The greatness of the Texas energy market is the fact that the grid goes down all the time. So deploy solar and a battery so you don’t die in the winter cold and the summer heat.
I just installed it yesterday and you are right it does not seem to have RAG but you can use something like anythingLLM to do the rag work and ut has built in integration with studio LM.
You do other things to make money and continue to make art for it's own sake. If you get to the point that others want your art you get commissions. Just like most artists in the current system.
Alright, so then you're NOT going to pay artists for their labor?
In the current system, artists might work for many years on a single work, or work many years perfecting their craft before anyone wants to pay for their work. Copyright gives them a way to earn money in the future that compensates them for the work they did in the past. It incentivizes creativity. Don't get me wrong, I don't think copyright is perfect, but you really ought to think more about the system you're proposing, because it's not making much sense.
Unfortunately, it’s hard to explain these things to techies who only see the world in their one-sided startupy way. The fact that there’re starving creatives who have already been massively marginalized by the likes of Spotify of this world, means nothing to these tech workers who only see everything as numbers, or a “business model” to “validate”.
(full disclosure, I’m a techie who’s gradually woken up to the idea that the tech might just be the most abused way to exploit people)
I'm in games, where art and tech crossroad. I 1000% empathize for the fact that art exploits, abuses, and underpays even if they at times may be doing more work than a junior web dev.
It's a bit ironic, because a lot of tech offers partial compensation in stock. Something else that really doesn't happen in games unless you work for like, the 3-4 largest studios. So they should at least understand that your compensation is not all based on labor for time worked.
"Nass and Reeves make a point of stating in their methodology that all the participants 'have extensive experience with computers … they were all daily users, and many even did their own programming'"
I really liked the review and the general breakdown.
BUT one thing stuck out, because they were so forceful, is their opinion "The radar screens aren’t the spinning ‘sonar blip’ bullshit you get in a lot of games, movies, and animation." That is horseshit. I was a military radar tech in Japan (95-98) and '‘sonar blip’ bullshit screens' were still the primary ATC displays on at least some mainland bases.
I see what you're saying, but his point seems to be, to me, that the "ACTUALLY!" crowd enjoy pooping on the display he's referring to as being something of an egregious anachronism, but in his experience (professionally and temporally relevant to the link discussed) that isn't the case.
What did I just read??? "Substantive facts"? That was all opinion. You didn't even directly respond to the poster until your last sentence and there you declared your opinion to be "fact-informed" and assigned both the feelings and actions of the average Unity dev using your, at best, subjective experience.
My current suggestion is to consider it the work of a just on-boarded intern. It will save you some time but you still need to walk thru the code to make sure it will work as intended.
First, it's worth noting the code in the blog post is not "production code," but rather one-off or periodically used scripts for accelerating manual business processes, with results that are easy to manually check.
But in regards to production code, I agree. When code is committed to a codebase, a human should review it. Assuming you trust your review process, it shouldn't matter whether the code submitted for review was written by a human or a language model. If it does make a difference, then your review process is already broken. It should catch bad code regardless of whether it was created by human or machine.
It's still worth knowing the source of commits, but only for context in understanding how it was generated. You know humans are likely to make certain classes of error, and you can learn to watch out for the blind spots of your teammates, just like you can learn the idiosyncrasies and weak points of GPT generated code.
Personally, I don't think we're quite at "ask GPT to commit directly to the repo," but we're getting close. The constant refrain of "try GPT-4" has become a trope, but the difference is immediately
noticeable. Whereas GPT-3.5 will make a mistake or two in every 50 line file, GPT-4 is capable of producing fully correct code that you can immediately run successfully. At the moment it works best for isolated prompts like "create a component to do X," or "write a script to do Y," but if you can provide it with the interface to call an external function, then suddenly that isolated code is just another part of an existing system.
As tooling improves for working collaboratively with large language models and providing them with realtime contextual feedback of code correctness (especially for statically analyzeble or type-checked languages), they will become increasingly indispensable to the workflow of productive developers. If you haven't used co-pilot yet, I encourage you to try it for at least a month. You'll develop an intuition for what it's capable of and will eventually wonder how you ever coded without it. Also make sure to try prompting GPT-4 to create functions, components or scripts. The results are truly surprising and exciting.
