Language Models

By connecting the global datasphere with computer vision, machine learning, and language modeling, computer science has paved the way for artificial intelligence.

Machines have long used human logic to automate routine and AI is not new, so why has this form of knowledge engineering earned so much attention lately? It’s because AI has learned to speak our language.

Language modeling has taught our digital counterparts how to articulate what it already knows. Not in some robotic, 8-bit voice. AI is now conversational. For example, chatbots are informative, engaging, and entertaining humanoids, while generative AI uses neural networking to transform simple prompts into impressive visuals.

When innovation threatens the status quo, a common response is fear followed by complacency. This is evident in the argument that AI will take all our jobs. Yes, advancing technology will continue to reduce the need for humans to turn knobs and here’s a 2023 Cornell University study on how large language models may impact labor markets. Gone are the days of clocking in on time and keeping your head down just long enough to climb a ladder built to resist change. The willingness to play it safe may extend a sense of temporary security, but this is a choice that makes you easy to replace with cheaper labor and faster tools. To remain indispensable, let AI dine on the dull, devour inefficiencies, and support our own ingenuity.

Start a journey before you see the end. Knowledge is required, but for students, intrapreneurs, and entrepreneurs who stay creative, it’s impossible to compete with being you! As AI munches on mediocre, more of us are invited to build without a map. To make a ruckus with no permission required. To do something for the love of doing it and to care enough to fail.

AI won’t take your job. People who use AI will. It’s a lousy time to be complacent and the perfect time to be creative.

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