Artificial intelligence isn't just changing the world; it's creating an entire new language to describe how it does so. If you spend just five minutes reading about this field, you'll encounter a barrage of acronyms like LLMs, RAG, RLHF, and other terms that might leave even the most tech-savvy people like you (my friend) feeling a bit confused. We at Phonegram, as enthusiasts of all things cutting-edge, decided to put an end to this confusion and provide you with a simplified guide that clearly explains these terms, so you're fully aware of what's happening behind the scenes of this technological revolution.
Large Language Models (LLM)
The term we hear every day is Large Language Models (LLM)This is the engine that powers tools like ChatGPT, Cloud, and Gemini. These models are deep neural networks containing billions of numerical parameters (weights) that learn the relationships between words and phrases. They are created by processing patterns found in billions of books and articles, allowing them to generate texts that closely resemble human writing.
deep learning (Deep Learning)
These models are based on Deep LearningDeep learning is a branch of machine learning inspired by the structure of neurons in the human brain. Its power lies in the ability of algorithms to identify important features in data on their own, without human intervention. Of course, this requires immense computing power, relying on advanced graphics processing units (GPUs), which explains the fierce competition among companies to acquire as many of these devices as possible.
Artificial General Intelligence (AGI)
Let's start with the most controversial term, artificial general intelligence or AGIThis term refers to a type of artificial intelligence that surpasses humans in most cognitive tasks. Some describe it as a fully autonomous system capable of easily performing human work, while others see it as a super-intelligent digital colleague. The truth is that experts themselves still debate its precise definition, but it represents the ultimate goal pursued by companies like OpenAI and Google.
Smart agents (AI Agent)
As for Intelligent Agent (AI Agent)It's a more practical step; it's not just a chatbot you reply to, but a tool that uses artificial intelligence to perform a series of tasks on your behalf. Imagine a digital assistant on your iPhone that can book flights, manage your expenses, or even write and debug code independently. This intelligent agent goes beyond mere words to action, connecting multiple systems to accomplish complex, multi-step tasks.
In a related context, we find Coding AgentsThese are the specialized version of intelligent agents in the software development field. Instead of suggesting code for you to copy, a programming agent can write, test, and debug code completely independently. Imagine hiring an incredibly fast, sleep-deprived, and focused trainee who can handle entire databases and fix bugs with minimal human intervention.
Chain of Thought
Have you ever faced a difficult math problem and needed to use pen and paper to break it down into smaller steps? That's exactly what artificial intelligence does when using technology. Chain of ThoughtInstead of giving an immediate, potentially incorrect answer, the model breaks down the problem into logical intermediate steps. This approach takes slightly longer, but it ensures more accurate results, especially in complex logic or programming problems.
Hallucinations: The Dark Side of Artificial Intelligence
Despite all this intelligence, artificial intelligence still falls into a trap. HallucinationThis seemingly innocuous technical term simply means that the model fabricates entirely false information and presents it with excessive confidence. Hallucinations pose a significant quality challenge and can be particularly dangerous in fields such as medical consulting. This problem typically arises from gaps in training data, leading companies to focus on more specialized models to mitigate the risk of misinformation.
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