Shivay Lamba

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Shivay Lamba

Shivay Lamba

@HowDevelop

AI Architect & Builder - Inference, LLMs, SLMs GSoC Org Admin - Jenkins | Docker Captain | CNCF Ambassador

New Delhi Katılım Aralık 2018
1.2K Takip Edilen8.2K Takipçiler
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Shivay Lamba
Shivay Lamba@HowDevelop·
What an amazing day! Presented a poster at @PyTorch Conference: how we optimised the RLM paper with pre-fix caching & batched Sub calls with @vllm_project And a full house for our Pytorch Conference talk on running LLMs using Executorch on Android!
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Shivay Lamba
Shivay Lamba@HowDevelop·
Open source maintainer burnout isn't an effort problem. It's an attention problem. The signal is buried under hundreds of issues, stale PRs, and scattered HN threads. So I built Maintainer Brief, a weekly intelligence email that does the triage for you. powered by @nebiustf 🧵
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Claude
Claude@claudeai·
We're extending Claude Fable 5 access on all paid plans, as well as keeping Claude Code’s weekly rate limits 50% higher, through July 19.
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Kartikey Rawat
Kartikey Rawat@carrycooldude·
Just with the OGs 🔥
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Shivay Lamba
Shivay Lamba@HowDevelop·
Why I built it: maintainer burnout is almost always an attention problem, not effort. The high-leverage action is there: it's just buried under noise. Maintainer Brief is like a chief of staff for your repo. Also powered by @ExaAILabs @resend
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Shivay Lamba
Shivay Lamba@HowDevelop·
It reads your repo's live GitHub state and computes 4 action lists, nothing generic: 🔍 Triage: dupe clusters, hot issues, unanswered threads 🚀Ship It: approved-ready PRs + a changelog draft 👥 People: first-time contributors going stale 💬 Worth Replying To: HN/Reddit/web mentions
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Shivay Lamba
Shivay Lamba@HowDevelop·
After spending 6 hours, building @PyTorch Executorch on Mac to run @Alibaba_Qwen 3 on Android, I documented the full path so others can skip the painful parts: Docker/Linux builds, @Qualcomm_Dev QAIRT/AAR packaging, FastRPC issues using a sample app: github.com/shivaylamba/ex…
Shivay Lamba@HowDevelop

Working on low-level AI stacks like @PyTorch ExecuTorch or LiteRT-LM for @googlegemma is a good reminder that, even in the age of AI agents, some parts of the developer experience are still surprisingly tricky. The tooling still heavily favors Linux. On Windows, you're often relying on WSL; on macOS, Linux containers become part of the workflow. It all works, but native parity across Linux, Windows, and macOS would make life a lot easier. @carrycooldude would agree 🙃

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Rudraksh
Rudraksh@rudrakshkarpe·
@abheer NVIDIA Dynamo is a awesome engineering project indeed!
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Abheer Singh
Abheer Singh@abheer·
NVIDIA Dynamo comes up in almost every large scale inference conversation. Ik a lot of people in the local AI community and beyond have seen the name floating around and are curious. Even if it never applies to your setup, the engineering is very cool. Worth breaking down.
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Saiyam Pathak
Saiyam Pathak@SaiyamPathak·
But need not to worry now I am on my RTX pro :D
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Saiyam Pathak
Saiyam Pathak@SaiyamPathak·
Every tool and model token limits exhausted including 250$ Weekends are for burning tokens!
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Kartikey Rawat
Kartikey Rawat@carrycooldude·
We are kicking it off 🔥
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Kushal Vijay
Kushal Vijay@KushalVijay_·
I'll be in Delhi for the next week. Please drop if there are any AI, startup, or developer community events happening? I'd love to meet fellow builders, founders, and engineers. If you're hosting something or know of an event, hmu
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Hrittik Roy
Hrittik Roy@hrittikhere·
Kubernetes will happily split your distributed GPU jobs across regions, killing performance. The fix? Pair topology-aware placement with gang scheduling to force tightly coupled workloads into a single region, zone, or rack. Read here: hrittikhere.com/posts/kubernet…
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@HaimantikaM @nebiustf @claudeai @carrycooldude @Arindam_1729 @ExaAILabs @resend @PyTorch