Added a little class of travel indicator to help guide the budget further… working on displaying raw price data clearly and cleanly within the result now
Added a little class of travel indicator to help guide the budget further… working on displaying raw price data clearly and cleanly within the result now
Took some time to learn how to link google flights, and have an accurate est. cost for trip options. Also am trying to implement some convinience measures to make input easier (multiple choice, checkboxes, etc.)
I’ve got soemthing working here. Going to implement a little more practicality in terms of finding fares and using real world pricing.
Got a nice UI going, trying to test.
Working on the initial server, trying to make it API-less…
Shipping now!
UI issue on the vercel, fix then push.
I added sources so you can tell where it got the data from, the issue was that edge and chrome were rejecting requests so I had to go a seperate route
Found an issue with the model will all of the characteristics clustered around 50… Will need to fixthat.
Implemented other insights and increased the different types of monetization models the model is trained on so it can make the best decision.
Working on implementing the mathematics into my model. So far so good, I will now look at improving other insights and adding sources…
Did some math, to calculate the success index. I realized that the LLM returns the ingredients (market size, growth, monetization, difficulty, competitor count, weaknesses).
So I have to normalize the signals from 0-1,
market = clamp( (log10(TAM_dollars) - 7) / 4 , 0, 1 )
growth = clamp( CAGR% / 30 , 0, 1 )
n = number of competitors
n = 0 → 0.40 (unvalidated market)
n = 1–3 → 0.90 (validated, room to enter)
n = 4–6 → 0.70
n = 7–9 → 0.50
n ≥ 10 → 0.30 (saturated)
feasible = (10 - difficulty) / 9
success% = round( 100 / (1 + e^(-6 * (S - 0.5))) )
Now working on implementation
Working on this validator, so far I have used knowledge from previous projects to get the website scraping to work, I am just not trying to get the predictions to work… Very rough right now, it may take a while for that to start working.
Starting to devlop this startup validator to give people a glimpse into how well their ideas will do on the market. Inspired by the bad sharktank pitches.
Finalized the project by redoing the UI and fixing small streaming issues
Redid the UI, fixed video streaming!
Tested it without speaking, and the judging seems pretty good!
Was able to figure out how to get the rooms working, just need to clean up some things on both sides for this to be finished.
Working on a room system, I was able to code the logic – still using the AI UI because I am simply too lazy right now, but I will get to it before ship.
You can invite people to debate you and the impartial AI scores you, is the concept so far.
Rooms need to be bugfixed, sitll working on that
I was able to split the two into video and transcript, and one uses videos processed locally.
I want to see if i can make rooms and have people join and debate their friends… also redo UI