Podcast appearances and mentions of paco nathan

GraphBI: Expanding Analytics to All Data Through the Combination of GenAI, Graph, & Visual Analytics // MLOps Podcast #310 with Paco Nathan, Principal DevRel Engineer at Senzing & Weidong Yang, CEO of Kineviz.Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractExisting BI and big data solutions depend largely on structured data, which makes up only about 20% of all available information, leaving the vast majority untapped. In this talk, we introduce GraphBI, which aims to address this challenge by combining GenAI, graph technology, and visual analytics to unlock the full potential of enterprise data.Recent technologies like RAG (Retrieval-Augmented Generation) and GraphRAG leverage GenAI for tasks such as summarization and Q&A, but they often function as black boxes, making verification challenging. In contrast, GraphBI uses GenAI for data pre-processing—converting unstructured data into a graph-based format—enabling a transparent, step-by-step analytics process that ensures reliability.We will walk through the GraphBI workflow, exploring best practices and challenges in each step of the process: managing both structured and unstructured data, data pre-processing with GenAI, iterative analytics using a BI-focused graph grammar, and final insight presentation. This approach uniquely surfaces business insights by effectively incorporating all types of data.// BioPaco NathanPaco Nathan is a "player/coach" who excels in data science, machine learning, and natural language, with 40 years of industry experience. He leads DevRel for the Entity Resolved Knowledge Graph practice area at Senzing.com and advises Argilla.io, Kurve.ai, KungFu.ai, and DataSpartan.co.uk, and is lead committer for the pytextrank​ and kglab​ open source projects. Formerly: Director of Learning Group at O'Reilly Media; and Director of Community Evangelism at Databricks.Weidong YangWeidong Yang, Ph.D., is the founder and CEO of Kineviz, a San Francisco-based company that develops interactive visual analytics based solutions to address complex big data problems. His expertise spans Physics, Computer Science and Performing Art, with significant contributions to the semiconductor industry and quantum dot research at UC, Berkeley and Silicon Valley. Yang also leads Kinetech Arts, a 501(c) non-profit blending dance, science, and technology. An eloquent public speaker and performer, he holds 11 US patents, including the groundbreaking Diffraction-based Overlay technology, vital for sub-10-nm semiconductor production.// Related LinksWebsite: https://www.kineviz.com/Blog: https://medium.com/kinevizWebsite: https://derwen.ai/pacohttps://huggingface.co/pacoidhttps://github.com/ceterihttps://neo4j.com/developer-blog/entity-resolved-knowledge-graphs/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Weidong on LinkedIn: /yangweidong/Connect with Paco on LinkedIn: /ceteri/

This is our semi-regular conversation on topics in AI and Technology with Paco Nathan, the founder of Derwen, a boutique consultancy focused on Data and AI. Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes - with links to many references - can be found on The Data Exchange web site.

This is our monthly conversation on topics in AI and Technology with Paco Nathan, the founder of Derwen, a boutique consultancy focused on Data and AI.Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes - with links to many references - can be found on The Data Exchange web site.

This is our monthly conversation on topics in AI and Technology with Paco Nathan, the founder of Derwen, a boutique consultancy focused on Data and AI.Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes - with links to many references - can be found on The Data Exchange web site.

This is our monthly conversation on topics in AI and Technology with Paco Nathan, the founder of Derwen, a boutique consultancy focused on Data and AI.Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes - with links to many references - can be found on The Data Exchange web site.

Speaker Resources:Neo4j+Senzing Tutorial: https://neo4j.com/developer-blog/entity-resolved-knowledge-graphs/#neo4jWhen GraphRAG Goes Bad: A Study in Why you Cannot Afford to Ignore Entity Resolution (Dr. Clair Sullivan): https://www.linkedin.com/pulse/when-graphrag-goesbad-study-why-you-cannot-afford-ignore-sullivan-7ymnc/Paco's NODES 2024 session: https://neo4j.com/nodes2024/agenda/entity-resolved-knowledge-graphs/Graph Power Hour: https://www.youtube.com/playlist?list=PL9-tchmsp1WMnZKYti-tMnt_wyk4nwcbHTomaz Bratanic on GraphReader: https://towardsdatascience.com/implementing-graphreader-with-neo4j-and-langgraph-e4c73826a8b7Tools of the Month:Neo4j GraphRAG Python package:  https://pypi.org/project/neo4j-graphrag/Spring Data Neo4j: https://spring.io/projects/spring-data-neo4jEntity Linking based on Entity Resolution tutorial: https://github.com/louisguitton/spacy-lancedb-linkerhttps://github.com/DerwenAI/strwythuraAskNews (build news datasets) https://asknews.app/The Sentry https://atlas.thesentry.org/azerbaijan-aliyev-empire/Announcements / News:Articles:GraphRAG – The Card Game https://neo4j.com/developer-blog/graphrag-card-game/Turn Your CSVs Into Graphs Using LLMs https://neo4j.com/developer-blog/csv-into-graph-using-llm/Detecting Bank Fraud With Neo4j: The Power of Graph Databases https://neo4j.com/developer-blog/detect-bank-fraud-neo4j-graph-database/Cypher Performance Improvements in Neo4j 5 https://neo4j.com/developer-blog/cypher-performance-neo4j-5/New GraphAcademy Course: Building Knowledge Graphs With LLMs https://neo4j.com/developer-blog/new-building-knowledge-graphs-llms/Efficiently Monitor Neo4j and Identify Problematic Queries https://neo4j.com/developer-blog/monitor-and-id-problem-queries/Videos:NODES 2023 playlist https://youtube.com/playlist?list=PL9Hl4pk2FsvUu4hzyhWed8Avu5nSUXYrb&si=8_0sYVRYz8CqqdIcEventsAll Neo4j events: https://neo4j.com/events/(Nov 5) Conference (virtual): XtremeJ https://xtremej.dev/2024/schedule/(Nov 7) Conference (virtual): NODES 2024 https://dev.neo4j.com/nodes24(Nov 8) Conference (Austin, TX, USA): MLOps World https://mlopsworld.com/(Nov 12) Conference (Baltimore, MD, USA): ISWC https://iswc2024.semanticweb.org/event/3715c6fc-e2d7-47eb-8c01-5fe4ac589a52/summary(Nov 13) Meetup (Seattle, WA, USA): Puget Sound Programming Python (PuPPY) - Talk night Rover https://www.meetup.com/psppython/events/303896335/?eventOrigin=group_events_list(Nov 14) Meetup (Seattle, WA, USA): AI Workflow Essentials (with Pinecone, Neo4J, Boundary, Union) https://lu.ma/75nv6dd3(Nov 14) Conference (Reston, VA, USA): Senzing User Conference https://senzing.com/senzing-event-calendar/(Nov 18) Meetup (Cleveland, OH, USA): Cleveland Big Data mega-meetup https://www.meetup.com/Cleveland-Hadoop/(Nov 19) Chicago Java User Group (Chicago, IL, USA): https://cjug.org/cjug-meeting-intro/#/(Dec 3) Conference (London, UK): Linkurious Days https://resources.linkurious.com/linkurious-days-london(Dec 10) Meetup (London, UK): ESR meetup in London by Neural Alpha(Dec 11-13) Conference (London, UK): Connected Data London https://2024.connected-data.london/

This is our monthly conversation on topics in AI and Technology with Paco Nathan, the founder of Derwen, a boutique consultancy focused on Data and AI.Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes - with links to many references - can be found on The Data Exchange web site.

The amount of hype and bullsh*t in AI is today is sky high. But there's also some awesome achievements happening in the field as well. How do you separate what's real and what's hype? Paco Nathan has been at the forefront of ML and AI, among other fields, for several decades. He joins us to chat about the myths and reality of AI.

This is our monthly conversation on topics in AI and Technology with Paco Nathan, the founder of Derwen, a boutique consultancy focused on Data and AI.Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes - with links to many references - can be found on The Data Exchange web site.

Paco Nathan is a national treasure. He's not only an OG in the field of AI, but he's also instrumental in early hacker and cyberpunk culture. When I first met Paco, it suddenly clicked that I'd seen his name in various cyberpunk and alternative zines back in the 1990s. We have a chat all sorts of crazy stuff, and I feel like we only got to 5% of the stories..

This is our monthly conversation on topics in AI and Technology with Paco Nathan, the founder of Derwen, a boutique consultancy focused on Data and AI.Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes - with links to many references - can be found on The Data Exchange web site.

This is our monthly conversation on trending topics in AI and Technology with Paco Nathan, the founder of Derwen, a boutique consultancy focused on Data and AI.Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes - with links to many references - can be found on The Data Exchange web site.

Paco Nathan and I chat about early chatbots, and all things AI, especially since the 1980s. We also riff on how we intersected in the early days of the Internet. Paco is one of my faves, so expect him back for another interview soon. X: https://twitter.com/pacoid LinkedIn: https://www.linkedin.com/in/ceteri/

Paco Nathan is the founder of Derwen, a boutique consultancy focused on Data and AI. This episode is part of our series of monthly roundups and covers: the proposed California Senate Bill 1047 for regulating AI models, including its feasibility and potential unintended consequences. We also discuss the rising popularity of graph retrieval augmented generation (GraphRAG) techniques to mitigate hallucinations in large language models, while acknowledging the current limitations and future potential of integrating symbolic and statistical AI approaches. Additionally, we explore the concept of AI avatars in the workplace, highlighting the challenges and ethical considerations surrounding digital twins and agent-based systems.Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes can be found on The Data Exchange web site.

Paco Nathan is the founder of Derwen, a boutique consultancy focused on Data and AI. This episode is part of our series of monthly roundups and covers: Llama 3 and other recent LLMs, the rise of open foundation models, the evolution of AI agents, and the importance of data engineering. We also explore the limitations of leaderboards in evaluating AI models and touch upon the ethical and societal implications of AI development.Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes can be found on The Data Exchange web site.

Paco Nathan is the founder of Derwen, a boutique consultancy focused on Data and AI. This episode is part of our series of monthly roundups and covers: recently released large language models,  Constraint-Driven Innovation, highlights from GTC 2024, and Lessons from the First AI Workload Security Exploit.Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Google • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes can be found on The Data Exchange web site.

Paco Nathan is the founder of Derwen, a boutique consultancy focused on Data and AI. This episode explores recent developments in AI, including text-to-video models like Sora, frameworks for productionizing AI models, analyses of systems like Google's Gemini, techniques to improve foundation models, AMD's software innovations for AI acceleration, and knowledge graph augmentations of language models.Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Google • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes can be found on The Data Exchange web site.

Paco Nathan has a career on bridging innovation and open source project on Data and AI to the real world. This episode will be his honest, no-bs take on the impact of open source in the real world. And of course, we will also talk about Knowledge Graphs and LLMs.

Paco Nathan is the Managing Partner at Derwen, Inc., and author of Latent Space, along with other books, plus popular videos and tutorials about machine learning, natural language, graph technologies, and related topics. MLOps podcast #201 with Paco Nathan, Managing Partner at Derwen, Inc., Language, Graphs, and AI in Industry. // Abstract Let's talk about key findings from these conferences, specifically summarizing teams that have ROI on machine learning in production: what are the things in common they're doing, and what are the most important caveats they urge other teams to consider when getting started? Because these key takeaways aren't found in the current AI news cycle. // MLOps Jobs board https://mlops.pallet.xyz/jobs // MLOps Swag/Merch https://mlops-community.myshopify.com/ // Related Links AI Conference: https://aiconference.com/ K1st World: https://www.k1st.world/ Corunna Innovation Summit: https://corunna.dataspartan.com/ "Cloud Computing on Amazon AWS EC2" UC Berkeley EECS guest lecture (2009) https://vimeo.com/manage/videos/3616394 "Hardware - Software - Process: Data Science in a Post-Moore's Law World" https://www.nvidia.com/en-us/ai-data-science/resources/hardware-software-process-book/ “LLMs in Production: Learning from Experience” by Waleed Kadous @ Anyscale https://www.youtube.com/watch?v=xa7k9MUeIdk "Supercharging Industrial Operations with Problem-Solving GenAI & Domain Knowledge" by Christopher Nguyen @ Aitomatic https://www.k1st.world/2023-program/supercharging-industrial-operations-with-problem-solving-genai-domain-knowledge “The Next Million AI Systems” by Mark Huang @ Gradient: https://www.youtube.com/watch?v=lA0Npe4PqFw "AI in a Box" by Useful Sensors https://usefulsensors.com/#products "Opportunities in AI - 2023" by Andrew Ng https://www.youtube.com/watch?v=5p248yoa3oE "Advancing the Marine Industry Through the Harmony of Fishermen Knowledge and Al" by Akinori Kasai @ Furuno https://www.k1st.world/2023-program/advancing-the-marine-industry-through-the-harmony-of-fishermen-knowledge-and-al Macy conferences (1941-1960) https://en.wikipedia.org/wiki/Macy_conferences https://www.asc-cybernetics.org/foundations/history/MacySummary.htm https://press.uchicago.edu/ucp/books/book/distributed/C/bo23348570.html second-order cybernetics https://pangaro.com/designconversation/wp-content/uploads/dubberly-pangaro-chk-journal-2015.pdf https://en.wikipedia.org/wiki/Second-order_cybernetics Project Cybersyn https://jacobin.com/2015/04/allende-chile-beer-medina-cybersyn/ https://thereader.mitpress.mit.edu/project-cybersyn-chiles-radical-experiment-in-cybernetic-socialism/ https://99percentinvisible.org/episode/project-cybersyn/ https://medium.com/@rjog/project-cybersyn-an-early-attempt-at-iot-governance-and-how-we-can-apply-its-learnings-5164be850413 https://www.sustema.com/post/project-cybersyn-how-a-chilean-government-almost-controlled-the-economy-from-a-control-room https://transform-social.org/en/texts/cybersyn/ Humberto Maturana, Francisco Varela: Autopoeisis "De Maquinas y Seres Vivos" "Everything said is said by an observer" https://proyectos.yura.website/wp-content/uploads/2021/06/de_maquinas_y_seres_vivos_-_maturana.pdf https://en.wikipedia.org/wiki/Autopoiesis_and_Cognition:_The_Realization_of_the_Living Fernando Flores (led Project Cybersyn, imprisoned, later worked with Prof. Terry Winograd @ Stanford, the grad advisor for what became Google) https://lorenabarba.com/gallery/prof-barba-gave-keynote-at-pycon-2016/ https://conversationsforaction.com/fernando-flores "Navigating the Risk Landscape: A Deep Dive into Generative AI" by Ben Lorica and Andrew Burt https://thedataexchange.media/mitigating-generative-ai-risks/ "SpanMarker" by Tom Aarsen @ Hugging Face https://tomaarsen.github.io/SpanMarkerNER/ Examples of "the math catching up with the machine learning": Guy Van den Broeck @ UCLA https://web.cs.ucla.edu/~guyvdb/talks/ Charles Martin @ Calculations Consulting https://weightwatcher.ai/

In this episode, Paco Nathan and I dive into insights from the inaugural AI Conference in San Francisco (video of talks can be found here). Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Google • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes can be found on The Data Exchange web site.

In “Autopoiesis in Systems of People and Machines,” Peter Wang welcomes Paco Nathan. Paco is a Managing Partner at Derwen, Inc., a company that offers enterprise customers full-stack engineering for AI applications at scale, with an emphasis on open-source integrations. Paco forged a career in artificial intelligence when many people were skeptical of it and now boasts over 40 years of computer science experience.   Peter and Paco discuss histories and frameworks that are impacting today's systems of people and machines. Paco touches on corporate law and how long ago, the concept of insurance allowed for the externalization of risk and corresponding enablement of capital ventures. Paco goes on to talk about autopoiesis, the Chilean Project Cybersyn and the significance of groupware, and the core of human intelligence.   Peter and Paco also discuss the increasing complexity of today's world in which less and less is linear, which requires improved cognition for survival, and the cybernetic future. Resources: “A Brief History Of Reinsurance” (David M. Holland) - https://www.soa.org/globalassets/assets/library/newsletters/reinsurance-section-news/2009/february/rsn-2009-iss65-holland.pdf     Santa Clara County v. Southern Pacific Railroad Co., 118 U.S. 394 (1886) - https://supreme.justia.com/cases/federal/us/118/394/     “Law as an Autopoietic System” (Gunther Teubner) - https://cadmus.eui.eu/handle/1814/23894 Autopoiesis and Cognition: The Realization of the Living (Humberto Maturana and Francisco Varela) - https://en.wikipedia.org/wiki/Autopoiesis_and_Cognition:_The_Realization_of_the_Living   Project Cybersyn - https://99percentinvisible.org/episode/project-cybersyn/    “Understanding Computers and Cognition” (Terry Winograd and Fernando Flores) - https://philpapers.org/rec/WINUCA   Macy Conferences - https://en.wikipedia.org/wiki/Macy_conferences   Norbert Wiener - https://en.wikipedia.org/wiki/Norbert_Wiener   “What the Frog's Eye Tells the Frog's Brain” (J.Y. Lettvin et al.) - https://hearingbrain.org/docs/letvin_ieee_1959.pdf   Social Systems - https://www.sup.org/books/title/?id=2225   Niklas Luhmann - https://en.wikipedia.org/wiki/Niklas_Luhmann   Dubberly Design (Paul Pangaro) (When Paco references Donoho Design, he means Dubberly Design.) - http://www.dubberly.com/articles/cybernetics-and-design.html   René Thom - https://en.wikipedia.org/wiki/Ren%C3%A9_Thom   “Corporate Metabolism” (Paco Nathan) - https://www.tripzine.com/listing.php?id=corporate_metabolism   You can find a human-verified transcript of this episode here - https://know.anaconda.com/rs/387-XNW-688/images/ANACON_Paco_Nathan_V1.docx.pdf   If you enjoyed today's show, please leave a 5-star review. For more information, visit Anaconda.com/podcast.

Let's meet Paco Nathan, the player/coach affectionately known as the evil mad scientist. You'll hear how his early career choices have become industry milestones; how he used data whilst serving in the US army; and, which tech game-changers he's worked with.

Paco has more than 40 years of tech industry experience with expertise in data science, natural language, and cloud computing. In this episode, you'll hear how Paco has built up practice as a hands-on manager and loves leading smaller teams and eschews job titles.

I have trouble wrapping any adequate labels around this episode's guest, Paco Nathan. Paco is a technologist, data scientist and an evangelist of a brighter data and technology future. He has an uncommon ability to synthesize the gaps and trends in this complex and evolving space, and gives me hope that we can create a more flourishing future within it.Show Notes:Origins of Artificial Intelligence and mentors (06:00)Humberto Maturana ("What the frog's eye tells the frog's brain")Fernando FloresFrancisco VarelaTerry WinogradCybernetics by Norbert Weiner (06:30)Project Cybersyn (07:00)Autopoiesis and Cognition by Humberto Maturana and Francisco VarelaExpert systems (13:20)Bell Labs (16:30)Hopfield network (16:50)Systems thinking (22:30)What is data science? (22:45)DJ PatilJohn TukeyThe complexities of today's world (29:50)Complexity and emergence (31:00)How Learning Works by Susan Ambrose (32:00)Panama papers (39:00)How to think in graphs daily (41:30)Have a shape in mind, even if you don't have the labels yetAmbiguity aversion (47:40)"Unknown unknowns"Dave Snowden and Cynefin Framework (47:45)Complex areas: no deterministic approach will arrive at a 'right answer'Medium posts: Sense and Scalability and Graph thinking (51:00)derwen.ai (52:30)How he takes notes (58:00)Lightning Round (01:01:00):Book: Ecotopia Emerging by Ernest CallenbachPassion: cookingHeart sing: sustainability and regenerative processes (open science)Screwed up: book storeRecommender systemFind guest online:Twitter: @pacoidWebsite: https://derwen.ai/paco'Five-Cut Fridays' five-song music playlist series  Paco's playlist

In this episode of the Data Exchange, our special correspondent and editor Jenn Webb organized a mini-panel composed of myself and Paco Nathan, author, teacher, and founder of Derwen.ai, a boutique consulting firm specializing in Data, machine learning, and AI.  Of late, Paco has been doing a lot of work with graphs and as such he's had to immerse himself in the world of graph data management technologies. This conversation is focused on what's new with graph databases, and why there's been a resurgence in interest in them. We also discuss use cases of graph databases, graph analytics, and graph neural networks. Subscribe: Apple • Android • Spotify • Stitcher • Google • RSS.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

Data discovery is one of the hardest problems to solve in data management in general and comes up as a major pain point in most data mesh discussions. Tune in to this all-star expert panel recorded in collaboration with the Data Mesh community, and hosted by a previous Open||Source||Data podcast guest, Paco Nathan of Derwen.ai. Paco engages panelists, Shinji Kim (Select Star), Sophie Watson (Red Hat), Mark Grover (Stemma), and Shirshanka Das (Acryl Data) in a 60-minute discussion on not only Data Mesh, but other data strategies and process needs for the data discovery future. See omnystudio.com/listener for privacy information.

Data Science player and coach, Author, and Venture Amplifier Paco Nathan talks with Sam Ramji about Hybrid AI, mathematical reversibility, and using AI to solve knowledge problems that the exponential growth of data will create for years to come. Join these two as they discuss how you can bring multiple data disciplines together using empathy and math. See omnystudio.com/listener for privacy information.

Subscribe: iTunes, Android, Spotify, Stitcher, Google, and RSS.In this episode of the Data Exchange, our special correspondent and editor Jenn Webb organized a mini-panel composed of myself and Paco Nathan, author, teacher, and founder of Derwen.ai, a boutique consulting firm specializing in Data, machine learning (ML), and AI.We began by discussing tools for scaling machine learning. Paco and I have been impressed with the growth in the number of libraries being built on top of Ray as well as the variety of use cases that are being addressed by Ray.We then discussed the upcoming Ray Summit, a FREE virtual conference featuring over 50 talks on machine learning, Python, serverless and cloud native technologies.We also looked back at the first eight months of this podcast (here's an archive of previous episodes).  Both Paco and Jenn were instrumental in getting this podcast started, and I wanted to mark crossing the 30episode threshold with a short retrospective.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

In this episode of The Data Exchange, I speak with Paco Nathan, author, teacher, and founder of Derwen.ai, a boutique consulting firm specializing in Data, ML, and AI. Paco consults with companies and speaks before audiences all over the world, and I plan to have him as a frequent guest on this podcast to draw on his observations of diverse organizations.This particular conversation spanned many topics, including:Data Governance: Paco's talk on the topicAutoML: Paco's talk on the topicPyTorch and TensorFlow: posts we discussed - [1], [2]Reproducibility and feature selectionThe Streamlit open source project for ML app development, and Grus Law (“if you can think up something crazy and/or dangerous to do with notebooks, people are doing it.”)I want this to be more than just a podcast. I want to create a community to help people make better decisions. A key part of this is getting you involved. I have ideas on how this community will grow, but as a first step, I want to ask a question related to one of the topics that Paco and I discussed: PyTorch and TensorFlow. I'd love to have you weigh in by filling out the survey form. I'll report on results and key insights in a future episode of this podcast.[full show notes can be found on the Data Exchange site.]

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

In this episode of the Data Show, I spoke with Jesse Anderson, managing director of the Big Data Institute, and my colleague Paco Nathan, who recently became co-chair of Jupytercon. This conversation grew out of a recent email thread the three of us had on machine learning engineers, a new job role that LinkedIn recently pegged […]

In this special sponsored episode, Chris talks with Paco Nathan about JupyterCon.

This week we talk with Paco Nathan, who runs Learning at O’Reilly Media – producers of Strata + Hadoop and OSCON conferences, along with some of the most notable books on programming and machine learning. Paco also makes his own cider!

Hadoop, Mesos, Cascading, Scalding, Cascalog and Data Science with Paco Nathan