AI Algorithms

Important: Register on [AICamp website](https://www.aicamp.ai/event/eventdetails/W2026061814) is required for admission. **Description:** Welcome to the AI meetup in Washington DC. Join us for deep dive tech talks on AI, GenAI, LLMs and Agents, hands-on experiences on code labs, workshops, and networking with speakers and fellow developers. **Agenda:** \* 5:30pm\~6:00pm: Checkin, Food/drink and networking \* 6:00pm\~8:00pm: Tech talks and Q&A \* 8:00pm: Happy Hour at Courthouse Social (cross the street) **Tech Talk: Secure Developer Environments in the Age of AI Agents** **Speaker:** Patrick Brown (Coder) **Abstract:** Federal engineering teams are under pressure to ship faster while meeting some of the most demanding security and compliance requirements in the world. In this talk, Patrick Brown of Coder explores how cloud development environments (CDEs) give agencies a foundation to accelerate software delivery without sacrificing control — and why that foundation matters even more as AI-powered coding agents enter the workflow. He'll cover how CDEs keep source code off endpoints, enforce zero-trust access patterns, and provide the consistent, ephemeral infrastructure that both human developers and AI agents need to operate safely at scale. **Speakers:** Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: [Submit Topics](https://forms.gle/JkMt91CZRtoJBSFUA) **Sponsors:** We are actively seeking sponsors to support AI developers community. Whether it is by offering venue spaces, providing food, or cash sponsorship. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 5,000+ AI developers in D.C and 500K+ worldwide.

**CAIRN Launch Meeting** **Community AI Research Network** **Humans + AI Solving Real-World Problems** **Date: June 13, 2026** **Time: 1:00 PM–3:00 PM** **Location: Bull Run Library, Manassas, Virginia** **1:00 PM – Welcome & Networking (20 min)** * **Meet members and introductions** * **Why you joined CAIRN** * **Networking** **Icebreaker: “What problem would you like AI to help solve?”** **1:20 PM – Welcome to CAIRN (15 min)** **Presenter: Edith Mbuyi** **Topics:** * **CAIRN’s mission and vision** * **AI for community impact** * **Member opportunities** * **Future projects and publications** **Motto: Research. Discuss. Create. Publish. Solve.** **1:35 PM – Meet the AI Team (20 min)** **Overview of ChatGPT, Claude, Gemini, Copilot, Perplexity, Grok, and NotebookLM.** **Discussion:** * **Strengths of each tool** * **Comparing perspectives** * **Fact-checking and responsible use** * **Importance of human judgment** **1:55 PM – Live AI Demonstration (25 min)** **Challenge: “How can communities better prepare students for the future workforce?”** **Activities:** * **Compare AI responses** * **Evaluate recommendations** * **Build a draft action plan** **2:20 PM – Break (10 min)** **2:30 PM – Small Group Research Challenge (20 min)** **Teams explore topics such as education, healthcare, transportation, digital equity, business, senior services, or safety.** **Each group:** 1. **Defines a problem** 1. **Uses AI to explore solutions** 1. **Discusses findings** 1. **Recommends an action** **2:50 PM – Group Presentations** **Share problem, AI findings, recommendation, and next steps.** **2:55 PM – Building CAIRN’s Future** **Discuss meeting topics, speakers, research teams, publications, and membership.** **3:00 PM – Closing** **Founding Question: “What challenge should CAIRN tackle next?”** **Collect contact information and invite attendees to become Founding Members.** **Goals** **✅ Learn collaborative AI research** **✅ Explore multiple AI systems** **✅ Connect with innovators** **✅ Develop real-world solutions** **✅ Help shape CAIRN’s future** **Community AI Research Network** **Humans + AI Solving Real-World Problems** **Research. Discuss. Create. Publish. Solve**

Join us for another session of our study group as we cover the book Build a Reasoning Model (from Scatch). In this session, we will try to cover Chapter 1 titled "Understanding Reasoning Models", which defines what a Reasoning Model is and Chapter 2, on "Generating Text with an LLM". This isn't just a lecture! Come ready to ask questions, share insights, and code along. Whether you're a beginner or have some experience, this is the perfect opportunity to continue to learn together. If you plan to work with the code on your own laptop during the session, try and download the code from it's GitHub repository at https://github.com/rasbt/reasoning-from-scratch ahead of time.

For decades, application security has been built around a simple assumption: humans are the primary producers of software. We train developers, review their pull requests, model threats in design meetings, and build controls around human decision-making. That assumption is rapidly breaking down. As AI coding assistants evolve into autonomous software agents, organizations will gain access to an effectively unlimited engineering workforce capable of producing software at a speed no human team can match. The pressure to adopt these systems will be driven not by curiosity, but by competition. Companies that successfully harness agentic development will ship faster, iterate faster, and potentially outpace those that do not. This shift forces a fundamental rethinking of application security. The future of AppSec is not securing developers—it is governing an agentic workforce. Threat modeling, code review, security testing, and change management will not disappear, but they will need to operate at machine speed and increasingly be performed by systems rather than people. In this talk, Ken Johnson, CTO of DryRun Security, explores what the next decade of application security may look like, the assumptions that will no longer hold, and why security professionals must understand these systems deeply if they hope to influence the future rather than react to it.

[Profs and Pints Northern Virginia](https://www.profsandpints.com/washingtondc) presents: **“Can Artificial Intelligence ‘See’?”** A look at how humans and artificial intelligence systems interpret the visual world in fundamentally different ways, with Arryn Robbins, assistant professor of psychology at the University of Richmond and cognitive scientist who researches visual attention, perception, and category learning. [Advance tickets: $13.50 plus sales tax and processing fees. Available at [https://events.ticketleap.com/tickets/profsandpints/nv-can-AI-see](https://events.ticketleap.com/tickets/profsandpints/nv-can-AI-see) .] Artificial intelligence can now identify faces, categorize objects, describe scenes, and outperform humans on certain visual tasks. But does AI actually “see” the world the way that people do? Or does it arrive at correct answers using representations that differ markedly from human perception? Join Arryn Robbins of the University of Richmond for a fascinating exploration of how humans and AI construct meaning from visual information and a look at comparisons between human perception and AI that reveal just how dynamic and context-dependent our own visual systems really are. Dr. Robbins, who previously has given excellent Profs and Pints talks on flaws and biases in human visual perception, will draw from research in cognitive science, visual perception, and AI vision systems. She’ll explain how human perception is not merely a simple recording of the world, but an active process shaped by expectations, context, goals, and recent experience. You’ll learn how humans form flexible mental representations that allow us to recognize objects across changing environments and conditions, and why those representations continuously adapt as we interact with the world. Many AI systems, by contrast, learn visual categories through statistical patterns in data. They can produce impressive results, but sometimes they also produce strange and unexpected failures, and sometimes they classify images in ways that seem strange to us. Dr. Robbins will discuss what these differences reveal about the nature of perception itself, and why the mismatch between human and AI representations matters for technologies like self-driving cars, medical imaging, facial recognition, and automated surveillance. Important for anyone trying to understand the rapidly growing role of AI in daily life, this talk will explore one of the biggest questions in cognitive science and artificial intelligence: What does it actually mean to “see” and understand the world? (Doors: $17, or $15 with a student ID. Listed time is for doors. The talk starts 30 minutes later.) Image: “Eye Farm” by Nevit Dilmen (Wikimedia Commons).