ai will use what you like to get into your head
what Age button like future artificial intelligence? Max Rebutin– PayPal’s co-founder and positive CEO acknowledges a new and invaluable role in reaching conclusions more along with people that human decision makers do, in favour of data to train AI.
In machine learning, it is well-known that computers that present clear reward features engage in relentless reinforcement learning to improve performance and maximize their rewards, but this optimization path is that humans often lead AI systems to very different outcomes than humans exert human judgments.
To introduce corrective power, AI developers often learn what is called reinforcement from human feedback (RLHF). Essentially, the computer places the human thumb on scale as it arrives at the model by training it with data reflecting the actual people’s preferences. However, where does that human preference data come from and how much is it necessary for the input to be valid? So far, this has been an issue with RLHF. It’s a costly way to hire a human supervisor and annotator to enter feedback.
And this is a problem that Levtin thinks can be solved with a similar button. He sees the accumulated resources he sits today FacebookA hand as a godsend for developers who want to train intelligent agents on human preference data. And how big a deal is it? “One of the most valuable things Facebook owns is the Mountain of Laint of Data,” Levchin said. Certainly, “This inflection point in the development of artificial intelligence that allows access to what human-favoured content is used to train AI models is perhaps one of the most valuable things on the Internet.”
Levchin assumes that AI will learn from human preferences via the Botton button, but AI is already changing the way in which these preferences are formed. In fact, social media platforms are actively using AI to not only analyze likes, but also to predict them. The button itself is outdated.
This was an impressive observation for us. Because when you talk to most people, predictions come mainly from a different angle, explaining how AI changes the world of Botton, rather than how buttons affect AI’s performance. I’ve already heard that AI is being applied to improve social media algorithms. For example, in early 2024, Facebook experimented. Use AI Redesign the algorithm that recommends reel video to users. Can you come up with better weightings for variables to predict which video users want to watch next? The results of this early test showed that it is possible: applying AI to tasks that have been rewarded by longer clock times – Performance Metric Facebook wanted a boost.
When I asked YouTube Co-founder Steve Chen said what the future holds for the button of the future:
However, he went on to point out that one of the reasons why buttons are always needed for life events or situations, such as buttons, is to always handle sharp or temporary changes in viewing needs. “For example, there are days when I want to see more relevant content for my kids,” he said. Chen also explained that “Like” buttons may have longevity because of their roles that help attract other important groups, advertisers, along with viewers and creators. With one tap, viewers simultaneously communicate their appreciation and feedback directly to content providers, and direct evidence of engagement and preferences to advertisers.