171–180 of 268 posts
I've been arguing this is the way AI should be deployed. Rather than trying to sell ai as an end to end solution, just let it do the small part that it can reliably do. It's cost effective for the host, and valuable for the user. win win engineering!
Earlier quoted context omitted.
I know it's infuriating but that's how marketing works, and since they are a successful company, idk why they would stop using it. Just like some people say "RTX" instead of RayTracing now, it's quite a success for the company if it managed to replace a technical term in the mind of most consumers
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Everyone's asking tech details and "how", but I wonder about the "why". Do we want LLMs to always write for us, or whisper in our ear what to say? By design LLMs tend toward the most commonplace, mainstream ideas and ways of saying things. They're not much for originality or human idiosyncracy. Are we engineering a bland world full of pablum?
This isn't to say a human element doesn't have a ton to offer! Just to say that we aren't necessarily engineering a bland world of pablum, either.
If you take an iOS simulator, turn off "Settings > General > Keyboard > Predictive", reboot it and then watch the console logs as you turn that switch back on, you'll see the "kbd" process load the models out of that bundle.
Everyone's asking tech details and "how", but I wonder about the "why". Do we want LLMs to always write for us, or whisper in our ear what to say? By design LLMs tend toward the most commonplace, mainstream ideas and ways of saying things. They're not much for originality or human idiosyncracy. Are we engineering a bland world full of pablum?
"Bing Chat's" implementation already allows you to select more creative generation of text. It's just a radio button option. There are also different technical solutions for the LLM to select which word to generate that allow either for more interesting, or more predictable, words. This isn't to say a human element doesn't have a ton to offer! Just to say that we aren't necessarily engineering a bland world of pablum…
E.g. try asking an LLM to name a real, non-famous person. The internet and it's training corpus is full of regular people, but you won't have much luck - they're statistically too uncommon to remember.
Everyone's asking tech details and "how", but I wonder about the "why". Do we want LLMs to always write for us, or whisper in our ear what to say? By design LLMs tend toward the most commonplace, mainstream ideas and ways of saying things. They're not much for originality or human idiosyncracy. Are we engineering a bland world full of pablum?
I really look forward to using GPT to help me throw together RFCs, documentation, announcement letters, daily standup write ups and other artifacts like that that prevent me from getting actual work done.
Everyone's asking tech details and "how", but I wonder about the "why". Do we want LLMs to always write for us, or whisper in our ear what to say? By design LLMs tend toward the most commonplace, mainstream ideas and ways of saying things. They're not much for originality or human idiosyncracy. Are we engineering a bland world full of pablum?
Think of it like spellcheck : the vast majority of the time it produces desired results, but if you really want to type bjPvc9fQ, you certainly can.
Everyone's asking tech details and "how", but I wonder about the "why". Do we want LLMs to always write for us, or whisper in our ear what to say? By design LLMs tend toward the most commonplace, mainstream ideas and ways of saying things. They're not much for originality or human idiosyncracy. Are we engineering a bland world full of pablum?
If the suggestion doesn't match what you were already planning on saying, you just ignore it.
The human desire to be original and authentic is always going to be stronger.
(It's much less effort to ignore it and keep typing your original thought, than it is to think about it, compare with what you were going to say, decide its version is better, and then accept it.)
Everyone's asking tech details and "how", but I wonder about the "why". Do we want LLMs to always write for us, or whisper in our ear what to say? By design LLMs tend toward the most commonplace, mainstream ideas and ways of saying things. They're not much for originality or human idiosyncracy. Are we engineering a bland world full of pablum?
Most human communication is bland, and people who make a point of being unpredictable and shocking are usually pretty annoying. Think of it like spellcheck : the vast majority of the time it produces desired results, but if you really want to type bjPvc9fQ, you certainly can.
Earlier quoted context omitted.
"Bing Chat's" implementation already allows you to select more creative generation of text. It's just a radio button option. There are also different technical solutions for the LLM to select which word to generate that allow either for more interesting, or more predictable, words. This isn't to say a human element doesn't have a ton to offer! Just to say that we aren't necessarily engineering a bland world of pablum…
That's just temperature, which evens out the random probability a little of the N most probable next words. It's still vastly favoring the N most common ones based on the training corpus, and will have a hard time producing uncommon ones. E.g. try asking an LLM to name a real, non-famous person. The internet and it's training corpus is full of regular people, but you won't have much luck - they're statistically too u…
Source? A MS exec said that creative and precise are GPT4 but balanced is a not (or not 100%): https://twitter.com/MParakhin/status/1693579775590224097