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Asked at Microsoft, Databricks, Glean & Palantir 🤔
You’re deploying a 70B-parameter LLM in production.
How much GPU memory do you actually need to serve it?
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Edgex@SahilExecOct 23
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bro asked claude for an office and got a whole GTA side quest 💀
I asked Claude to build an office for the @tavus PALs...
I was not expecting it to build THAT kind of office
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Interviewer:
If I increase an LLM's context window from 32K to 1M tokens, does that mean it can reliably remember everything in that context?
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Edgex@SahilExecOct 16
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3D generation is entering its Agent-Ready era. Hyper3D is leading the shift.
I created a production-ready 3D camera using Hyper3D Rodin Agentic Mode.
Instead of manually deciding the workflow, Agentic Mode analyzed the reference, selected the best generation approach, and handled the heavy lifting automatically.
Workflow:
🔹 Upload reference
🔹 Agentic Mode chooses the optimal modeling path
🔹 Generate the 3D camera
🔹 Refine and iterate with natural language
* Parameter Controls -- adjust dimensions and add custom controls for specific parts.
* Animation Presets -- describe a movement or gesture and generate an animation with natural language.
* Enhanced Materials -- modify the material of specific parts while keeping the rest of the model intact.
🔹 Export production-ready results
In this demo, I show the complete process from a camera reference to a fully realized 3D model and the final refined result.
Try Agentic Mode on hyper3d.ai
#Hyper3D #DeemosTech #Rodin #AI3D #agentready #3DModeling #Agent #agenticmode
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Agentic AI interview question:
The agent claims it successfully updated a customer’s address, but the database was never changed.
How would you design the system so the agent can’t declare success without evidence?
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Edgex@SahilExecSep 21
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IndiaConnected via India Android AppAccount-level information, not a live location or per-post device.
3D generation is moving from “generate an asset” → “build and refine the asset.”
@DeemosTech’s Hyper3D Agentic Mode can generate editable 3D models, adjust dimensions and proportions through natural language, add animation, and even combine multiple reference views into one coherent model.
That’s a much more interesting workflow than one-shot generation - you create, talk to the model, refine, and keep building.
If you work with 3D, CAD, games or product design, this is worth checking out.
Just wrapped up my backend project an e-commerce system, but not the basic CRUD kind. Node.js + Express, JWT auth with refresh rotation, Redis caching + locks, Razorpay webhooks with HMAC verification, atomic stock reservation.
Would genuinely appreciate feedback from other backend devs what's missing, what you'd do differently, what breaks at scale.
Also open to suggestions what's a good next backend project to build?
repo: github.com/devdeepdhariwal/e…
(don't tell me "JS is bad for backend" tell me what a beginner should actually start with instead )
🤖 Made with AI






