@JensenHuang Don't give up! You've never given up in 30+ years - keep going! Nvidia and the entire AI community still need your energy, courage, and support! ๐๐ค
GTC Berlin ๐ฉ๐ช | Two days of conversations, connections, and confirmation. ๐
Day 2 was packed with meetings, valuable discussions, and opportunities to exchange knowledge with people shaping the future of technology.
For us at NIMBUS21, GTC was more than an opportunity to explore new developments. It was a valuable confirmation that the technologies we build and the methods we implement are at the forefront of an industry that continues to evolve at incredible speed.
We exchanged insights, strengthened existing relationships, established promising new connections, and explored perspectives that will help us continue moving forward.
One of the most valuable aspects of events like GTC is the opportunity to compare ideas, challenge assumptions, and see how your work aligns with the direction the industry is heading.
We leave GTC Berlin with new connections, valuable insights, and even greater confidence in the direction we're taking at NIMBUS21.
A genuinely fruitful experience โ and plenty to build on from here.
Thank you to everyone we met and connected with throughout the event. Looking forward to continuing the conversations.
#GTCBerlin #NIMBUS21 #AI #Innovation #Technology
Day 1 at GTC Berlin ๐ฉ๐ช | The energy around AI is incredible. ๐
Day 1 started inside Tempodrom, where, thanks to our partners, we had the opportunity to experience the event from a great spot in the room.
Beyond that, I explored and participated in different parts of the event, gaining new perspectives on the rapidly evolving AI ecosystem.
What stood out to me wasnโt just the scale of GTC Berlin, but the energy, ideas, and conversations bringing people together around the future of AI.
Sometimes, the most valuable part of an event isnโt just what happens on stage. Itโs being present, listening, exchanging ideas, and connecting with people who are building whatโs next.
Day 1: Done. Day 2: Letโs go. ๐ฅ
Looking forward to more conversations, new perspectives, and insights worth sharing.
If youโre at GTC Berlin, what has been your biggest takeaway so far?
#GTCBerlin #AI #ArtificialIntelligence #Innovation #NIMBUS21 @nvidia@NVIDIAGTC@JensenHuang
GTC Berlin is on my calendar this October! I'll be exploring the latest innovations in AI, accelerated computing, and robotics, and GTC is where a lot of what's next is shown for the first time. If you're going to be there, let's connect in person. Drop a comment or send me a message.
https://t.co/YUeJJvdqpE
I donโt think statelessness means the full tool catalog has to be sent on every request. That feels more like a harness design limitation. (Most harnesses solved that long ago)
A harness could expose only a few stable meta-tools: search_tools, mount_tool, unmount_tool.
The actual MCP registry lives outside the model context. The LLM sees a compact, session-scoped capability index, searches it when needed, then the harness resolves the MCP server and exposes only the relevant tools.
So instead of:
10,000 tools โ prompt
you get:
intent โ search โ resolve MCP โ mount relevant tools โ use โ unload
And if changing the tool schema hurts prompt caching, keep the model-facing interface stable and route execution through a universal tool proxy.
I think this is primarily an orchestration/harness problem, not a protocol problem.
Maybe we donโt need another agent protocol.
We need self-mounting MCP.
Agent needs a capability โ discovers MCP โ checks trust/auth โ mounts โ uses โ unloads.
MCP is already the common interface. The innovation may be orchestration, not another protocol.
What am I missing?
@SebastianRoehl Just to compare each of our team members have minimum 60+ machines in cloud developers 100+. Minimum spec for machine is 8 CPU cores 16 GB RAM .
When you have this brilliant idea to invest 1 week to build an agent which reads emails and buys you coffee - please be informed that, others also have same ideas, same coding agents and are already doing exactly same maybe a little more different - brand colors .
Solve the problem which others canโt. Be creative you can do better then that !
The biggest bottleneck to AGI isnโt the model.
Itโs memory.
We evaluated 10 of the leading AI memory systems.
Different architectures. Different marketing. But fundamentally, most are still playing on the same field.
No real breakthrough yet.
At NIMBUS21, weโve been researching this problem from a different angle - and the results are getting interesting.
Too early to share the details.
But one thing is becoming clear:
The real AI race may not be won by whoever builds the biggest model.
It may be won by whoever solves memory.
Keep an eye on NIMBUS21 AI. ๐