Compelling argument for on-prem AI in regulated environments. The data sovereignity point is especially critical when firms operate across GDPR, CCPA, and PCI DSS jurisdictions simultaneously. What often gets missed is the latency advantage, sub-10ms inference times matter way more than poeple think for fraud detection in high-frequency trading scenarios where every millisecond of delay compounds risk exposure.
Really exciting to see if On-Prem will make a comeback because of AI. The security aspect alone makes it very compelling but also potential cost savings in cloud and API costs.
The cloud is convenient because you no longer need a technical team to manage physical infrastructure but it comes with a cost that is constantly rising.
I’m interested in how open source models are reducing the hardware requirements needed to operate. They already give you 80% of what frontiers models give you with a fraction of the compute required.
Agreed. While the upfront costs may be difficult to look past, the savings, efficiency gains, security improvements, and customization capabilities make local systems much better in the long run. As more institutions discover these benefits, adoption of on-prem systems will rise.
Compelling argument for on-prem AI in regulated environments. The data sovereignity point is especially critical when firms operate across GDPR, CCPA, and PCI DSS jurisdictions simultaneously. What often gets missed is the latency advantage, sub-10ms inference times matter way more than poeple think for fraud detection in high-frequency trading scenarios where every millisecond of delay compounds risk exposure.
The security benefits of local systems cannot be overstated.
Really exciting to see if On-Prem will make a comeback because of AI. The security aspect alone makes it very compelling but also potential cost savings in cloud and API costs.
The cloud is convenient because you no longer need a technical team to manage physical infrastructure but it comes with a cost that is constantly rising.
I’m interested in how open source models are reducing the hardware requirements needed to operate. They already give you 80% of what frontiers models give you with a fraction of the compute required.
Agreed. While the upfront costs may be difficult to look past, the savings, efficiency gains, security improvements, and customization capabilities make local systems much better in the long run. As more institutions discover these benefits, adoption of on-prem systems will rise.