We are getting 2 new devices from NVIDIA and Microsoft:
1. The DGX Station, with GB300 superchip and up to 748GB of memory.
2. The RTX Spark laptop, with 1 petaflop of AI performance and 128GB of unified memory.
The hardware here is pretty bonkers!
Think about it this way:
Positive users are excited about NVIDIA and Microsoft’s DGX Station and RTX Spark enabling powerful local AI models on personal devices while negative users object to the high price limiting access.
For the first time ever, you will be able to run a trillion-parameter model on your personal hardware.
They announced many more things, but there's something else I want to share:
They are running a 5-day mini-program to help developers ship agentic AI running on NVIDIA-accelerated Azure AI Foundry.
Here is the Builder's Arcade program:
• Day 1 - Run your first AI workload • Day 2 - Deploy your model as a service • Day 3 - Wire your model into an agentic workflow • Day 4 - Make your model faster and cheaper • Day 5 - Focus on governance, monitoring, and observability
Go through this. It will take a few hours, and you'll learn a TON!
Link to the Builder's Arcade: https://aka.ms/Build-Arcade-TR-SV
Here is the link to the announcements: https://aka.ms/Build-Blog-TR-SV
Thanks to the Microsoft and NVIDIA teams for partnering with me on this post.
We are getting 2 new devices from NVIDIA and Microsoft:
1. The DGX Station, with GB300 superchip and up to 748GB of memory.
2. The RTX Spark laptop, with 1 petaflop of AI performance and 128GB of unified memory.
The hardware here is pretty bonkers!
Think about it this way:
@svpino A time will come when you’ll be able to run big ai models on your laptop itself
@svpino more and more hardware built specifically for AI is appearing
@svpino 1 petaflop inference, 748GB training. Both companies announcing because custom silicon is coming. This is what it looks like when a duopoly gets spooked.
@svpino I really want the RTX Spark. Could run Deepseek like a dream.
@svpino you forgot to mention the ONE thing that's going to disqualify 90% of users. what's the price of this unicorn known as the DGX station?
fuck the spark. i can and DO do better with my desktop for less and don't give me that bullshit edge case argument.
@svpino Frontier capability is becoming personal.
@svpino RTX Sparkの128GB統合メモリは素晴らしいが、1ペタFLOPの性能を維持するには冷却と電源供給が鍵だ。
@svpino a dgx station class box on the factory floor changes the math — no cloud bill, no latency, production data never leaves the building. we've held off on vision models partly over connectivity 🤔 wonder how they'll price these vs a year of cloud inference?
@svpino I'm not worried about the hardware. I'm more worried about Microsoft executing the software well. ARM laptops have existed before.
@svpino Running voice agents on edge hardware, latency matters more than size. What's the actual inference speed on consumer GPUs? Trillion-param means nothing if it's slow.
@svpino A petaflop laptop with 128GB unified memory changes local model math completely.
@svpino Wait, limited supply plus automatic burn mechanics? If the GameOn token is genuinely launching with zero venture capital allocations, this CryptoSeed drop is going to be massive. Tracking this closely. 👀🤔
@svpino Wait, limited supply plus automatic burn mechanics? If the GameOn token is genuinely launching with zero venture capital allocations, this CryptoSeed drop is going to be massive. Tracking this closely. 👀🤔
@svpino Awesome. Pretty keen to see the laptop pricing when it eventually comes out. Hopefully some 'budget' 32GB and 48GB type options are released also.
We are getting 2 new devices from NVIDIA and Microsoft:
1. The DGX Station, with GB300 superchip and up to 748GB of memory.
2. The RTX Spark laptop, with 1 petaflop of AI performance and 128GB of unified memory.
The hardware here is pretty bonkers!
Think about it this way: