This Plug-and-Play AI Memory Works With Any Model
Author(s): MKWriteshere Originally published on Towards AI. Memory Decoder instantly adds domain expertise to GPT, Claude, Llama, and any language model family Your startup needs GPT-4 to understand medical terminology. Your fintech app requires Claude to grasp financial jargon. Image by AuthorThis …
New Study: AI Models Fail at Basic Human Psychology Despite $50 Million Investment
Author(s): MKWriteshere Originally published on Towards AI. Bielefeld University research reveals why AI can’t replace humans in psychological studies Sarah Schröder knew something was wrong the moment she saw the results. Image Generated by Author Using GPT-5 ThinkingIn this article, researcher Sarah …
How AI Exposed 75 Years of Housing Discrimination Hidden in 5.2 Million Property Records
Author(s): MKWriteshere Originally published on Towards AI. A technical deep dive into Stanford’s fine-tuned language model that saved 86,500 hours of manual work and revealed shocking patterns of racial exclusion Imagine discovering that one in four properties in your county was once …
Why Your Data Lake Needs BLM, Not LLM
Author(s): MKWriteshere Originally published on Towards AI. The “Godfather of Data Warehousing” reveals why LLM can’t solve enterprise text analytics. Your $15+ billion data lake investment just became a liability. Image Generated by Author Using Gpt-4oThis article highlights the failures of current …
Why Context Engineering Matters More Than Prompt Engineering
Author(s): MKWriteshere Originally published on Towards AI. Master the emerging discipline that’s becoming the #1 skill for AI developers building production agents Your AI agent just burned through 500,000 tokens in a single session. The bill hit several dollars. The performance degraded …
Authors v. Anthropic: How 7 Million Books Redefined AI Copyright Law
Author(s): MKWriteshere Originally published on Towards AI. Why Anthropic’s partial legal victory changes everything for AI development A landmark court ruling just redefined how AI companies can use copyrighted content. Here’s what every developer and tech professional needs to know. Generated by …
From Bytes to Ideas: LLMs Without Tokenization
Author(s): MKWriteshere Originally published on Towards AI. Meta’s AU-Net eliminates the 30-year bottleneck that breaks every language model Your AI chatbot struggles with typos. It can’t handle new languages without expensive retraining. And it needs a massive dictionary to understand basic words. …
Sufficient Context: A New Lens on RAG Hallucination Problems
Author(s): MKWriteshere Originally published on Towards AI. New research reveals the hidden flaw in RAG systems that makes even GPT-4 and Claude hallucinate You ask your AI assistant about a recent news event, providing comprehensive context from reliable sources. The AI responds …
Why Andrej Karpathy Says Software 3.0 is eating 1.0 and 2.0
Author(s): MKWriteshere Originally published on Towards AI. The Tesla AI architect predicts Software 3.0 will replace most code you write today You spend hours debugging syntax errors. You wrestle with complex frameworks. You translate business requirements into thousands of lines of code. …
Why Large Language Models Are Surprisingly Easy to Hack
Author(s): MKWriteshere Originally published on Towards AI. New research shows that AI systems costing millions to build can be fooled by simple tricks that require no technical knowledge whatsoever Your AI assistant just cost you $5,000. Image Generated by Author using Gpt-4oThe …
A Production Engineer’s Guide to Shipping LLMs That Work
Author(s): MKWriteshere Originally published on Towards AI. Why experienced developers delete frameworks, avoid fine-tuning, and ship faster using surprisingly simple principles Building with LLMs feels like navigating a minefield of overhyped frameworks and premature optimization. Image Source : framerusercontent.comThis article delves into …
Reinforcement Pre-Training: Teaching AI to Think Instead of Memorize
Author(s): MKWriteshere Originally published on Towards AI. Microsoft’s reasoning-first approach transforms how AI learns, making smaller models more capable than larger ones Microsoft Research has introduced Reinforcement Pre-Training (RPT), a method that transforms how language models learn. Figure 1 from Research paperThe …
How Qwen3 Embedding Beat Google at Its Own RAG Game
Author(s): MKWriteshere Originally published on Towards AI. Inside Qwen3’s Secret Recipe for State-of-Art Text Embeddings Just as DNA sequencing revolutionized biology by revealing the genetic code that connects all life, Qwen3 Embedding revolutionizes artificial intelligence by decoding the genetic structure of meaning …
When AI Speaks in Tongues: The Hidden Languages of Tomorrow
Author(s): MKWriteshere Originally published on Towards AI. What happens when machines start having conversations we can’t understand? Imagine walking into a room where two colleagues are deep in conversation, but instead of words, they’re exchanging rapid-fire gibberish that somehow makes perfect sense …
We’re Back to Square One: Why AI is Forcing Us to Reinvent Programming Languages (Again)
Author(s): MKWriteshere Originally published on Towards AI. How artificial intelligence brought us full circle to the same problems that created programming languages in the first place Imagine you’re trying to give directions to someone who speaks your language perfectly but has never …
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