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Jev, Simply Explained
A beginner's guide to Jev, the AI model that returns typed decisions and calibrated probabilities instead of text.
Sep 28
•
Dr. Ashish Bamania
18
4
3
10 LLM Inference Metrics Every AI Engineer Must Know
TTFT, TPOT, ITL, Goodput, MBU, MFU, and more.
Sep 21
•
Dr. Ashish Bamania
9
1
PPO vs GRPO, Simply Explained
An easy lesson on two important LLM post-training algorithms.
Sep 17
•
Dr. Ashish Bamania
8
On-Policy Distillation, Simply Explained
A lesson on how On-Policy Distillation (OPD) is used to train a student model on its own responses, using a stronger teacher model.
Sep 9
•
Dr. Ashish Bamania
11
2
How to Read GPU Specs
A simple and jargon-free guide to reading GPU specs for LLM training and inference.
Sep 4
•
Dr. Ashish Bamania
24
6
August 2026
9 GPU Concepts Every AI Engineer Should Know
A simple and practical guide to GPU internals that AI engineers actually need.
Aug 27
•
Dr. Ashish Bamania
54
7
5 LLM inference batching techniques every AI engineer should know
Static, Dynamic, and Continuous batching, Chunked prefill, and Prefill–decode disaggregation, simply explained.
Aug 22
•
Dr. Ashish Bamania
14
How does Claude watermark text?
Visually understand how Anthropic watermarks and detects Claude-generated text.
Aug 20
•
Dr. Ashish Bamania
13
1
🗓️ This Week In AI Research (1-7 August 26)
The top 10 AI research papers and releases that you must know about this week.
Aug 13
•
Dr. Ashish Bamania
10
2
How LLMs are distilled, step by step
A visual guide to understanding how LLMs are trained using model distillation.
Aug 10
•
Dr. Ashish Bamania
10
1
🗓️ This Week In AI Research (25-31 July 26)
The top 10 AI research papers and releases this week.
Aug 7
•
Dr. Ashish Bamania
7
1
10 LLM Inference Optimization Techniques, Simply Explained
10 techniques that make LLM inference faster and cheaper: KV caching, Quantization, FlashAttention, PagedAttention, Speculative decoding, and more.
Aug 1
•
Dr. Ashish Bamania
22
7
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