Shruti ✓
@heyshrutimishra · joined 31 Aug 2022
Reality is programmable | Building digital leverage w/ AI | Stay ahead with the latest AI & robotics developments | Business inquiries : hey@shrutimishra.co
181 767Followers
1 001Following
42 738Posts total
888.7KViews on collected posts
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The memory race is over. The judgment race hasn't started.
Every agent I've tested this year can recall what I told it. None can tell which of the 400 things I said this week actually matters to me, because that signal lives mostly in what I never typed.
Storage got cheap.
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You hired a coding agent. It hired you as its reviewer.
"Are you sure?"
"Check that again."
"Did you consider what this breaks?"
The agent keeps generating. You're still the only quality check.
@qodoAI Agentic Toolbox brings independent review into that workflow.
It plugs htt
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@heyshrutimishra It's crazy that you can spin up a hardware-isolated sandbox in under 60ms with <5MB overhead. Makes my Docker setup feel ancient.
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v0.7.0 also fixes two things that have been painful for production:
Multi-version component coexistence. Upgrading no longer breaks old templates and snapshots.
Control plane separated from ops. Clearer responsibilities, smaller blast radius. https://t.co/YnuWssTkd9
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E2B-compatible too. Existing E2B apps migrate by changing one config line.
Open source. Self-hostable. Production-ready.
@CubeSandbox #CubeSandbox #OpenSource #AIAgents
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The headline feature: cross-node pause & resume (Preview)
Pause a sandbox on Node A. Resume it on Node B. Node going down for maintenance? Your agent's entire state, memory and filesystem, survives the migration. https://t.co/KsuA28mmsV
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CubeSandbox solves this with RustVMM and KVM.
Every sandbox gets its own kernel. Hardware-level isolation. Millisecond startup. Snapshots, cloning, pause/resume. https://t.co/x84EDUVL4l
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The problem: containers don't isolate enough.
A container escape means your agent reads files it shouldn't, accesses secrets it shouldn't, and corrupts other agents on the same host.
For AI agents running untrusted code, that's a real risk.
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Stop worrying about container escapes for your AI agents.
CubeSandbox v0.7.0 just dropped, and it's built different:
Link: https://t.co/O2U2R4tz5K 👇 https://t.co/XrSzX9C6aF
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AI video has gotten very good at making a convincing frame.
But filmmaking has never really been about one frame.
It's about whether the camera, characters and environment can work together across an entire sequence. https://t.co/dudN8blGuc
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3:30
@heyshrutimishra Hey Shruti! You got a big shout in The Week in AI #4 not just for a great thread about GTC Paris... but because you got to meet The Wizard!
https://t.co/jLGlJjR2xB
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We're back for the never-ending drama of AGI
12 topics in a rapid-fire format with @quantspec
"All incumbents are going to get nuked," @pmarca
Plus more from @Scobleizer @HarperSCarroll @danielnewmanUV @slow_developer @businessbarista @RihardJarc
https://t.co/FGpkAJP9gw
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Beyond the announcements, the highlight for me was meeting Jensen Huang, CEO of NVIDIA, an absolute honor.
This is the man whose vision and perseverance helped birth an entire era of AI, starting with GPUs for graphics, then CUDA for compute, and now systems that power https://t
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7/ @NVIDIA and Hugging Face have teamed
With DGX Cloud Lepton, developers get instant access to a global GPU network - no complex setup required.
You can train, fine-tune, and deploy models at scale, all with minimal overhead.
Built for speed, flexibility, and open https://t.c
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1:45
6/ Sovereign AI in progress @NVIDIAAI
France, Italy, Spain, UK, Finland, Germany all building local AI infra.
BV-backed partnerships with Mistral, NAISS, Barcelona Supercomputing Center, others to build region-specific LLMs using Nemotron + DGX Cloud https://t.co/R0IETMFQAt
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5/ CUDA-Q is now available for Grace Blackwell
It brings quantum and classical computing into a single workflow.
You can now write hybrid code that runs across CPUs, GPUs, and QPUs seamlessly. https://t.co/XnxHEaXS2L
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1:10
4/ Agentic AI will be the next big shift.
We’re moving from static models to systems that can observe, reason, act and improve.
These agents don’t just respond. They reflect, retry, and make real-world decisions.
AI is no longer a tool. It’s becoming a teammate. https://t.co/C
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2:55
3/ AI factories are coming.
Stargate is just one example that is gonna hold over 5,000 GPU dies.
Jensen called them “factories for intelligence” and that’s exactly what they are.
Massive physical racks that generate, reason, and run nonstop. Powered by Blackwell, NVLink, and h
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4:21
2/ Digital twins
Everything physical will be built digitally first.” – That’s what Jensen said on stage at GTC Paris
From cars to factories... tested, optimized, perfected in simulation
AI + Digital Twins are becoming the new foundation of how we build https://t.co/7nTp1AwfYy
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3:25
1/ 🚨 130 TB/s bandwidth
The Grace Blackwell NVL72 (One Giant GPU) system connects 72 Blackwell GPUs, moving more data per second than the entire global internet. https://t.co/hbdNVH1QNG
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1:20
🚨 BREAKING: NVIDIA just revealed its roadmap for physical AI, robotics and national-scale AI factories.
Most people don’t know it: In 2016, they built their first AI supercomputer with zero customers. OpenAI was the first to say yes.
Here’s a breakdown of the most important htt
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1:36
Against accounts of the same size
10 posts from the last 90 days, next to the 100K–1M follower range. below its peers on both reach and engagement.
Median views470this account4 817median for 100K–1M
Reach, %0.26%this account1.79%median for 100K–1M
Engagement, %0.70%this account1.32%median for 100K–1M
| Metric | This account | Median for 100K–1M | Ratio |
|---|---|---|---|
| Median views per post | 470 | 4 817 | 0.10× |
| Reach (views ÷ followers) | 0.26% | 1.79% | 0.14× |
| Engagement rate | 0.70% | 1.32% | 0.53× |
Others in this range → Compare with another account → How these benchmarks are built →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
19.1K12 Jun
1.8K14 Jun
1102 May
9014 May
4.5K8 Sep
6.1K
193
127
88
452
488
59 Sep
1.9K
1.5K
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.19%12 Jun
0.11%14 Jun
0.91%2 May
1.11%14 May
0.58%8 Sep
0.20%
0.52%
2.36%
2.27%
0.88%
0.82%
0.00%9 Sep
1.65%
0.33%
Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.32%.
What the audience does
Likes61.2%3 060 in total
Reposts6.5%324 in total
Replies3.2%162 in total
Bookmarks29.1%1 456 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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