What happens when the most demanding AI workflows are no longer confined to a desk? Together with AMD, we're helping redefine what's possible with AI workstations, enabling professionals to run advanced AI models locally, orchestrate multiple AI agents, and work without the limitations of traditional setups. Because the future of work should adapt to people, not the other way around. Stay tuned. https://hp.com/unlockAI
Execution at the edge is a game-changer for AI deployment. Being able to orchestrate multiple AI agents locally not only tackles performance bottlenecks, but also offers the data privacy and flexibility modern enterprise workflows require. Exciting step forward by HP and AMD in building the hardware backbone for the future of work! 🚀👏
Exciting to see AI moving beyond the desktop. As AI becomes increasingly distributed and autonomous, one challenge becomes even more important: how do you know you can trust the device that’s running it?
AI is becoming most valuable when it empowers people to work more effectively, wherever they are. Running advanced AI locally while maintaining security and performance has the potential to reshape the way many organisations work. Exciting to see where this is heading.
We're seeing this shift at Neolumin too. As AI workloads become more demanding, having the flexibility to run them locally can make a real difference for teams.
AI is changing fast. It'll be interesting to see how solutions like this improve productivity across different industries.
The smarter our tools become, the more obvious good judgement becomes.
I just have to say I love HP!!! I am running three corperations out of a moble hotspot on a 6 year old HP Envy that got ran over by a car 6 years ago! I will never by anyother brand. HP owns my absolute loyalty. Most amazing company ever! and litterally ? My touch screen doesn't work any more but I am building a Neurochemical AI on a HP laptop that refuses to give up!
Running models locally solves a real problem around latency and data control, that part makes sense. What I'd push back on is the framing that portability is the main bottleneck for demanding AI workflows. Most professionals I've seen struggle with are things like context management across agents, reliable output quality, and integration with their actual domain tools — problems that exist regardless of whether the hardware fits in a backpack. Curious how much of the product thinking here goes beyond the compute layer into the orchestration side.