<div dir="ltr"><div dir="ltr">I would suggest trying virtualization on the platform, being an HP z840 server with 44 cores and 256 GB of RAM. With this setup, deploy the Local AI LLMs in one VM, followed by deploying the ML & DL Dev Tools into another VM. For further information, please refer to the attached screenshot of my AI Lab. I look forward to speaking with you tomorrow.<div><br></div><div><img src="cid:ii_m9m8g69i0" alt="image.png" width="562" height="290"><br></div><div><br></div><div>Best regards,</div><div>Al Maclang</div><div>Company website: <a href="https://al-masih.com.au/">https://al-masih.com.au/</a><br>Company email: al.maclang at <a href="http://al-masih.com.au">al-masih.com.au</a></div><div>Personal email: almaclang at <a href="http://google.com">google.com</a></div><div>LinkedIn: <a href="https://www.linkedin.com/company/al-masih/">https://www.linkedin.com/company/al-masih/</a></div><div><br></div></div><div class="gmail_quote gmail_quote_container"><div dir="ltr" class="gmail_attr">On Fri, 18 Apr 2025 at 01:48, Russell Coker via linux-aus <<a href="mailto:linux-aus@lists.linux.org.au">linux-aus@lists.linux.org.au</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><a href="https://flounder.linux.org.au/events/flounder-apr-2025-hack-day/" rel="noreferrer" target="_blank">https://flounder.linux.org.au/events/flounder-apr-2025-hack-day/</a><br>
<br>
A day of hacking on various things using the new (to us) HP z840 server with <br>
44 cores and 256G of RAM. Some ML stuff will be involved, probably other <br>
interesting things too.<br>
<br>
Meeting will be at <a href="http://b.coker.com.au" rel="noreferrer" target="_blank">http://b.coker.com.au</a>. No need to register just click on <br>
the link on the day.<br>
<br>
Meeting officially opens at 1PM Melbourne time (03:00UTC), 19th of April.<br>
<br>
Some useful URLs:<br>
<br>
<a href="https://www.tensorflow.org/lite" rel="noreferrer" target="_blank">https://www.tensorflow.org/lite</a> – libraries for doing ML on small devices <br>
(Android, iOS, and Raspberry Pi).<br>
<a href="https://huggingface.co/" rel="noreferrer" target="_blank">https://huggingface.co/</a> – HuggingFace AI community with models to download.<br>
<a href="https://github.com/EleutherAI/the-pile" rel="noreferrer" target="_blank">https://github.com/EleutherAI/the-pile</a> – The Pile of open training data.<br>
<a href="https://blends.debian.org/science/tasks/machine-learning" rel="noreferrer" target="_blank">https://blends.debian.org/science/tasks/machine-learning</a> – Debian Science <br>
machine learning packages.<br>
<a href="https://wiki.debian.org/MachineLearning/Tensorflow" rel="noreferrer" target="_blank">https://wiki.debian.org/MachineLearning/Tensorflow</a><br>
<a href="https://github.com/mitutitu16/Awesome-Mobile-Machine-Learning" rel="noreferrer" target="_blank">https://github.com/mitutitu16/Awesome-Mobile-Machine-Learning</a> Links to useful <br>
resources.<br>
<br>
-- <br>
My Main Blog         <a href="http://etbe.coker.com.au/" rel="noreferrer" target="_blank">http://etbe.coker.com.au/</a><br>
My Documents Blog    <a href="http://doc.coker.com.au/" rel="noreferrer" target="_blank">http://doc.coker.com.au/</a><br>
<br>
<br>
<br>
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</blockquote></div></div>