Model Optimization & CPU Based Inferencing

Name: Model Optimization & CPU Based Inferencing
Start: 2026-09-24T15:00:00.000Z
End: 2026-09-24T18:00:00.000Z
Location: AI Sweden

AI Sweden, stockholmThursday, Sep 24 · 11:00 AM

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Doors 11:00 AM

The Story

All right!!! **Meetup #39** will take place September 24 at **[AI Sweden](https://www.ai.se/sv)** and focus on **"Model Optimization & CPU Based Inferencing".** We're super excited to team up with Spanish Quantum AI wizards **[Multiverse Computing](https://multiversecomputing.com/)** and tech giants **[Intel](https://www.intel.com/content/www/us/en/homepage.html)**[ ](https://www.intel.com/content/www/us/en/homepage.html)and **[HPE](https://www.hpe.com/se/en/home.html)**. The program is currently being worked out, so stay tuned for updates! There is a tremendous amount happening in the area of model optimization and inferencing. Novel approaches to both seem to be announced daily, such as making it possible to [run the recently released 2.78 trillion parameter model Kimi K3 on a single CPU with 8GB of memory](https://www.linkedin.com/posts/shubhamsaboo_someone-just-ran-278-trillion-parameter-activity-7489869417720217600-iczc?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAFArBkB-7ohHpRVVW-wZ903gEP9O1PCgEw)...!!! or Multiverse Computing's [July 23 announcement that all their compressed models now run on Intel Xeon 6 Processors](https://multiversecomputing.com/resources/multiverse-computing-unveils-breakthrough-all-compactifai-models-now-run-on-intel-xeon-6). So buckle up and brace for impact! **Event Program** \- Doors open at 17:00 CET \- Talks begin at 17:45 CET \- There will be pizzas & drinks \- There may be a moderated Q&A session\.\.\.\. **Speaker Line-Up TBD...** **- [Franco Serra](https://www.linkedin.com/in/franco-serra-139994171/)**, Solutions Architect at **[Multiverse Computing](https://multiversecomputing.com/)** will give a talk titled **"Ultra Efficient Models to Scale your GenAI Datacenter & Fit for purpose on the Edge deployment"**. Abstract: As organizations race to deploy Generative AI, two challenges dominate: how to scale inference economically in the datacenter, and how to bring intelligence on the edge where connectivity, power and f

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