As you have domain expertise you will agree with us that, despite not being AGI, as it is now, deep learning, reinforcement learning, generative AI are an incredible creation of humanity, that, among other things, are capable already of:

1. solving long standing scientific challenges such as protein folding,
2. taking independent decisions and develop strategies that, on specific tasks, surpass human experts
3. mapping human languages and artistic creations in high dimensional vector spaces where concepts and relationships are retained as properties of the spaces, allowing to perform math and statistical inference, generating original images and text (a thing for which, few decades ago, not many would have guessed such manageable mathematical representation could even exist).

On top of this we give for granted all the current already existing applications, such as image recognition, translation, text classification...

You would also agree with us that the potential of current AI methodologies in all fields of science and technology is already enormous, as demonstrated by alphafold for instance. We just need few more years to see even more groundbreaking applications of the exising methodologies, while we wait for even more powerful techniques or, why stop dreaming, AGI in few decades.