Can anyone tell me what the value of GPT-3 actually is other than generating meaningless prose? What would a business use it for
They can also all be adapted and fine tuned for other tasks in content classification, search, discovery etc. Think facnial recognition for topics. Want to mine a whole social network for anywhere people are talking about _______ even indirectly with very low false negative rate? You want to fine tune a transformer model.
Bert tends to get used for this more because it is freely available, established and not too expensive to fine tune but i suspect this is what microsoft licensing gpt-3 is all about.
Nice trick: write a comment describing quickly what your code will do (“// order an item on click”) and enjoy the complete suggested implementation !
Other nice trick: write the code yourself, and then just before your code, start a comment saying “// this code” and let copilot finishe the sentence with a judgement about your code like “// this code does not work in case x is negative”. Pretty fun !
Simply leading the horse to water is enough in something like PHP:
// instantiate cURL event from API URL, POST vars to it using key as variable name, store output in JSON array and pretty print to screen
Usually results in code that is 95-100% of the way done.
I'd love to use it but not when there's such a risk of compromising the code base.
I was a Jetbrains fan but this thing takes productivity to a whole new level. I really don't think I can go back to my normal programming without it anymore.
Why? 99.9% of programming being done is composition of trivial logical propositions, in some semantic context. The things we implement are trivial, unless you're thinking about symbolic proofs etc
> The fact that GPT3 works at all for English indicates that English is too low level and forces a lot of redundancy (low entropy).
I don't think the goal is to compress information/language and maximize "surprise".
https://sdtimes.com/monitor/using-gpt-3-for-root-cause-incid...
Of course this will be another blow for journalists, who rely on this skill for their income.
How would you tell the difference from the real thing these days?
You can use this instead of having to train a custom model for every specific task.
A good example is DALL-E[0]. Now, what's interesting to me is the emerging idea of "prompt engineering" where once you spend long enough with a model, you're able to ask it for some pretty specific results.
This gives us a foothold in creating interfaces whereby you can query things using natural language. It's not going to replace things like SQL tomorrow (or maybe ever?) but it certainly is promising.
Life online is about to become very annoying.
One example of GPT-3 powered chat bot: https://www.quickchat.ai/emerson
If you think about business uses you can actually get advices from Jerome Powell, simulated by GPT-3.
If someone use GPT-3 to simulate Warren Buffet, he can extract even more value.
https://www.institutionalinvestor.com/article/b1tktmhcfdyqsk...
> Interviewer: How do you think a global pandemic would impact the financial system?
> Mr. Powell: A pandemic will have impact on the economy. It will have an impact on the financial system.
> Interviewer: What would the impact be?
> Mr. Powell: If a major pandemic occurred, the economy would be affected, and the financial system would be affected.
Yes, GPT-3 can provide a convincing chatbot, but it shouldn't be confused for domain expertise.
> > Interviewer: What would the impact be? > Mr. Powell: If a major pandemic occurred)
Output( it could be very disruptive. > > Interviewer: How disruptive? > Mr. Powell: Well, it could be disruptive in a number of ways. > > Interviewer: How so? > Mr. Powell: Well, one of the first things that would be disrupted would be the supply chain. )
Using prompts well makes a huge difference.
If you parse the generated output, classify it, then develop a decision tree that uses further prompts to refine the response, you can get more sophisticated, valuable responses.
The output in the parent is comparable to an off-the-cuff interview response. If you emulate a deeper thought process, you can get more meaningful output, and if you use the right prompts, you can access the semantic networks in the model related to your domain of interest.
> Mr. Powell: I don’t want to get into the details of taxes.
> Interviewer: Are you in favor of a cap and trade system?
> Mr. Powell: I don’t want to get into the details of a cap and trade system.
> Interviewer: How do you think a global pandemic would impact the financial system?
> Mr. Powell: A pandemic will have impact on the economy. It will have an impact on the financial system.
> Interviewer: What would the impact be?
> Mr. Powell: If a major pandemic occurred, the economy would be affected, and the financial system would be affected.
Maybe I'm a bit harsh on GPT-3, but I'm not nearly as fascinated by this kind of output as the author.