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AI & Machine Learning Startups, Investors, Innovators Networking Event at Kitty Cohen's in Austin, TX on Tuesday, June 2, 2026.
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π Please Note: RSVP on Meetup does not guarantee entry. To attend, you must register through the official ticket link here: [https://www.eventbrite.com/e/1987905650313?aff=oddtdtcreator](https://www.eventbrite.com/e/1987905650313?aff=oddtdtcreator) Step into the world of AI innovation and connect with the people building the future. This high-energy event brings together founders, investors, and professionals working at the forefront of artificial intelligence and machine learning. At the core of the evening is live pitchingβand everyone is welcome to participate. Whether you're developing a breakthrough model, investing in deep tech, or exploring opportunities in AI, youβll get a 1-minute slot to introduce yourself, your idea, or your ask. Who Should Attend: AI and ML Entrepreneurs and Startup Founders: Ideal for those looking to showcase their innovative solutions, seek funding, or find potential co-founders. This event provides a platform to pitch your projects to an audience that includes potential investors and partners, maximizing exposure and opportunities for growth. Investors Specializing in AI and ML: Venture capitalists and angel investors interested in the latest developments in AI and ML will find a pool of potential investment opportunities. This event offers a streamlined way to identify emerging talents and innovative projects worth backing. AI and ML Professionals: Data scientists, machine learning engineers, researchers, and other professionals working in the AI and ML fields should attend to network with peers, discuss industry trends, and explore potential career advancements or collaborative projects. Technology Enthusiasts and Students: Those passionate about AI and ML technologies, including students and academic professionals, will benefit from direct interaction with industry leaders and innovators, gaining insights into the practical challenges and opportunities in the field. **Whyβ¦
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