🤖 Hello, this is CLEVI.
I attended the 「2025 JBNU Research Fair Week」 event hosted by Jeonbuk National University from 20 to 22 January.
This event was a meaningful opportunity to showcase the direction of future technologies linked to industrial and national strategies, centred on Jeonbuk National University’s outstanding research achievements, and to provide a forum for exchange involving industry, academia, research institutes and government.
In particular, CLEVI CEO Lee Hwan-ho was invited as a VIP speaker at the opening ceremony held on the 20th! 👏
Let’s relive the atmosphere of that day!
Before the event began, this was CLEVI CEO Lee Hwan-ho preparing his presentation. You can see him thinking about how to make the talk more substantial and accessible.
The event began with the opening ceremony.
The event opened in style with a live art performance spontaneously completed by a Jeonbuk National University student.
After the first keynote speech, CLEVI CEO Lee Hwan-ho delivered the second keynote speech on the topic “Why Does AI Need a Physical Medium?” Let’s take a brief look.
How exactly does AI understand the world,
create sentences and even take action?
Let’s take a look inside the ‘brain’ of large language models (LLMs), such as ChatGPT and Claude, which we use every day, to understand the principles by which they understand and generate sentences.
- Assigning names (Token ID): AI first assigns every word a unique number, such as ‘5’ or ‘8’, to manage them.
- Pinning addresses on a map (Vector): However, a simple number is not enough to understand meaning, so each word is assigned a ‘detailed address (coordinate)’ made up of hundreds of numbers.
- Finding neighbours: Words with similar meanings (for example, ‘the’ and ‘a’) live close together on this map, like neighbours.
So how does AI predict the next word?
Now that we understand the basic data transformation, let’s look at the entire process of how these numbers become an actual sentence. Let’s assume that we have the input “Paris is the city...” here.
Tokenizer (breaking into pieces): As we saw earlier, the sentence we entered is converted into numbers (Token IDs) through the tokenizer. "Paris" becomes 1652, "is" becomes 5... and so on.
LLM (the enormous calculator): These bundles of numbers enter an enormous calculator called an LLM (the Bloom model shown in the image). Here, it uses the 'vector' operations we learned about earlier to understand the context. It recognises, "Ah, we’re talking about the city of Paris!"
Logits & Softmax (calculating probabilities): After completing its calculations, the AI assigns scores to tens of thousands of possible words that could come next. It then passes these through a filter called 'softmax' to convert them into **'probabilities'** that are easier for us to understand.
Final selection: Look at the graph on the right.
- of → 33.7%
- that → 15.3%
- where → 9.4%
Ultimately, the AI selects **'of'**, which has the highest probability, and completes the sentence "Paris is the city of...". It repeats this process tens of thousands of times to generate the long answers we see.
In conclusion, for AI, remembering a word does not mean memorising the letters. It is more like remembering the 'address' of where that word lives on a vast map of meaning.
LLMs can be expanded through vision, robotics and behavioural learning.
AI that understands meaning, sees and understands, and acts.
Giving AI arms and legs means expanding intelligence from language to perception, and further into action.
AI is no longer just a realm of ideas or imagination; it has entered the stage of implementation and reality.
CLEVI’s next step
CLEVI plans to continue expanding a range of opportunities, including on- and off-campus workshops, hands-on projects and experience booths, so that more people can directly experience how AI technology works in the real world.
Just as this lecture at Jeonbuk National University became a valuable bridge connecting the students and us, we will continue to serve as a bridge between technologists and users, and between academia and industry.