AI Alliance to enable a better understanding of what AI Openness is
Amanda Brock, CEO of OpenUK, was quoted in this article.
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AI.dev | Open Source GenAI & ML Summit, Panel, San Jose
AI.dev is a nexus for developers delving into the intricate realm of open source generative AI and machine learning. At the heart of this event is the belief that open source is the engine of innovation in AI. By uniting the brightest developers from around the world, we aim to ignite discussions, foster collaborations, and
AI.dev | Open Source GenAI & ML Summit, Panel, San Jose Read More »
7-8 Dec 2023, Tech.Rocks Summit, Keynote, “What does AI Openness mean for us all?”, Paris
Amanda Brock will be Keynote at Tech Rocks in Paris in December. This year, the 7th edition of the Tech.Rocks Summit will take place on December 7 and 8, 2023!
5 Dec 2023, GeoCom 2023, London
GeoCom 2023. View Amanda’s Panel here: https://www.agi.org.uk/wp-content/uploads/2023/12/GeoCom-2023-Conference-Brochure.pdf
5 Dec 2023, GeoCom 2023, London Read More »
Surfacing the people in the Open Source Submarine under the digital economy in OpenUK’s phase three report – Skills or Bust, in computing.
Amanda Brock, CEO of OpenUK, was quoted in this article.
Beta News reports on OpenUK’s Skills report and the potential for Open Source to drive tech skills in the UK
Amanda Brock, CEO of OpenUK, was quoted in this article.
Letter to Editor re: appointment of Palantir
Amanda Brock, CEO of OpenUK, was quoted in this article.
Letter to Editor re: appointment of Palantir Read More »
ITPro reporting on State of Open 23, Skills or Bust and the potential of Open Source
Amanda Brock, CEO of OpenUK, was quoted in this article.
ITPro reporting on State of Open 23, Skills or Bust and the potential of Open Source Read More »
Future of AI Summit 2023, Panel, “In Conversation: The AI Divide – Will data inequality destroy healthy competition?”, London
In conversation: The AI Divide – Will data inequality destroy healthy competition? (16 Nov 2023) Generating AI’s game-changing future products and services requires large quantities of data, which may create a market problem. How do smaller companies that can’t afford big data sets compete? Are there cheaper ways to develop large language models (LLMs)? Amanda