h22166.www2.hpe.com Open in urlscan Pro
16.230.112.18  Public Scan

URL: https://h22166.www2.hpe.com/event/eventpage.aspx?eventid=MgA4ADAAMAAzADgA&cc=emea&lang=en*eEssentials
Submission: On October 07 via api from DE — Scanned from IT

Form analysis 2 forms found in the DOM

Name: hpehf-search-form https://www.hpe.com/emea_europe/en/search-results.html?page=1&q=&autocomplete=0

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</form>

POST ./eventpage.aspx?eventid=MgA4ADAAMAAzADgA&cc=emea&lang=en*eEssentials

<form method="post" action="./eventpage.aspx?eventid=MgA4ADAAMAAzADgA&amp;cc=emea&amp;lang=en*eEssentials" id="Form1" class="leadgen">
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                              <div style="margin:0cm">
                                <div style="margin:0cm"><strong>In collaboration with NVIDIA, HPE invites you to attend our 'Building Self-Hosted Generative AI Solutions at Scale' workshop in Frankfurt.</strong></div>
                                <div style="margin:0cm">&nbsp;</div>
                                <div style="margin:0cm">If you are an IT professional, Machine Learning Engineer, or Data Scientist tasked with implementing on-prem Gen AI Solutions at Scale, this event is for you!</div>
                                <div style="margin:0cm">&nbsp;</div>
                                <div style="margin:0cm"><strong>What will you get out of the day as an IT professional:</strong></div>
                                <div style="margin:0cm">•<span style="white-space:pre"> </span>How to build your ML platform for Generative AI</div>
                                <div style="margin:0cm">•<span style="white-space:pre"> </span>Which infrastructure, platform software, and resources are required when building for scalability</div>
                                <div style="margin:0cm">&nbsp;</div>
                                <div style="margin:0cm"><strong>What will you get out of the day as a Machine Learning Engineer:</strong></div>
                                <div style="margin:0cm">•<span style="white-space:pre"> </span>How you can scale your AI model training across billions of parameters efficiently and sustainably and simultaneously build production-ready full-stack
                                  GenAI applications</div>
                                <div style="margin:0cm">•<span style="white-space:pre"> </span>How to quickly deploy NVIDIA Inferencing Microservices (NIMS) with HPE tools&nbsp;</div>
                                <div style="margin:0cm">&nbsp;</div>
                                <div style="margin:0cm"><strong>What will you get out of the day as a Data Scientist:</strong></div>
                                <div style="margin:0cm">•<span style="white-space:pre"> </span>How to maintain complete reproducibility through data and experiment lineage</div>
                                <div style="margin:0cm">•<span style="white-space:pre"> </span>How to build a data pipeline across multiple different data silos</div>
                                <div style="margin:0cm">&nbsp;</div>
                                <div style="margin:0cm"><strong>Understand HPE and NVIDIAs joint strategy for enterprise computing solution for Generative AI</strong></div>
                                <div style="margin:0cm">•<span style="white-space:pre"> </span>How to avoid escalating costs of cloud and why you should consider on-prem deployment with HPE Private Cloud AI</div>
                                <div style="margin:0cm">•<span style="white-space:pre"> </span>How HPE and NVIDIA provide an unmatched better together solution for Generative AI</div>
                                <div style="margin:0cm">&nbsp;</div>
                                <div style="margin:0cm"><strong>Hands-on AI/ML exercises and demonstrations (remember to bring your laptop!)&nbsp;</strong></div>
                                <div style="margin-top:1em; margin-bottom:0.5em"><strong>For more insights, check out the video below</strong><br> &nbsp;</div>
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                                <br>
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                              <p><img src="https://h40132.www4.hpe.com/filelib/emea/en/638585447346585908_1c407bdb345831d4c6e72ddb6cb57625.png" alt="Christophe Menichetti" width="250" height="250"></p>
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                              <h4>Christophe Menichetti</h4>
                              <p>AI Solution Architect<br> at HPE</p>
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                              <br>
                              <h4>Chris Lacey</h4>
                              <p>HPC &amp; AI Principal Architect<br> at HPE</p>
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                              <h4>Guillaume Barat</h4>
                              <p>EMEA Alliance Director<br> at NVIDIA</p>
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                                  <p><strong>Optimized infrastructure for AI-at-Scale workloads<br> HPE and NVIDIAs joint strategy for Generative AI – HPE Private Cloud AI</strong></p>
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                                  <p><strong>Model Development, Training and Tuning at Scale</strong></p>
                                  <p>Train large-scale machine learning models faster while hiding the complexity of underlying heterogeneous infrastructure</p>
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                                  <p>Deploy &amp; manage models and run inference on heterogeneous infrastructure from data center to edge</p>
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BUILDING SELF-HOSTED GENERATIVE AI SOLUTIONS AT SCALE - FRANKFURT


Event Essentials
Overview
Speakers
Agenda
Additional Info




EVENT ESSENTIALS

Selected Event

Design Offices Wiesenhüttenplatz


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Date

10. October 2024

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Location

Design Offices Wiesenhüttenplatz
Wiesenhüttenplatz 25
60329 Frankfurt

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Registration deadline
09. October 2024 12:00 a.m. (GMT+1)

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Free Seats


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OVERVIEW

In collaboration with NVIDIA, HPE invites you to attend our 'Building
Self-Hosted Generative AI Solutions at Scale' workshop in Frankfurt.
 
If you are an IT professional, Machine Learning Engineer, or Data Scientist
tasked with implementing on-prem Gen AI Solutions at Scale, this event is for
you!
 
What will you get out of the day as an IT professional:
• How to build your ML platform for Generative AI
• Which infrastructure, platform software, and resources are required when
building for scalability
 
What will you get out of the day as a Machine Learning Engineer:
• How you can scale your AI model training across billions of parameters
efficiently and sustainably and simultaneously build production-ready full-stack
GenAI applications
• How to quickly deploy NVIDIA Inferencing Microservices (NIMS) with HPE tools 
 
What will you get out of the day as a Data Scientist:
• How to maintain complete reproducibility through data and experiment lineage
• How to build a data pipeline across multiple different data silos
 
Understand HPE and NVIDIAs joint strategy for enterprise computing solution for
Generative AI
• How to avoid escalating costs of cloud and why you should consider on-prem
deployment with HPE Private Cloud AI
• How HPE and NVIDIA provide an unmatched better together solution for
Generative AI
 
Hands-on AI/ML exercises and demonstrations (remember to bring your laptop!) 
For more insights, check out the video below
 


 



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SPEAKERS




CHRISTOPHE MENICHETTI

AI Solution Architect
at HPE

Visit his LinkedIn profile
 




CHRIS LACEY

HPC & AI Principal Architect
at HPE

Visit his LinkedIn profile
 




GUILLAUME BARAT

EMEA Alliance Director
at NVIDIA

Visit his LinkedIn profile
 

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AGENDA

08:00 - 09:00

Registration & Breakfast

09:00 - 09:15

Welcome & Agenda

09:15 - 10:30

Optimized infrastructure for AI-at-Scale workloads
HPE and NVIDIAs joint strategy for Generative AI – HPE Private Cloud AI

10:30 - 11:00

Coffee break

11:00 - 11:45

Model Development, Training and Tuning at Scale

Train large-scale machine learning models faster while hiding the complexity of
underlying heterogeneous infrastructure

11:45 - 12:30

Model Deployment & Inference at Scale

Deploy & manage models and run inference on heterogeneous infrastructure from
data center to edge

12:30 - 13:30

Lunch

13:30 - 14:30

Optional hands-on session

Foundation models and RAG implementing practical GenAI 

13:30 - 14:30

One to one discussions

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LINKS

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