Then it is Eric ChongThe 37-year-old who has experience in dentistry and previously co-founded a startup who simplifies medical settlements for dentists. He was placed in the “Machine” team.
“I will be honest and I will say that I feel relief in the machine team,” says Chong.
At Hackathon Chong, he built a software that uses voice and face recognition to detect autism. Of course, my first question was: wouldn’t it be wealth problems with this, such as biased data leading to false positives?
“Short answer, yes,” says Chong. “I think there may be several false positives, but I think that with a voice and expression on the face, I think we could improve the accuracy of early detection.”
Agi “Tacover”
Coworking space, like many things related to AI in San Francisco, has connections with effective altruism.
If you don’t know the movement through Bomb fraud headersHe tries to maximize the good that can be done with the lend a hand of time, money and resources of participants. The day after this event in the event space hosted the discussion on how to apply YouTube “to convey important ideas, such as why people should eat less meat.”
On the fourth floor of the building, the leaflets covered the walls-“AI 2027: Will Agi Tacover” shows the Bulletin for the Taco event, which has recently passed, another entitled “Pro-Animal Coworking” is no other context.
Half an hour before the date of notification, the coders chewed vegan meatball submarines from Ike’s and rushed to complete their projects. One floor down, the judges began to arrive: Brian Fioca AND Shyamal Hitsh Anadkat from the AI Applied AI Openai team, Marius Bulionra from the anthropic of the AI i i Protected NAIRAI starter engineer Factory (which also coholts the event).
As the referee began, a member of the Metr team, Nate Rush, showed me the Excel table, which followed the results of the players, with colorful green and human AI projects. Each group rose up and down when the judges made their decisions. “Do you see it?” He asked me. No, no – Mishmash colors did not show a clear winner even half an hour to refereeing. It was his point of view. To everyone’s surprise, the man versus the machine was a close race.
Show time
Ultimately, the finalists were equally divided: three from the “man” and three of the “machine”. After each demo, the crowd was asked to raise his hands and guess whether the band used artificial intelligence.
At first there was Viewsense, a tool designed to lend a hand people impair people in navigation in the environment through live video transcription to the text so that the screen reader reads aloud. Given the compact construction time, it was technically impressive, and 60 percent of the room (according to Count Emcee) thought he used AI. That’s not.
Then there was a team that built a platform for designing sites with a pen and paper, using a camera to track sketches in real time – without AI involved in the coding process. The pianists’ project was promoted to the finals with a system that allows users to send piano sessions for feedback generated by AI; It was on the machine side. Another team presented a tool that generates thermal maps of code changes: critical security problems appear in red, and routine editions appear green. He used artificial intelligence.