typeiierror

I know this is satire, but I have an adjacent problem I could use help with. In my company, we have some legacy apps that run, but we no longer have the source, any everyone that worked on them has probably left the planet.

We need to replatform them at some point, and ideally I'd like to let some agents "use" the apps as a means to copy them / rebuild. Most of these are desktop apps, but some have browser interfaces. Has anyone tried something like this or can recommend a service that's worked for them?

Looks great! How much optimization (e.g. deep sleep, wake trigger) was needed to get battery life with the ESP32 to where you wanted it? Also curious if the project is running on MicroPython or if you moved to something with less overhead.

I've always wanted to do this - do you have any articles / videos that helped you get started? Is Fighter Factory Studio still the way to go?

As an aside, this feels like a fun application of Gen AI (generating sprites + movesets based on photos of friends or hand drawn characters, etc).

I've been looking for something like this to query / interface with the mountain of home appliance manuals I've hung onto as PDFs - use case being that instead of having to fish out and read a manual once something breaks, I can just chat with the corpus to quickly find what I need to fix something. Will give it a shot!

This headline isn't accurate - the referenced report from Flurry shows an average opt-in rate for apps they track, which notably _excludes_ Facebook.

Try applying the problem to other issues to see the impact:

* An advertiser wants to place ads on sites / tv networks that have an audience that is more likely to buy their product upon seeing their ads. If they don't want to violate privacy, they run a survey. What if the response rate among a historical disenfranchised group (e.g. African Americans) is terrible? The modern "data driven" marketer would see little reason to advertise on Black media properties. This isn't a fictious example - it's a current problem in the media planning / agency industry.

* A local government has to decide between investing in more ESL resources in public education vs. other competing budget needs. They look at census / community survey data (which some Hispanic and immigrant populations are fearful of responding to d/t politicization) and decide to prioritize other asks due to undercounted demand. The data could also be skewed in other ways that warp their decision, like allocating budget to school zones that only represent specific immigrant communities that haven't historically been disenfranchised.

The big picture issue here is governments/businesses making decisions with bias information leading to incorrect conclusions, and the only know recourse currently is to scrap privacy.

The sample selection / non-response bias highlighted in this write-up is a _Big Idea_ problem I've been thinking about recently:

  Limitations...*Trust in surveys and political leanings:*
  About 95 percent of people contacted for the panel chose not to participate because of lack of trust in having a third-party application installed on their computer or other concerns for privacy.

Think about that - a reputable, privacy-first organization asked people to opt-in to fully consented, voluntary, compensated research and ~95% declined! I can't even imagine what hidden skews are present in the 5% that agreed. This issue is systemic in consumer research and impacts both public (e.g. election polling, U.S. census) and private (pharmaceutical trials, media/advertising research, voluntary AI/ML training daat) polling.

Governments and businesses make biased, potentially discriminatory decisions if a non-random segment of the population chooses to never be counted. The ad industry attempts to circumvent this through non-voluntary passive tracking, which trades off non-response bias with bulldozing user privacy. The headwinds are only growing too, as consumer awareness of privacy lapses and the politicization of polling continues to reduce who participates in opt-in research.

Finding a solution to this that doesn't resort to privacy-eroding tactics is a moonshot level problem in terms of the size-of-the-prize if solved.