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Why are foundation models different?
The way foundation models are trained solves one of the biggest bottlenecks in AI: labeling data.
This is traditionally how AI models are trained; using data labeled by humans.
Its a time-consuming process and requires many humans to label data.
Foundation models dont need this bang out of labeling.
This makes foundation models more accessible for industries that dont already have a wide-range of data available.
But foundation models are not limited to human language.
Emergent properties
Foundation models are characterized by two very interesting properties: emergence and homogenization.
Emergence means new unexpected properties that models show which were not available in previous generations.
It typically happens when model sizes grow.
But foundation models are not limited to human language.
Lets unpack that with an example.
Physics and chemistry dictate that molecules can exist only in certain configurations.
The next step would be to define a use for molecules, such as medicines.
drugs) interact with the human body when treating diseases.
Of course, models like these can also generate controversy.
However, as mentioned, this can at times produce unexpected results.
Of course, models like these generate controversy.
Theres also a case to be made about the energy use needed to train a large-scale model.
Will more advanced AI models take our jobs?
Well, yes and no.
The way most AI researchers see these models is as a tool.
Take IBMs foundation model Ansible Wisdom.
With it, developers can use natural language to ask the model to e.g.
suggest the ansible automation to deploy a new web server.
Agrawal thinks this will completely revolutionize programmers jobs.
The whole innovation cycle will accelerate thanks to AI.
Im sure it will double productivity in just a few years.
This use is similar to the electric screwdriver.
I think 80% of the US population used to be in farming.
Foundation models have the potential to change many processes which are now tedious or repetitive for humans.
They also offer the possibility for creating radical and unpredicted solutions to some of the hardest problems were facing.
In effect, foundation models could mean a complete paradigm shift in how knowledge is created and applied.
