15 AI Research Voices on X
@amaarora= AI papers explained through code.
@cwolferesearch= Clear, in-depth LLM research breakdowns.
@sedielem= Diffusion models explained deeply.
@MaartenGr= Complex AI made visual.
@seb_ruder= NLP and multilingual AI insights.
@Tim_Dettmers= Quantization and efficient LLMs demystified.
@arankomatsuzaki= Research papers distilled into takeaways.
@srush_nlp= Transformers explained with hands-on code.
@ai_explorer25= New AI tools, peoples and ai commentary
@rasbt= LLM research translated into practical code.
@natolambert= RLHF and post-training unpacked.
@eugeneyan= AI research meets real-world systems.
@sh_reya= AI evaluation beyond benchmark scores.
@HamelHusain= Practical, no-nonsense AI evaluation.
@ch402= Neural networks decoded from within.
Met a guy who got a $750,000 offer from Anthropic
I asked him how he broke into AI so fast
He sent me the exact video that got him in. Andrej Karpathy's 3.5 hour deep dive into LLMs
You won't find anything better about how LLMs work than this video
I watched it last night
Halfway through, I realized I have been using AI completely wrong for years
Bookmark this.
AI engineering interview in 2026.
How many of these can you explain clearly:
KV cache
Prompt caching
Semantic caching
Speculative decoding
Context window vs effective context
Hybrid search (BM25 + vectors)
Reranking
Structured outputs
Tool calling
LLM-as-a-judge
Eval sets
Guardrails
Prompt injection
Token budgets
Model routing
If it's less than 8, you're not ready.
If it's 15, you're probably the one taking the interview.