A partnership with OpenAI will let podcasters replicate their voices to automatically create foreign-language versions of their shows.
A partnership with OpenAI will let podcasters replicate their voices to automatically create foreign-language versions of their shows.
A large language model took a 3 second snippet of a voice and extrapolated from that the whole spoken English lexicon from that voice in a way that was indistinguishable from the real person to banking voice verification algorithms.
We are so far beyond what you think of when we say the word AI, because we replaced the underlying thing that it is without most people realizing it. The speed of large language models progress at current is mind boggling.
These models when shown FMRI data for a patient, can figure out what image the patient is looking at, and then render it. Patient looks at a picture of a giraffe in a jungle, and the model renders it having never before seen a giraffe… from brain scan data, in real time.
Not good enough? The same FMRI data was examined in real time by a large language model while a patient was watching a short movie and asked to think about what they saw in words. The sentence the person thought, was rendered as English sentences by the model, in real time, looking at fMRI data.
That’s a step from reading dreams and that too will happen inside 20 months.
We, are very much there.
Sources?
Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding: https://aiimpacts.org/2022-expert-survey-on-progress-in-ai/
High-resolution image reconstruction with latent diffusion models from human brain activity: https://www.biorxiv.org/content/10.1101/2022.11.18.517004v3
Semantic reconstruction of continuous language from non-invasive brain recordings: https://www.biorxiv.org/content/10.1101/2022.09.29.509744v1
Interesting and scary to think ai understands the black box of human neurology more than we understand the black box of ai.