FTFuture Tech Career Hubinfuturetechcareerhub.hashnode.dev·5d ago · 12 min readAI Training in India: A Practical Roadmap for Building Modern AI ApplicationsArtificial Intelligence development has moved far beyond traditional machine learning models. Modern AI applications can combine machine learning, large language models, retrieval systems, APIs, AI ag00
SSSwarit Shuklainswaritshukla.hashnode.dev·6d ago · 5 min readGRPO: How Language Models Learn to ReasonDo you remember the times when we used to make LLMs count the occurrence of a specific letter in a word, like "How many r's in strawberry?" Back then, LLMs used to get it wrong a lot of times, but now00
ACADEKUNLE CHRISTIANAH AYOMIDEini-am-christy.hashnode.dev·Sep 19 · 15 min readUnderstanding the Economics of Repeated Context: Prompt Caching...In this article you'll learn: What prompt caching is and what it actually saves How it works, step by step, in plain terms How to tell whether it will save you money, with a simple formula How Ant00
SSSunney Soodinsunneysood.hashnode.dev·Sep 18 · 17 min readTokens & Tokenizers: How a Computer "Reads" a Sentence Here's a weird fact: when you read the sentence "I love pizza", your brain doesn't see letters one by one — I, then space, then l, o, v, e... You just see the words. Your brain has already chopped the00
THTaha husseinintahahussein.hashnode.dev·Sep 18 · 7 min readFine-Tuning an LLM: What Actually Happens Under the Hood?Fine-Tuning an LLM: What Actually Happens Under the Hood? You have probably heard phrases like: "Fine-tune the model." "Use LoRA." "Train the LLM on your own data." "Use PEFT." But what do these ter00
JMJoselo Martinezindesignednotmagic.hashnode.dev·Sep 16 · 4 min readAgentic AI Beyond the Hype: Why the Boundaries Are Key in Deterministic and Non-Deterministic Behavior for AgentsLet’s imagine we are implementing deterministic behavior for agent systems using control techniques (harnessing). Suddenly, we observe that the agent's actions and responses begin to become clumsy, an02JB
DSDoogal Simpsonindoogal.dev·Sep 14 · 5 min readOptimize Cheap LLMs for Frontier-Level AccuracyYou don't always need expensive frontier LLMs to achieve production-grade results. By investing in context engineering, structured tool access, and strict guardrails, you can optimize cheap utility mo00
SSSameer Selokarinblogbysameer.hashnode.dev·Sep 13 · 16 min readWhy AI Applications Need Background WorkflowsPicture this: a user drops a 40-page PDF into your app and asks for a summary. Or they connect a GitHub repo and expect an AI-generated wiki a few seconds later. Or they open a PR and expect an AI cod01R
SSSunney Soodinsunneysood.hashnode.dev·Sep 11 · 26 min readHow Large Language Models Actually Work: From Your Prompt to Every Word They WriteA complete, plain-English mental model — from tokens to attention to the exact moment ChatGPT picks its next word. When you type a question into ChatGPT and an answer appears a few seconds later, it00
Ttechpotionsintechpotions.hashnode.dev·Sep 11 · 5 min readWhen to Use an Open Source Model Instead of a Frontier APIOriginally published at techpotions.com. The open-source model vs API decision isn't a religious war, it's a practical trade-off every founder must make when adding AI features. Our team at techpotion00