Aalto AI Assistant
A chat-based application powered by the same language models as ChatGPT
We leverage the potential of data, analytics and AI to enhance efficiency and decision-making
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Below are the core AI concepts used in Aalto and how they relate to everyday work.
| Term | Description | Main task | Role of the user |
| AI (Artificial Intelligence) | Umbrella term for all AI technologies, such as spam filters or recommendation systems. | Analyses data and makes predictions or inferences based on it. | Uses system recommendations to support decision-making. |
| GenAI (Generative AI) | Subfield of AI specialised in producing new content, e.g. text, images or code (such as ChatGPT). | Creates new content based on statistical probabilities. | Designs precise prompts and critically evaluates results, including possible hallucinations. |
| AI Agent | Autonomous actor that uses AI to perform tasks. | Executes multi-step task chains independently. | Defines the goal, selects tools and monitors that the process succeeds. |
AI is a broad term for computer systems that can reason based on the information they receive and produce results such as predictions, content, recommendations or decisions. A key characteristic is that the system operates with a certain level of autonomy to reach a given goal. Because AI works with statistics and probabilities instead of fixed rules, its outputs always contain some uncertainty and the system can sometimes make mistakes.
Unlike traditional software, which only executes predefined commands, AI systems are trained to recognise patterns in large datasets and can apply what they have learned to new, previously unseen situations. Everyday examples include spam filters, route suggestions from search and navigation tools, or systems that generate sales forecasts from historical data.
Generative AI is a subfield of AI specialised in creating completely new content such as text, images, code or audio. It is based on large language models (LLMs) that have been trained on vast amounts of data.
Generative AI does not "understand" information in a human way. Instead, it calculates which word or element is most likely to follow another based on the given prompt. This probability-based mechanism means there is always a risk of hallucination: the system may invent facts that look very convincing if it lacks the right information.
Examples in everyday use include Microsoft Copilot or ChatGPT, which can be used to summarise long documents, draft emails or translate text.
AI agents build on generative AI capabilities. While a typical GenAI system acts as an assistant that responds to questions, an agent can work autonomously towards a defined goal.
An agent is given a goal and access to tools such as a web browser, spreadsheet or email. It can break down a broad task into smaller steps, execute them in a logical order and correct its own mistakes along the way.
An example: an agent is asked to "find the latest product launches from three competitors' websites, compile a comparison table and send a summary to our team channel". The agent performs these steps one after another without human intervention.
The AI intranet pages are organized into the following sections (see the side navigation):
If you are new to AI, the following resources are a good starting point:
Use these services in line with the guidelines in the "Work with AI" and other sections, and always review AI outputs critically.
A chat-based application powered by the same language models as ChatGPT
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Information on Aalto University's official and productized AI services
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