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About us

Warsaw Data Tech Talks (dawniej Warsaw Hadoop User Group) - jeszcze jako WHUG, była jedną z pierwszych w Europie grupą sympatyków technologii Hadoop. Od początku działania grupy(kwiecień 2012), udało nam się z sukcesem zorganizować 36 spotkań i przekonać do dołączenia do grupy 1974 osób :) Mieliśmy przyjemność gościć takie firmy jak Spotify, Criteo, GetinData, dataArtisans, GridGain, TouK oraz wiele innych.
Przez wiele lat Hadoop zyskiwał na świecie popularność, otwierając wielu firmom drzwi do świata Big Data, z upływem lat jednak i rosnącym zainteresowaniem szerok pojętą analizą danych, pojawiło się na rynku wiele innych, użytecznych technologii i metod przetwarzania/analizy danych, które są warte naszej uwagi.
W lutym 2019 roku, jako organizatorzy postanowliśmy zmienić nazwę grupy i nieco rozszczerzyć zakres tematyczny, aby członkowie grupy byli na bieżąco z najnowszymi rozwiązaniami z obszaru Big Data.

Zapraszamy!

Upcoming events

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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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    10 attendees

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Organizers

kevinl is a Super Organizer

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