قسم قاعدة البيانات · 12 السجلات
بحث
The papers the modern stack is built on — from the transformer to scaling laws, RLHF and reasoning models.
ملاحظات ميدانية
عشرات الأوراق البحثية بنت بنية تحتية بتريليون دولار. هذه هي الأوراق التي ظهرت فيها الأفكار لأول مرة — معظمها قابل للقراءة بشكل مفاجئ، وكل سجل هنا يخبرك بما كان مهمًا دون الرياضيات.
ابدأ بهذه الثلاثة
AI
Attention Is All You Need (2017)
ثمانية مؤلفين، معمارية واحدة، وكل ما جاء بعدها.
TC
Training Compute-Optimal LLMs — Chinchilla (2022)
التصحيح الذي غيّر طريقة تدريب كل نموذج.
DR
DeepSeek-R1 — Reasoning via RL (2025)
الوصفة المفتوحة للاستدلال — نُشرت بينما أبقى المنافسون وصفاتهم سرًا.
Foundational papers
12
AI
Attention Is All You Need (2017)
The eight Google authors who invented the transformer.
A(
AlexNet (2012)
The ImageNet result that started the deep-learning era — on two gaming GPUs.
CA
Constitutional AI (2022)
Anthropic's method: models critique themselves against written principles.
DR
DeepSeek-R1 — Reasoning via RL (2025)
The open recipe for reasoning models — a Nature cover, from a hedge fund's lab.
DD
Denoising Diffusion Probabilistic Models (2020)
The DDPM paper behind every image and video generator.
F(
FlashAttention (2022)
The kernel trick that made long context affordable.
HA
Highly Accurate Protein Structure Prediction (2021)
AlphaFold 2 in Nature — the result that won a Nobel.
I—
InstructGPT — RLHF at Scale (2022)
How raw language models became assistants people can use.
LM
Language Models are Few-Shot Learners (2020)
The GPT-3 paper: capability from scale, tasks from prompts.
LL
LoRA: Low-Rank Adaptation (2021)
Fine-tuning for the GPU-poor — tiny adapters instead of full weights.
SL
Scaling Laws for Neural Language Models (2020)
Kaplan et al.: loss falls as a power law in compute — the investment thesis, quantified.
TC
Training Compute-Optimal LLMs — Chinchilla (2022)
DeepMind's correction: most models were undertrained on data.