Hype untangled
My mind has been swamped by the amount of information, hype, misinformation, hype, advice, hype, chaos, hype, progress, and hype. Staying sane and calm while on top of the news is hard.
I now adapt on-the-fly translations to help me distinguish the vocabulary used by the media or other CS papers, and my own interpretation of those words. Cognitive science or psychology people are usually more careful when dealing with these concepts than the CS folks. And anthropomorphizing computer programs, as far as in the media and the papers, is an unfortunate and unproductive namespace pollution/inflation. These words are so ill-defined in the CS context that replacing them actually incurs zero loss of communication. Try:
- Replace “intelligent” with “good” or “smart”
- This intelligent model boosts your work productivity. → This is a good model that boosts your work productivity.
- This intelligent coding model gets pretty much everything done for you. → This good coding model gets pretty much everything done for you.
- Self-reflection is a unique skill core to intelligent systems. → Self-reflection is a unique skill core to smart systems.
- Replace “reasoning” with “do something complex”. We can keep well-defined ones like “deductive reasoning” or “logical reasoning”.
- A visual reasoning task → do something complex with visual inputs
- Chain-of-thought reasoning → generating long, somewhat connected, sequences to do something complex
- A reasoning model → a model that does something complex
- Replace “agent” with “someone that gets things done”. And the “someone” here can refer to a human or a computer program.
- Our best intelligent multi-agent AI will cater to your business needs 24/7. → Our smart team of people/programs who gets things done will cater to your business needs 24/7.
To go one step further, I didn’t really like “learning” in “machine learning” when I first encounter it: what does it even mean for a machine to “learn”? Is it “explain a bunch of generated/curated data with a model”? Then it should be statistics, not the way kids (or adults) actually go through in an education, by acquiring information (I will constrain myself from using inflated words like “knowledge”) mostly second-hand like how we read from textbook about dinosaurs (no human have ever seen them), Antarctica (few of us have been there), or all kinds of abstract ideologies.
I also have a complaint with “artificial intelligence”: not only is it poorly defined, but also it is egotistic - it sort of implies that, only, we humans have intelligence, and everything else is either not smart enough, or artificial (created by us), but what about the dolphins, the aliens? That said, I have no better alternative right now.
I can empathize with the desire to anthropomorphize non-human activities though - we are a lonely species, blessed and cursed with the motivation to understand itself. Yet messing up with the vocabulary is counterproductive to achieving that goal, however convenient/compiling/attractive that is to an investor, a funding agency, a customer, and the public.