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UID:pretalx-foss4g-2022-EALH73@talks.staging.osgeo.org
DTSTART;TZID=CET:20220824T151500
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DESCRIPTION:Artificial Intelligence (AI) has made an impact in almost every
  field and has become an incredibly powerful technology. However\, while s
 ome players in big tech and academia have access to a highly skilful workf
 orce that can create sophisticated AI solutions\, many companies\, governm
 ents\, public organisations\, and other societal stakeholders are lacking 
 sufficient AI expertise and know-how. \n\nMany AI and Machine Learning (ML
 ) frameworks aim to simplify and democratise AI development\, even if typi
 cally focusing on those with software engineering skills. Some of these so
 lutions\, those that provide no-code tools\, get the closest to the ideal 
 of enabling "any person without prior training”. Collectively\, these co
 uld represent a major breakthrough\, as it has been proven time and time a
 gain that many businesses and organisations still struggle to implement AI
  to its full potential and scale.\n\nVisual\, often drag-and-drop\, no-cod
 e AI tools can make AI less intimidating and more comprehensible to non-te
 chnical profiles and those who lack the time and resources to build such s
 ystems from the ground up. No-code AI frameworks are expected to require m
 inimum technical knowledge to develop practical AI solutions at scale. Thi
 s is an emerging field\, like was previously the case with no-code web dev
 elopment\, starting with Dreamweaver and MS Frontpage\, the first WYSIWYG 
 (what you see is what you get) solutions\, both launched in 1997. \n\nThe 
 European Commission is supporting the establishment of an AI-on-demand pla
 tform that will provide easy and simple access to AI tools that are made i
 n Europe and are ‘trustworthy’. The platform will gather all the AI re
 sources (algorithms and tools)\, and make them available to the potential 
 users\, businesses\, and public administration\, with the necessary servic
 es to facilitate their integration.\n\nWithin the context of the EU’s co
 mmitment to trustworthy AI\, we are exploring the landscape of AI solution
 s for non-experts\, including no-code\, low-code\, AutoML and similar appr
 oaches\, and evaluating them in an experimental setting via prototyping. O
 ur findings are expected to inform the development of relevant European di
 gital initiatives. For instance\, we will consider how these emerging AI s
 olutions for non-experts could be integrated and used in the context of di
 gital infrastructures such as EuroGEOSS or the European Data Spaces. \n\nF
 urther democratization of AI will happen when domain experts without prior
  AI expertise are enabled to tap into high-quality data to solve complex p
 roblems on their own\, with technical details being abstracted away\, such
  as algorithm selection\, model training\, software frameworks\, hardware 
 dependencies\, and platform aspects. We expect that open-source AI technol
 ogies for non-experts represent a step towards such a future.\n\nDuring th
 e conference\, we will present the initial results of our geoAI activity\,
  including a high-level architecture and a stack expected to be composed o
 f various open-source software tools and open standards for digital infras
 tructures\, data engineering and AI development. Our intention is to gathe
 r feedback from the audience and establish possible future collaborations 
 in this space.
DTSTAMP:20260403T212218Z
LOCATION:Auditorium
SUMMARY:No-code geoAI - Blagoj Delipetrev
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/EALH73/
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