Will LLM lead to artificial general intelligence, AGI?

"Artificial general intelligence (AGI) is a type of highly autonomous artificial intelligence (AI) intended to match or surpass human capabilities across most or all economically valuable cognitive work. This contrasts with narrow AI, which is limited to specific tasks.[1] Artificial superintelligence (ASI), on the other hand, refers to AGI that greatly exceeds human cognitive capabilities. AGI is considered one of the definitions of strong AI." (Wikipedia, Artificial general intelligence)

When we think about the AGI and its relationship with humans we can say that the AGI is only an extremely large language model, LLM. That means that to turn into AGI the LLM requires only an extremely large database structure. That kind of database structure is hard to drive. But it's possible. The AGI makes "droplets" of the small language model, SML for each mission. 

We can put all our equipment under the control of the large language model, LLM. Those systems require the computer and socket that the LLM can use to control them. In the traditional model, every single device and system. that we have can involve the computer the system that drives the vehicle on the road or cleans our house. The artificial general intelligence, AGI requires those sockets to control the vehicle. When the user says "Car come here" the AGI locates the person. And gives instructions to the vehicle that drives to pick up the person. 

In that model, the AGI requires that we update all things. That we have. But then we can make another way to create things. That thing is a humanoid robot that has an extremely large database structure. That system can operate in every situation that we can. So, we can say that the AGI is only a large-scale LLM. The robot has only a small computer. However, the internet allows it to communicate with data centers. When a robot gets a new mission the data center generates the data structure or dataset that the robot needs. 

And then creates a more limited, but compact database for that robot. In that model, the LLM creates a series of SLMs to make the robot operate in situations like visiting shops. 

The robot can use three, or four datasets in that mission. 

First, the robot must go out. Then it deletes the "home" dataset and uploads the "walk to shop dataset". 

At the shop, the robot changes the dataset to "operate at the shop". 

Then it changes the dataset to "go home and carry things that you bought". And finally, the last needed dataset involves data that the robot must do when it takes its shopping to the kitchen. In this model, every skill. That the robot has a different database structure or dataset. The central computer cuts a small part of its master data to the dataset series that the robot needs for missions. The humanoid robot is the thing. That can use all kinds of stuff. 

The system can use old-fashioned cars, trucks, and hovering machines. And we can say that the humanoid robot is the socket that can connect everything to the Internet. The robot can use machine learning to find new skills. If a robot must fix the TV it must only know the model of the TV. And then it makes checks like cable checks and other things. Just like humans. 

When we talk about AGI we must realize that even humans cannot do everything. We need to practice everything. When we face some system that is unknown to us, we must read instructions. When a robot learns something it creates a new dataset. And if some data center handles thousands of robots one of them can learn new things and then the system can scale that dataset all over the network. 

Will LLM lead to artificial general intelligence, AGI? That is a good question. The answer depends on what we mean about the AGI. If we think about the situation we can use every single vehicle, that we see. From microwave ovens to taxi cars and street sweeper robots using the AI that asks when we want that street sweeper to clean our yard and robot taxi when it comes to get us we can say that the LLM can be the AGI. The street-sweeping robot can also ask if we need help with our baggage and maybe that same robot can cut our hair. 

Then we must say that the robot that we see in front of us can make everything that we ask. It can turn to cab drivers cutting our hair cleaning our homes and making pizza for us. That kind of robot has a large scale of skills that it can use in every situation. Every skill that a robot has is a database in a large database structure. The central computer can upload the right dataset to a robot. That it controls. 

When we think about the order "pick up my baggage and take them to the car and then drive car to pick me up". The fast internet makes it possible to download and change needed datasets in the robot computer's memory. In that case, the AI. That control's robot. Creates a small language model, SLM for each stage of the mission. The SLM is a compact, reflex version of the LLM. The system can use SLM in cases where the robot requires fast reactions. 

https://scitechdaily.com/quantum-computers-just-got-smart-enough-to-study-their-own-entanglement/

https://en.wikipedia.org/wiki/Artificial_general_intelligence