Inside the man in front of the hacatone car
Then, 37 -year -old Eric Chong, who has a dental history and has already created a launch that simplifies medical bills for dentists. He was on the “car” team.
“I will be honest and say that I am very comfortable with being in the machinery team,” Chong says.
In Hakaton, Chong was developing software that uses sound and face detection to detect autism. Of course my first question was: wouldn’t there be wealth Of these, such as biased data that lead to false positive?
“Short answer, yes.” “I think there are false positives that may come out, but I think with voice and face expression, I think we can really improve the accuracy of early diagnosis.”
Agi ‘tacover’
The co -operative space, like many artificial intelligence things in San Francisco, is related to effective altruism.
If you are not familiar with the movement through the bomb fraud titles, it is looking to maximize things that can be done using time, money and resources. The next day after the event, the host event space is a discussion of how YouTube leverage “to communicate with important ideas like why people should eat less meat.”
On the fourth floor of the building, Flyers covered the walls. “AI 2027: Will Agi Tacover” shows the bulletin for a Taco party that recently passed, no one another “Animal Partner” offers another field.
Half an hour before the deadline, the encrypters took the vegan meat subsidiaries from the IKE and hurriedly finished to complete their projects. The downstairs, the referees began to enter: Brian Fika and the chemical Hitshah Anadkat of the OPA, Marius Bollandra of AI Application Antropic and Varin Nair, an artificial intelligence factory engineer (which also considers the event).
With the start of the refereeing, a member of the Metr team, Nate Rush, showed me an Excel table that tracked the competition scores, with the artificial intelligence groups of green and human -colored projects. With the arrival of the judges of their decisions, each group moved up and down. “Do you see it?” He asked me. No, I am not – the horrible colors were not even half an hour of the winning judgment. That was his opinion. Surprisingly, Man Versus Machine was a close match.
Show time
In the end, the finalists were equally divided: three by the “man” and three of the “machine”. After each show, the crowd was asked to raise their hands and guess if the team used artificial intelligence.
It was the first time ViewSense, a tool that moves in its surroundings to help low -vision people transcribe live videos to text to text for a screen singer to read loudly. Due to the short construction time, it was technically significant, and 60 percent of the room (because of the number of EMCEE) believed it was using AI. Didn’t do it
The next team was a platform for designing a web site with pen and paper, using a camera to track real -time designs – no AI involved in the programming process. The pianist project went to the final with a system that allows users to load piano sessions for feedback produced by AI. It was on the side of the device. Another team showed a tool that creates the heat maps of code changes: critical security issues are shown in red, while routine edits appear green. It used this one of the artificial intelligence.
