A tiny trained classifier sorts his email at 95 percent accuracy
The AI or the AI built an embeddings plus logistic classifier for his emails reaching 95 percent accuracy from 50 to 100 examples, trained in under 5 minutes locally.
A random mix from the whole library. Shuffle for a new set.
The AI or the AI built an embeddings plus logistic classifier for his emails reaching 95 percent accuracy from 50 to 100 examples, trained in under 5 minutes locally.
Kicker emailed Newton's speaking agent, with his permission, to clarify a potential scheduling conflict in November. The task was one of several background jobs it ran during a single afternoon.
Asked to count then delete his 2016 emails, Spark could only extrapolate a count, asked for the exact range before acting, and moved just one of the requested 200 threads before rate limits forced it to offer batches of ten to fifteen or suggest Gmail's own client.
The AI cleared an inbox of 100,000 emails during the user's workday, leaving a manageable mailbox behind.
He had the AI collect his will and trust documents and check them against state statutes. The review found missing signatures, an illegal clause, and outdated law references, and he fired his attorney the same day.
Before a speaking engagement, Ulanoff couldn't recall where he was talking or where to park. He asked the AI to find the original note from his contact, misspelling the contact's name.
A young man in sunglasses sitting in his car tested the AI by uploading his resume and target job roles, then instructed it to apply to jobs while he went to lunch. Screen recordings showed multiple browser tasks running and a notification confirming an application submitted to 'ioTech Solutions.' The AI asked for information once for the first application, then reused it — resulting in 50 applications submitted while he was idle.
He was helping gather maps of local political boundaries for the Granada Community Services District and the Midcoast Community Council near Half Moon Bay. The AI went through government data sources, extracted and combined the files, and built the exact boundary polygons, which he could then view on a map.
Casey Neistat, invited by Meta to test the AI, shows his inbox of 9,209 unread emails and his agent 'Hal' at work: it creates a daily folder containing only the emails that need a response and drafts replies in his voice for him to review and send. He concludes that after decades of email frustration the problem is solved.
The same setup reads his incoming email and texts, builds his weekly to do list, sends him a digest every morning with the list and any scheduling clashes he might miss, and adds events to the family calendar on its own. A spreadsheet of every house appliance and its service schedule feeds the list, and it drafts the messages to repair firms for him to send.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.