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Intern to Founder | Justin Collins | Breaking Into CyberEpisode SummaryIn this episode, Justin Collins shares his unique journey from a PhD student in Computer Science to becoming a key figure in the application security space. Justin explains how a funding shortage led him to a life-changing internship at AT&T Interactive, where he combined his passion for compiler theory with cybersecurity to create the open-source tool Brakeman. We dive into how he balanced a full-time job while co-founding a startup and the importance of preparation when breaking into a new field.Key Takeaways- Preparation as a Differentiator: Justin secured his first security role simply by researching the specific topics (SQL injection and XSS) the interviewers mentioned beforehand—a step many other candidates neglected.- Applying Niche Skills to Security: Rather than starting from scratch, Justin leveraged his deep knowledge of programming languages and compilers to build a static analysis tool, proving that specialized non-security backgrounds are highly valuable.- The Power of Open Source: Developing and open-sourcing Brakeman during an internship served as a massive career catalyst, eventually leading to a business acquisition.- The "Side-Hustle" Startup Model: Justin highlights that successful startups don't always require VC funding or fancy offices; his company was built while the founders maintained their "real" jobs.- Negotiating Flexibility: Early in his career, Justin successfully negotiated a part-time security role, which allowed him to support his family while simultaneously building his own business.Resources Mentioned- Brakeman: The open-source static analysis security tool for Ruby on Rails created by Justin.- OWASP: Cited as a critical resource for learning about web vulnerabilities like SQL injection and XSS.- Ruby on Rails: The programming framework that served as the foundation for Justin's early work.- Black Duck (formerly Synopsys): The company that eventually acquired Justin's startup.About the GuestJustin Collins is a cybersecurity expert and the creator of Brakeman, a widely used static analysis tool for Ruby on Rails. With an extensive background in Computer Science and programming languages, Justin transitioned from academia to entrepreneurship, co-founding a boutique security firm that was later acquired by Synopsys. He is a specialist in application security and program analysis.Sponsored by CPF Coaching LLC - http://cpf-coaching.comCheck out our books:
Most founders think they have a sales problem. According to Lou Shipley, they usually have a customer understanding problem.Lou is a 3x CEO, Senior Lecturer at Harvard Business School, former CEO of Black Duck Software, and co-author of Unlikely Entrepreneurs.During his time at Black Duck, Lou repositioned the company from open-source compliance to open-source security, quadrupled revenue, and helped lead the company to a $565 million acquisition by Synopsys.In this conversation, we discuss: Why founders should not hand off sales too early The real purpose of your first 100 customer conversations How to know if you're solving a painful enough problem Why competitive markets can be better than new markets The go-to-market framework that helped scale Black Duck How to identify product-market fit before building too much What causes churn and how to spot it before it happens Why most founders misunderstand scaling a sales team The reality of AI and what founders should pay attention to Lessons from six startups, multiple exits, and decades of leadership This is a practical conversation about sales, positioning, product-market fit, scaling teams, and building companies that customers actually want.00:00 Introduction to Lou Shipley and Black Duck Software02:00 The Black Duck acquisition story and repositioning strategy04:30 Why founders should own sales longer than they think09:10 Learning from customers before chasing revenue12:00 Why competitive markets are often better opportunities15:00 The myth of the young founder and why experience matters18:40 Understanding customer pain deeply enough to build a company21:20 Signs you're building a solution nobody truly needs22:45 Building software for yourself vs guessing what customers want25:00 How Lou repositioned Black Duck around security27:30 Managing vs leading as your company scales31:00 Escaping the weeds and thinking like an investor33:10 The sales framework behind Black Duck's growth39:00 Churn, product-market fit, and customer retention43:30 AI, software startups, and what founders should watch51:30 What Lou learned after running multiple companies57:20 The one message every founder needs to hearUnlikely Entrepreneurs: Wins, Losses, and Crucial Lessons on Building Great Companies: https://a.co/d/0fPfhi1D
Every founder who has ever handed sales off too early has paid for it. Every single one.In this episode, John sits down with Lou Shipley, a Harvard Business School lecturer, board member, investor, and author of Unlikely Entrepreneurs, to dig into why sales is still the most misunderstood function in business, and why founders who treat it as a second-class citizen almost always fail. Lou draws from decades of experience running companies, building sales cultures from scratch, and teaching MBAs how to sell before they ever launch a product.From cold-calling encyclopedia buyers to opening Asia for Avid Technology to building the sales curriculum at HBS, Lou has lived every stage of the sales journey, and he's done it at the highest level.If you're a founder, a sales professional, or anyone trying to understand what it actually takes to build a company in the age of AI, this conversation will challenge everything you think you know about selling. Visit www.jbarrows.com and learn how you can Make It Happen.What You'll LearnWhy founders who delegate sales too early almost always failHow Lou built one of Harvard's most in-demand coursesThe cultural disdain of salesWhy sales is not about convincing anyone of anythingHow to use AI as a learning tool instead of an answer machineWhat the Guy Kawasaki GPT experiment revealedWhy curiosity is the most important professional skill in the AI eraWhat SaaS companies should be doing right nowHow to build a farm system for sales talent17 stories that prove anyone can build something worth buyingLou Shipley is a multi-time tech CEO, entrepreneur, and enterprise software leader with over 25 years of experience driving growth and innovation. He has led several successful startups through rapid expansion and acquisition, including Black Duck, WebLine (acquired by Cisco), Reflectent (acquired by Citrix), and VMTurbo. In addition to his executive leadership, Lou serves on multiple boards, teaches technology sales at Harvard Business School, and is a respected mentor, speaker, and commentator in the tech industry.Connect with Lou Shipley:Website: https://www.loushipley.com/LinkedIn: https://www.linkedin.com/in/loushipley/Grab a copy of Lou Shipley's book, “Unlikely Entrepreneurs: Wins, Losses, and Crucial Lessons on Building Great Companies,“ on Amazon: https://www.amazon.com/Unlikely-Entrepreneurs-Lou-Shipley/dp/1394345895/John Barrows is a sales trainer, speaker, and founder of JB Sales with over 25 years of experience in the industry. He has made hundreds of cold calls a week, led startups to acquisition, and trained high-performing teams at companies like Salesforce, LinkedIn, Amazon, and Okta. Through JB Sales, John focuses on practical sales execution—helping reps fill pipeline, close deals, and build trust with buyers in today's AI-driven sales environment.Connect with John Barrows:LinkedIn: https://www.linkedin.com/in/johnbarrows/ Instagram: https://www.instagram.com/johnmbarrows/TikTok: https://www.tiktok.com/@johnmbarrowsCheck out John's Membership: https://go.jbarrows.com/Join John's Newsletter: https://www.jbarrows.com/newsletter
This episode of The UK Flooring Podcast welcomes back Ben from Black Duck Flooring for a proper conversation about training, growth, and what it really takes to build a flooring business that does not rely on you being everywhere at once.Ben shares how Black Duck has grown from humble beginnings, just him, a van, and one young lad, into a much bigger operation with multiple teams out on site at once. But this episode is not just about growth for the sake of it. It is about what helped make that growth possible: investing in training, building better systems, trusting good people, and being willing to learn from others instead of trying to do everything the hard way.A big part of the conversation centres around the first wood floor fitting course run with Cockerill & Co, where installers from different backgrounds got hands-on experience with plank, herringbone, borders, and proper setting out. Ben explains why practical training matters so much, why better skills lead to better jobs and better margins, and why too many people still see asking for help as a weakness when it is often the fastest way to improve.If you fit floors, manage fitters, or want to move into higher value wood floor work, this episode is packed with insight.BOOK THE WOOD FLOOR FITTING TRAINING HERE:https://www.tickettailor.com/events/cockerillco/2150757What You'll Learn in This Episode:Why training gives flooring businesses a faster route to growth, fewer mistakes, and a much better return over time.How Ben has grown Black Duck Flooring from a small operation into a business with multiple teams on site, without the wheels falling off.Why practical, hands-on training matters more than endless theory, especially when it comes to wood floor fitting.What happened on the first wood floor fitting course, including plank installation, herringbone, border work, and setting out.Why learning specialist skills like borders and herringbone can help fitters win better jobs and charge properly for high-end work.How systems, paperwork, trust, and delegation allow a business owner to step away from the tools and still keep standards high.Why so many people hold themselves back by refusing help, and why getting the right support often shortens the journey massively.What Make or Break, Flooring Freedom, and the wider Cockerill & Co training environment can do for confidence, mindset, and long-term progress.Memorable Quote:“Why make loads of mistakes and get things wrong and take five years when you could do it in a year?”Speaker InformationBenBlack Duck FlooringInstagram: https://www.instagram.com/blackduckflooring/Book the Wood Floor Fitting Training:https://www.tickettailor.com/events/cockerillco/2150757Where to Find The UK Flooring Podcast:Website: https://theukflooringpodcast.co.uk/Instagram: https://www.instagram.com/theukflooringpodcast/Facebook: https://www.facebook.com/theukflooringpodcast/Spotify: https://open.spotify.com/show/59DLhGPVKNtVoS656EYtxqApple Podcasts: https://podcasts.apple.com/gb/podcast/the-uk-flooring-podcast/id1606720642 Hosted on Acast. See acast.com/privacy for more information.
RSA Conference 2026 produced hundreds of announcements from San Francisco’s Moscone Center this week. We curated the ones that matter for Canadian IT channel partners into three themes: agentic AI as the new attack surface, identity and hardware resilience, and partner economics. The big theme: agentic AI is the new attack surface The dominant message from RSA 2026 was clear — AI agents are a brand new attack surface, and the security industry arrived with its first wave of answers. Cisco extended its Zero Trust framework to treat AI agents as a new identity type, with visibility, access controls, and real-time monitoring for autonomous agents operating on the network. CrowdStrike launched Next-Gen SIEM support for Microsoft Defender for Endpoint with no Falcon sensor required, plus Shadow AI Discovery and AI Runtime Protection for finding unauthorized AI tools across client environments, and Agentic MDR for managed detection and response at machine speed. Proofpoint unveiled its AI Security platform and Agent Integrity Framework, defining a new standard for governing autonomous AI agents in the enterprise, alongside email and data security updates for the agentic workspace. Black Duck brought Signal to general availability, an agentic application security platform designed to secure AI-generated code in autonomous development workflows. Other notable RSA announcements along the agentic AI theme included Arctic Wolf’s Aurora Agentic SOC, Darktrace’s managed email security offering for MSSPs, and Huntress expanding ITDR coverage to Google Workspace while surpassing 10 million Microsoft 365 identities protected. Identity and resilience RSA launched ID Plus Sovereign Deployment, fully air-gapped, on-premises identity security for environments where cloud isn’t an option — directly relevant for Canadian organizations navigating data sovereignty requirements. RSA also announced an expanded partnership with Microsoft around M365 E7 and passwordless authentication, going deep on cloud integration at the same time as the sovereign deployment — both directions simultaneously. Dell Technologies expanded cybersecurity and resilience for the AI era and emerging quantum risks, including quantum-ready commercial PCs with post-quantum cryptography at the firmware level, AI-powered ransomware recovery for PowerProtect, and MDR extended to AI data platforms. HP launched TPM Guard from their Imagine event in New York, a hardware-enforced security feature protecting TPM-to-CPU communications from physical attacks — a similar hardware-level security play announced the same week. And here’s what you can sell Barracuda advanced the BarracudaONE cybersecurity platform alongside updates to the Partner Success Program, investing in both platform and partner program at the same time. Sectigo introduced an industry-first multi-tenant partner platform for certificate lifecycle management as a managed service, designed to help MSPs turn the shift to shorter certificate lifespans — now 200 days and eventually shrinking to 47 days by 2029 — into a scalable, recurring revenue stream. Further reading SecurityWeek’s RSAC 2026 Day 1 announcements summary SecurityWeek’s RSAC 2026 Day 2 announcements summary CRN: 10 hot new cybersecurity tools announced at RSAC 2026 Read Full Transcript Hello and welcome to a special midweek edition of In Case You Missed It from ChannelBuzz.ca. I’m Robert Dutt, and this week, RSA Conference 2026 took over San Francisco’s Moscone Center. Hundreds of announcements, dozens of press releases, and a whole lot of noise. So we went through the pile and pulled out what we think actually matters for Canadian IT channel partners. Let’s get into it. If there was one defining message from RSA this year, it’s this: the AI agents your clients are starting to deploy? They’re not just productivity tools. They’re a brand new attack surface, and the security industry just showed up with the first wave of answers. Cisco made the biggest splash, extending their Zero Trust framework to treat AI agents as a new identity type. Their pitch: if an AI agent can browse, query, and act on behalf of a user, it needs the same visibility, access controls, and real-time monitoring as any human on the network. CrowdStrike came in heavy across multiple days. Their Next-Gen SIEM now ingests Microsoft Defender for Endpoint telemetry with no Falcon sensor required — which is a big deal for MSPs managing mixed Microsoft environments. They also launched Shadow AI Discovery, which finds unauthorized AI applications running across client environments. If you’ve ever had to track down rogue SaaS subscriptions, imagine that problem, but with AI tools that can actually take actions on behalf of employees. CrowdStrike also introduced Agentic MDR — managed detection and response that operates at machine speed against AI-driven threats. Proofpoint went after the same problem from the email and collaboration side, launching their AI Security platform and Agent Integrity Framework. Their angle: securing the “agentic workspace” where humans and AI agents are operating side by side across email, cloud, and collaboration tools like Teams and Slack. And Black Duck brought their Signal platform to general availability — agentic application security designed specifically for AI-generated code. When your developers are using AI to write code, who’s checking the AI’s work? That’s the gap Signal is designed to close. They weren’t alone. Arctic Wolf launched what they’re calling the world’s largest commercial agentic SOC. Darktrace rolled out a managed email security offering for MSSPs. Huntress expanded their identity threat detection to Google Workspace. The message from the industry was unanimous: agentic AI security is not a future problem. It’s a right-now problem. If you’re advising clients on AI adoption, the security conversation just got significantly more complex. And that complexity is an opportunity — because your clients are going to need help navigating it. RSA — the company, at their own conference — made two announcements that pulled in opposite directions, and that was the point. They launched ID Plus Sovereign Deployment — fully air-gapped, on-premises identity security for environments where cloud is not an option. Think regulated industries, government, anyone with serious data sovereignty requirements. For Canadian partners dealing with OSFI E-21 or federal procurement, that’s directly relevant. At the same time, they announced an expanded Microsoft partnership around M365 E7 and passwordless authentication. So RSA is going both directions: as sovereign as you need on one end, as deeply cloud-integrated as you need on the other. On the hardware side, Dell announced quantum-ready commercial PCs with post-quantum cryptography built into the firmware, AI-powered ransomware recovery for their PowerProtect line, and an extension of their managed detection and response service to cover AI data platforms like PowerScale. HP made a similar hardware security move from their own event in New York this week, launching TPM Guard to protect TPM-to-CPU communications from physical attacks. The common thread: the security conversation is moving below the operating system and into the silicon. Two announcements that translate directly to partner economics. Barracuda — a hundred percent channel company — advanced their BarracudaONE cybersecurity platform alongside updates to their Partner Success Program. Platform investment and partner investment at the same time. That’s the kind of announcement that tells you a vendor is serious about the relationship, not just the product. And Sectigo launched a new partner platform built around the reality that SSL certificate lifespans that are already shrinking and headed to 47 days. When certificates need to be renewed every 47 days instead of every year, that’s either a massive headache or a recurring revenue opportunity. Sectigo is betting that partners who automate the process will turn a compliance burden into a managed service. That’s RSA Conference 2026 through the Canadian channel lens. Agentic AI security dominated the conversation. Identity and hardware resilience matured. And a couple of vendors made moves that directly affect your bottom line. Links and details for everything we covered are in the show notes. We’ll be back on Monday with the regular edition of ICYMI. Until then, I’m Robert Dutt for ChannelBuzz.ca, and I’ll see you in the channel.
Derek Champagne talks with Lou Shipley, author of Unlikely Entrepreneurs.Lou brings more than three decades of experience in enterprise software as an executive, entrepreneur, and sales leader. Previously, Shipley was President and CEO of Black Duck Software, where he repositioned the leader in open source license and compliance software into an open source security company which led it to a successful acquisition by Synopsys. Prior to Black Duck, Shipley served as President and CEO of Turbonomic (acquired by IBM), and Reflectent Software (acquired by Citrix Systems). Shipley serves on the boards of Wasabi, Fairmarkit and CustomerGauge. He serves on the advisory boards of Exodigo, Teamworks, RapidSOS, SpoilerAlert, Tomorrow..io and Logz.io.Shipley holds a degree in Economics from Trinity College-Hartford (where he also a Trustee), and an MBA from Harvard Business School. He is currently a senior lecturer at Harvard Business School where he teaches four separate classes in Entrepreneurial Sales and go to market strategy. In Unlikely Entrepreneurs: Wins, Losses and Crucial Advice in Building Great Companies, the authors―who hail from Harvard Business School and MIT Sloan School of Management―combine expert insights, elements of the case study method, and an engaging story-telling style to take a deep dive into the key challenges that founders face. They set the stage for each profile-―including those of entrepreneurs helming billion dollar companies to mom-and-pop businesses―whose colorful, unlikely stories showcase entrepreneurial best practices that readers can adopt to succeed. Order Unlikely EntrepreneursBusiness Leadership Series Intro and Outro music provided by Just Off Turner: https://music.apple.com/za/album/the-long-walk-back/268386576
Derek Champagne talks with Lou Shipley, author of Unlikely Entrepreneurs.Lou brings more than three decades of experience in enterprise software as an executive, entrepreneur, and sales leader. Previously, Shipley was President and CEO of Black Duck Software, where he repositioned the leader in open source license and compliance software into an open source security company which led it to a successful acquisition by Synopsys. Prior to Black Duck, Shipley served as President and CEO of Turbonomic (acquired by IBM), and Reflectent Software (acquired by Citrix Systems). Shipley serves on the boards of Wasabi, Fairmarkit and CustomerGauge. He serves on the advisory boards of Exodigo, Teamworks, RapidSOS, SpoilerAlert, Tomorrow..io and Logz.io.Shipley holds a degree in Economics from Trinity College-Hartford (where he also a Trustee), and an MBA from Harvard Business School. He is currently a senior lecturer at Harvard Business School where he teaches four separate classes in Entrepreneurial Sales and go to market strategy. In Unlikely Entrepreneurs: Wins, Losses and Crucial Advice in Building Great Companies, the authors―who hail from Harvard Business School and MIT Sloan School of Management―combine expert insights, elements of the case study method, and an engaging story-telling style to take a deep dive into the key challenges that founders face. They set the stage for each profile-―including those of entrepreneurs helming billion dollar companies to mom-and-pop businesses―whose colorful, unlikely stories showcase entrepreneurial best practices that readers can adopt to succeed. Order Unlikely Entrepreneurs Business Leadership Series Intro and Outro music provided by Just Off Turner: https://music.apple.com/za/album/the-long-walk-back/268386576
From its eyebrow to its shimmering wing panel, there is lots to learn about the Pacific Black Duck. Scientist and conservationist Jason Graham does a deep-dive (pun intended) into this impressive bird and provides insights into a large conservation story unfolding in Tasmania.
This week we're joined by serious waterfowler Chris Paradise and Brendan Shirkey, a research biologist, hunter, and punter with the Winous Point Marsh Conservancy, believed to be the oldest duck hunting club in North America. The Black Duck is a favorite among waterfowlers, yet many hunters feel they don't see the numbers they once did. We dive into this secretive species, discussing its habitat preferences, breeding range, behavior, how to hunt it, and whether its population is truly in decline. It's an informative and engaging conversation. Listen, learn, and enjoy.Send a text message to the show! Support the showStay connected with GameKeepers: Instagram: @mossyoakgamekeepers Facebook: @GameKeepers Twitter: @MOGameKeepers YouTube: @MossyOakGameKeepers Website: https://mossyoakgamekeeper.com/ Enter The Gamekeeper Giveaway: https://bit.ly/GK_Giveaway Subscribe to Gamekeepers Magazine: https://bit.ly/GK_Magazine Buy a Single Issue of Gamekeepers Magazine: https://bit.ly/GK_Single_Issue Join our Newsletters: Field Notes - https://bit.ly/GKField_Notes | The Branch - https://bit.ly/the_branch Have a question for us or a podcast idea? Email us at gamekeepers@mossyoak.com
This week on The Maggie Williams Podcast, our host, Maggie Williams, sits down with Andrew Ewing and Zach Olson, the duo behind Migration Destination Outfitters, after three incredible days of hunting on Long Island with Migration Destination and Beau and Lexie Brooks!After getting Kate to pick up her first black ducks, we sit down and discuss what it really takes to run a successful waterfowl operation on the edge of the Atlantic. From early struggles to unforgettable guided hunts, to the time Zach put his entire life on the line to save the business, this episode pulls back the curtain on a side of duck hunting most people never see.Find our host Maggie at:TikTok: https://www.tiktok.com/@themaggiewilliams?lang=enInstagram: https://www.instagram.com/themaggiewilliams/Facebook: https://www.facebook.com/themaggiewilliamspodcast/YouTube: https://www.youtube.com/channel/UCnJHqUBdfgnFLc3P87r88VwFind Migration Destination Outfitters Here:Instagram: https://www.instagram.com/migrationdestinationoutfitters/YouTube: https://www.youtube.com/@migrationdestinationoutfittersFacebook: https://www.facebook.com/p/Migration-Destination-Outfitters-100089916227032/Website: https://www.migrationdestinationoutfitters.com/duck-hunts
In this episode, Seth and Ken debate OpenAI's Atlas browser, which embeds AI into web browsing. Ken views it as a major privacy concern, potentially accelerating invasive data collection and surveillance. Seth noted that new browsers historically have critical flaws. They acknowledged that AI is very useful for generic and technical internet searches. They discussed the Co-Fish attack, a phishing vulnerability in Microsoft Copilot Studio that could exfiltrate access tokens via a seemingly valid Microsoft URL. Finally, they noted that big companies like Snyk and Black Duck are moving toward agentic AI capabilities, confirming the industry trend.
From rugged Atlantic marshes to southern wintering grounds, Ted Barney lays out the story of the American black duck—where they go, how they survive, and why they matter. A long-time Canadian Wildlife Services biologist, Barney uses hard data, field insights, and decades of banding to reveal what separates black ducks from the rest. Habitat battles, breeding and wintering distributions, migrational trends, mallard competition and hybridization, habitat, and the realities of managing a truly iconic waterfowl species. Visit the Legendary Brands That Make MOJO's Duck Season Somewhere Podcast Possible: MOJO Outdoors Alberta Professional Outfitters Society Benelli Shotguns BOSS Shotshells Bow and Arrow Outdoors Ducks Unlimited Flash Back Decoys GetDucks.com HuntProof Premium Waterfowl App Inukshuk Professional Dog Food onX Maps Use code GetDucks25 Sitka Gear Tom Beckbe USHuntList.com Voormi Like what you heard? Let us know! • Tap Subscribe so you never miss an episode. • Drop a rating—it's like a high-five in the duck blind. • Leave a quick comment: What hit home? What made you laugh? What hunt did it remind you of? • Share this episode with a buddy who lives for duck season. Want to partner? Have or know a story to share? Contact: Ramsey Russell ramsey@getducks.com
duckDNA recently concluded its second season, which brought continued enthusiasm from hunters and several never-before-seen hybrids! On this episode, Dr. Mike Brasher is joined by conservation science assistants, Kayci Messerly and Katie Tucker, and Dr. Phil Lavretsky to share initial results from season 2 while discussing genetic mysteries uncovered through the analysis of several unique hybrid ducks. Also discussed are behind-the-scenes interactions with participating hunters and the potential future of duckDNA. Thanks to hunters for their support and participation and a special thanks to our year 2 funding partners -- Pinola Conservancy, Rice Pond Preserve, and Brian Hornung.Listen now: www.ducks.org/DUPodcastSend feedback: DUPodcast@ducks.org
In this episode of the Ducks Unlimited podcast, host Katie Burke sits down with decoy carver George Strunk in his workshop in Glendora, New Jersey. George shares his journey into the outdoors, revealing his passion for hunting predates his love for crafting decoys. Growing up in a family that embraced the outdoors, George recounts childhood memories spent at a hunting and fishing cabin built by his parents in the early 1950s, near the Dennisville Wildlife Refuge. As the oldest sibling, he and his brother enjoyed exploring the woods and hunting from a young age, starting with rabbit hunting. Join Katie and George as they dive into the world of hunting and the art of decoy carving, celebrating the rich traditions of outdoor life.Listen now: www.ducks.org/DUPodcastSend feedback: DUPodcast@ducks.org
"Future Thoughts Ft. Spaceface" by Brothers Griin from Joy City; "Docudrama" by Nyx Nott from Themes From; "DISinformation Desk" by The Black Dog from Music for Real Airports; "The Yips" by James Ellis Ford from The Hum. Courtesy of Warp; The single "Vento a Favor" by Sessa. Courtesy of Mexican Summer; "Cascade" by Niecy Blues from Exit Simulation. Courtesy of Kranky; "Sacred and Profane" by Moundabout from An Cnoc Mor. Courtesy of Rocket Recordings; "Reel Life (Evolution 2)" by Cinematic Orchestra from Man with a Movie Camera. Courtesy of Ninja Tune; "Theme from a Personal Prison" by Emil Amos from Zone Black. Courtesy of Drag City; "Delivery" by Black Duck from the self titled album. Courtesy of Thrill Jockey; "Visiting" by Craig Leon from Anthology of Interplanetary Folk Music Vol. 1. Courtesy of RVNG Intl; "Sunset Theater" by Golden Hallway Music from Rules and Chance Vol 3. Courtesy of Not Not Fun; The Actress remix of Carmen Villain from Smalltown Supersound Remix Anthology Vol. 1-4 2002-2022.
Reed Smith partners Howard Womersley Smith and Bryan Tan with AI Verify community manager Harish Pillay discuss why transparency and explain-ability in AI solutions are essential, especially for clients who will not accept a “black box” explanation. Subscribers to AI models claiming to be “open source” may be disappointed to learn the model had proprietary material mixed in, which might cause issues. The session describes a growing effort to learn how to track and understand the inputs used in AI systems training. ----more---- Transcript: Intro: Hello and welcome to Tech Law Talks, a podcast brought to you by Reed Smith's Emerging Technologies Group. In each episode of this podcast, we will discuss cutting-edge issues on technology, data, and the law. We will provide practical observations on a wide variety of technology and data topics to give you quick and actionable tips to address the issues you are dealing with every day. Bryan: Welcome to Tech Law Talks and our new series on artificial intelligence. Over the coming months, we'll explore the key challenges and opportunities within the rapidly evolving AI landscape. My name is Bryan Tan and I'm a partner at Reed Smith Singapore. Today we will focus on AI and open source software. Howard: My name is Howard Womersley Smith. I'm a partner in the Emerging Technologies team of Reed Smith in London and New York. And I'm very pleased to be in this podcast today with Bryan and Harish. Bryan: Great. And so today we have with us Mr. Harish Pillay. And before we start, I'm going to just ask Harish to tell us a little bit, well, not really a little bit, because he's done a lot about himself and how he got here. Harish: Well, thanks, Bryan. Thanks, Howard. My name is Harish Pillay. I'm based here in Singapore, and I've been in the tech space for over 30 years. And I did a lot of things primarily in the open source world, both open source software, as well as in the hardware design and so on. So I've covered the spectrum. When I was way back in the graduate school, I did things in AI and chip design. That was in the late 1980s. And there was not much from an AI point of view that I could do then. It was the second winter for AI. But in the last few years, there was the resurgence in AI and the technologies and the opportunities that can happen with the newer ways of doing things with AI make a lot more sense. So now I'm part of an organization here in Singapore known as AI Verify Foundation. It is a non-profit open-source software foundation that was set up about a year ago to provide tools, software testing tools, to test AI solutions that people may be creating to understand whether those tools are fair, are unbiased, are transparent. There's about 11 criteria it tests against. So both traditional AI types of solutions as well as generative AI solutions. So these are the two open source projects that are globally available for anyone to participate in. So that's currently what I'm doing. Bryan: Wow, that's really fascinating. Would you say, Harish, that kind of your experience over the, I guess, the three decades with the open source movement, with the whole Linux user groups, has that kind of culminated in this place where now there's an opportunity to kind of shape the development of AI in an open-source context? Harish: I think we need to put some parameters around it as well. The AI that we talk about today could never have happened if it's not for open-source tools. That is plain and simple. So things like TensorFlow and all the tooling that goes around in trying to do the model building and so on and so forth could not have happened without open source tools and libraries, a Python library and a whole slew of other tools. If these were all dependent on non-open source solutions, we will still be talking about one fine day something is going to happen. So it's a given that that's the baseline. Now, what we need to do is to get this to the next level of understanding as to what does it mean when you say it's open source and artificial intelligence or open source AI, for that matter. Because now we have a different problem that we are trying to grapple with. The problem we're trying to grapple with is the definition of what is open-source AI. We understand open-source from a software point of view, from a hardware point of view. We understand that I have access to the code, I have access to the chip designs, and so on and so forth. No questions there. It's very clear to understand. But when you talk about generative AI as a specific instance of open-source AI, I can have access to the models. I can have access to the weights. I can do those kinds of stuff. But what was it that made those models become the models? Where were the data from? What's the data? What's the provenance of the data? Are these data openly available? Or are they hidden away somewhere? Understandably, we have a huge problem because in order to train the kind of models we're training today, it takes a significant amount of data and computing power to train the models. The average software developer does not have the resources to do that, like what we could do with a Linux environment or Apache or Firefox or anything like that. So there is this problem. So the question still comes back to is, what is open source AI? So the open source initiative, OSI, is now in the process of formulating what does it mean to have open source AI. The challenge we find today is that because of the success of open source in every sector of the industry, you find a lot of organizations now bending around and throwing around the label, our stuff is open source, our stuff is open source, when it is not. And they are conveniently using it as a means to gain attention and so on. No one is going to come and say, hey, do you have a proprietary tool? Adding that ship has sailed. It's not going to happen anymore. But the moment you say, oh, we have an open source fancy tool, oh, everybody wants to come and talk to you. But the way they craft that open source message is actually quite sadly disingenuous because they are putting restrictions on what you can actually do. It is contrary completely to what the open-source licensing says in open-source initiative. I'll pause there for a while because I threw a lot of stuff at you. Bryan: No, no, no. That's a lot to unpack here, right? And there's a term I learned last week, and it's called AI washing. And that's where people try to bandy the terms, throw it together. It ends up representing something it's not. But that's fascinating. I think you talked a little bit about being able to see what's behind the AI. And I think that's kind of part of those 11 criteria that you talked about. I think auditability, transparency would be kind of one of those things. I think we're beginning to go into some of the challenges, kind of pitfalls that we need to look out for. But I'm going to just put a pause on that and I'm going to ask Howard to jump in with some questions on his phone. I think he's got some interesting questions for you also. Howard: Yeah, thank you, Bryan. So, Harris, you spoke about the open source initiative, which we're very familiar with, and particularly the kind of guardrails that they're putting around what open source should be applied to AI systems. You've got a separate foundation. What's your view on where open source should feature in AI systems? Harish: It's exactly the same as what OSI says. We are making no difference because the moment you make a distinction, then you bifurcate or you completely fragment the entire industry. You need to have a single perspective and a perspective that everybody buys into. It is a hard sell currently because not everybody agrees to the various components inside there, but there is good reasoning for some of the challenges. But at the same time, if that conversation doesn't happen, we have a problem. But from AI Verify Foundation perspective, it is our code that we make. Our code, interestingly, it's not an AI tool. It is a testing tool. It is written purely to test AI solutions. And it's on an Apache license. This is a no-brainer type of licensing perspective. It's not an AI solution in and of itself. It's just taking an input, run through the test, and spit out an output, and Mr. Developer, take that and do what you want with it. Howard: Yeah, thank you for that. And what about your view on open source training data? I mean, that is really a bone of contention. Harish: That is really where the problem comes in because I think we do have some open source trading data, like the Common Crawl data and a whole slew of different components there. So as long as you stick to those that have been publicly available and you then train your models based on that, or you take models that were trained based on that, I think we don't have any contention or any issue at the end of the day. You do whatever you want with it. The challenge happens when you mix the trading data, whether it was originally Common Crawl or any of the, you know, creative license content, and you mix it with non-licensed or licensed under proprietary stuff with no permission, and you mix it up, then we have a problem. And this is actually an issue that we have to collectively come to an agreement as to how to handle it. Now, should it be done on a two-tier basis? Should it be done with different nuances behind it? This is still a discussion that is ongoing, constantly ongoing. And OSI is taking the mother load of the weight to make this happen. And it's not an easy conversation to have because there's many perspectives. Bryan: Yeah, thank you, for that. So, Harish, just coming back to some of the other challenges that we see, what kind of challenges do you foresee the continued development of open source with AI we'll see in the near future you've already said we've encountered some of them some of the the problems are really kind of in the sense a man-made because we're a lot of us rushing into it what kind of challenges do you see coming up the road soon. Harish: I think the, part of the the challenge you know it's an ongoing thing part of the challenge is not enough people understand this black box called the foundational model. They don't know how that thing actually works. Now, there is a lot of effort that is going into that space. Now, this is a man-made artifact. This piece of software that you put in something and you get something out or get this model to go and look at a bunch of files and then fine-tune against those files. And then you query the model, and then you get your answer back, a rag for that matter. It is a great way of doing it. Now, the challenge, again, goes back to because people are finding it hard to understand, how does this black box do what it does? Now, let's step back and say, okay, has physics and chemistry and anything in science solved some of these problems before? We do have some solutions that we think that make sense to look at. One of them is known as, well, it's called Computational Fluid Dynamics, CFD. CFD is used, for example, if you want to do a fluid analysis or flow analysis over the wing of an aircraft to see where the turbulences are. This is all well understood, mathematically sound. You can model it. You can do all kinds of stuff with it. You can do the same thing with cloud formation. You can do the same thing with water flow and laminar flow and so on and so forth. There's a lot of work that's already been done over decades. So the thinking now is, can we now take those same ideas that has been around for a long time and we have understood them and try and see if we can apply this into what happens in a foundational model. And one of the ideas that's being worked on is something called PINN, which stands for Physics Informed Neural Networks. So using physics, standard physics, to figure out how does this model actually work. Now, once you have those things working, then it becomes a lot more clearer. And I would hazard a guess that within the next 18 to 24 months, we'll have a far clearer understanding of what is it inside that black box that we call the foundational model. With all these known ways of solving problems that, you know, who knew we could figure out how water flows or how, who knew we could figure out how, you know, the air turbulence happens over a wing of a plane. We figured it out. We have the math behind it. So that's where I feel that we are solving some of these problems step by step. Bryan: And look, I take your point that we all need to try to understand this. And I think you're right. That is the biggest challenge that we all face. Again, when it's all coming thick and fast at you, that becomes a bigger challenge. Before I kind of go into my last question, Howard, any further questions for Harish? Howard: I think what Harish just came up with in terms of the explanation of how the models actually operate is really the killer question that everybody is poised with the work the type of work that I do is on the procurement of technology for financial sector clients and when they want to understand when procuring AI what the model does it they often receive the answer that it is a black box and not explainable which kind of defies the logic of what their experience is in terms of deterministic software you know if this then that you know ] find it very difficult to get their head around the answer being a black box box methodology and often ask you know what why can't you just reverse engineer the logic and plot a point back from the answer as a breadcrumb trail to the input? Have you got any views on that sort of question from our clients? Harish: Yeah, there's plenty of opportunities to do that kind of work. Not necessarily going back from a breadcrumb perspective, but using the example of the PINN, Physics Informed Neuro Networks. Not all of them can explain stuff today. We have to, no one, an organization and a CIO who is worth their weight in gold should ever agree to an AI solution that they cannot explain. If they cannot explain, you are asking for trouble. So that is a starting point. So don't go down the path just because your neighbor is doing that. That is being very silly from my perspective. So if we want to solve this problem, we have to collectively figure out what to do. So I give you another example of an organization called KWAAI.ai. They are a nonprofit based in California, and they are trying to build a personal AI solution. And it's all open source, 100%. And they are trying really, really hard to explain how is it that these things work. And so this is an open source project that people can participate in if they choose to and understand more and at some point some of these things will become available as model for any other solution to be tested against so so and then let me then come back to what the verify foundation does we have two sets of tools that we have created one is to create One is called AI Verified Toolkit. What it does is if you have your application you're developing that you claim is an AI solution, great. Now, what I want you to do is, Mr. Developer, put this as part of your tool chain, your CICD cycle. When you do that, what happens, you change some stuff in your code. Then you run this through this toolkit, and the toolkit will spit out a bunch of reports. Now, in the report, it will tell you whether it is biased, unbiased, is it fair, unfair, is it transparent, a whole bunch of things it spits out. Then you, Mr. Developer, make a call and say, oh, is that right or is that wrong? If it's wrong, we'll fix it before you actually deploy it. And so this is a cycle that has to go continuously. That is for traditional AI stuff. Now, you take the same idea in the traditional AI and you look at generative AI. So there's another project called Moonshot. That's the name of the project called Moonshot. It allows you to test large language models of your choosing with some inputs and what outputs come up with the models that you are testing against. Again, you do the same process. The important thing for people to understand and developers to understand, and especially businesses to understand is, as you rightly pointed out, Howard, the challenge we have, this is not deterministic outputs. These are all probabilistic outputs. So if I were to query a large language model, like AAM in London, by the time I ask the question at 10 a.m. in Singapore, it may give me a completely different answer. With the same prompt, exactly the same model, a different answer. Now, is the answer acceptable within your band of acceptance? If it is not acceptable, then you have a problem. That is one understanding. The other part of that understanding is, it suggests to me that I have to continuously test my output every single time for every single output throughout the life of the production of the system because it is probabilistic. And that's a problem. That's not easy. Howard: Great. Thank you, Harish. Very well explained. But it's good to hear that people are trying to address the problem and we're not just living in an inexplicable world. Harish: There's a lot of effort underway. There's a significant amount. MLCommons is another group of people. It's another open source project out of Europe who's doing that. AI Verified Foundation, that's what we are doing. We're working with them as well. And there's many other open source projects that are trying to address this real problem. Yeah so one of the outcomes hopefully that you know makes a lot of sense is at some point in time the tools that we have created maybe be multiple tools can be then used by some entity who is a certification authority so to speak takes the tool and says hey Mr. company a company b, we can test your ai solutions against these tools and once it is done you pass we give you a rubber stamp and say you have tested against it so that raises the confidence level from a consumer's perspective, oh, this organization has tested their tools against this toolkit and as more people start using it, the awareness of the tools being available becomes greater and greater. Then people can ask the question, oh, don't just provide me a solution to do X. Was this tested against this particular set of tools, a testing framework? If it's not, why not? That kind of stuff. Howard: And that reminds me of the Black Duck software that tests for the prevalence of open source in traditional software. Harish: Yeah, yeah. In some sense, that is a corollary to it, but it's slightly different. And the thing is, it is about how one is able to make sure that you... I mean, it's just like ISO 9000 certification. I can set up the standards. If I'm the standards entity, I cannot go and certify somebody else against my own standards. So somebody else must do it, right? Otherwise, it doesn't make sense. So likewise, from AI Verify Foundation perspective, we have created all these tools. Hopefully this becomes accepted as a standard and somebody else takes it and then goes and certifies people or whatever else that needs to be done from that point. Howard: Yeah and and we we do see standards a lot you know in the form of iso standards recovering almost like software development and cyber security again that also makes me think about certification which we're is seeing appear in European regulation. We saw it in the GDPR, but it never came into production as something that you certify your compliance with the GDPR. We have now seen it appear in the EU AI Act. And because of our experience of not seeing it appear in the GDPR, we're all questioning, you know, whether it will come to fruition in the AI Act or whether we have learned about the advantages of certification, and it will be focused on when the AI Act comes into force on the 1st of August. I think we have many years to understand the impact of the AI Act before certification will start to even make a small appearance. Harish: It's one thing to have legislative or regulated aspects of behavior. It's another one when you voluntarily do it on the basis of this makes sense. Because then there is less of hindrance or less of resistance to do it. It's just like ISO 9000, right? No one legislates it, but people still do it. Organizations still do it because it's their, oh yeah, we are an ISO 9035 organization, And so we have quality processes in place and so on and so forth, which is good for those that is important. That becomes a selling point. So likewise, I would love to see something that right now, ISO 42001, which is all the series of AI-related standards. I don't think any one of them has got anything that can be right now be certified yet. Doesn't mean it will never happen. So that could be another one, right? So again, the tools that AI Verified Foundation creates and Mel Korman creates and everybody feeds into it. Hopefully that makes sense. I'd rather see a voluntary take-up rather than a mandated regulatory one because things change. And it's much harder to change the rules than to do anything else. Howard: Well, I think that's a question in itself, but probably it will take us way over our time whether the market forces us to drive standardization. And we could probably have our own session on that, but it's a fascinating subject. Thank you, Harish. Bryan: Exactly I think standards and certifications are possibly the kind of the next thing to look out for for AI you know Harish you could be correct. But on that note last question from me Harish so, interestingly the term you use moonshot right and so personally for you what kind of moonshot wish would you have for open source and AI. Leave aside resources, yeah if you could choose what kind of development would you think would be the one that you would look out for, the one that excites you? Harish: I would rather that, for me, we need to go all the way back to the start from an AI training perspective, right? So the data. We have to start from the data, the provenance of the data. We need to make sure that that data is actually okay to be used. Now, instead of everybody going and doing their own thing, Can we have a pool where, you know, I tap into the resources and then I create my models based on the pool of well-known, well-identified data to train on. Then at least the outcome from that arrangement is we know the provenance of the data. We know how it was trained. We can see the model. model, and hopefully in that process, we also begin to understand how the model actually works with whichever physics related understanding that we can throw at it. And then people can start benefiting and using it in a coherent manner. Instead of what we have today, I mean, in a way, what we have today is called a Cambrian explosion, right? There are a billion experiments happening right now. And majority, 99.9% of it will fail at some point. And 0.1% needs to succeed. And I think we are getting to that point where there's a lot more failures happening rather than successes. And so my sense is that we need to have data that we can prove that it's okay to get and okay to use, and it is being replenished as and when needed. And then you go through the cycle. That's really my, you know, Mojoc perspective. Bryan: I think there's really a lot for us to unpack, to think about, but I think it's really been an interesting discussion from my perspective. I'm sure, Howard, you think the same. And I think with this, I want to thank you for coming online and joining us this afternoon in Singapore, this morning in Europe on this discussion. I think it's been really interesting from a perspective of somebody who's been in technology and interesting for the ReadSmith clients who are looking at this from a legal and technology perspective. And I just wanted to thank you for this. And I also wanted to thank the people who are tuning into this. Thank you for joining us on this podcast. Stay tuned to the other podcasts that the firm will be producing, and I do have a good day. Harish: Thank you. Howard: Thank you very much. Outro: Tech Law Talks is a Reed Smith production. Our producers are Ali McCardell and Shannon Ryan. For more information about Reed Smith's Emerging Technologies practice, please email techlawtalks@reedsmith.com. You can find our podcasts on Spotify, Apple Podcasts, Google Podcasts, reedsmith.com, and our social media accounts. Disclaimer: This podcast is provided for educational purposes. It does not constitute legal advice and is not intended to establish an attorney-client relationship, nor is it intended to suggest or establish standards of care applicable to particular lawyers in any given situation. Prior results do not guarantee a similar outcome. Any views, opinions, or comments made by any external guest speaker are not to be attributed to Reed Smith LLP or its individual lawyers. All rights reserved. Transcript is auto-generated.
With duckDNA season 1 now in the books, DU teams up with Ramsey Russell of It's Duck Season Somewhere and Dr. Phil Lavretsky to review early scientific insights, odd ducks, and the overall excitement around the project. Co-hosts Dr. Mike Brasher and Dr. Jerad Henson visit with Ramsey and Phil compare notes on their experiences and take a deep dive into some of the results, including an examination of several unique hybrids. Also discussed are the status of season 2, important changes coming your way, and a reminder of how you can participate. Follow the project this season on Instagram at @theduckDNA, and apply to participate at www.duckDNA.com.www.ducks.org/DUPodcast
10 years ago this June, Matt Stanton figured it was time to take his motorcycle out for a ride. His dad was staying in Black Duck near Bemidji, and Stanton decided to avoid the interstates and take back roads from Minneapolis on his bike to join them for a few days of camping and fishing. He was having a great ride up until he was right outside of Cromwell, when his motorcycle broke down. Stanton coasted in front of the only driveway for miles. And the man who owned that house, couldn't have been the more perfect stranger to help him out.
On this episode of the Ducks Unlimited podcast, host Katie Burke chats with Bruce Lowe, a collector of Louisiana and teal decoys. They delve into Bruce's introduction to hunting and the outdoors, sharing how he got started waterfowl hunting. Bruce also shares how he got into collection and why both Louisiana and teal decoys are important to him. Tune in to her more about Bruce's passion for the outdoors and vintage decoys.www.ducks.org/DUPodcast
Host Chris Jennings and Dr. Mike Brasher sit down and discuss the hot topics of discussion for duck and goose hunters this spring. It may be turkey season, but avid duck and goose hunters still want to talk about waterfowl. Brasher provides an in-depth overview of avian flu, Season in Review document, habitat conditions, and a few other bits of must-know information.www.ducks.org/DUPodcast
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Thank you so much for listening to the Podcast! *Sorry guys! I forgot to do an example with "The Three..." So here you go: The three stars - النجوم الثلاثة The three wives - الزوجات الثلاث Join our Academy at Arabic Unlocked! (currently 10% for Humanitarian aid in Gaza) https://samburr--arabicunlocked.thrivecart.com/offer/ Website: https://www.sammartinburr.com/ _________________________________ Arabic Unlocked:
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"Future Thoughts Ft. Spaceface" by Brothers Griin from Joy City; "Docudrama" by Nyx Nott from Themes From; "DISinformation Desk" by The Black Dog from Music for Real Airports; "The Yips" by James Ellis Ford from The Hum. Courtesy of Warp; The single "Vento a Favor" by Sessa. Courtesy of Mexican Summer; "Cascade" by Niecy Blues from Exit Simulation. Courtesy of Kranky; "Sacred and Profane" by Moundabout from An Cnoc Mor. Courtesy of Rocket Recordings; "Reel Life (Evolution 2)" by Cinematic Orchestra from Man with a Movie Camera. Courtesy of Ninja Tune; "Theme from a Personal Prison" by Emil Amos from Zone Black. Courtesy of Drag City; "Delivery" by Black Duck from the self titled album. Courtesy of Thrill Jockey; "Visiting" by Craig Leon from Anthology of Interplanetary Folk Music Vol. 1. Courtesy of RVNG Intl; "Sunset Theater" by Golden Hallway Music from Rules and Chance Vol 3. Courtesy of Not Not Fun; The Actress remix of Carmen Villain from Smalltown Supersound Remix Anthology Vol. 1-4 2002-2022.
Beau Martonik is joined by Jonathan Wilkins. Jonathan is an avid waterfowl hunter, bear hunter, deer hunter, wild game cook, and the founder of Black Duck Revival from Arkansas. They discuss Jonathan's journey to bowhunting, bear hunting in the big woods, hunting smarter, wild game cooking, living a fulfilled life, and much more. Topics: 00:00:00 - Start 00:06:13 - The Swapcast 00:07:02 - It's weird being in the spotlight, but get to go to cool places 00:08:43 - Being out west helps with hunting back home 00:09:46 - Never killed a turkey in Arkansas 00:11:05 - Merriam's turkey hunting 00:12:30 - “If you want to catch a lot of fish, go to a place with a lot of fish” 00:14:21 - Shooting target bucks and luck 00:17:13 - Dog takes out the Podcast Rig 00:17:39 - Jonathan's first bow and archery deer 00:22:12 - Speaking the animal's language 00:24:01 - Jonathan's woodsmanship with bears 00:32:24 - Hunt bears when it's hot 00:35:58 - Using time to hunt smarter, not harder 00:39:38 - Do stuff that other people don't see any value in 00:41:02 - New York hunt and challenging yourself with something new 00:45:51 - Validation from operating with animals on their turf 00:49:00 - Jonathan's cooking 00:51:40 - Meals can communicate who you are 00:56:09 - Building your brand 00:58:00 - What gave Beau the confidence to leave the 9-5 job 01:01:03 - Know when to walk away, but not quitting is vital 01:03:01 - Why not try to live the most fulfilling life you can 01:07:59 - Hard work and consistency - Four years to kill an elk 01:12:14 - Set priorities in life 01:13:41 - Effort and “want” can get you past lack of experience 01:15:51 - The mustache origin story 01:20:40 - Fresh sushi Note** timestamps might be off by roughly 4 minutes on the audio version due to ad length changes. Resources: GoWild: Beau Martonik (East Meets West Hunt) Instagram: @eastmeetswesthunt @beau.martonik @blackduckrevival Facebook: East Meets West Outdoors Website/Apparel/Deals: https://www.eastmeetswesthunt.com/ YouTube: Beau Martonik - https://www.youtube.com/channel/UCQJon93sYfu9HUMKpCMps3w Partner Discounts and Affiliate Links: https://www.eastmeetswesthunt.com/partners Amazon Influencer Page https://www.amazon.com/shop/beau.martonik Learn more about your ad choices. Visit megaphone.fm/adchoices
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