I wanted to start a broader future possibilities thread around AI Workstations.
A useful angle is integration, but it also connects with performance. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where AI Workstations is genuinely useful and where it still needs improvement.
A useful angle is integration, but it also connects with performance. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where AI Workstations is genuinely useful and where it still needs improvement.