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Artificial intelligence has made great strides in recent years, and one of the most disruptive innovations in this sector is represented by AI models called Large Language Models (LLM). An AI model is a mathematical system based on artificial intelligence algorithms that analyzes data, learns from it, and makes predictions or content generations.
LLMs are transforming the way we interact with technology and opening up new perspectives in many fields. But what exactly are LLMs and how do they impact the world of technology?
What are LLMs?
Large Language Models (LLMs) are artificial intelligence models based on large-scale neural networks, trained on huge amounts of text to understand and generate natural language. They are built on advanced deep learning architectures, such as Transformers, introduced by Google in 2017, and work by predicting which word should come after another in a text, based on huge amounts of data. (If you want to learn more about how it works, I recommend the article How ChatGPT works? Tokenization).
Thanks to advances in machine learning and the availability of large-scale data, LLMs can now:
✅ Writing complex texts
✅ Answering questions in natural language
✅ Translate languages with high precision
✅ Generate code and assist developers
✅ Analyze data and provide real-time insights
Some of the more advanced models include GPT-4 (OpenAI - which ChatGPT is based on), Gemini (Google DeepMind), LLaMA (Meta), and Claude (Anthropic).
Why are LLMs revolutionizing technology?
Imagine working in a company and having to write a complex report in a few minutes. Or being a developer who needs help fixing a bug in the code. Or having to instantly translate a technical document into multiple languages. Until a few years ago, all of this would have required time and specific skills, but today there is an artificial intelligence capable of doing it for us: LLMs (Large Language Models).
In recent years, artificial intelligence has come a long way, with models specializing in different tasks: some recognize images, others generate music, and still others predict financial data. However, one type of AI model has taken over due to its extraordinary capabilities: Large Language Models (LLMs). These models are used to understand and generate natural language in an advanced way (such as ChatGPT), transforming the way we interact with technology.
In what context do they fit?
LLMs are part of the broader category of generative AI, which includes models that can create original content, from writing and music to images and videos. The world's largest technology companies are investing billions of dollars in developing these models to make them more powerful and accessible.
Today, LLMs are used in:
💬 Conversational chatbots (e.g. ChatGPT, Gemini, Claude)
🖥 Virtual assistants (e.g. Microsoft Copilot)
🌎 Translation systems (e.g. DeepL, Google Translate)
🖥 Developer tools (e.g. GitHub Copilot, Amazon CodeWhisperer)
💼 Business and market analysis (e.g. AI tools for business intelligence)
Additionally, LLMs find application in highly specialized fields, such as medicine, law and finance, where they are used to analyze complex documents and provide decision support.
Concrete examples of use
🔹 Healthcare: IBM Watson uses AI models to analyze medical records and suggest diagnoses. Google is piloting Med-PaLM, an LLM specializing in medicine.
🔹 Law: Some law firms use LLM to analyze thousands of pages of documents and identify key information in seconds.
🔹 E-commerce and customer service: Companies like Amazon and Shopify use LLM to improve customer service with advanced chatbots that can answer users' questions more naturally and effectively.
🔹 Finance: Bloomberg has developed BloombergGPT, an AI model specialized in analyzing financial data to support investment decisions.
Why couldn't we do without it anymore?
LLMs are changing our relationship with technology for several reasons:
1️⃣ Increased productivity – Automate complex tasks, reducing production times and costs.
2️⃣ Accessibility of AI – LLM-based tools allow anyone to harness the power of AI, even without technical skills.
3️⃣ Transforming Work – In many industries, LLMs are eliminating repetitive tasks, allowing people to focus on more strategic tasks.
4️⃣ Continuous Evolution – With increasing computing power and new training methods, LLMs are becoming increasingly sophisticated and capable.
The challenges and risks of LLMs
Despite their enormous potential, LLMs also present significant challenges:
⚠️ Data Bias – Being trained on existing texts, they may reflect biases present in the starting data (e.g. favoring certain ethnicities, continental areas or sexual genders).
⚠️ Disinformation – They can generate false or inaccurate content with convincing language, increasing the risk of fake news.
⚠️ Privacy and Security – The use of sensitive data in models raises privacy protection and regulatory compliance issues.
⚠️ AI Addiction – Overuse of LLMs could reduce people’s critical thinking and autonomous analysis skills.
⚠️ AI Hallucinations – LLMs can generate completely fabricated or inaccurate information, even when expressed convincingly. This is because the model does not have “knowledge” in the human sense of the word, but simply predicts the next word based on training data.
Hallucinations can be particularly problematic in fields such as medicine and law, where a mistake could have serious consequences. For this reason, companies such as OpenAI and Google are working to reduce the problem, implementing data verification mechanisms and improving the way LLMs access reliable sources (for example through the use of RAG, which we discussed in the article Overcoming static AI models with RAG).
To address these challenges, it is essential to develop ethical regulations and monitoring systems, ensuring that LLMs are used responsibly.
Observations on the future
Large Language Models are revolutionizing the world of technology, bringing extraordinary innovations to several sectors. However, their use also poses crucial challenges that must be carefully addressed.
The future of generative AI will depend on our ability to balance innovation and responsibility, ensuring that these tools are used to improve society without compromising safety and reliability.
🚀 We are only at the beginning of this revolution: the potential of LLMs is immense and their impact will only grow in the coming years.
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