| I like your hachiko characterization of a patient and loyal car. That level of automation would be nice, I find cars to be a chore sometimes. What I'm trying to get at is deeper. I guess it's a question of philosophical form. Can you grow an software package to the point of transcending a looped format? Usually a program has our goals and desires established in the coding process and we may through in some qualitative checking functions. We then compile it into a binary form that runs on a CPU that has a clock. That CPU always runs, and the human relevant meaning in the code like function names, the human interpretation of images, video, maps and sound was evaporated only leaving streams of binary. The binary flows through logic gates that act like plumbing tools. The tools can check their own output and proceed down different qualitative paths. ML as a form grinds out the problem of optimizing the path through those logic gates against qualitative checks. Then we store the working model and loop it at runtime. So why can you give a human the idea 'making cars can be sold and get you laid' and the human will change their entire career, living location and lifestyle to suit a better economic output, but the program cannot reason/create a form that is not a loop? If we give a car body sensors and body 'brains' it can synthesize many different perspectives at once. Tactile door handles could give fingerprint/heartbeat/temperature senses on the human driver, as one tiny example. You could program in assumptions about what a high temperature human needs and wants. You could give the car every kind of imaging sensor, air quality sensors, moisture level sensors. You could track and synthesize all that data across time and evolve in a sense for when it's going to rain like ants have, or whatever. It could 'feel' the world. But it would still be that sheepdog waiting at home. Could it anticipate your needs? Only as a historical projection and whatever you program in. Can you infer human intent, thought or value from sensors? Computer vision applied to human faces or voices? I don't think so. Humans use different forms of language to transmit intent, values, stories, feelings. The idea that we could have a language or sensor inference that we talk to the car with that will perceive and adapt to the conflict our own mind is wrestling with and seeks to solve is difficult. Google's automated hair dressing appointment booker is cool, it is extending the breadth of voice commands a computer can respond to without having to understand what the words mean or the conflicts implied in understanding their meaning but only how they should be plumbed around as electric bits. I guess the endless hope is that we just have enough quantity of processed information we can build a machine that you can interface with, it'll solve the problem and that you don't need to know how the innards of the machine work. Which always seems like a plausible goal until it isn't. Web apps break, the internet can behave unpredictably, washing machines require cleaning and soap/ washing knowledge, cars break. Stuff that can be ignored is usually because we pay others to fix the problems quietly. Shifting the burden of understanding how to deal with looped quantative machines to the capatalist/currency system, another quantative system. The challenge of allowing a human to ignore the new loops one must learn the structure of and thus be able to say the machine 'understands' me instead of I having to understand it, is a forever doomed hope that we benefit from trying to solve. |
This looping, CPU, "programming it in", and app concept are not the direction machine learning is going in. That's not how deep learning and neural networks work. You can integrate them with an app and do looping yes, but you can also just connect them to each other. No looping, no "programming it in", no apps.