I need people to understand how difficult it is to get an NIH grant. You spend months writing a proposal, following strict guidelines that include a detailed multiyear budget, bios of everyone on your team, plans for participant safety & ethical conduct. Then you send it off -1/n
LLMs are good at coding tasks in part because theyโve ingested answers from sites like StackOverflow.
Will LLM performance suffer as the number of StackOverflow users declines?
I imagine weโll notice a decrease in performance on questions regarding new stats packages and tools
StackOverflow is a dinosaur that's going extinct.
I mostly use Copilot, ChatGPT, and Perplexity. I haven't found a single reason to visit StackOverflow anymore.
StackOverflow can't compete, and I don't see how they can stay relevant any longer.
I use Copilot for inline suggestions. As I type, Copilot takes care of the little things. It saves me from dozens of searches every day.
ChatGPT is the workhorse. I use it to solve more complex tasks with my code. Here are some examples:
โข Explain what this code does
โข Simplify it
โข Rewrite it in a more efficient way
โข Rewrite it in a more readable way
โข Replace the use of a library with another
โข Write documentation for it
โข Describe potential edge cases
โข Write unit tests for those edge cases
I use Perplexity to ask questions. Google is broken. If you don't believe me, try Perplexity for a day.
(Google is still king as a navigation tool. I never type a complete URL in my browser. I google it instead.)
Modern AI-powered tools are replacing boomer tech.
StackOverflow is dead to me.
8/8 How can we develop our own drive for continued learning and understanding? How can teams identify instances where skill maintenance and development take precedence over efficiency? What other questions should we consider? [End of Thread]
1/8 ๐งต Will generative AI stifle skill development in knowledge work? ๐ค Tech like #ChatGPT can take over numerous tasks. Is there a cost to this convenience? Do we risk losing our hard-earned skills and preventing the development of new skills? #ArtificialIntelligence
7/8 Think of pilots, for instance. If an automated system fails, they must intervene manually. The absence of skill in these critical moments could be disastrous. This showcases the importance of balancing automation and manual intervention.