
learning to engineer intelligence // 21 // Ex Intern @iitrpr, @IndianNavy
Delhi, India
Joined June 2024
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just saw a post on r/iitbombay stressing about placements.
"just get into a good college and you're set"
okay which one 💀
Om retweeted
The latest Qwen Code (v0.26.3) already has the Qwen4 lineup baked into the code. Every model starting with qwen4 defaults to a 1M-token context.
Named in testing: qwen4-max, qwen4-plus, qwen4-coder-plus, plus dated ones like qwen4-max-2026-10-01, and even qwen4.5-max is prewired.
This is a preset in the official coding tool, not an official Apsara announcement. Amsterdam kicks off today; something should move this afternoon.
Feels close.
alibabacloud.com/apsara-conf…
Hoping the conference drops a surprise.
unpopular opinion but yearly subscriptions for ai make no sense to me atp.
new models keep dropping, and the one i'd pick this month might not be the one i'd pick next month.
maine notice kiya hai ye anime pfp lagane waalo ko bohot reach aur followers milte hai🥀
Mai bhi lagalu kya😔
Then what's stopping me from earning this much?🤔
creators.unfair.so/worth/piu…
Here's a cure to your brain rot feed. Thank me later
historicaltechtree.com/
Great stuff, @adxtyahq
This is beautiful. Hope more of our learning resources get this 3B1B treatment.
I've been wanting to revise AI engineering concepts anyway. Seems like I've got the resource sorted out.
Today, I'm launching llmdojo.dev:
- The hands-on way to learn AI engineering: LLMs, RAG, agents, evals and inference.
- 50+ interactive labs. Tweak tokenizers, attention, embeddings and KV caches live.
- Train a neural network in your browser and watch it learn.
- Build agentic workflows with tool calls, memory, guardrails and bounded autonomy.
- Ship RAG that works: chunking, hybrid search, reranking, and LLM-as-a-judge evals.
- Production AI: model routing, fallbacks, quantization, caching and cost per request.
- 490+ interview questions, reported from OpenAI, Anthropic, Google, Meta, Amazon, Microsoft, Mistral and 50+ more.
- Every answer is cited from papers and books, or measured on real models.
To-do List: (26/10/26)
-Revise Deep Learning Concepts
-Work on Project Documentation
-2 Leetcode Question
-Work on some OpenSource Contribution
If I don't complete it by end of today, then no @X tomorrow.
Turns out there's a whole war going on in this comment section. 🪖
Never did I expect to see a beef going on in Leetcode comment section.
Update:
-Complete ML Fundamental Series Notes (Done)
-CS Fundamentals Revision (Some topics yes)
-2 Leetcode Question (2 easy , more coming on this)
-Work on Project Alloy (Done, sharing soon)
Seems like one more day of @X unlocked😋
To-do List: (24/10/26)
-Complete ML Fundamental Series Notes
-CS Fundamentals Revision
-2 Leetcode Question
-Work on Project Alloy
If I don't complete it by end of today, then no @X tomorrow.














