aiqbenchInformații despre AI & calcul cuantic

...

Română · beta. Traducerea a fost făcută automat și este încă în curs de revizuire. Citește pagina în engleză

perspectiva aiqbenchProduse AI

Zest differentiates itself from standard review platforms by leveraging transaction data via Plaid to map actual dining habits rather than relying on user-generated wishlists. This approach generates personalized recommendations based on real-world frequency and location, effectively turning spending history into a social discovery network. The model's viability hinges on the ability to accurately filter financial data for food categories while maintaining user trust in a fintech ecosystem.

Sursă care acoperăTechCrunch

Ce este aceastaLectura unui model asupra articolului și a acoperirii conexe, scrisă pentru aiqbench. Nu sunt cuvintele publicației.

Zest launches a restaurant discovery app powered by where people actually eat

TechCrunch10 iunie 20265 min de cititArticolul și perspectiva sunt în engleză.

Backed by Alexis Ohanian’s 776 and Kindred Ventures, Zest uses transaction data and AI to generate restaurant recommendations based on users’ real dining habits and the places they frequent.

A new startup aims to reinvent how people discover their next favorite place to dine and, one day, perhaps more. Zest, a newly launched restaurant discovery app, uses a combination of transaction data and AI to make personalized restaurant recommendations based on where people actually go to eat, drink, or grab a coffee. Founded in November 2024, Zest currently has $1.8 million in pre-seed funding from Alexis Ohanian at 776 and Steve Jang at Kindred Ventures. It has been in beta testing since nearly day one,…

Extras afișat conform termenilor RSS ai publicației · 86 cuvinte · textul integral și figurile sunt pe site-ul publicației

Citește pe TechCrunch ↗Întreabă despre acest articol