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Join us to learn and practice AI, Generative AI, LLMs, Agentic AI, Machine Learning, Deep Learning, MLOps, ML and Data technology together with like-minded developers, engineers, builders, founders, and tech leaders.

Our goal is to congregate with AI developers from all over Zurich to learn and practice AI tech, through tech talks, workshops, code labs, hackathons, etc.. we regularly invite tech leads from innovated companies, successful startups to share their practice experiences and practices in the world of Data, AI, GenAI, ML, Agent.

If you’d like to speak at meetups, co-host your meetup or inquire about partnership opportunities, feel free to reach out to us. info@aicamp.ai

Eventi futuri

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  • AI Deep Dive (Virtual) - Building Self-Improving Agents

    AI Deep Dive (Virtual) - Building Self-Improving Agents

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    Online
    Online

    Important: Register on the event website to receive the joining link. (rsvp on meetup will NOT receive anything).

    This is virtual event for our AI global community, please double-check your local time. Can't make it live? Register anyway to receive the webinar recording.

    Join Snowflake to learn how to build self-improving agents

    Tech Talk: Your Agent Should Fix Itself: Building Self-Improving Agents
    Speaker: Elliot Botwick, Principal AI/ML Architect, Snowflake
    Abstract: In this talk, we will share how coding agents help developers build high quality agents faster.
    A key insight from building agents in production is that high quality agents operate with their goals, plans and actions aligned. We introduce the Agent Goal-Plan-Action (Agent GPA) framework to capture this insight, which achieved state of the art benchmarks on TRAIL/GAIA with 95% error coverage and 86% error localization.
    The Agent GPA framework assesses the full agent's process:

    • Was the goal achieved efficiently?
    • Did the plan make sense?
    • Were the right tools used?
    • Did the agent follow through?

    Without visibility into these steps, teams risk deploying agents that look reliable but create hidden costs in production. Inaccuracies can waste compute, inflate latency and lead to the wrong business decisions, all of which erode trust at scale.
    We will show how to use coding agents to automate the process of measuring and improving your agent's GPA by using optimization skills that take advantage of the GPA evaluation framework. By the end, you’ll be able to use coding agents and the GPA framework to identify common agent failures, improve their agent and make it ready for production.

    Venue:
    Virtual, join from anywhere

    More virtual sessions:

    • July 22nd: AI Deep Dive with Google Ep1. RSVP
    • July 29th: AI Deep Dive with Snowflake. RSVP
    • Aug 5th: AI Deep Dive with Google Ep 2. RSVP
    • Sep 2nd: AI Deep Dive with Google Ep 3. RSVP
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