Transformer
The model architecture behind almost every modern AI system, introduced in 2017. Its trick is paying attention to how every word in a passage relates to every other, which is what made fluent machine writing possible.
angkor@design~query "Angkor Design"
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The model architecture behind almost every modern AI system, introduced in 2017. Its trick is paying attention to how every word in a passage relates to every other, which is what made fluent machine writing possible.
Turning spoken words into text. It underpins voice search, dictation and call transcription, and it now handles accents and background noise far better than it used to.
When a model gets worse over time because the world moved on and it did not. A pricing or demand model trained two years ago quietly stops matching how customers behave now.
When a system produces unfair results because its training data reflected an unfair world. It matters commercially as well as ethically: a biased model makes confidently wrong decisions about real people.
A system that suggests what somebody might want next based on behaviour — the “customers also bought” of an online shop. One of the oldest commercial uses of machine learning.
Perplexity’s crawler. Perplexity cites its sources prominently, so being readable by it is one of the more direct routes to a visible citation.
An open standard for connecting AI assistants to outside tools and data in a consistent way. It matters to businesses because it is how an assistant might one day query your booking system directly.