love the interior, not sure how i feel about that front end however. "The lowest drag coefficient in Ferrari history" is not what i would have guessed just seeing the picture alone, so props to them on making this possible!
In the US (to start) there's now a flavor of Gemini 2.5 to power Search experiences like AI Mode and AI Overviews. Should be sufficiently good at this point.
Dumb question, but how do they know it's not an escaped (or abandoned) pet? There are sadly many exotic pets on display on social media, particularly in this area of the world.
requiring a telephone contact (SMS verification or code from robocall) would provide enough sufficiency in scaring the perps to probably solve 90%+ of these.
"After you make an app or game available for pre-registration, users can visit your store listing to learn about and pre-register for your new app or game.
Then, when you publish your app or game later, all pre-registered users will receive a push notification from Google Play to install it.
Eligible devices will also have the app or game auto installed on the day it launches. (more details on this in documentation)
The challenge with that approach is the variation in both (a) queries and (b) other players.
(a) There are a small % of queries that are knowable for you to target on exact, or you are required to update and prune infinitely over time. [https://twitter.com/Google/status/1493681643290300425?lang=e...].
(b) A mix is better than a fixed CPA at a set price, up to to the player to pick the acceptable range. At a fixed price and many players competing for the same 100 10$ conversions, the price would quickly rise for those same conversions anyways. You're replicating the work the computer is doing, but doing so with the illusion of control.
Would respectfully disagree. Matching a consumers query to an ad, and optimizing that outcome at a given return on investment threshold is a task best left to a computer to optimize. It is a perfect use case for reinforcement learning, and a computer can work 24 hours a day and you need to sleep. In my experience, 100/100 times the machine beats the confident manual optimizer. We (humans) don't have a great track record in beating computers at these kinds of problems, certainly not a game as simple as optimizing for a high score (driving results from an ad).
I would agree with this, SWE is actually the easier role to replace with AI given the literal binary nature of the work. Dealing with humans is much more complicated, given they do not directly follow logic.