Gavriel Amati

The GenAI Divide: State of AI in Business 2025 - Industry Reactions and Reality Check

Despite massive hype, most corporate AI initiatives are failing. While 80% of companies pilot generative AI tools, only 5% generate millions in actual business value. This gap between promise and performance is the "GenAI Divide." Economic Potential vs. Reality: * AI could boost global GDP by 15 percentage points

AI Chatbot Conversations Archive

The LMSYS-Chat-1M dataset exposed the sheer scale of modern chatbot interactions, 1 million real-world conversations from 210,000 unique users with state-of-the-art language models. This revelation is a window into the massive infrastructure quietly recording every exchange between humans and AI systems worldwide. Behind every chatbot interaction lies an archive;

Grok 5: What We Expect

Elon Musk recently dropped a bombshell claim that sent ripples through the AI community: Grok 5 has a "10% and rising" chance of achieving AGI—or something indistinguishable from it. This isn't just another tech CEO making bold predictions; it's a direct challenge to

Unstable Diffusion: The Uncensored AI Silicon Valley Won't Touch

In August 2022, a Discord community launched what would become one of AI's most controversial projects: an "uncensored" image generator that grew to 350,000+ users generating half a million images daily. Yet it couldn't raise money on mainstream platforms. This is the story

Edge AI Implementations: A Practical Guide

97% of CIOs now have Edge AI on their roadmap, intelligence is moving from cloud data centers to the devices around us. From factory floors where split-second decisions prevent costly downtime to autonomous vehicles navigating busy streets, artificial intelligence is migrating to where data originates. This shift is a transformation

GPT-5 Context Window: The AI Memory Revolution That Changes Everything

Like Moore's Law transformed computing power, context windows in AI have been doubling every year, and GPT-5's massive 400K-token leap represents the most dramatic expansion yet. This isn't just another incremental upgrade; it's a fundamental shift in what artificial intelligence can process,

Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights Synthesis

What if you could customize an AI model in seconds, just by describing what you want it to do? This is the revolutionary promise of Drag-and-Drop LLMs, a breakthrough approach that transforms how we adapt language models for specific tasks. Traditional model fine-tuning through methods like LoRA requires hours of

Composer: What Cursor's New Coding Model Means for LLMs

Cursor just released Composer, an AI model that completes coding tasks in under 30 seconds, 4× faster than comparable systems, and it's trained inside real codebases using reinforcement learning. This isn't merely an incremental improvement to existing AI coding assistants; Composer represents a fundamental shift from

text-embedding-3-small: High-Quality Embeddings at Scale

OpenAI pulled off an impressive feat: they made embeddings both better AND 5× cheaper, a model that outperforms its predecessor by 13% while costing just $0.02 per million tokens. This breakthrough, known as text-embedding-3-small, transforms text into 1536-dimensional vectors for semantic search, clustering, and RAG applications, an exponential increase

The GenAI Divide: State of AI in Business 2025 - Industry Reactions and Reality Check

AI Chatbot Conversations Archive

Grok 5: What We Expect

Unstable Diffusion: The Uncensored AI Silicon Valley Won't Touch

Edge AI Implementations: A Practical Guide

GPT-5 Context Window: The AI Memory Revolution That Changes Everything

Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights Synthesis

Composer: What Cursor's New Coding Model Means for LLMs

text-embedding-3-small: High-Quality Embeddings at Scale

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