
Learn how to Run LLMs Locally ~ CUNY
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Join our engaging workshop and learn how to run Local LLMs on your laptop or phone! 🖥️📱
Led by CUNY students Ethan and Hussam, this workshop dives deep into the exciting realm of artificial intelligence. As New York invests over $500M into Empire AI, we stand at the forefront of AI research, collaborating alongside prestigious institutions like Columbia, Cornell, and NYU. But true leadership happens not just in meetings, but when students can boot a frontier-grade model on their personal devices and start innovating!
What to Expect:
- Hands-on experience with Google's latest Gemma 4, launched in April and based on the groundbreaking technology of Gemini 3. The smallest variant (E2B) is capable of running on a phone, while the larger models (26B MoE, 31B) outperform last year's frontier models.
- Walk away with a working local-LLM setup on your own machine. 💻
- Gain insights into when using local models triumphs over cloud solutions. ☁️
- Discover concrete avenues this technology opens up, including privacy-first tools for small to medium businesses, on-device educational solutions, and offline agents.
- Explore research opportunities relevant to you as a CUNY student, particularly with the growing traction of Empire AI.
Who Should Join:
This event is designed for any CUNY student eager to dive into AI, with no prior experience in AI or ML needed. Just bring your laptop or a relatively modern phone and get ready to learn!
The Vision:
New York is rich with talent, resources, and a vibrant network, and CUNY proudly stands as the largest urban public university in the country. It's crucial that the future of AI reflects the diversity of our city. So come, engage, and build with us! 🌆🤖
This is a student-run event, independent of CUNY as an institution.
Get your tickets here: lu.ma/8v4l0526 🎟️
HINWEIS: Wir können die Richtigkeit der Informationen zu dieser Veranstaltung nicht garantieren. Besuchen Sie die Webseite der Veranstaltung, um Details wie Datum, Öffnungszeiten, Preise und Ort zu überprüfen.
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