Lee Vinsel, talks to Emily Bender, Professor of Linguistics, Director of the Masters of Science in Computational Linguistics program, and Director of the Computational Linguistics Laboratory at University of Washington, about her work on artificial intelligence criticism. Bender is also an adjunct professor in the School of Computer Science and Engineering and the Information School at UW; she is a member of the Tech Policy Lab, the Value Sensitive Design Lab, the Distributed AI Research Institute, and RAISE, or Responsibilities in AI Systems and Experiences; *AND*, with Alex Hanna, she is co-host of the Mystery AI Hype Theater podcast, which you should check out. Vinsel and Bender talk about the current AI bubble, what is driving it, and the technological potentials and limitations of this technology. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

Peoples & Things host, Lee Vinsel, talks to Emily Bender, Professor of Linguistics, Director of the Masters of Science in Computational Linguistics program, and Director of the Computational Linguistics Laboratory at University of Washington, about her work on artificial intelligence criticism. Bender is also an adjunct professor in the School of Computer Science and Engineering and the Information School at UW; she is a member of the Tech Policy Lab, the Value Sensitive Design Lab, the Distributed AI Research Institute, and RAISE, or Responsibilities in AI Systems and Experiences; *AND*, with Alex Hanna, she is co-host of the Mystery AI Hype Theater podcast, which you should check out. Vinsel and Bender talk about the current AI bubble, what is driving it, and the technological potentials and limitations of this technology. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/economics

Peoples & Things host, Lee Vinsel, talks to Emily Bender, Professor of Linguistics, Director of the Masters of Science in Computational Linguistics program, and Director of the Computational Linguistics Laboratory at University of Washington, about her work on artificial intelligence criticism. Bender is also an adjunct professor in the School of Computer Science and Engineering and the Information School at UW; she is a member of the Tech Policy Lab, the Value Sensitive Design Lab, the Distributed AI Research Institute, and RAISE, or Responsibilities in AI Systems and Experiences; *AND*, with Alex Hanna, she is co-host of the Mystery AI Hype Theater podcast, which you should check out. Vinsel and Bender talk about the current AI bubble, what is driving it, and the technological potentials and limitations of this technology. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/politics-and-polemics

Peoples & Things host, Lee Vinsel, talks to Emily Bender, Professor of Linguistics, Director of the Masters of Science in Computational Linguistics program, and Director of the Computational Linguistics Laboratory at University of Washington, about her work on artificial intelligence criticism. Bender is also an adjunct professor in the School of Computer Science and Engineering and the Information School at UW; she is a member of the Tech Policy Lab, the Value Sensitive Design Lab, the Distributed AI Research Institute, and RAISE, or Responsibilities in AI Systems and Experiences; *AND*, with Alex Hanna, she is co-host of the Mystery AI Hype Theater podcast, which you should check out. Vinsel and Bender talk about the current AI bubble, what is driving it, and the technological potentials and limitations of this technology. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/science-technology-and-society

Peoples & Things host, Lee Vinsel, talks to Emily Bender, Professor of Linguistics, Director of the Masters of Science in Computational Linguistics program, and Director of the Computational Linguistics Laboratory at University of Washington, about her work on artificial intelligence criticism. Bender is also an adjunct professor in the School of Computer Science and Engineering and the Information School at UW; she is a member of the Tech Policy Lab, the Value Sensitive Design Lab, the Distributed AI Research Institute, and RAISE, or Responsibilities in AI Systems and Experiences; *AND*, with Alex Hanna, she is co-host of the Mystery AI Hype Theater podcast, which you should check out. Vinsel and Bender talk about the current AI bubble, what is driving it, and the technological potentials and limitations of this technology. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/technology

In this podcast episode, Diana and Nicole discuss the use of Generative AI in scholarly and genealogical writing, emphasizing the importance of transparency in disclosing AI assistance. They talk about editorial guidelines from scholarly journals and the Association of Computational Linguistics, which suggest clear declarations of AI's involvement in literature searches, drafting, and idea generation. Key points include recommendations for crediting AI-generated content not as authors but by detailing the AI's role. They also explore citation practices, such as including the AI model and user details, and stress the user's responsibility to verify and refine AI outputs in professional settings, advocating for explicit disclosures in various document sections. Nicole generated this summary with ChatGPT 4. Links Disclosing Use of AI for Writing Assistance in Genealogy - https://familylocket.com/disclosing-use-of-ai-for-writing-assistance-in-genealogy/  Jordan Boyd-Graber et al., “ACL 2023 Policy on AI Writing Assistance,” ACL 2023, January 10, 2023, https://2023.aclweb.org/blog/ACL-2023-policy/. Association for Computational Linguistics (ACL) Rolling Review, “Call for Papers,” ACL Rolling Review, 2024, https://aclrollingreview.org/cfp. Baldy Dyer research report from log – Claude AI April 2024 - https://familylocket.com/wp-content/uploads/2024/04/Baldy-Dyer-research-report-from-log-Claude-AI-April-2024.pdf Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code “FamilyLocket” at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product/airtable-research-logs-for-genealogy-quick-reference/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series 2024 - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product/research-like-a-pro-webinar-series-2024/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes, Stitcher, Google Podcasts, or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Top 20 Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

Greg Baker knows more than most about AI and where it's headed. As an AI futurist and lecturer in Computational Linguistics at Macquarie University, Greg educates students on the intricacies of Artificial Intelligence for Text and Vision, and blends his theoretical insights with practical applications.  He helps the C-suite understand the future of labour, how to maximise AI productivity gains and how to gain a deep technical understanding of what is possible. He is a director at the Institute for Open Systems Technologies and has worked at Google and CSIRO and is a leading voice in how to understand the opportunities that AI offers us today and into the future. If you're looking to discover how AI is impacting copywriters and the writing industry, this is the episode you have been waiting for.  Read the show notes This podcast is brought to you by the Australian Writers' Centre. WritersCentre.com.au Join our community of copywriters at CopyClub.com.au.See omnystudio.com/listener for privacy information.

“I’m a jack of all trades – all linguists are” Falene McKenna is a linguist, tech enthusiast, conversation wizard, and a “true robot whisperer”. She studied Computational Linguistics at the University of Alberta. Since then, she’s led QA crusades, expanded beta programs across North American homes, and built customer support systems from the ground up. Falene has presented at various events, including the Conversation Design Festival 2022, emphasizing the importance of bot building standards, language expertise in AI experiences, and persona building. She is also an active member of Women in Voice, promoting gender diversity in the voice technology industry. Falene McKenna on LinkedIn Falene McKenna’s speaking profile on Sessionize Alberta Language Technology Lab (ALT Lab) Conversation Design Institute Danielle Boyer’s Skobots Topics include – language revitalization – computational linguistics – QA – robotics – conversational AI – conversation design – data science – academic precarity – job interviewsThe post Episode #37: Falene McKenna first appeared on Linguistics Careercast.

Emily and Alex are joined by Stanford PhD student Haley Lepp to examine the increasing hype around LLMs in education spaces - whether they're pitched as ways to reduce teacher workloads, increase accessibility, or simply "democratize learning and knowing" in the Global South. Plus a double dose of devaluating educator expertise and fatalism about the 'inevitability' of LLMs in the classroom.Haley Lepp is a Ph.D. student in the Stanford University Graduate School of Education. She draws on critical data studies, computational social science, and qualitative methods to understand the rise of language technologies and their use for educational purposes. Haley has worked in many roles in the education technology sector, including curriculum design and NLP engineering. She holds an M.S. in Computational Linguistics from the University of Washington and B.S. in Science, Technology, and International Affairs from Georgetown University.References:University of Michigan debuts 'customized AI services'Al Jazeera: An AI classroom revolution is comingCalifornia Teachers Association: The Future of Education?Politico: AI is not just for cheatingExtra credit: "Teaching Machines: The History of Personalized Learning" by Audrey WattersFresh AI Hell:AI generated travel article for Ottawa -- visit the food bank! Microsoft Copilot is “usefully wrong”* Response from Jeff Doctor“Ethical” production of “AI girlfriends”Withdrawn AI-written preprint on millipedes resurfaces, causing alarm among myriapodological communityNew York Times: How to Tell if Your A.I. Is Conscious* Response from VentureBeat: Today's AI is alchemy.EUYou can check out future livestreams at https://twitch.tv/DAIR_Institute. Follow us!Emily Twitter: https://twitter.com/EmilyMBender Mastodon: https://dair-community.social/@EmilyMBender Bluesky: https://bsky.app/profile/emilymbender.bsky.social Alex Twitter: https://twitter.com/@alexhanna Mastodon: https://dair-community.social/@alex Bluesky: https://bsky.app/profile/alexhanna.bsky.social Music by Toby Menon.Artwork by Naomi Pleasure-Park. Production by Christie Taylor.

Over the last year, AI large-language models (LLMs) like ChatGPT have demonstrated a remarkable ability to carry on human-like conversations in a variety of different concepts. But the way these LLMs "learn" is very different from how human beings learn, and the same can be said for how they "reason." It's reasonable to ask, do these AI programs really understand the world they are talking about? Do they possess a common-sense picture of reality, or can they just string together words in convincing ways without any underlying understanding? Computer scientist Yejin Choi is a leader in trying to understand the sense in which AIs are actually intelligent, and why in some ways they're still shockingly stupid.Blog post with transcript: https://www.preposterousuniverse.com/podcast/2023/08/28/248-yejin-choi-on-ai-and-common-sense/Support Mindscape on Patreon.Yejin Choi received a Ph.D. in computer science from Cornell University. She is currently the Wissner-Slivka Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington and also a senior research director at AI2 overseeing the project Mosaic. Among her awards are a MacArthur fellowship and a fellow of the Association for Computational Linguistics.University of Washington web pageGoogle Scholar publicationsWikipediaSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

MLOps Coffee Sessions #171 with Thibaut Labarre, Using Large Language Models at AngelList co-hosted by Ryan Russon. We are now accepting talk proposals for our next LLM in Production virtual conference on October 3rd. Apply to speak here: https://go.mlops.community/NSAX1O // Abstract Thibaut innovatively addressed previous system constraints, achieving scalability and cost efficiency. Leveraging AngelList investing and natural language processing expertise, they refined news article classification for investor dashboards. Central is their groundbreaking platform, AngelList Relay, automating parsing and offering vital insights to investors. Amid challenges like Azure OpenAI collaboration and rate limit solutions, Thibaut reflects candidly. The narrative highlights prompt engineering's strategic importance and empowering domain experts for ongoing advancement. // Bio Thibaut LaBarre is an engineering lead with a background in Natural Language Processing (NLP). Currently, Thibaut focuses on unlocking the potential of Large Language Model (LLM) technology at AngelList, enabling everyone within the organization to become prompt engineers on a quest to streamline and automate the infrastructure for Venture Capital. Prior to that, Thibaut began his journey at Amazon as an intern where he built Heartbeat, a state-of-the-art NLP tool that consolidates millions of data points from various feedback sources, such as product reviews, customer contacts, and social media, to provide valuable insights to global product teams. Over the span of seven years, he expanded his internship project into an organization of 20 engineers. He received a M.S. in Computational Linguistics from the University of Washington. // MLOps Jobs board https://mlops.pallet.xyz/jobs // MLOps Swag/Merch https://mlops-community.myshopify.com/ // Related Links ⁠Website: https://www.angellist.com/venture/relay --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Catch all episodes, blogs, newsletters, and more: https://mlops.community/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Ryan on LinkedIn: https://www.linkedin.com/in/ryanrusson/ Connect with Thibaut on LinkedIn: https://www.linkedin.com/in/thibautlabarre/

#dungeonsanddragons #dnd #criticalrole What does science say about dungeons and dragons? is it dangerous for your mental health? Is D&D a religion or a cult? Academic review and research studies on the Psychology and Religious elements in dungeons and dragons. RECOMMENDED READINGS Dangerous Games by Laycock https://amzn.to/3YrACEU Invented Religions by Cusack https://amzn.to/3ROfjeV D&D Player's Handbook https://amzn.to/3l9kvh8 Player's Handbook Dungeons and Dragons 5th Edition with DND Dice and Complete Printable Kit https://amzn.to/3Y72Yob D&D Dungeon Master's Guide https://amzn.to/3X3zhmQ D&D Monster Manual https://amzn.to/3X9LaaG MY SET UP Canon 90D camera https://amzn.to/3ZtfT4W Canon EF-S 18-55mm f/3.5-5.6 https://amzn.to/3XwOP36 Teleprompter https://amzn.to/3ZE4KhK Shure SM7B Microphone https://amzn.to/3CMz3ZX Microphone stand https://amzn.to/3QJbgzY lights https://amzn.to/3w3VAxr REFERENCES Adams, A. 2013. Needs Met Through Role-Playing Games: A Fantasy Theme Analysis of Dungeons & Dragons. Kaleidoscope: A Graduate Journal of Qualitative Communication Research. 12(1). Blackmon, W.D. 1994. Dungeons and Dragons: The Use of a Fantasy Game in the Psychotherapeutic Treatment of a Young Adult. American Journal of Psychotherapy. 48(4), pp.624–632. DeRenard, L.A. and Kline, L.M. 1990. Alienation and the Game Dungeons and Dragons. Psychological Reports. 66(3_suppl), pp.1219–1222. Laycock, J.P. 2015. Dangerous Games: What the Moral Panic over Role-Playing Games Says about Play, Religion, and Imagined Worlds. University of California Press. Perlini-Pfister, F. 2012. Philosophers with Clubs: Negotiating Cosmology and Worldviews in Dungeons & Dragons In: P. Bornet and M. Burger, eds. Religions in Play: Games, Rituals, and Virtual Worlds. Zürich: Theologischer Verlag Zürich, pp.275–294. Rameshkumar, R. and Bailey, P. 2020. Storytelling with Dialogue: A Critical Role Dungeons and Dragons Dataset In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics [Online]. Online: Association for Computational Linguistics, pp.5121–5134. [Accessed 31 January 2023]. Available from: https://aclanthology.org/2020.acl-main.459. Simón, A. 1987. Emotional stability pertaining to the game of Dungeons & Dragons. Psychology in the Schools. 24(4), pp.329–332. 0:00 Introduction: Dungeons and Dragons 01:04 D&D Beginning and early reaction 01:47 Is D&D dangerous? 04:15 The religious side of D&D 05:33 The Gods 07:47 The Alignment ethical system 10:27 Other Worlds 12:20 Mircea Eliade - theory of the sacred 14:25 Support Angela's Symposium BECOME MY PATRON! https://www.patreon.com/angelapuca ONE-OFF DONATIONS https://paypal.me/angelasymposium JOIN MEMBERSHIPS https://www.youtube.com/channel/UCPSbip_LX2AxbGeAQfLp-Ig/join FOLLOW ME: Facebook (Angela's Symposium), Instagram (angela_symposium), Twitter (@angelapuca11), TikTok (Angela's Symposium). Music by Erose MusicBand. Check them out! https://www.youtube.com/watch?v=Ja2mMNC5ybc

It's the Season 10 finale of the Elixir Wizards podcast! José Valim, Guillaume Duboc, and Giuseppe Castagna join Wizards Owen Bickford and Dan Ivovich to dive into the prospect of types in the Elixir programming language! They break down their research on set-theoretical typing and highlight their goal of creating a type system that supports as many Elixir idioms as possible while balancing simplicity and pragmatism. José, Guillaume, and Giuseppe talk about what initially sparked this project, the challenges in bringing types to Elixir, and the benefits that the Elixir community can expect from this exciting work. Guillaume's formalization and Giuseppe's "cutting-edge research" balance José's pragmatism and "Guardian of Orthodoxy" role. Decades of theory meet the needs of a living language, with open challenges like multi-process typing ahead. They come together with a shared joy of problem-solving that will accelerate Elixir's continued growth. Key Topics Discussed in this Episode: Adding type safety to Elixir through set theoretical typing How the team chose a type system that supports as many Elixir idioms as possible Balancing simplicity and pragmatism in type system design Addressing challenges like typing maps, pattern matching, and guards The tradeoffs between Dialyzer and making types part of the core language Advantages of typing for catching bugs, documentation, and tooling The differences between typing in the Gleam programming language vs. Elixir The possibility of type inference in a set-theoretic type system The history and development of set-theoretic types over 20 years Gradual typing techniques for integrating typed and untyped code How José and Giuseppe initially connected through research papers Using types as a form of "mechanized documentation" The risks and tradeoffs of choosing syntax Cheers to another decade of Elixir! A big thanks to this season's guests and all the listeners! Links and Resources Mentioned in this Episode: Bringing Types to Elixir | Guillaume Duboc & Giuseppe Castagna | ElixirConf EU 2023 (https://youtu.be/gJJH7a2J9O8) Keynote: Celebrating the 10 Years of Elixir | José Valim | ElixirConf EU 2022 (https://youtu.be/Jf5Hsa1KOc8) OCaml industrial-strength functional programming https://ocaml.org/ ℂDuce: a language for transformation of XML documents http://www.cduce.org/ Ballerina coding language https://ballerina.io/ Luau coding language https://luau-lang.org/ Gleam type language https://gleam.run/ "The Design Principles of the Elixir Type System" (https://www.irif.fr/_media/users/gduboc/elixir-types.pdf) by G. Castagna, G. Duboc, and J. Valim "A Gradual Type System for Elixir" (https://dlnext.acm.org/doi/abs/10.1145/3427081.3427084) by M. Cassola, A. Talagorria, A. Pardo, and M. Viera "Programming with union, intersection, and negation types" (https://www.irif.fr/~gc/papers/set-theoretic-types-2022.pdf), by Giuseppe Castagna "Covariance and Contravariance: a fresh look at an old issue (a primer in advanced type systems for learning functional programmers)" (https://www.irif.fr/~gc/papers/covcon-again.pdf) by Giuseppe Castagna "A reckless introduction to Hindley-Milner type inference" (https://www.lesswrong.com/posts/vTS8K4NBSi9iyCrPo/a-reckless-introduction-to-hindley-milner-type-inference) Special Guests: Giuseppe Castagna, Guillaume Duboc, and José Valim.

In this episode Lauren Hawker Zafer is joined by Janna Lipenkova Who Can Benefit From This Conversation?  Tune in to this captivating podcast episode, delving into the realm of detecting and combating greenwashing. Engage with Lauren and Janna as they unravel the intricacies of LLMs and other NLP techniques, and how they can help uncover the truth behind environmental and sustainability claims. Learn and grow while you listen, arming yourself with invaluable knowledge to navigate the world of sustainability with clarity and confidence. Who is Janna Lipenkova?Janna Lipenkova holds a Master in Chinese Studies and Economics, a PhD in Computational Linguistics and speaks seven languages fluently. After several years of work in AI in academia and industry, she started her own analytics business and is now the CEO and Co-Founder of Equintel. Equintel uses AI and NLP methods to deliver timely and objective ESG and impact analytics. Janna is fascinated by the current developments in Generative AI and their impact on our society and actively contributes to public discourse in the AI space on Medium and her blog (jannalipenkova.com). REDEFINING AI is powered by The Squirro Academy - learn.squirro.com. Try our free courses on AI, ML, NLP and Cognitive Search at the Squirro Academy and find out more about Squirro here.

Spotlight Nine is a snippet from our upcoming episode: Janna Lipenkova - Detecting and Mitigating Greenwashing Risks with LLMs and Other NLP Approaches. Listen to the full episode, as soon as it comes out by subscribing to Redefining AI. Who is Janna Lipenkova?Janna Lipenkova holds a Master in Chinese Studies and Economics, a PhD in Computational Linguistics and speaks seven languages fluently. After several years of work in AI in academia and industry, she started her own analytics business and is now the CEO and Co-Founder of Equintel. Equintel uses AI and NLP methods to deliver timely and objective ESG and impact analytics. Janna is fascinated by the current developments in Generative AI and their impact on our society and actively contributes to public discourse in the AI space. You can find out more about her contribution on her blog (jannalipenkova.com) and Medium (https://medium.com/@janna.lipenkova_52659). Why this Episode? Tune in to this captivating podcast episode, delving into the realm of detecting and combating greenwashing. Engage with Janna as she unravels the intricacies of LLMS and other NLP techniques and how they can help you to uncover the truth behind environmental claims. Learn and grow while you listen, arming yourself with invaluable knowledge to navigate the world of sustainability with clarity and confidence.

Sign up for the next LLM in production conference here: https://go.mlops.community/LLMinprod Watch all the talks from the first conference: https://go.mlops.community/llmconfpart1 // Abstract In this panel discussion, the topic of the cost of running large language models (LLMs) is explored, along with potential solutions. The benefits of bringing LLMs in-house, such as latency optimization and greater control, are also discussed. The panelists explore methods such as structured pruning and knowledge distillation for optimizing LLMs. OctoML's platform is mentioned as a tool for the automatic deployment of custom models and for selecting the most appropriate hardware for them. Overall, the discussion provides insights into the challenges of managing LLMs and potential strategies for overcoming them. // Bio Lina Weichbrodt Lina is a pragmatic freelancer and machine learning consultant that likes to solve business problems end-to-end and make machine learning or a simple, fast heuristic work in the real world. In her spare time, Lina likes to exchange with other people on how they can implement best practices in machine learning, talk to her at the Machine Learning Ops Slack: shorturl.at/swxIN. Luis Ceze Luis Ceze is Co-Founder and CEO of OctoML, which enables businesses to seamlessly deploy ML models to production making the most out of the hardware. OctoML is backed by Tiger Global, Addition, Amplify Partners, and Madrona Venture Group. Ceze is the Lazowska Professor in the Paul G. Allen School of Computer Science and Engineering at the University of Washington, where he has taught for 15 years. Luis co-directs the Systems and Architectures for Machine Learning lab (sampl.ai), which co-authored Apache TVM, a leading open-source ML stack for performance and portability that is used in widely deployed AI applications. Luis is also co-director of the Molecular Information Systems Lab (misl.bio), which led pioneering research in the intersection of computing and biology for IT applications such as DNA data storage. His research has been featured prominently in the media including New York Times, Popular Science, MIT Technology Review, and the Wall Street Journal. Ceze is a Venture Partner at Madrona Venture Group and leads their technical advisory board. Jared Zoneraich Co-Founder of PromptLayer, enabling data-driven prompt engineering. Compulsive builder. Jersey native, with a brief stint in California (UC Berkeley '20) and now residing in NYC. Daniel Campos Hailing from Mexico Daniel started his NLP journey with his BS in CS from RPI. He then worked at Microsoft on Ranking at Bing with LLM(back when they had 2 commas) and helped build out popular datasets like MSMARCO and TREC Deep Learning. While at Microsoft he got his MS in Computational Linguistics from the University of Washington with a focus on Curriculum Learning for Language Models. Most recently, he has been pursuing his Ph.D. at the University of Illinois Urbana Champaign focusing on efficient inference for LLMs and robust dense retrieval. During his Ph.D., he worked for companies like Neural Magic, Walmart, Qualtrics, and Mendel.AI and now works on bringing LLMs to search at Neeva. Mario Kostelac Currently building AI-powered products in Intercom in a small, highly effective team. I roam between practical research and engineering but lean more towards engineering and challenges around running reliable, safe, and predictable ML systems. You can imagine how fun it is in LLM era :). Generally interested in the intersection of product and tech, and building a differentiation by solving hard challenges (technical or non-technical). Software engineer turned into Machine Learning engineer 5 years ago.

Our guest, Christopher Manning, is a computational linguist. He builds computer models that understand and generate language using math. Words are the key component of human intelligence, he says, and why generative AI, like ChatGPT, has caused such a stir. We used to hope a model might produce one coherent sentence and suddenly ChatGPT is composing five-paragraph stories and doing mathematical proofs in rhyming verse, Manning tells host Russ Altman in this episode of Stanford Engineering's The Future of Everything podcast.

Our guest, Christopher Manning, is a computational linguist. He builds computer models that understand and generate language using math. Words are the key component of human intelligence, he says, and why generative AI, like ChatGPT, has caused such a stir. We used to hope a model might produce one coherent sentence and suddenly ChatGPT is composing five-paragraph stories and doing mathematical proofs in rhyming verse, Manning tells host Russ Altman in this episode of Stanford Engineering's The Future of Everything podcast.

Has ChatGPT made copywriters redundant?  Far from it, according to Greg Baker, a lecturer in Artificial Intelligence and Computational Linguistics at Macquarie University. Greg, more than most, has his finger on the pulse on not just where ChatGPT is heading but how it actually works!   He has spent his life researching natural language processing and has a deep knowledge of what these tools can do and more importantly, how we copywriters and creative folk can harness them to our advantage. Read the show notes This podcast is brought to you by the Australian Writers' Centre. WritersCentre.com.au Join our community of copywriters at CopyClub.com.au.See omnystudio.com/listener for privacy information.

Paris Marx is joined by Emily M. Bender to discuss what it means to say that ChatGPT is a “stochastic parrot,” why Elon Musk is calling to pause AI development, and how the tech industry uses language to trick us into buying its narratives about technology. Emily M. Bender is a professor in the Department of Linguistics at the University of Washington and the Faculty Director of the Computational Linguistics Master's Program. She's also the director of the Computational Linguistics Laboratory. Follow Emily on Twitter at @emilymbender or on Mastodon at @emilymbender@dair-community.social. Tech Won't Save Us offers a critical perspective on tech, its worldview, and wider society with the goal of inspiring people to demand better tech and a better world. Follow the podcast (@techwontsaveus) and host Paris Marx (@parismarx) on Twitter, and support the show on Patreon. The podcast is produced by Eric Wickham and part of the Harbinger Media Network.  Also mentioned in this episode:Emily was one of the co-authors on the “On the Dangers of Stochastic Parrots” paper and co-wrote the “Octopus Paper” with Alexander Koller. She was also recently profiled in New York Magazine and has written about why policymakers shouldn't fall for the AI hype.The Future of Life Institute put out the “Pause Giant AI Experiments” letter and the authors of the “Stochastic Parrots” paper responded through DAIR Institute.Zachary Loeb has written about Joseph Weizenbaum and the ELIZA chatbot.Leslie Kay Jones has researched how Black women use and experience social media.As generative AI is rolled out, many tech companies are firing their AI ethics teams.Emily points to Algorithmic Justice League and AI Incident Database.Deborah Raji wrote about data and systemic racism for MIT Tech Review.Books mentioned: Weapons of Math Destruction by Cathy O'Neil, Algorithms of Oppression by Safiya Noble, The Age of Surveillance Capitalism by Shoshana Zuboff, Race After Technology by Ruha Benjamin, Ghost Work by Mary L Gray & Siddharth Suri, Artificial Unintelligence by Meredith Broussard, Design Justice by Sasha Costanza-Chock, Data Conscience: Algorithmic S1ege on our Hum4n1ty by Brandeis Marshall.Support the show

In this Silicon Valley Tech & AI episode presented by GSD Venture Studios Gary Fowler interviews De Kai. Guest: De Kai is Professor of Computer Science and Engineering at HKUST, and Distinguished Research Scholar at Berkeley's International Computer Science Institute. He is among only 17 scientists worldwide named by the Association for Computational Linguistics as a Founding ACL Fellow, for his pioneering contributions to machine translation and machine learning foundations of systems like the Google/Yahoo/Microsoft translators. Recruited as founding faculty of HKUST directly from UC Berkeley, where his PhD thesis was one of the first to spur the paradigm shift toward machine learning based natural language processing technologies, he founded HKUST's internationally funded Human Language Technology Center which launched the world's first web translator over twenty years ago.

Think of this as the impossible lecture on AI. Recorded across time, but presented as one flow, a series of AI experts line up to contribute to the conversation. https://authoredby.ai DISCLAIMER: The sound quality (and only sound quality!) from calls in this episode has been enhanced using AI. The otherwise identical unenhanced version can be found here: https://www.authoredby.ai/03unenhanced/ Hosted by Stephen Follows and Eliel Camargo-Molina Guests (in order of appearance) Mike Kanaan, Author of "T-Minus AI", Chief of Staff of the U.S. Air Force FellowBob Fisher, Professor of Computer Vision at University of EdinburghAngelina McMillan-Major, PhD Candidate in Computational Linguistics at the University of WashingtonMagnus Sahlgren, Head of research for natural language understanding at AI SwedenChristoph Molnar, Researcher and author of "Interpretable Machine Learning"Sameer Singh, Associate Professor of Computer Science at the University of CaliforniaAmandalynne Paullada, Researcher in Computational Linguistics at the University of WashingtonDan Rockmore, Professor of Math and Computer Science at the University of DartmouthKen Stanley, AI Researcher, former Open-endedness Team Lead at OpenAIGPT-3Edited by Eliel Camargo-Molina and Jess YungMusic by Eliel Camargo-Molina and GPT-3Mastering by Adanze "Lady Ze" UnaegbuG46PUiGigCepW8Ld0R0D

Support us! https://www.patreon.com/mlst MLST Discord: https://discord.gg/aNPkGUQtc5 YT: https://youtu.be/i9VPPmQn9HQ Edward Grefenstette is a Franco-American computer scientist who currently serves as Head of Machine Learning at Cohere and Honorary Professor at UCL. He has previously been a research scientist at Facebook AI Research and staff research scientist at DeepMind, and was also the CTO of Dark Blue Labs. Prior to his move to industry, Edward was a Fulford Junior Research Fellow at Somerville College, University of Oxford, and was lecturing at Hertford College. He obtained his BSc in Physics and Philosophy from the University of Sheffield and did graduate work in the philosophy departments at the University of St Andrews. His research draws on topics and methods from Machine Learning, Computational Linguistics and Quantum Information Theory, and has done work implementing and evaluating compositional vector-based models of natural language semantics and empirical semantic knowledge discovery. https://www.egrefen.com/ https://cohere.ai/ TOC: [00:00:00] Introduction [00:02:52] Differential Semantics [00:06:56] Concepts [00:10:20] Ontology [00:14:02] Pragmatics [00:16:55] Code helps with language [00:19:02] Montague [00:22:13] RLHF [00:31:54] Swiss cheese problem / retrieval augmented [00:37:06] Intelligence / Agency [00:43:33] Creativity [00:46:41] Common sense [00:53:46] Thinking vs knowing References: Large language models are not zero-shot communicators (Laura Ruis) https://arxiv.org/abs/2210.14986 Some remarks on Large Language Models (Yoav Goldberg) https://gist.github.com/yoavg/59d174608e92e845c8994ac2e234c8a9 Quantum Natural Language Processing (Bob Coecke) https://www.cs.ox.ac.uk/people/bob.coecke/QNLP-ACT.pdf Constitutional AI: Harmlessness from AI Feedback https://www.anthropic.com/constitutional.pdf Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (Patrick Lewis) https://www.patricklewis.io/publication/rag/ Natural General Intelligence (Prof. Christopher Summerfield) https://global.oup.com/academic/product/natural-general-intelligence-9780192843883 ChatGPT with Rob Miles - Computerphile https://www.youtube.com/watch?v=viJt_DXTfwA

There's rarely an expected path in science. This week's episode, produced in partnership with The Carl R. Woese Institute for Genomic Biology, features two stories from scientists of their cutting-edge research institute at the University of Illinois Urbana-Champaign who took unexpected journeys to get where they are today. Part 1: After a troubling personal experience with the health care system, Heng Ji decides to try to fix it. Part 2: When Brendan Harley is diagnosed with leukaemia in high school, it changes everything. Heng Ji is a professor at Computer Science Department, and an affiliated faculty member at Electrical and Computer Engineering Department of University of Illinois at Urbana-Champaign. She is also an Amazon Scholar. She received her B.A. and M. A. in Computational Linguistics from Tsinghua University, and her M.S. and Ph.D. in Computer Science from New York University. Her research interests focus on Natural Language Processing, especially on Multimedia Multilingual Information Extraction, Knowledge Base Population and Knowledge-driven Generation. She was selected as "Young Scientist" and a member of the Global Future Council on the Future of Computing by the World Economic Forum in 2016 and 2017. She was named as part of Women Leaders of Conversational AI (Class of 2023) by Project Voice. The awards she received include "AI's 10 to Watch" Award by IEEE Intelligent Systems in 2013, NSF CAREER award in 2009, PACLIC2012 Best paper runner-up, "Best of ICDM2013" paper award, "Best of SDM2013" paper award, ACL2018 Best Demo paper nomination, ACL2020 Best Demo Paper Award, NAACL2021 Best Demo Paper Award, Google Research Award in 2009 and 2014, IBM Watson Faculty Award in 2012 and 2014 and Bosch Research Award in 2014-2018. She was invited by the Secretary of the U.S. Air Force and AFRL to join Air Force Data Analytics Expert Panel to inform the Air Force Strategy 2030. She is the lead of many multi-institution projects and tasks, including the U.S. ARL projects on information fusion and knowledge networks construction, DARPA DEFT Tinker Bell team and DARPA KAIROS RESIN team. She has coordinated the NIST TAC Knowledge Base Population task since 2010. She was the associate editor for IEEE/ACM Transaction on Audio, Speech, and Language Processing, and served as the Program Committee Co-Chair of many conferences including NAACL-HLT2018 and AACL-IJCNLP2022. She is elected as the North American Chapter of the Association for Computational Linguistics (NAACL) secretary 2020-2023. Her research has been widely supported by the U.S. government agencies (DARPA, ARL, IARPA, NSF, AFRL, DHS) and industry (Amazon, Google, Facebook, Bosch, IBM, Disney). Heng Ji is supported by NSF AI Institute on Molecule Synthesis, and collaborating with Prof. Marty Burke at Chemistry Department at UIUC and Prof. Kyunghyun Cho at New York University and Genetech on using AI for drug discovery. Dr. Brendan Harley is a Professor of Chemical and Biomolecular Engineering at the University of Illinois at Urbana-Champaign. His research group develops biomaterial that can be implanted in the body to regenerate musculoskeletal tissues or that can be used outside the body as tissue models to study biological events linked to endometrium, brain cancer, and stem cell behavior. He's a distance runner who dreams of (eventually) running ultramarathons. Follow him @Prof_Harley and www.harleylab.org. Learn more about your ad choices. Visit podcastchoices.com/adchoices

“Closed mouths don’t get fed.” Victoria Hamilton is a computational linguist with an interest in language learning technology. She earned her Master's in Computational Linguistics at Stony Brook University. Over the years she's had a number of jobs, including as a graduate career coach and graduate coordinator at Stony Brook. She is now working as an analytical linguist at Grammarly. Victoria Hamilton at LinkedIn Topics covered: – Music – Life priorities – Employment during grad school – Being Black in linguistics – Networking Download a transcript here (Word doc) or view it online here courtesy of Luca DinuThe post Episode #8: Victoria Hamilton first appeared on Linguistics Careercast.

#naturallanguageprocessing #nlp #artificialintelligence #machinelearning #toctw Author of Cognitively inspired natural language processing, Professor Pushpak Bhattacharyya is a computer scientist and a professor at Computer Science and Engineering Department, IIT Bombay. He served as the director of the Indian Institute of Technology Patna from 2015 to 2021. He is a past president of the Association for Computational Linguistics and Ex-Vijay and Sita Vashee Chair Professor He currently heads the Natural language processing research group Center For Indian Language Technology (CFILT) lab at IIT Bombay which was established in 2000 at the Computer Science and Engineering Department, IIT Bombay. Formerly known as the Center for Indian Language Technology CFILT lab has been publishing in the area of Natural Language Processing and Artificial Intelligence year after year. The principal investigator for this lab is Prof. Pushpak Bhattacharyya (CSE, IITB) Prof. Bhattacharyya has published more than 350 research papers in different areas of NLP and ML. He is the author of ‘Machine Translation. 'Cognitively Inspired Natural Language Processing- An Investigation Based on Eye Tracking and 'Low Resource Machine Translation and Transliteration. https://in.linkedin.com/in/pushpakbh https://www.cse.iitb.ac.in/~pb/ https://www.iitb.ac.in/en/employee/prof-pushpak-bhattacharya Watch our highest viewed videos: 1-India;s 1st Quantum Computer- https://youtu.be/ldKFbHb8nvQDR R VIJAYARAGHAVAN - PROF & PRINCIPAL INVESTIGATOR AT TIFR 2-Breakthrough in Age Reversal- -https://youtu.be/214jry8z3d4DR HAROLD KATCHER - CTO NUGENICS RESEARCH 3-Head of Artificial Intelligence-JIO - https://youtu.be/q2yR14rkmZQShailesh Kumar 4-STARTUP FROM INDIA AIMING FOR LEVEL 5 AUTONOMY - SANJEEV SHARMA CEO SWAAYATT ROBOTS -https://youtu.be/Wg7SqmIsSew 5-TRANSHUMANISM & THE FUTURE OF MANKIND - NATASHA VITA-MORE: HUMANITY PLUS -https://youtu.be/OUIJawwR4PY 6-MAN BEHIND GOOGLE QUANTUM SUPREMACY - JOHN MARTINIS -https://youtu.be/Y6ZaeNlVRsE 7-1000 KM RANGE ELECTRIC VEHICLES WITH ALUMINUM AIR FUEL BATTERIES - AKSHAY SINGHAL -https://youtu.be/cUp68Zt6yTI 8-Garima Bharadwaj Chief Strategist IoT & AI at Enlite Research -https://youtu.be/efu3zIhRxEY 9-BANKING 4.0 - BRETT KING FUTURIST, BESTSELLING AUTHOR & FOUNDER MOVEN -https://youtu.be/2bxHAai0UG0 10-E-VTOL & HYPERLOOP- FUTURE OF INDIA"S MOBILITY- SATYANARAYANA CHAKRAVARTHY -https://youtu.be/ZiK0EAelFYY 11-NON-INVASIVE BRAIN COMPUTER INTERFACE - KRISHNAN THYAGARAJAN -https://youtu.be/fFsGkyW3xc4 12-SATELLITES THE NEW MULTI-BILLION DOLLAR SPACE RACE - MAHESH MURTHY -https://youtu.be/UarOYOLUMGk Connect & Follow us at: https://in.linkedin.com/in/eddieavil https://in.linkedin.com/company/change-transform-india https://www.facebook.com/changetransformindia/ https://twitter.com/intothechange https://www.instagram.com/changetransformindia/ Listen to the Audio Podcast at: https://anchor.fm/transform-impossible https://podcasts.apple.com/us/podcast/change-i-m-possibleid1497201007?uo=4 https://open.spotify.com/show/56IZXdzH7M0OZUIZDb5mUZ https://www.breaker.audio/change-i-m-possible https://www.google.com/podcasts?feed=aHR0cHM6Ly9hbmNob3IuZm0vcy8xMjg4YzRmMC9wb2RjYXN0L3Jzcw Dont Forget to Subscribe www.youtube.com/ctipodcast

This week we are joined by Sebastian Ruder. He is a research scientist at DeepMind, London. He has also worked at a variety of institutions such as AYLIEN, Microsoft, IBM's Extreme Blue, Google Summer of Code, and SAP. These experiences were completed in tangent with his studies which included studying Computational Linguistics at the University of Heidelberg, Germany and at Trinity College, Dublin before undertaking a PhD in Natural Language Processing and Deep Learning at the Insight Research Centre for Data Analytics.This week we discuss language independence and diversity in natural language processing whilst also taking a look at the attempts to identify material properties from images.As discussed in the podcast if you would like to donate to the current campaign of "CREATE DONATE EDUCATE" which supports Stop Hate UK then please find the link below:https://www.shorturl.at/glmszPlease also find additional links to help support black colleagues in the area of research;Black in AI twitter account: https://twitter.com/black_in_aiMentoring and proofreading sign-up to support our Black colleagues in research: https://twitter.com/le_roux_nicolas/status/1267896907621433344?s=20Underrated ML Twitter: https://twitter.com/underrated_mlSebastian Ruder Twitter: https://twitter.com/seb_ruderPlease let us know who you thought presented the most underrated paper in the form below: https://forms.gle/97MgHvTkXgdB41TC8Links to the papers:“On Achieving and Evaluating Language-Independence in NLP” - https://journals.linguisticsociety.org/elanguage/lilt/article/view/2624.html"The State and Fate of Linguistic Diversity and Inclusion in the NLP World” - https://arxiv.org/abs/2004.09095"Recognizing Material Properties from Images" - https://arxiv.org/pdf/1801.03127.pdfAdditional Links:Student perspectives on applying to NLP PhD programs: https://blog.nelsonliu.me/2019/10/24/student-perspectives-on-applying-to-nlp-phd-programs/Tim Dettmer's post on how to pick your grad school: https://timdettmers.com/2020/03/10/how-to-pick-your-grad-school/Rachel Thomas' blog post on why you should blog: https://medium.com/@racheltho/why-you-yes-you-should-blog-7d2544ac1045Emily Bender's The Gradient article: https://thegradient.pub/the-benderrule-on-naming-the-languages-we-study-and-why-it-matters/Paper on order-sensitive vs order-free methods: https://www.aclweb.org/anthology/N19-1253.pdf"Exploring the Origins and Prevalence of Texture Bias in Convolutional Neural Networks": https://arxiv.org/abs/1911.09071Sebastian's website where you can find all his blog posts: https://ruder.io/

This week we feature our interview with Eric Daimler, PhD. Eric and I discussed how AI can unlock the potential of humanity.   Dr. Eric Daimler is an authority in Artificial Intelligence with over 20 years of experience in the field as an entrepreneur, executive, investor, technologist, and policy advisor. Daimler has co-founded six technology companies that have done pioneering work in fields ranging from software systems to statistical arbitrage. Daimler is the author of the forthcoming book "The Coming Composability: The roadmap for using technology to solve society's biggest problems." A frequent speaker, lecturer, and commentator, he works to empower communities and citizens to leverage AI for a more sustainable, secure, and prosperous future. As a Presidential Innovation Fellow during the Obama Administration, Daimler helped drive the agenda for U.S. leadership in research, commercialization, and public adoption of AI. He has also served as Assistant Dean and Assistant Professor of Software Engineering in Carnegie Mellon's School of Computer Science. His academic research focuses on the intersection of Machine Learning, Computational Linguistics, and Network Science (Graph Theory). He has a specialization in public policy and economics, helped launch Carnegie Mellon's Silicon Valley Campus, and founded its Entrepreneurial Management program. A frequent keynote speaker, he has presented at venues including the engineering schools of MIT, Stanford, and Harvard. Daimler studied at Stanford University, the University of Washington-Seattle, and Carnegie Mellon University, where he earned his PhD in its School of Computer Science. Contact Information Twitter: @ead LinkedIn: linkedin.com/in/ericdaimler Website: http://www.conexus.com/  Re-read Saturday  News Multitasking is the first or second greatest LIE in the modern business world. The best description of multitasking would include thrash, waste, and hubris. The problem is that EVERYONE thinks they are special and can multitask their way to the effective delivery of value. Chapter 3 of Why Limit WIP: We Are Drowning In Work blasts away at multitasking (another take on the topic from 2015: Multitasking Yourself Away From Efficiency | Software Process and Measurement https://bit.ly/37XmrSY). Multitasking is bad, don't do it.   Remember to buy a copy and read along.  Amazon Affiliate LInk:  https://amzn.to/36Rq3p5  Previous Entries Week 1: Preface, Foreword, Introduction, and Logistics – https://bit.ly/3iDezbp Week 2: Processing and Memory – https://bit.ly/3qYR4yg  Week 3: Completion - https://bit.ly/3usMiLm Week 4: Multitasking - https://bit.ly/37hUh5z    Upcoming Events: Final Call!  Free Webinar When Prioritization Goes Bad https://www.greatpro.org/Webinar-Live-Register?id=1954  April 19, 2022 11 AM EDT to 1230 EDT   Next SPaMCAST  Next week for SPaMCAST 700 we will feature our interview with Slater Victoroff. Slater presents an alternate definition for AI.  Compare and contrast to Dr. Daimler's definition?    

Ever wondered if we could predict people's actions through their words? Renowned social psychologist and linguist Dr Jamie Pennebaker shares how words can give away our secrets, feelings and inner state of mind from Putin's language which predicted his invasion of Ukraine to poets whose use of the word “I” can predict a higher risk of suicide. Dr. Pennebaker's groundbreaking research in computational linguistics analyzing and counting the frequency of words, shows that our most forgettable words, such as pronouns I, me and my, can be the most revealing.  He explains what the words Vladimir Putin, Xi Jinping, and Joe Biden use (and even the ones they don't use) reveal about their inner feelings and the “tell” that predicted Vladimir Putin's invasion of Ukraine.  He also talks about how American Presidents have become more likeable and less analytical, the differences in men's and women's words, and how writing about traumatic experiences can help people heal and improve their physical health. This podcast is available on all major podcast streaming platforms. Did you enjoy this episode? Consider leaving a review on Apple Podcasts.Receive updates on upcoming guests and more in our weekly e-mail newsletter. Subscribe today at www.3takeaways.com. 

Eneko Agirre, EHUko IXA taldeko informatikaria. Association of Computational Linguistics erakundeko kide egin dute (fellow). Mundu osoan 75 bakarrik daude eta Europan 15. Aitziber Agirre, "Elhuyar" aldizkariko zuzendaria, martxoko zenbakia atera berritan....

Eneko Agirre, EHUko IXA taldeko informatikaria. Association of Computational Linguistics erakundeko kide egin dute (fellow). Mundu osoan 75 bakarrik daude eta Europan 15. Aitziber Agirre, "Elhuyar" aldizkariko zuzendaria, martxoko zenbakia atera berritan....

In this episode of “Technically Human,” I sit down with Dr. Eric Daimler. We talk about one of the biggest technology problems facing us today—data deluge—and how new computational models and theories can help solve it and, Dr. Daimler weighs in on the gaps, differences, and possibilities for collaboration between policy, industry, and academia. And we talk about what a vision of “AI for Good” might look like in a world of increasingly infinite data. Dr. Eric Daimler is a leading authority in robotics and artificial intelligence with over 20 years of experience as an entrepreneur, investor, technologist, and policymaker. He served under the Obama Administration as a Presidential Innovation Fellow for AI and Robotics in the Executive Office of President, as the sole authority driving the agenda for U.S. leadership in research, commercialization, and public adoption of AI & Robotics. Dr. Daimler has incubated, built and led several technology companies recognized as pioneers in their fields ranging from software systems to statistical arbitrage. His newest venture, Conexus, is a groundbreaking solution for what is perhaps today's biggest information technology problem — data deluge. As founder and CEO of Conexus, Dr. Daimler  is leading the development of CQL, a patent-pending platform founded upon category theory — a revolution in mathematics — to help companies manage the overwhelming and rapidly growing challenge of data integration and migration. His academic research has been at the intersection of AI, Computational Linguistics, and Network Science (Graph Theory). His work has expanding to include economics and public policy. He served as Assistant Professor and Assistant Dean at Carnegie Mellon's School of Computer Science where he founded the university's Entrepreneurial Management program and helped to launch Carnegie Mellon's Silicon Valley Campus. He has studied at the University of Washington-Seattle, Stanford University, and Carnegie Mellon University, where he earned his Ph.D. in Computer Science. Dr. Daimler's extensive career spanning business, academics and policy give him a rare perspective on the next generation of AI. Dr. Daimler sees clearly how information technology can dramatically improve our world. However, it demands our engagement. Neither a utopia nor dystopia is inevitable. What matters is how we shape and react to, its development. This episode was produced by Matt Perry. Our head of reseaarch is Sakina Nuruddin. Art by Desi Aleman.

This week, we are kicking off a special series of “Technically Human” focused on the intersection of democracy and tech. In the first episode in the series, I sit down with Dr. Foaad Khosmood. We talk about the relationship between access to information and functional democracy, and how digital technologies can expand civil discourse. Dr. Foaad Khosmood is the Forbes Professor of Computer Engineering and Associate Professor of Computer Science at California Polytechnic State University.  His research interests include natural language processing (NLP), artificial intelligence, interactive entertainment, game AI and game jams. At Cal Poly, Professor Khosmood usually teaches AI, Interactive Entertainment, Computational Linguistics, Data Mining and Operating Systems. He serves as the faculty advisor for the Cal Poly Game Development (CPGD), SLO Hacks and Color Coded student clubs. He is the founder of the Digital Democracy Project, a platform that seeks to use digital technologies to Make Government More Transparent one Video at a Time, and the lead researcher on a new project at the Cal Poly Institute for Advanced Technology and Public Policy to strengthen democracy by developing an artificial intelligence system that will expand and improve state government coverage at local and regional media outlets—an area of journalism that has especially suffered amid the economic slide of the news industry. Dr. Khosmood is the Senior Research Fellow at the Institute for Advanced Technology & Public Policy. He is also a board member, former CTO and past president of Global Game Jam, Inc. where he helps to organize the world's largest game creation activity (120+ countries). He is also the general chair of the Foundations of Digital Games, a major international "big tent" academic conference dedicated to exploring the latest research in all aspects of digital games, and to increasing diversity and inclusion in the world of computing . This episode was produced by Matt Perry. Art by Desi Aleman.

In this episode, Emily and Lukas dive into the problems with bigger and bigger language models, the difference between form and meaning, the limits of benchmarks, and why it's important to name the languages we study. Show notes (links to papers and transcript): http://wandb.me/gd-emily-m-bender --- Emily M. Bender is a Professor of Linguistics at and Faculty Director of the Master's Program in Computational Linguistics at University of Washington. Her research areas include multilingual grammar engineering, variation (within and across languages), the relationship between linguistics and computational linguistics, and societal issues in NLP. --- Timestamps: 0:00 Sneak peek, intro 1:03 Stochastic Parrots 9:57 The societal impact of big language models 16:49 How language models can be harmful 26:00 The important difference between linguistic form and meaning 34:40 The octopus thought experiment 42:11 Language acquisition and the future of language models 49:47 Why benchmarks are limited 54:38 Ways of complementing benchmarks 1:01:20 The #BenderRule 1:03:50 Language diversity and linguistics 1:12:49 Outro

Jonan Scheffler interviews Developer Advocate at Observable, Anjana Vakil, about the rise of data visualization, Computational Linguistics, and the importance of finding an incredible community to guide you through your learning journey.Should you find a burning need to share your thoughts or rants about the show, please spray them at devrel@newrelic.com. While you're going to all the trouble of shipping us some bytes, please consider taking a moment to let us know what you'd like to hear on the show in the future. Despite the all-caps flaming you will receive in response, please know that we are sincerely interested in your feedback; we aim to appease. Follow us on the Twitters: @ObservyMcObserv.

Talk by Dr Barbara McGillivray, senior research associate at the University of Cambridge Section of Theoretical and Applied Linguistics and Research Fellow at The Alan Turing Institute

The Naked Dialogue Podcast EP#30: Shira Eisenberg | Computational Linguistics, Psychoanalysis & Cognitive Architectures around Human Behavior Shira Eisenberg- https://shira.dev/ | https://twitter.com/shiraeis Shira Eisenberg is an AI Language Systems Researcher @MIT Lincoln Laboratory & a technical consultant @CDC, (most recently on, Changes in the Scientific Information During the COVID-19 Pandemic: The Importance of Scientific Situational Awareness in Responding to the Infodemic. Sanjana Singh (The Host): https://itsa2amgrunge.com/ --- Support this podcast: https://anchor.fm/sanjanasinghx/support

Samuel Läubli, Partner and CTO at TextShuttle, joins the pod to talk about the ins and outs of a language technology provider, and the current state of machine translation.The CTO touches on his background in Computational Linguistics and decision to go back to the academe in 2016. He gives his take on the current state of machine translation, particularly weaknesses around sentence-by-sentence structure and limited control.Samuel discusses his thesis, which tackles three key challenges in MT for professionals: quality, presentation, and adaptability. He debates whether machine translation can become truly creative without artificial general intelligence — or if it will always be considered imitation.He then walks listeners through TextShuttle's business model as well as the key problems the company solves for clients, ranging from producing MT systems to helping with configurations, workflows, and training translators.First up, Florian and Esther discuss the language industry news of the week, where RSI platform Interactio announced that it had raised USD 30m in series A funding, led by VCs Eight Roads Ventures and Storm Ventures.Esther delves into Straker's 100-page annual report, which showed the Australia-listed LSP's 13% revenue growth to USD 22.6m for the 12 months to March 31, 2021. The duo also discusses Akorbi, another fast-growing language service provider (LSP), which recently acquired the low-code process automation platform RunMyProcess from Fujitsu.Heading to Japan, Florian goes over Honyaku Center's 2020 financial results, which saw revenues decline 14% to USD 91m and operating income nearly halved to USD 3.8m.Florian closes the Pod full circle with more machine translation news: a research paper presented by Bering Lab about IntelliCAT, an MT post-editing and interactive translation model; and, out of big tech, Microsoft Document Translation, a recent addition to their enterprise MT offerings.

Speaker introduction

Colin Tattersall is the Product Manager at Sopheon. He has a strong background initially working in a research capacity in linguistics and knowledge management, eventually moving into new product development and innovation. He was previously an Associate Professor at Open Universiteit Nederlands, a Consultant at QNH Consulting, and a Project Leader at KPN Research. Colin has a Bachelor's degree in Computational Science and a Doctor of Philosophy in Computational Linguistics and Knowledge-Based Systems from the University of Leeds. Colin joins me today to discuss IoT-based innovation management. He explores how we might make use of the insights we get from smart product data in the innovation process itself. He shares how closed-loop product lifecycle management should be informed at the front end by what's really happening with products. He shares his views on device cooperation and the industrial and product development opportunities that are available from IoT data. We discuss how far it is appropriate to go in using customer data. Colin also shares details on how Accolade is being developed for use in smart products and highlights the challenges of retaining oversight when many tools and techniques are being used. “Smart products offer the possibility of getting some insight into what really is being used, which feature is getting used all day every day, and which is not hitting the mark.” - Colin Tattersall This week on Innovation Talks: Why machine learning and knowledge management systems are taking off How Electrolux have leveraged Accolade Innovation Management Software in their success story, compressing product time to market The key challenges and opportunities around innovation Getting data from smart products and putting it back into the innovation process for the next generation The types of insights that closed-loop product lifecycle management systems provide Learning trends in how networks of products are used and working together The difficulties in protecting and regulating customer's data and data sharing Connect with Colin Tattersall: Colin Tattersall on LinkedIn This Podcast is brought to you by Sopheon Thanks for tuning into this week's episode of Innovation Talks. If you enjoyed this episode, please subscribe and leave a review wherever you get your podcasts. Apple Podcasts | TuneIn | GooglePlay | Stitcher | Spotify | iHeart Be sure to connect with us on Facebook, Twitter, and LinkedIn, and share your favorite episodes on social media to help us reach more listeners, like you. For additional information around new product development or corporate innovation, sign up for Sopheon's newsletter where we share news and industry best practices monthly! The fastest way to do this is to go to sopheon.com and click here.

On this episode of Silicon Valley Insider (#SVIN), Keith Koo’s guest is Preetham Vishwanatha, Founder and CEO of Kena.ai Preetham shares his early history learning violin at a young age as both an academic and religious experience. After a very successful career as a technology executive and innovator Preetham turned his focus towards his passions for technology and music leading to the start of Kena.ai. Keith and Preetham discuss how Kena.ai is disrupting how people can learn to play music using A.I, and how the platform can be used to do music genre “mashups” such as heavy metal mixed with classical.   More about Preetham: He is an executive leader in AI with 25+ years in hi-tech, research and startups. His expertise involves areas of Computational Creativity, Musical Acoustics, Computational Linguistics, Reinforcement Learning, Complex Dynamical Systems and Game theoretical models. At Kena, Preetham is building a Music Neural Graph through Artificial Intelligence with applications in Musicology, Compositions and Learning. He is also an avid guitar player and composes songs at leisure. In the past 25 years, he has built large-scale machine intelligence platforms for evidence-driven decision-making in Ed-tech, Ad-tech, commerce exchanges, retail demand chain solutions, and cloud-based analytics domains. Linked In: https://linkedin.com/in/vvpreetham To find out more about Kena.ai: https://kena.ai Subscribe and Download to “Silicon Valley Insider” to find out more: https://www.svin.biz/ Listen Saturdays 10-11am 860AM KTRB Silicon Valley | San Francisco Listen Thursdays 2-3pm on 1220AM KDOW Silicon Valley | San Francisco Listen and subscribe to the "Silicon Valley Insider" Podcast ahead of time to make sure you don't miss this show. Download the podcast at 3:00pm on Mondays For questions or comments, email: info@svin.biz

This conversation is part of the 'Understanding Noam Chomsky' Series ('Dare to know!' Philosophy Podcast). Today we are joined by Robert C. Berwick. Robert C. Berwick is Professor of Computer Science and Computational Linguistics at the Massachusetts Institute of Technology. Professor Berwick has written 8 books and more than 200 articles on the nature of human language and its computational properties, how language is learned, how it develops and differs, and how it evolves and changes over time.

Daphne Keller, platform regulation expert at Stanford University and former Associate General Counsel for Google, joins Ellysse and Ashley to explain Section 230's role in shaping how large companies approach content moderation on a massive scale, and how intermediary liability protections allow platforms of all sizes to thrive.MentionedJennifer M. Urban, Joe Karaganis, and Brianna L. Shofield, Notice and Takedown in Everyday Practice(Berkeley Law, 2016).Maarten Sap et al., “The Risk of Racial Bias in Hate Speech Detection,” Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (2019): 1668-78.Thomas Davidson, Debasmita Bhattacharya, and Ingmar Weber, “Racial Bias in Hate Speech and Abusive Language Detection Datasets,” Proceedings of the Third Workshop on Abusive Language Online (2019): 25-35.“H.R.1865 - Allow States and Victims to Fight Online Sex Trafficking Act of 2017,” Congress.gov.Woodhull Freedom Foundation v. United States, No. 18-5298 (D.C. Cir. 2020).Daphne Keller, “SESTA and the Teachings of Intermediary Liability” (The Center for Internet and Society, November 2017).Daphne Keller, “For platform regulation Congress should use a European cheat sheet,” The Hill, January 15, 2021.Renee Diresta, “Free Speech Is Not the Same As Free Reach,” Wired, August 30, 2018.

https://www.engati.com/ Engati is the world's leading no-code, multi-lingual chatbot platform. https://open.spotify.com/show/3G0uQwPnQib22emRi9VhUg Blog link: https://engati.com/blog | Subscribe now. Check out CX Community page - https://www.engati.com/cx-community And CX Content page - https://www.engati.com/cx-content Thomas Wolf, Co-founder and CSO at Hugging Face talks to us about what lacks and what can change in Cumputational Linguistics. He tells us why NLP has a very bright future and would be a Global AI term soon. Follow us on Facebook: http://s.engati.com/157 LinkedIn: http://s.engati.com/158 Twitter: http://s.engati.com/156 Instagram: https://www.instagram.com/getengati/  #EngatiCX #digital #CX #technology #NLP #AI

Alzheimer's Speaks Radio - Shifting dementia care from crisis to comfort around the world one episode at a time by raising all voices and delivering sounds news, not just sound bites since 2011. Lori La Bey and her Co-Host Michael Ellenbogen, who is living with dementia will talk with Dr. Guillermo Cecchi who is part of IBM’s Research team.  Dr Cecchi works on computational linguistics approaches to quantify brain function. He is specifically looking at short speech samples and utilizing Artificial Intelligence.to see if there is a correlation with the progression of dementia. This show promises to be a fascinating conversation. I hope you can make the time to listen! Contact Information for IBM IBM Research Blog            IBM Research Twitter- @IBMResearch     IBM & Pfizer Article   Contact Lori La Bey with questions or branding needs and visit Alzheimer’s Speaks.  

Philip Resnik, PhD, returns to the Psychcast, this time with his research partner and wife, Rebecca Resnik, PsyD, to discuss the interface between language, psychiatry, psychology, and health. Dr. Philip Resnik appeared on the show previously to discuss artificial intelligence, natural language processing, and mental illness. He is a professor in the department of linguistics at the University of Maryland, College Park, and has a joint appointment with the university’s Institute for Advanced Computer Studies. Dr. Philip Resnik has disclosed being an adviser for Converseon, a social media analysis firm; FiscalNote, a government relationship management platform; and SoloSegment, which specializes in enterprise website optimization. Some of the work Dr. Philip Resnik discusses has been supported by an Amazon AWS Machine Learning Research Award. Dr. Rebecca Resnik is a licensed psychologist in private practice who specializes in neuropsychological assessment. In 2014, she served as cofounder of the Computational Linguistics and Clinical Psychology workshop at the North American Association for Computational Linguistics. She continues to serve as a workshop organizer and clinical consultant to the cross-disciplinary community. She has no disclosures. Dr. Norris disclosed having no conflicts of interest. Take-home points Dr. Rebecca Resnik and Dr. Philip Resnik are interested in finding measurable, observable features to apply to the assessment of psychological and psychiatric diagnoses. They point out that finding an objective measure is essential for scaling up mental health evaluations and treatment. Natural language processing (NLP) is focused on analyzing language content. NLP technology has generated tools such as Siri, Alexa, and Google Translate, and NLP allows computers to do things more intelligently with human language. Individuals are using machine learning and NLP to analyze language data sets to evaluate diagnostic criteria. The goal is to create or use language sets that can be analyzed outside of the clinic. Dr. Rebecca Resnik imagines a world where a patient gives a “language sample” to an app or an avatar that would be evaluated by NLP that would, in turn, offer some overarching hypotheses about the person. So much of evaluations is trying to home in on the correct signal, explicit and implicit, from the patient. In addition, neuropsychiatric tests/scales are standardized against a limited scope of the population, so NLP would be matched to the individual. Dr. Philip Resnik looks at signals in text and speech content, acoustics, microexpressions, and even biometric data. Machine learning can process and distill a huge amount of data with various signals more easily than any human. Dr. Rebecca Resnik revisits the idea of clinical white space, which is the “space” or the time between clinical encounters, and this is where decompensation and high-risk suicidal behaviors occur. She suggests that NLP software could be used to fill this white space by using apps to collect text samples from patients, and the software would analyze the samples and warn of patients who are at risk of decompensation or suicide. If clinicians were to use text or speech samples from people’s smart technology, we could assess an individual's risk in the moment and use nudge-type interventions to prevent suicide. Finally, Dr. Philip Resnik emphasizes that there are technologists who have the skills and technology that is on the verge of helping clinicians, but the key to progress is collaborating with clinicians. References Resnik P et al. J Analytical Psychol. 2020 Sep 10. doi: 10.111/sltb.12674. Coppersmith G et al. Biomed Inform Insights. 2018;10:1178222618792860. Zirikly A et al. CLPsych 2019 shared task: Predicting the degree of suicide risk in Reddit posts. Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology. 2019 Jun 16. Yoo DW et al. JMIR Mental Health. 2020;7(8):e16969. American Medical Informatics Association and Mental Health: https://www.amia.org/mental-health-informatics-working-group Selanikio J. The big-data revolution in health care.  TEDxAustin. 2013 Feb. CLPsych: Computational Linguistics and Clinical Psychology Workshop. 2019 Program. *  *  * Show notes by Jacqueline Posada, MD, associate producer of the Psychcast; assistant clinical professor in the department of psychiatry and behavioral sciences at George Washington University in Washington; and staff physician at George Washington Medical Faculty Associates, also in Washington. Dr. Posada has no conflicts of interest. *  *  * For more MDedge Podcasts, go to mdedge.com/podcasts Email the show: podcasts@mdedge.com

In this episode of OutBüro Voices featuring LGBTQ professionals, entrepreneurs, and community leaders from around the world, host Dennis Velco chats with Lorenzo Thione, Managing Director of Gaingles (https://www.gaingels.com), an LGTQ equality centric venture capital syndicate. Lorenzo is a serial out gay entrepreneur, venture capitalist, writer, Broadway producer, and LGBTQ non-profit founder. Born and raised in Italy, he moved to the United States to attend college in Texas focusing on computational linguistic artificial intelligence. He co-founded his first start-up business right out of college and it's been the entrepreneur's path ever since. Lorenzo Thione is the Managing Producer of Sing Out, Louise! Productions, the co-founder and CEO of The Social Edge, and a Managing Director at Gaingels (https://www.gaingels.com), a venture investment group based in NYC focused on investing and supporting LGBT+ founded/led startups, and socially responsible companies focused on supporting LGBTQ equality. In addition to his work as an entrepreneur, technologist and venture investor, Lorenzo is the co-creator/co-book writer and the lead producer of Allegiance, the 2015 Broadway musical starring George Takei and Lea Salonga. In developing Allegiance, he developed and deployed social-media viral strategies that led to the astounding growth and unprecedented awareness and audience engagement for both George Takei and Allegiance's social media platforms, and – in turn - to the founding of The Social Edge, a social media management and marketing firm based in NYC. His producing credits include The Inheritance, Slave Play, Hadestown (Tony Award), Cher Show, The New One, Catch Me If You Can (Tony Nomination), and American Idiot. Additional IMDB credits: George Takei's Allegiance (Director, Executive Producer), Bandstand – The Boys Are Back (Director, Executive Producer), Allegiance To Broadway (Executive Producer) Besides being an active investor in the LGBT+ startup ecosystem via his position in Gaingels, Lorenzo is a founding board member and Chair Emeritus of StartOut, a non-profit organization dedicated to fostering and developing entrepreneurship within the LGBT community. A native of Milan, Italy, Lorenzo holds an M.S. in Computer Engineering from the University of Texas at Austin and has co-authored several publications in Software Engineering and Computational Linguistics. He is an active investor, advisor, or board member, in over 80+ startups and a named inventor on over 30 pending and issued patents in the US and worldwide. Connect with Lorenzo on OutBüro at: https://www.outburo.com/profile/lorenzothione/ Join Myles on OutBüro, the LGBTQ professional and entrepreneur online community network for gay, lesbian, bisexual, transgender, queer, allies and our employers who support LGBTQ welcoming workplace equality focused benefits, policies, and business practices. https://www.OutBuro.com Would you like to be featured like this? Contact the host Dennis Velco. https://www.outburo.com/profile/dennisvelco/ --- Send in a voice message: https://anchor.fm/outburo/message

In today's Success September interview I chat with Nimish Gatam who is a Technical consultant, Data journalist, and Political Strategist. He was born in Nepal, grew up in the Southern US (mostly), and has lived in New Zealand, The US, Germany, Denmark and Sweden where he is currently living. He went to undergrad for Computer Science, grad school for Computational Linguistics, spent parts of the 2000's/2010's in Silicon Valley working with start-ups. Most of his consulting is still with Startups and he was one of the first 12 employees at Wikipedia. Nimish is very politically active in Sweden and Denmark. He is a parent and has dabbled in various hobbies which include Taiko drumming, and acroyoga (acrobatics+yoga). To connect with Nimish: https://blog.nimishg.com/ https://nimishg.com/ As always we appreciate your support! ***Every penny helps... $.99 a MONTH (99 Cents!) really does help and make a difference! https://anchor.fm/successfuldiligence/support Thank you for listening and sharing!*** Send us a voice message: https://anchor.fm/successfuldiligence/message we would LOVE to hear from you! **Sign up for the Successful Diligence™ Newsletter so you never miss a thing! https://successfuldiligence.ck.page/ There are lots of new opportunities to interact with the Successful Diligence Community and some content is ONLY released via the Newsletter - So don't miss out!! https://linktr.ee/shelmy_life **Enrollment is open for our Mini Courses: Gateway to Gratitude™ and The Butterfly Impact™ , as well as our signature course: The Butterfly Transformation™ (at the Launch Price) at https://successful-diligence.teachable.com*Email us through the Contact tab on https://www.successfuldiligence.com to get a 50% coupon! Podcast listeners get 50% off ALL paid courses available in the school! ** (Code: Podcast50) ~ Successful Diligence™ Merchandise is available! Click to check it out! https://www.teepublic.com/user/successfuldiligence / https://teespring.com/stores/successful-diligence ~ Copyright © 2020 Successful Diligence™, LLC All rights reserved. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app --- Send in a voice message: https://anchor.fm/successfuldiligence/message Support this podcast: https://anchor.fm/successfuldiligence/support

Chris Brown, VP International Basis Technology chats with Marie Lundberg and Sam Sheen about his career move from professional footballer to financial crime technology innovation, the age old problem of screening customer names, transliteration and the Boston Bombers, links between PEPs and their family members, use of computational linguistics, the challenges of screening using phonetics alone, shedding the "black box" approach as a technology provider, and and criminals creative use of lexicons and how Basis' technology uncovers semantic similarities to detect nefarious communications. Think you can avoid detection by referring to "barbeques" instead "laundering" in phone texts or emails? Find out how Basis tackle this challenge. 

Show Notes(2:55) Patricia talked about his interest in learning languages and living in different cultures.(4:05) Patricia talked about her experience volunteering as a translator at the International Network of Street Papers.(5:00) Patricia studied Liberal Arts at John Abbott College, English Literature at Concordia University, and Computer Science and Linguistics at McGill University during her undergraduate years.(8:06) Patricia worked at McGill Language Development Lab as a Research Assistant, which studied how children learn different types of words and sentences.(9:15) Patricia described her graduate school experience at the University of Toronto, where she researched lost language decipherment and writing systems.(11:19) Patricia talked about MedStory, which is a text-oriented visual prototype built to support the complexity of medical narratives (spearheaded by Nicole Sultanum).(12:35) Patricia explained her research paper, “Vowel and Consonant Classification through Spectral Decomposition.”(15:29) Patricia unpacked her blog post, “Why is Privacy-Preserving NLP Important?”(19:02) Patricia dissected her paper “Privacy-Preserving Character Language Modelling” that proposes a method for calculating character bigram and trigram probabilities over sensitive data using homomorphic encryption.(21:13) Patricia wrote a two-part series called “Homomorphic Encryption for Beginners.”(22:21) Patricia unwrapped her paper “Efficient Evaluation of Activation Functions over Encrypted Data” that shows how to represent the value of any function over a defined and bounded interval, given encrypted input data, without needing to decrypt any intermediate values before obtaining the function’s output.(25:33) Patricia elaborated on her paper “Extracting Bark-Frequency Cepstral Coefficients from Encrypted Signals,” which claims that extracting spectral features from encrypted signals is the first step towards achieving secure end-to-end automatic speech recognition over encrypted data.(27:38) Patricia explained why privacy is an essential attribute for speech recognition applications.(29:53) Patricia discussed her comprehensive guide on “Perfectly Privacy-Preserving AI” which dives into the four pillars of perfectly privacy-preserving AI and outlines potential combinatorial solutions to satisfy all four pillars.(37:53) Patricia shared her take on the differences working in academic and commercial settings (she is the founder and CEO of Private AI).(40:50) Patricia talked about Private AI’s GALATEA Anonymization Suite, which anonymizes data at the source and encrypts them using quantum-safe cryptography.(45:05) Patricia emphasized the importance of talking to customers when building a commercial product.(46:58) Patricia shared her experience as a Postgraduate Affiliate at Vector Institute, which works with institutions, industry, startups, incubators, and accelerators to advance AI research and drive its application, adoption, and commercialization across Canada.(49:09) Patricia shared her advice for young researchers by going deep into at least two domains and combining the knowledge.(50:30) Patricia shared her excitement for privacy and NLP research in the upcoming years.(52:36) Closing segment.Her Contact InfoWebsiteTwitterLinkedInGoogle ScholarMediumGitHubHer Recommended ResourcesHomomorphic EncryptionSecure Multiparty ComputationFederated LearningDifferential PrivacyVector InstituteMILA Montreal InstituteAlberta Machine Intelligence InstituteReza Shokri (Assistant Professor at National University of Singapore)Parinaz Sobhani (Director of Machine Learning at Georgian Partners)Doina Precup (Associate Professor at McGill University)

Show Notes(2:55) Patricia talked about his interest in learning languages and living in different cultures.(4:05) Patricia talked about her experience volunteering as a translator at the International Network of Street Papers.(5:00) Patricia studied Liberal Arts at John Abbott College, English Literature at Concordia University, and Computer Science and Linguistics at McGill University during her undergraduate years.(8:06) Patricia worked at McGill Language Development Lab as a Research Assistant, which studied how children learn different types of words and sentences.(9:15) Patricia described her graduate school experience at the University of Toronto, where she researched lost language decipherment and writing systems.(11:19) Patricia talked about MedStory, which is a text-oriented visual prototype built to support the complexity of medical narratives (spearheaded by Nicole Sultanum).(12:35) Patricia explained her research paper, “Vowel and Consonant Classification through Spectral Decomposition.”(15:29) Patricia unpacked her blog post, “Why is Privacy-Preserving NLP Important?”(19:02) Patricia dissected her paper “Privacy-Preserving Character Language Modelling” that proposes a method for calculating character bigram and trigram probabilities over sensitive data using homomorphic encryption.(21:13) Patricia wrote a two-part series called “Homomorphic Encryption for Beginners.”(22:21) Patricia unwrapped her paper “Efficient Evaluation of Activation Functions over Encrypted Data” that shows how to represent the value of any function over a defined and bounded interval, given encrypted input data, without needing to decrypt any intermediate values before obtaining the function’s output.(25:33) Patricia elaborated on her paper “Extracting Bark-Frequency Cepstral Coefficients from Encrypted Signals,” which claims that extracting spectral features from encrypted signals is the first step towards achieving secure end-to-end automatic speech recognition over encrypted data.(27:38) Patricia explained why privacy is an essential attribute for speech recognition applications.(29:53) Patricia discussed her comprehensive guide on “Perfectly Privacy-Preserving AI” which dives into the four pillars of perfectly privacy-preserving AI and outlines potential combinatorial solutions to satisfy all four pillars.(37:53) Patricia shared her take on the differences working in academic and commercial settings (she is the founder and CEO of Private AI).(40:50) Patricia talked about Private AI’s GALATEA Anonymization Suite, which anonymizes data at the source and encrypts them using quantum-safe cryptography.(45:05) Patricia emphasized the importance of talking to customers when building a commercial product.(46:58) Patricia shared her experience as a Postgraduate Affiliate at Vector Institute, which works with institutions, industry, startups, incubators, and accelerators to advance AI research and drive its application, adoption, and commercialization across Canada.(49:09) Patricia shared her advice for young researchers by going deep into at least two domains and combining the knowledge.(50:30) Patricia shared her excitement for privacy and NLP research in the upcoming years.(52:36) Closing segment.Her Contact InfoWebsiteTwitterLinkedInGoogle ScholarMediumGitHubHer Recommended ResourcesHomomorphic EncryptionSecure Multiparty ComputationFederated LearningDifferential PrivacyVector InstituteMILA Montreal InstituteAlberta Machine Intelligence InstituteReza Shokri (Assistant Professor at National University of Singapore)Parinaz Sobhani (Director of Machine Learning at Georgian Partners)Doina Precup (Associate Professor at McGill University)

Philip Resnik, PhD, joins host Lorenzo Norris, MD, to discuss the use of AI and natural language processing to help clinicians identify patterns in the behaviors of patients with mental illness. Dr. Resnik is a professor in the department of linguistics at the University of Maryland, College Park. He also has a joint appointment with the university’s Institute for Advanced Computer Studies. Dr. Resnik has disclosed being an adviser for Converseon, a social media analysis firm; FiscalNote, a government relationship management platform; and SoloSegment, which specializes in enterprise website optimization. Some of the work Dr. Resnik discusses has been supported by an Amazon AWS Machine Learning Research Award. Dr. Norris disclosed having no conflicts of interest.  And don’t miss the “Dr. RK” segment, with Renee Kohanski, MD.  Take-home points  Artificial intelligence (AI) refers to the effort to get computers to develop capabilities that humans would consider intelligent when people do them. For example, a “smart” thermostat learns patterns of behaviors and changes the temperature accordingly. Natural language processing (NLP), an AI approach, focuses on the content of language from the words used and looks for cues within the content. NLP technology allows computers to do things more intelligently with human language, and NLP has generated technologies such as Siri, Alexa, and Google Translate. Much of clinical work is focused on language, and clinicians look for cues within the content. Dr. Resnik is a technologist who believes that NLP can help facilitate clinical progress, especially in the face of a shortage of mental health clinicians and the limited amount of time that clinicians are able to spend with their patients. Research aimed at using machine learning and NLP to analyze social media and other types of online presence to evaluate for suicide risk and the presence of mood disorders is underway. Dr. Resnik imagines an ecosystem in which computers and humans balance their efforts, with each “brain” doing what they are best at; he believes in technology’s ability to save us time so we can prioritize our efforts. Summary A common example of NLP is automatic dictation and transcription software embedded in medical records. Dr. Resnik thinks of technology as an enabler and augmentation strategy. Resnik and his wife, Rebecca Resnik, PsyD, completed a study using NLP to automatically detect clusters of language in the writing samples of college students. NLP software evaluated the natural patterns of language that might correlate with vegetative and somatic symptoms of depression and social isolation. His team was able to home in on language themes specific to college students that suggest specific symptoms of depression. Another example of NLP in mental health is using predictive modeling, taking in data, and then making a prediction about a pertinent variable to understand mental health outcomes. For example, Glen Coppersmith, PhD, and associates evaluated social media posts with NLP software and concluded that analysis of language in social media posts can accurately identify individuals at risk of suicide and facilitate earlier interventions. Resnik imagines a future in which speech and language samples are used to give a point-of-care evaluation of a patient’s mood and suicide risk. “Clinical white space” is all the “space” (for example, the time between clinical encounters) and this is where decompensation occurs. Resnik suggests that NLP software could be used to fill this white space by using apps to collect text samples from patients. Software would analyze the samples and warn of patients who are at risk of decompensation or suicide. Barriers to using this technology include engaging the technologists and clinicians, and accessing data samples because of privacy concerns, especially because HIPPA was written before the emergence of mega data. References Coppersmith G et al. Natural Language Processing of Social Media as Screening for Suicide Risk. Biomed Inform Insights. 2018 Aug 27. doi: 10.1177/1178222618792860. Zirikly A et al. CLPsych 2019 Shared Task: Predicting the Degree of Suicide Risk in Reddit Posts. In Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology. 2019 Jun 6. 24-33. Lynn V et al. CLPsych 2018 Shared Task: Predicting Current and Future Psychological Health from Childhood Essays. In Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic. 2018.  37-46. Selanikio J. The big-data revolution in health care. TEDx talk. Graham S et al. Artificial Intelligence for Mental Health and Mental Illnesses: An Overview. Curr Psychiatry Rep. 2019 Nov 7;21(11):116. doi: 10.1007/s11920-019-1094-0. Show notes by Jacqueline Posada, MD, who is associate producer of the Psychcast and consultation-liaison psychiatry fellow with the Inova Fairfax Hospital/George Washington University program in Falls Church, Va.  Dr. Posada has no conflicts of interest. For more MDedge Podcasts, go to mdedge.com/podcasts Email the show: podcasts@mdedge.com  

"Stay focused on the truth, even if you don't like them" ~ Prof. De Kai De Kai is an American activist, musician, professor of Computer Science and Engineering at HKUST, and Distinguished Research Scholar at Berkeley's International Computer Science Institute. He is among only 17 scientists named Founding Fellow by the Association for Computational Linguistics, for his pioneering contributions to machine learning foundations of machine translation that led to the Google/Microsoft/Yahoo/etc translators. De Kai was recruited as founding faculty of the University of Science and Technology in Hong Kong directly from UC Berkeley, where his Ph.D. thesis was one of the first to argue for the paradigm shift toward machine learning-based natural language processing. He holds a Kellogg-HKUST Executive MBA and a BS in Computer Engineering (Phi Beta Kappa, cum laude, Revelle College honors) from UCSD. For his work on AI, machine learning, machine translation, natural language processing, music technology, computational creativity, Debrett's HK 100 recognized De Kai as one of the 100 most influential figures of Hong Kong. For his work on AI ethics and society, De Kai was one of eight inaugural members selected by Google in 2019 for its AI ethics council. Dedicated to intercultural understanding, he created the HK-based world music collective ReOrientate and has spoken and performed for many TEDx, media, and other international venues. Fun fact: If you have ever used google translate; you got De Kai to thank for that. Connect with De Kai: AI ethics & society http://dek.ai Music & culture http://dekai.org Facebook http://fb.com/dekai1 His social media handle: @dekai123 If you enjoy the podcast, would you please consider leaving a short review on Apple Podcasts/iTunes? It takes less than 60 seconds, and it really makes a difference in helping us get to a new listener. For show notes and past guests, please visit https://www.christopherategeka.com/gratitribe Become a patron and support our creative work: https://www.patreon.com/chrisategeka Interested in sponsoring the podcast? Please send us some love here https://www.christopherategeka.com/contact Follow us on social media: Twitter: https://twitter.com/chrisategeka Instagram:https://www.instagram.com/chrisategeka PODCAST Links / Handles / Contact info: Podcast Link: www.christopherategeka.com/gratitribe Instagram: @Gratitribe Twitter: @Gratitribe Facebook Page: Gratitribe Podcast Email / Contact info: Gratitribe@gmail.com Hashtags: #gratitribe #gratitude #podcast #podcastsofinstagram #chrisategeka --- Support this podcast: https://anchor.fm/christopher-ategeka/support

Professor Kai von Fintel is a world-leading linguist (Section Head at MIT) who is well known for his contributions to Semantics, an academic fields which sits at the intersection of many disciplines which is typically concerned with the meaning of linguistic expressions. He is the co-founder of the open access journal Semantics & Pragmatics. You can find more about his work on his website: https://www.kaivonfintel.org Conversation Outline: 00:00 Introduction00:18 What is special about language? 03:31 How did we (as a species) get linguistic abilities?05:24 What do people who work in Semantics do? 09:19 How can babies pick up language? 15:07 What is the meaning of words? Aren't they just dictionary entries? 19:03 On idiolects 27:00 The meanings of sentences33:43 What are possible worlds? Are they the same as the many-worlds of quantum theory? 39:52 Differences between ‘school' grammar, syntax and formal logic49:07 What is the meaning of ‘if'? 01:04:54 Does the research of Semanticists impact the field of Computational Linguistics?01:07:39 The relationship between thought and languageTwitter: https://twitter.com/tedynenuApple Podcasts:https://podcasts.apple.com/gb/podcast/philosophical-trials/id1513707135Spotify: https://open.spotify.com/show/3Sz88leU8tmeKe3MAZ9i10Google Podcasts:https://podcasts.google.com/?q=philosophical%20trialsInstagram: https://www.instagram.com/tedynenu/

This week we are joined by Sebastian Ruder. He is a research scientist at DeepMind, London. He has also worked at a variety of institutions such as AYLIEN, Microsoft, IBM's Extreme Blue, Google Summer of Code, and SAP. These experiences were completed in tangent with his studies which included studying Computational Linguistics at the University of Heidelberg, Germany and at Trinity College, Dublin before undertaking a PhD in Natural Language Processing and Deep Learning at the Insight Research Centre for Data Analytics. This week we discuss language independence and diversity in natural language processing whilst also taking a look at the attempts to identify material properties from images.As discussed in the podcast if you would like to donate to the current campaign of "CREATE DONATE EDUCATE" which supports Stop Hate UK then please find the link below: https://www.shorturl.at/glmszPlease also find additional links to help support black colleagues in the area of research;Black in AI twitter account: https://twitter.com/black_in_aiMentoring and proofreading sign-up to support our Black colleagues in research: https://twitter.com/le_roux_nicolas/status/1267896907621433344?s=20Underrated ML Twitter: https://twitter.com/underrated_mlSebastian Ruder Twitter: https://twitter.com/seb_ruderPlease let us know who you thought presented the most underrated paper in the form below: https://forms.gle/97MgHvTkXgdB41TC8Links to the papers:“On Achieving and Evaluating Language-Independence in NLP” - https://journals.linguisticsociety.org/elanguage/lilt/article/view/2624.html"The State and Fate of Linguistic Diversity and Inclusion in the NLP World” - https://arxiv.org/abs/2004.09095"Recognizing Material Properties from Images" - https://arxiv.org/pdf/1801.03127.pdfAdditional Links:Student perspectives on applying to NLP PhD programs: https://blog.nelsonliu.me/2019/10/24/student-perspectives-on-applying-to-nlp-phd-programs/Tim Dettmer's post on how to pick your grad school: https://timdettmers.com/2020/03/10/how-to-pick-your-grad-school/Rachel Thomas' blog post on why you should blog: https://medium.com/@racheltho/why-you-yes-you-should-blog-7d2544ac1045Emily Bender's The Gradient article: https://thegradient.pub/the-benderrule-on-naming-the-languages-we-study-and-why-it-matters/Paper on order-sensitive vs order-free methods: https://www.aclweb.org/anthology/N19-1253.pdf"Exploring the Origins and Prevalence of Texture Bias in Convolutional Neural Networks": https://arxiv.org/abs/1911.09071Sebastian's website where you can find all his blog posts: https://ruder.io/

In this interview De Kai talks about Artificial Intelligence from his cross-disciplinary perspective. We talk about the meaning of creativity, consciousness and mindfullness for modern AI, various misconceptions about modern AI and whether it is still programmable in the classical sense at all, about AI ethics and what AI means for us as a society, humanity and our future.About De KaiDe Kai is Professor of Computer Science and Engineering at HKUST and Distinguished Research Scholar at Berkeley's International Computer Science Institute. He is among only 17 scientists named Founding Fellow by the Association for Computational Linguistics, for his pioneering contributions to machine learning foundations of machine translation that led to the Google/Microsoft/Yahoo/etc translators. De Kai was recruited as founding faculty of the University of Science and Technology in Hong Kong directly from UC Berkeley, where his PhD thesis was one of the first to argue for the paradigm shift toward machine learning based natural language processing. He holds a Kellogg-HKUST Executive MBA and a BS in Computer Engineering (Phi Beta Kappa, cum laude, Revelle College honors) from UCSD.For his work on AI, machine learning, machine translation, natural language processing, music technology, computational creativity, Debrett's HK 100 recognized De Kai as one of the 100 most influential figures of Hong Kong.For his work on AI ethics and society, De Kai was one of eight inaugural members selected by Google in 2019 for its AI ethics council.See http://dek.ai for details.De Kai’s LinksWebsite: http://dek.aiUniversal Masking Project: http://dek.ai/masks4allTwitter: @dekai123Facebook: https://www.facebook.com/dekai1YouTube, 26 Apr 22, Visual simulations show why we all need to wear masks now https://youtu.be/yfeW2l8G_W4South China Morning Post, 25 May 2020, Coronavirus spread would dramatically drop if 80% of a population wore masks, AI researcher says https://www.scmp.com/video/coronavirus/3085971/coronavirus-spread-would-dramatically-drop-if-80-population-wore-masks-aiBoma COVID-19 Summit, 23 Mar 2020, The disastrous consequences of information disorder erupting around COVID-19: AI is preying upon our unconscious cognitive biases https://youtu.be/ZidC7oRd7PcTEDxChiangMai, Thailand, 7 Sep 2019, The Paradox of AI Ethics: Why Rule-based AI Ethics Will Fail https://www.youtube.com/watch?v=rKPhvb_9tawTEDxOakland, California, 18 Nov 2018, Why AI is impossible without mindfulness https://www.youtube.com/watch?v=w_Sd2ZPPhv8TEDxKlagenfurt, Austria, 16 Jun 2018, Artificial Gossips https://www.youtube.com/watch?v=hHyjSgCoNlwTEDxBlackRockCity, Nevada, 29 Aug 2017, Artificial Children (no video due to technical difficulties)TEDxZhujiangNewTown, Guangzhou, 14 Jan 2017 Why Meaningful AI is Musical https://v.youku.com/v_show/id_XMzA4MDQwODE4MA==.html or https://v.qq.com/x/page/i05088lu78h.htmlTEDxBlackRockCity, Nevada, 31 Aug 2016 (no video due to technical difficulties)TEDxXi'Support the show (https://www.patreon.com/xerxesre)

In this interview De Kai talks about Artificial Intelligence from his cross-disciplinary perspective. We talk about the meaning of creativity, consciousness and mindfullness for modern AI, various misconceptions about modern AI and whether it is still programmable in the classical sense at all, about AI ethics and what AI means for us as a society, humanity and our future.About De KaiDe Kai is Professor of Computer Science and Engineering at HKUST and Distinguished Research Scholar at Berkeley's International Computer Science Institute. He is among only 17 scientists named Founding Fellow by the Association for Computational Linguistics, for his pioneering contributions to machine learning foundations of machine translation that led to the Google/Microsoft/Yahoo/etc translators. De Kai was recruited as founding faculty of the University of Science and Technology in Hong Kong directly from UC Berkeley, where his PhD thesis was one of the first to argue for the paradigm shift toward machine learning based natural language processing. He holds a Kellogg-HKUST Executive MBA and a BS in Computer Engineering (Phi Beta Kappa, cum laude, Revelle College honors) from UCSD.For his work on AI, machine learning, machine translation, natural language processing, music technology, computational creativity, Debrett's HK 100 recognized De Kai as one of the 100 most influential figures of Hong Kong.For his work on AI ethics and society, De Kai was one of eight inaugural members selected by Google in 2019 for its AI ethics council.See http://dek.ai for details.De Kai’s LinksWebsite: http://dek.aiUniversal Masking Project: http://dek.ai/masks4allTwitter: @dekai123Facebook: https://www.facebook.com/dekai1YouTube, 26 Apr 22, Visual simulations show why we all need to wear masks now https://youtu.be/yfeW2l8G_W4South China Morning Post, 25 May 2020, Coronavirus spread would dramatically drop if 80% of a population wore masks, AI researcher says https://www.scmp.com/video/coronavirus/3085971/coronavirus-spread-would-dramatically-drop-if-80-population-wore-masks-aiBoma COVID-19 Summit, 23 Mar 2020, The disastrous consequences of information disorder erupting around COVID-19: AI is preying upon our unconscious cognitive biases https://youtu.be/ZidC7oRd7PcTEDxChiangMai, Thailand, 7 Sep 2019, The Paradox of AI Ethics: Why Rule-based AI Ethics Will Fail https://www.youtube.com/watch?v=rKPhvb_9tawTEDxOakland, California, 18 Nov 2018, Why AI is impossible without mindfulness https://www.youtube.com/watch?v=w_Sd2ZPPhv8TEDxKlagenfurt, Austria, 16 Jun 2018, Artificial Gossips https://www.youtube.com/watch?v=hHyjSgCoNlwTEDxBlackRockCity, Nevada, 29 Aug 2017, Artificial Children (no video due to technical difficulties)TEDxZhujiangNewTown, Guangzhou, 14 Jan 2017 Why Meaningful AI is Musical https://v.youku.com/v_show/id_XMzA4MDQwODE4MA==.html or https://v.qq.com/x/page/i05088lu78h.htmlTEDxBlackRockCity, Nevada, 31 Aug 2016 (no video due to technical difficulties)TEDxXi'Support the show (https://www.patreon.com/xerxesre)

Miko is a Data Scientist who focuses on Natural Language Processing and Computational Linguistics. Soundtrack composed by AIVA (Artificial Intelligence Virtual Artist): https://www.aiva.ai

Anjana started by clarifying what Computational Linguistics is, and the research she did in this field. We then talked about idiomatic programming and echo-chambers, which led us to talking about communities. Anjana then described the coding retreat she did in 2015 and how it was a forming experience in her life. We finished the interview by talking about Developer Advocacy and Public Speaking.Anjana suffers from a debilitating case of curiosity, which led her from philosophy to English teaching to computational linguistics to software development. As a developer/advocate at Observable, she can often be found coding from her home base in San Francisco; that is, when she's not speaking at events around the world to share the joy of programming and promote a more diverse, equitable, and ethical tech industry. Ask her about the Recurse Center, Outreachy, and Mozilla TechSpeakers!Here are the links of the show:https://www.twitter.com/AnjanaVakilhttps://observablehq.comhttps://www.recurse.comhttps://www.outreachy.orgCreditsMusic Aye by Yung Kartz is licensed CC BY-NC-ND 4.0.Your hostSoftware Developer‘s Journey is hosted and produced by Timothée (Tim) Bourguignon, a crazy frenchman living in Germany, who dedicated his life to helping others learn & grow. More about him at timbourguignon.fr.Gift the podcast a ratingPlease do me and your fellow listeners a favor by spreading the word about this podcast. And please leave a rating on the podcasting platforms. This is the best way to increase the visibility of the podcast. Find all the links here: https://devjourney.info/subscribe.htmlPatreonFinally, if you want to help produce the podcast, support us on Patreon. Every cent you pledge will help pay the hosting billsSupport the show (http://bit.ly/2yBfySB)

Spence Green is the co-founder and CEO at Lilt, a San Francisco-based startup that builds intelligent software to automate translation for businesses. Spence and his partner, John DeNero, started Lilt because they believed that a person’s native language shouldn’t limit their ability to learn, grow, and support themselves. Social problems such as social inequity - resources in a given society are distributed unevenly - rarely have satisfactory technical solutions. Steady advances in computational linguistics have brought us to a time at which universal information access is not just a dream. Insights Why an automated translator is important for the corporate world? A CEO’s job and how he influences the organizational culture. Bringing people from stabilized occupations to take the risk to join a start-up. How automated translators are going to increase the efficiency of multilingual content publishing and marketing. Two books that inspire and guide the CEO of Lilt. The importance of a manager in an organization. Spence and Lilt Connect on LinkedIn (https://www.linkedin.com/in/spencegreen/) Lilt (https://lilt.com/) Blog (http://www.spencegreen.com/) Twitter (https://twitter.com/lilthq) ABOUT THE HOST My name is Sam Harris. I am a British entrepreneur, investor and explorer. From hitchhiking across Kazakstan to programming AI doctors I am always pushing myself in the spirit of curiosity and Growth. My background is in Biology and Psychology with a passion for improving the world and human behaviour. I have built and sold companies from an early age and love coming up with unique ways to make life more enjoyable and meaningful. Sam: Instagram (https://www.instagram.com/samjamsnaps/) Quora (https://www.quora.com/profile/Sam-Harris-58) Twitter (https://twitter.com/samharristweets) LinkedIn (https://www.linkedin.com/in/sharris48/) Sam's blog - SamWebsterHarris.com (https://samwebsterharris.com/) Support the Show - Patreon (https://www.patreon.com/growthmindset) Episode Summary Meet Spence Green – currently working on machine-assisted language translation as the CEO of Lilt and with a diverse professional portfolio of having worked as a research assistant at Stanford University, a software and research intern at Google, and much more. Having graduated from Stanford with a PhD in computer science back in 2014, his research area is the intersection of natural language processing and human-computer interaction. Learn why Spence decided on this field of technology and why he thinks that it is important for the corporate businesses across the globe who have to resort to other means of language translation. He works to remove the cross-language barriers hindering significant progress for people. When you’re a business, you want to translate something. You hire one of these companies from the language industry and they hire a bunch of freelancers. You give them the words and they hire these people and they translate the words and they give it back to you. And it’s slow and inefficient. And this is kind of the main reason why more stuff doesn’t get translated. It’s expensive. So, we started to build systems to make that process more efficient. And that’s what we do now. So, we build this system that institutions who these are businesses, governments and academic institutions can use to publish information across language barriers and do that in a much more efficient way. He explains what he does in simple words for the audience and then explains the scope that this research has in different domains. In our field we’re in natural language processing, which is some discipline of artificial intelligence, which is a sub discipline of computer science. Spence also elaborates how getting a chance to work at Google Translate was a significant and unexpected career opportunity for him – almost an adventure. It’s a complicated technology to build that requires in the early days we need to do level people to build the system. And they’re not that many of those people in the world and most of them work for tech companies for very large salaries. He shares what allowed him to convince people from different fields to take the risk to join his start-up company. It’s less my ability to sell or persuade and more how interesting and important the problem in the mission is. And good scientists and engineers are attracted to hard problems. So, if you have heart problems to solve, that’s probably the best thing that you can do to attract great people. Spence also has much to say about what his company has been doing for the past few years and what the business processes and mechanisms are. The process for the last couple of years, is positioning the product in the market so it solves a specific business need. It’s presented in a way that people can understand. You can compare to what they their existing solutions to the problem. It’s priced in way that people understand, and they can get through their procurement departments. Spencer says that he finds comfort in knowing that his human experience is not unique and the problem that he’s facing, other people have faced and solved. And oftentimes, if you have a good mentor or if you’re surrounded by people who have seen more of the film than you have, then you can focus on solving original problems and not resolving problems. Somebody told me a long time ago that a CEO has three responsibilities. People, culture and vision and not running out of cash. And those are kind of a unique things that a CEO can do. And I think that people and culture part that has a lot to do with being able to hire well and then being able to articulate expectations for how you want to mobilize a group of people to work together. And a lot of that is being a very good communicator. He also explains what he expects from the field and the industry overall in the coming few years and how it is going to impact people. Workload will move to machines. I’m less of an optimist. I guess that the entire field will be fully automated and there’s some sort of dystopian future where nobody has a job anymore. I think that’s not really the history of technology, really. The history of technology is you mechanized things that can be mechanized and that frees people up to work on higher order problems. Maybe that’s not true in places like, I don’t know, the copy shop in a business and now you have a printer and you don’t need a copy person. Having been a project manager, he also emphasizes the importance of a manager for organizational performance and the impact that he has. A manager as an individual contributor – you go from assessing your own performance in terms of your individual output to being an organization leader and your performance is the output of your organization. Key Discussion Points [7:50] The importance of automated translators and removal of cross-language barriers. [12:04] How they convinced people to take the risk to join a start-up [15:53] Importance of having good mentors [17:35] Strategies that Spence and his company are currently using. [21:33] Developing into an effective CEO [28:45] The future of the industry and its impact on people. [34:54] Two books by Peter Drucker that guide and inspire our guest – “The Effective Executive” and “Management.” Top Tips Overcoming the language barrier through technology We live in an era of rapid globalization, which is demonstrated by the growing demand for language services. Translation technology solves this problem in two ways. First, it enables translation at a level where it does not need to involve a human. Secondly, we’ve seen translation technology increase human translator productivity. Ultimately, translation is important because it facilitates multilingual communication and allows people from around the world to better understand one another culturally, economically and socially. Translation technology is just getting to the point where the general public will start to see its impact in their everyday lives. Not only are there free, general translation engines online, but even the more tailored, advanced technology is becoming accessible Having a good mentor by your side A good mentor is willing and able to take you on. A good mentor iwill help you stay accountable to your goals, they will help you pay attention and stay on track. A mentor essentially fills those gaps that are missing from your career and professional development growth. If you are lucky enough to find a personal mentor who can be all of these things to you, you will gain an advantage, because you have a secret weapon that can take you to new heights. Lead by example "A leader knows the way, goes the way and shows the way" -John Maxwell Lead a team honestly and authentically. Make sure you "walk the walk." When leaders don't "practice what they preach," it can be almost impossible for a team to work together successfully. How can anyone trust a leader who talks about one thing, but does another? Good leadership takes strength of character and a firm commitment to do the right thing, at the right time, for the right reason. This means doing what you say, when you say it. If your team knows that you'll also do whatever you expect from them, they'll likely work hard to help you achieve your goal. Books Get any of the books free on audible (https://www.amazon.co.uk/Audible-Free-Trial-Digital-Membership/dp/B00OPA2XFG?tag=samharris48%E2%80%9321) The Effective Executive - Peter Drucker (https://www.amazon.com/dp/0060833459/?tag=devonfir-20) Managing Oneself: The Key to Success - Peter Drucker (https://www.amazon.co.uk/Managing-Oneself-Peter-F-Drucker/dp/163369304X/ref=sr_1_4?crid=106CDRCKL3IAY&keywords=peter+drucker&qid=1581614768&sprefix=peter+dru%2Caps%2C404&sr=8-4) Introduction to Deep Learning (The MIT Press) (https://www.amazon.co.uk/Introduction-Deep-Learning-MIT-Press/dp/0262039516/ref=sr_1_1?keywords=charniak&qid=1581614712&s=books&sr=8-1) Subscribe! If you enjoyed the podcast please subscribe and rate it. And of course, share with your friends!

In this week's episode, I was joined by former Chief Data Officer and Partner of Text Analytics company Gavagai and now of RISE (Research Institutes of Sweden), Fredrik Olsson. Fredrik is someone who has an impressive background within the sphere of Language Technology (PhD in Computational Linguistics), and he offers a unique insight as to what life is like when you move from the commercial sector back into research (where he is now). I think that Fredrik is an excellent example of someone who is comfortable with being uncomfortable and is always open to stepping outside of his comfort zone. I always enjoy having a chat with him and thank you for recording this with me Fredrik!

Talk by Dr Christian Bentz, Assistant Professor, University of Tübingen

This week, Microsoft Research and University of Montreal show that machines can learn through interactive language by answering questions (question answering with interactive text, or QAit). The Allen Institute for AI’s Aristo system, a suite of eight solves, can pass (90%+) the New York 8th Grade regents science exams (for non-diagram, multiple choice questions), and can exceed 83% on the 12th grade exam, though Melanie Mitchell suggests the achievement may not be as profound as it seems. A “meta-research” paper from Milan and Klagenfurt takes a broader look at neural network research and highlights concerns of reproducibility (or lack thereof) as well as utility (or lack thereof, where simple heuristic methods can outperform the neural networks). From a workshop organized by Max Tegmark and Emilia Javorsky, a group of diverse authors produced a “possibility of a middle road” look at roadmapping a way ahead for Autonomous Weapons Systems. An opinion piece from Zachary Kallenborn on War on the Rocks look at What If the US Military Neglects AI? A paper in Nature provides an overview of open-ended evolution, as a part of artificial life. Gary Marcus and Ernest Davis publish a book on Rebooting AI: Building AI We Can Trust. The 57th Annual Meeting of the Association for Computational Linguistics occurred at the end of July, and Kate Koidan provides a summary of the top trends. The IEEE ranks robot creepiness with the top 100 creepy robots. Booz Allen releases a documentary on the Dawn of Generation AI. And the Naval Facilities Engineering and Expeditionary Warfare Center (NAVFAC EXWC) will host an industry day conference on cyber, control system, and machine learning in December.  Click here to visit our website and explore the links mentioned in the episode.   

A project combining English literature, experimental psychology, and computational linguistics, with a focus on entropy, abstraction, and mental health. James Carney's current research investigates how mental illness interacts with textual structures – specifically, using machine learning to investigate the potential therapeutic qualities of literature with different levels of entropy (unpredictability) and abstraction, for anxiety disorders versus depression. We also touch on wider questions of motivation in the health humanities and literary studies, the appeal of belief in the transformative power of literature, and the expansion of textual/computational inquiry out into structural anthropology.

On this week’s show, we spoke with Narjès Boufaden, CEO @ Keatext. Narjès is passionate about solving technical challenges involving natural language understanding, Narjès is among first researchers who specialized in Text mining technologies for conversational text, such as dialogues and telephone conversations. She has contributed in the field with more than 15 scientific publications and several conference talks.  Under the supervision of Drs Guy Lapalme and Yoshua Bengio, she completed her Ph.D in Computational Linguistics in 2004 at Université de Montréal and worked as researcher in several universities and then at CRIM (Centre de Recherche Informatique de Montréal) where she helped organizations dealing with information management challenges.    We had an amazing discussion where we focused on: How she got interested in machine & human interactions The founding story of Keatext and her early struggles Their change in business model How she plans to make recommendations prescriptive instead of descriptive The hype of the industry and how it’s potentially changing   Narjès is the most passionate person I’ve meet on the topic of artificial intelligence. She really knows her stuff. I hope that you enjoy the conversation!   Let us know what you think. What types of guests would like to see on the show? What topics interest you the most? Send me your thoughts at nectar@thepnr.com   Subscribe | iTunes | Google Play |Spotify | YouTube | Stitcher

We are thrilled to welcome Toni Ressaire, a technical communicator, trainer and consultant, to join the #InVinoFab podcast for episode no. 6. Besides working with companies in the software development industry on five continents (we secretly think she's Carmen Sandiego), Toni shares with us her rather non-traditional uses for traditional technology communication (tech comm) tools. She's currently working with a team developing innovative tools and methodologies to answer the need for information applied to existing and new technologies, such as virtual reality, artificial intelligence (AI), and chatbots.Fun Wine Facts: Vigneron = Winemaker; What's a Vigneron? Aperitif = a light drink to have before dinner; something refreshing to enjoy prior to the meal No such thing as a “wino” ... but maybe this wino term needs to be redefined. Meals in Italy are lengthy -- so sit back, sip and enjoy the company & many courses! The Information Energy Conference 2018: https://www.informationenergy.org/Q: There is a lot of interesting things about your work: you mentioned research and work that is being done to reach an "intelligent" conversation that is more human-like. While it's not your job to create algorithms and natural language processors, you use them in designing bots and I like understanding the technology behind it. Can you tell us about what is going on in research and how educators could better collaborate with researchers in industry?A:  AI is still so far away from true machine intelligence. Chatbots will change the way we work because they can help with things like customer service, allowing humans to have time to do more meaningful work. They can do the rote repetitive work, manage phone calls, answer student emails. Chatbots say what you tell them to say, they are not intelligent or learning deeply. They learn patterns based upon the information they gather. We need to teach chatbots intentions, so we give them the questions and answers. They can learn through Twitter and Facebook conversations.  Chatbots don't have intuition, so they can't determine when a response is appropriate or not they gather that information to follow dialogue flow accurately. Here are a few chatbot stories http://www.latimes.com/business/la-fi-0325-microsoft-chatbot-20160326-story.htmlQ: Are there logic models connected to the chatbots you work with?A: Toni designs chatbot conversations and dialog flow. She doesn't work with the logic models (more with scripting chatbots), but is keen to learn and she shared about one of the speakers at the conference: Carlos Perez. READ his Medium article: Alpha Zero: How Intuition Demolished Logic: https://medium.com/intuitionmachine/alphazero-how-intuition-demolished-logic-66a4841e6810  Why it failed early, based on logic and newer is based on intuition, alpha zero, gamebot, able to beat logic as it is built on logic Our thinking is based on intuition Logic is the layer on top of intuition. Intuition has traditionally been frowned upon. This is interesting as the tendency is to say we make decisions based upon intuition and that this is not as good as logic. We make decision on patterns based upon patterns The intuitive mind is a sacred gift and the rational mind is a faithful servant. We have created a society that honors the servant and has forgotten the gift. — Albert EinsteinQ: are there any new ideas or projects percolating for you right now that you care to share? You mentioned an article you recently read about intelligence and intuition, and how it got you thinking about human intelligence?A: According to the article machines that use intuitive cognition perform better than those that use logic. Traditional thinking tells us that logic is more reliable. This is interesting as some same men think in a more logical way, while women tend to be more intuitive and some people align this with capability to do certain jobs such as nurse vs. coder. Twinery http://twinery.org/ Small pieces of information, molecular, machine reads and puts together depending on the path you choose Molecular content that can be read by machines “What I'm afraid of, there's a huge need for engineers and knowledge of natural language processing language.” ~ Toni Ressaire Traditional basic knowledge Technical and scientific communication A taste of certain things-look at curriculum, 10 years behind, need basic, but the approach used, give reading materials easily learned by reading and class time for doing and talking about things like new technologies and how we could use them. Need to allow time for play, exploration and asking questions Computational linguistics-links to programs https://thebestschools.org/rankings/best-computational-linguistics-graduate-programs/ Information specialists can no longer deal with only words, must also deal with technology. Must also understand tech so we can understand how to write Chatbot example of how we will need to change our thinking about writing Understand we can't think in a linear fashion or write, need to be multidimensional like a chatbot Fun Fact: UNT has a Computational Linguistics, MS degree: https://interdisciplinarystudies.unt.edu/concentrations/computational-linguistics-ms  Q: What recommendations do you have for people thinking about working with chatbots (or, in general, in this field)?A: These professionals need to be multidisciplinary and be able to collaborate with different parts of chatbot production. It's recommended to not live in a silo -- be sure to partner with other departments, disciplines, or industry partners. READ and REVIEW: The AI #DLNchat summary: https://www.edsurge.com/news/2018-03-29-dlnchat-how-could-artificial-intelligence-shape-the-future-of-higher-educationQ: Do women in other countries pursue STEM in greater numbers than US?A: Toni-thinks that because it is a new opportunity for a lot of women in other countries they are jumping on it. Culture differences? The More Gender Equality, the Fewer Women in STEM https://www.theatlantic.com/science/archive/2018/02/the-more-gender-equality-the-fewer-women-in-stem/553592/ Mind the Gap EU Project  http://mindthegapproject.eu/ How gender equality in STEM education leads to economic growth http://eige.europa.eu/gender-mainstreaming/policy-areas/economic-and-financial-affairs/economic-benefits-gender-equality/ste Connect and learn more interesting things Toni is involved in:--LinkedIn: https://www.linkedin.com/in/toniressaire/--Website: http://info4design.com/ --Twitter: @ToniRessaire--Self-Publishing Links: @route11ebooks & http://pub.ink/--Book Recommendation: Eat Pray Love by Elizabeth Gilbert https://www.elizabethgilbert.com/books/eat-pray-love/ --Favorite red wine: Côtes du Rhône - NegroamaroDo you have a story to share with us on  a future #InVinoFab podcast? Is there someone we should bring on as a future guest? Let us know! Feel free to send us an email: invinofabulum@gmail.com or stay connected to the #InVinoFab Podcast: Hosts: Patrice (@profpatrice) & Laura (@laurapasquini); pronouns: she/her Twitter: https://twitter.com/invinofab Instagram: https://www.instagram.com/invinofab/ 

Tobias Goebel is Senior Director, Emerging Technologies for Aspect Software. He has a Masters Degree in Computational Linguistics and has studied at both the University of Bonn and University of Edinburgh. Tobias also has 15 years experience working in voice technology, first as a developer, then as a designer and more recently as a strategist and marketer. Aspect has a big focus on customer service and contact center automation. Chat and voice are now a rapidly growing part of that work, but these technologies are also taking Aspect customers into conversational marketing and direct outreach to new customers.

Vi konsulter pratar om digitaliseringen med våra kunder dagligen. Vi sprider vår vision och visar kunderna hur de kan utnyttja ny teknik för att uppnå största möjliga effekt i sin verksamhet. Men digitalisering är inte bara business. Vi begav oss till Linköpings Universitet för att prata med Jody Foo, kognitionsvetare och adjunkt som undervisar i Computational Linguistics på Linköpings Universitet. Världen digitaliseras nu, på samma sätt som den industrialiserades under 1800-talet. Internet och smarta telefoner kickade igång digitaliseringen hos gemene man runt millenieskiftet och nu är vi vana konsumenter av digitala produkter som gör oss mindre beroende av tid och rum. Nu satsar Skolverket på digital kompetens och EU har sitt Digital Competence Framework. Jody beskriver mognadsprocessen ur ett individperspektiv. Var befinner du dig? Jody Foo, Micke Norbäck, Jonas Jaani (20:25) Jody Foo. Mer material / länkar Lyssna på extra material med Jody Foo Skolverket jobb med hur skolan ska digitaliseras http://www.skolverket.se/skolutveckling/resurser-for-larande/itiskolan/nationell-strategi  Digital kompetens enligt EU https://ec.europa.eu/jrc/en/digcomp/digital-competence-framework PRENUMERERA på podcasten Effekten. Direktleverans av nya avsnitt till: iPhone, Android eller e-post

There's not that many serial tech entrepreneurs in the legal space, but Gary Sangha is one of them. Sangha is CEO and founder of Lit IQ, which is applying machine learning and computational linguistics to legal documents to help lawyers avoid making drafting mistakes. In this episode, Sangha talks about where this type of software is most useful and legitimate, what the legal landscape in relationship to machine learning may look like in the next few years, and how this technology may apply across industries.

Those who think comic book geeks and computer nerds are two mutually exclusive groups have never met Ryan North. The Toronto resident and writer behind The Unbeatable Squirrel Girl, Adventure Time and Dinosaur Comics also holds a masters in computer science with a focus on Computational Linguistics — teaching artificial intelligence how to speak more naturally. His love of computer science also bleeds into the pages of the Unbeatable Squirrel Girl, aiding in its progressive picture of what makes a female heroine. Even his effort to bring back the choose your own adventure genre – Romeo and/or Juliet – refuses to define society along gender lines. Not bad for a guy who can’t draw, but still left what his parents called, “a respectable profession” to create comics.@ryanqnorthwww.ryannorth.caEpisode Sponsor: Hairy Tarantula

We have a great talk with Emily Bender of University of Washington. Where she details and highlights information about Computational Linguistics. Currently a Professor in the Department of Linguistics, an Adjunct Professor in the Department of Computer Science and Engineering, the faculty director of the CLMS program, and the director of the Computational Linguistics Laboratory, current Chair (2016-2017) of the Executive Board of NAACL as well as a member of the ICCL (the committee responsible for Coling). Emily received her PhD from the Linguistics Department at Stanford University, where she joined the HPSG and LinGO projects at CSLI.Please see additional links:Planning ahead page: http://www.compling.uw.edu/admissions/prep/ACL Anthology: https://aclweb.org/anthology/Our jobs database: https://vervet.ling.washington.edu/db/livesearch-job-form.php

Maps are useful things, but it turns out that projecting a 3D object on a 2D map can cause a lot of unexpected problems. They even inspired an XKCD comic. This week we explore maps and map projections. We also chat about machine learning as part of #FunPaperFriday. What’s the big problem? The Earth is a sphere, actually it’s an ellipsoid, actually it’s really bumpy and messy Taking 3D information and pushing in onto a 2D medium means that you must sacrifice something, you are losing a dimension with which you can express information. Projections are a well thought out as researched problem, even in pure mathematics. You have to pick a projection that will tell you want you need to know accurately, and know that you lose some other information. There is even a West Wing clip about this A few examples of projection problems There are geographical properties that we care about: area, shape, direction, conformality, distance, scale… and you can’t get them all at once. In fact, some it’s hard to get more than approximately the right answer. Area: Maps that preserve area relationships between things on the globe are called equal area maps. Distance: Some maps (equidistant maps) show an accurate distance from the center of the projection to all points. Scale: The same scaling relation applied across the map will give accurate values for scale relations on the globe. Conformality: Scale in any direction at any point is identical. This means that parallels and meridians are at right angles. (Local shape preserved) http://www.colorado.edu/geography/gcraft/notes/mapproj/mapproj_f.html A few projections Projections can be generally classified as cylindrical, conic, azimuthal, or other. These are as you would think, projections onto cylinders, cones, planes, or with rules of “rectangular meridians” or something else. There are lots of sub-classes, you can view them here. Wikipedia lists over 60 different projections! Fun Paper Friday That’s what she said. Can we teach computers to better understand human speech patterns? This paper takes a humorous problem as a test case. Kiddon, C., & Brun, Y. (2011). That’s What She Said: Double Entendre Identification (pp. 89–94). Presented at the Annual Meeting of the Association for Computational Linguistics. Contact us: Show - www.dontpanicgeocast.com - @dontpanicgeo - show@dontpanicgeocast.com John Leeman - www.johnrleeman.com - @geo_leeman Shannon Dulin - @ShannonDulin

Software Process and Measurement Cast 352 features our interview with Gil Broza.  We discussed Gil’s new book The Agile Mind-Set. Do you know what the Agile Mind-Set is or how to get one?  Gil’s new book explains the concept of the Agile Mind-Set and how you can find it in order to deliver more value! Gil Broza helps organizations, teams and individuals implement high-performance Agile principles and practices that work for them. His coaching and training clients – over 1,300 professionals in 40 companies – have delighted their customers, shipped working software on time, increased their productivity and decimated their software defects. Beyond teaching, Gil helps people overcome limiting habits, fears of change, blind spots and outdated beliefs, and reach higher levels of performance, confidence and accomplishment. Gil is the author of The Agile Mind-Set and The Human Side of Agile: How to Help Your Team Deliver. Gil has a M.Sc. in Computational Linguistics and a B.Sc. in Computer Science and Mathematics from the Hebrew University of Jerusalem, Israel. He is a certified NLP Master Practitioner and has studied organizational behavior and development extensively. He has written several practical papers for the Cutter IT Journal, other trade magazines, and for conferences, winning the Best Practical Paper award at XP/Agile Universe 2004. Gil co-produced the Agile Coaching stage for the “Agile 2010” and “Agile 2009” conferences. Gil lives in Toronto, Canada. Contact Data:http://www.3pvantage.com/index.htmhttps://leanpub.com/theagilemindsethttp://thehumansideofagile.com/https://twitter.com/gilbroza Gil was last interviewed on SPaMCAST 210.  We discussed his first book The Human Side of Agile.     Call to Action! I have a challenge for the Software Process and Measurement Cast listeners for the next few weeks. I would like you to find one person that you think would like the podcast and introduce them to the cast. This might mean sending them the URL or teaching them how to download podcasts. If you like the podcast and think it is valuable they will be thankful to you for introducing them to the Software Process and Measurement Cast. Thank you in advance! Re-Read Saturday News Remember that the Re-Read Saturday of The Mythical Man-Month is in full swing.  This week we tackle the essay titled “Aristocracy, Democracy and System Design”! The Re-Read Saturday and other great articles can be found on the Software Process and Measurement Blog. Remember: We just completed the Re-Read Saturday of Eliyahu M. Goldratt and Jeff Cox’s The Goal: A Process of Ongoing Improvement which began on February 21nd. What did you think?  Did the re-read cause you to read The Goal for a refresher? Visit the Software Process and Measurement Blog and review the whole re-read. Note: If you don’t have a copy of the book, buy one. If you use the link below it will support the Software Process and Measurement blog and podcast. Dead Tree Version or Kindle Version  Upcoming Events Software Quality and Test Management September 13 – 18, 2015San Diego, California http://qualitymanagementconference.com/ I will be speaking on the impact of cognitive biases on teams!  Let me know if you are attending! If you are still deciding on attending let me know because I have a discount code!   More on other great conferences soon!   Next SPaMCAST The next Software Process and Measurement Cast features three columns.  The first is our essay on leaning styles.  Learning styles are an interesting set of constructs that are useful to consider when you are trying to change the world or just and an organization.  We will also include Steve Tendon’s column discussing the TameFlow methodology and his great new book, Hyper-Productive Knowledge Work Performance. Anchoring the cast will be Gene Hughson returning with an entry from his Form Follows Function column.    Shameless Ad for my book! Mastering Software Project Management: Best Practices, Tools and Techniques co-authored by Murali Chematuri and myself and published by J. Ross Publishing. We have received unsolicited reviews like the following: “This book will prove that software projects should not be a tedious process, neither for you or your team.” Support SPaMCAST by buying the book here. Available in English and Chinese.

Voula Giouli is a research associate and has been working at ILSP / R.C. "Athena" since 1998 conducting basic and applied research in Computational Linguistics, the focus being on the analysis and modeling of natural language and the development of electronic language resources. We talk about how computational linguistics and natural language processing applications can benefit humans and how we can use the information & audio data derived from these. As Voula Giouli mentions, the challenge is to spot the unstructured information in various channels and mediums and serve this to the right user at the right time. She talks about her recent work on the development of an M2M conceptual dictionary of modern greek. She also shares insights and various commercial applications that could benefit from NLP technologies like consumer ratings and recommendations, authoring autocomplete aid while writing and others. Interviewed by Venetia Kyritsi for Tech Talks Central.

The Patented SpecGram 5 Minute Interview: Philip Resnik — My guest today is Philip Resnik, a professor at the University of Maryland, with joint appointments in the Department of Linguistics and at the Institute for Advanced Computer Studies. Phillip is the director of the University of Maryland Computational Linguistics and Information Processing Laboratory, and a researcher and consultant with extensive experience in natural language processing and text analytics, specializing in combining knowledge based and corpus based statistical techniques. He is also a Strategic Technology Advisor to 3M Health Information Systems and the Founder of React Labs.

Language Made Difficult, Vol. XXXIV — The SpecGram LingNerds are joined by once again by returning guest Devan Steiner. After some Lies, Damned Lies, and Linguistics, the LingNerds discuss whether or not all the forms of "to be" in Indo-European languages are derived from Arabic roots (hint: they're not!), and take on Comprehensive Exam Questions in computational linguistics, pidgins, phonology, and more.

To the Computational Linguists; by The Managing Editor; From Volume CLXV, Number 3, of Speculative Grammarian, September 2012 — First, why isn’t there more Computational Philology out there? Okay, I know no one is going to actually answer that, and most computational linguists don’t even know that Computational Philology exists. Kids these days—no respect for their elders, and no knowledge of the classics! (Read by Trey Jones.)

Recision and Precall—Accuracy Measures for the 21st Century; by Jonathan van der Meer; From Volume CLII, Number 4, of Speculative Grammarian, July 2007 — Thanks to a decades-long case of physics envy and the advent of cheap computational power, linguistics has devolved from a cultured gentlemen’s pseudo-science into a debased money-grubbing quasi-science. (Read by Jonathan van der Meer.)

Nicholas Asher, Richard Holton, Kasia Jaszczolt, Stephen Clark, Ann Copestake, Aurelie Herbelot, William Marslen-Wilson

Podcast

Podcast

This paper presents a meaning-based method to spam filtering by distinguishing text without content from text with little content from text with normal content, based on the amount of meaning that can be automatically processed in the way humans do. The basic method assumes that a semantic analyzer will be able to produce less output from semantically less grammatical input text than from semantically well-formed text. The method was pilot-tested on a corpus of blog spam. Future improvements, including a method to distinguish semantically unified from semantically disparate text are sketched. The tested method, but even more the projected improvements, will open up the way to taking the spam filtering arms race to a new level very costly to spam producers. About the speaker: Christian F. Hempelmann, is Assistant Professor of Computational Linguistics and Director of the Ontological Semantic Technology Lab at Texas A&M-Commerce. He received his PhD in 2003 from Purdue University with a specialization in ontological semantics and NLP applied to information security at the Center for Education and Research in Information Assurance and Security (CERIAS), and humor. After a post-doc in psychology at Memphis University and a professorship at Georgia Southern University, he has worked in the NLP industry since 2006, first at the Internet search engine hakia.com, then at Riverglass, Inc., developing full-scale ontological-semantic solutions. He is a member of the Editorial Board of the International Journal on Advances in Intelligent Systems and the Journal for Humor Research and has (co-)authored over forty articles.