AI uses love you to enter your head
What The future of the button -like in the age of artificial intelligence? Max Luchin – founder of PayPal and CEO of Confirmation – sees a new and very valuable role in loving data for AI training to achieve more conclusions according to that human decision maker.
It is a well-known point in machine learning that a computer with a clear reward performance will be involved in learning reinforced reinforcement to improve its performance and maximize the reward-but this pathway often results in artificial intelligence systems to produce very different results than humans.
To introduce a corrective force, artificial intelligence developers often use what is called a reinforcing human feedback (RLHF). In essence, they put a human thumb on a scale by entering the computer by teaching it on data that reflects the real preferences of real people. But where does this human priority data come from and how much is it necessary for entry validity? So far, this has been the problem of RLHF: If it needs to hire supervisors and human beings to bring feedback, this is a costly method.
And that’s a problem Luchin thinks with the Like button can be solved. He observes the accumulated source today in the hands of Facebook as a god for any developer who wants to teach a smart factor about human preference data. And how big is this transaction? Luchin told us, “I argue that one of the most valuable things that Facebook has is that the mountain is loving data.” In fact, at this point of inflation in the development of artificial intelligence, access to “what content is human -friendly, for use to teach artificial intelligence models is probably one of the most valuable things on the Internet.”
While Lucin predicts artificial intelligence learning from human preferences through the Like button, artificial intelligence is changing how these preferences are formed in the first place. In fact, social media operating systems actively use AI not only to analyze the likes but also to predict them – potentially disrupt the button itself.
It was an interesting observation for us because, as we talked to most people, the forecasts were more than another angle, and did not describe how the Like button affects AI performance but how artificial intelligence changes the Like button world. Currently, we have heard, artificial intelligence is applied to improve social media algorithms. For example, in early 2024, Facebook tested AI to redesign the algorithm, which recommends to recommend movies to users. Can it provide a better weight of variables to predict which one of a user would like to watch more? The outcome of this initial experiment showed that it could be: the use of artificial intelligence in the job paid in longer times – Facebook metric performance hoped to be reinforced.
When asked by Steve Chen, the founder of YouTube what the future for the Like button, he said, “I sometimes wonder if the button would be like the AI to be advanced enough to accurately 100 % to what you want to say based on your view and sharing patterns.”
However, one of the reasons that always requires the Like button is to make severe or temporary changes in observation of needs because of events or situations. “There are days when I want to watch the content that is a little more about my kids,” he said. Chen also explained that the Like button may be because of its role in attracting advertisers – another main group alongside viewers and creators – because of these, as the simplest possible hinge to connect those three groups. With a faucet, a viewer simultaneously gives a gratitude and feedback directly to the content provider and the evidence of interaction and priority to the advertiser.
