Building AlphaZero with Project Goose
- Date
- 2025-07-23
- Location
- Chippendale, New South Wales, Australia
- Host
- Personal
About this event
If you’ve been curious about how systems like AlphaZero are actually built, this meetup gives you a grounded place to explore the idea with other people who are equally interested. Building AlphaZero with Project Goose is an in-person evening for learning, discussion, and connection around one of the most ambitious challenges in modern AI: creating agents that learn strong decision-making through self-play and iteration. Whether you come from a technical background or you’re simply fascinated by how these systems work, the event is designed to make the topic approachable without flattening the complexity. You’ll spend time with a community that wants to talk seriously about reinforcement learning, experimentation, and building things that push beyond tutorials. About the Event This is a community meetup held in Chippendale, Australia, bringing people together in person to talk through the ideas, tools, and practical challenges involved in building an AlphaZero-style system with Project Goose. The focus is not just on theory, but on how ambitious AI projects take shape through implementation decisions, experimentation, and shared problem-solving. Expect a format that feels more interactive than a one-way presentation. The event sits at the intersection of community, networking, and technical curiosity, making it a good fit if you want both substance and conversation. It’s a space to meet others who are thinking about game-playing agents, search, training loops, evaluation, and what it really takes to move from concept to working system. If you’ve seen plenty of high-level AI content but want something more concrete, this meetup is meant to close that gap. It creates room for real discussion about architecture, tradeoffs, and the practical reality of building systems inspired by landmark research. What to Expect You can expect an evening structured around shared exploration of the topic rather than passive attendance. The session will likely move through the core ideas behind AlphaZero-style learning, how Project Goose fits into that effort, and the technical and conceptual components that matter most when building something similar. The conversation may touch on themes like: Self-play and iterative improvement Search and decision-making frameworks Training workflows and experimentation What makes implementation difficult in practice How to think about progress, evaluation, and failure modes Because this is also a meetup, there will be room for discussion before, during, or after the main session. You should come ready to ask questions, compare approaches, and learn from people with different perspectives. Some attendees may be interested in the research side, others in software implementation, and others in the broader implications of these systems. Just as important, the social side of the evening matters. This is a chance to meet people in your local area who care about AI deeply enough to show up in person and talk through the details. Those conversations often become the most valuable part of the night. Why Attend The biggest reason to attend is simple: topics like AlphaZero are often discussed at a distance, but much harder to understand at the level of building. This event gives you a more practical lens. Instead of only hearing what these systems can do, you’ll be in a room thinking about how they are assembled, tested, and improved. You should also come if you value learning through community. Complex technical ideas become easier to work with when you can ask follow-up questions, challenge assumptions, and hear how others are approaching the same problems. An in-person setting makes that exchange faster, clearer, and more memorable than reading alone. There’s also real value if you’re looking to expand your network in a way that aligns with your interests. The people drawn to this event are likely to be builders, researchers, hobbyists, and thoughtful newcomers who share a serious interest in AI systems. If you’ve been looking for more local peers to trade ideas with, this is a strong place to start. You may leave with: A clearer mental model of what an AlphaZero-style project involves Better questions to ask in your own learning or building process New connections with people interested in AI, reinforcement learning, and experimentation A stronger sense of where Project Goose fits into the broader landscape Practical Details The event takes place in person in Chippendale, Australia, which makes it especially useful if you want face-to-face conversation rather than another online session. Being physically in the room changes the quality of discussion, especially for technical topics that benefit from back-and-forth exchange. It’s happening on Wednesday, July 23 at 6:00 PM GMT+10, making it well suited to an after-work or evening visit. You can plan for a focused midweek session that combines learning with community. Because this is a meetup with networking and social elements, it’s worth arriving ready to introduce yourself and share what brought you there. You do not need to be an expert to get value from the event, but you’ll get more out of it if you come with genuine curiosity about AI systems, learning algorithms, or ambitious technical projects. If this topic has been living in your browser tabs, notes app, or side-project ideas for a while, this is a good moment to bring that interest into a real conversation with other people.
Who should attend
This is for you if you want to move beyond abstract AI discussion and spend time with people who care about how these systems are actually built. - You’re interested in **AlphaZero, reinforcement learning, self-play, or search-based decision systems** and want a more practical understanding of what goes into building them. - You’re a **developer, researcher, student, or technical hobbyist** who enjoys unpacking complex systems and learning through conversation with others. - You’ve been following AI closely and want an **in-person community space** where the discussion can be more serious, detailed, and interactive than what you usually get online. - You’re working on, thinking about, or planning your own experiments and would benefit from hearing how others approach **implementation tradeoffs, architecture choices, and iteration**. - You value **networking with people who share your curiosity**, whether you’re looking for collaborators, peers, or simply better local conversations. - You’re newer to this area but motivated enough to show up, ask smart questions, and learn from people who are further along without needing the event to be beginner-only.