Although the Claude OPUS 4 will be limited to pushing the anthropologist, the second model, Claude Sonnet 4, will be available for both the levels of paid and free users. OPUS 4 is marketed as a strong and large model of complex challenges, while Sonnet 4 is described as an intelligent and effective model for daily use.
Both new models are hybrid, which means that they can provide a quick response or a deeper and more caused response depending on the nature of the demand. During the response account, both models can search in the web or use other tools to improve its output.
Stefano Albricht, director of artificial intelligence at Deeplow and Coauthor, says artificial intelligence companies are currently reserved in a race to create a really useful Amnesty International agents who are able to plan and mind and implement them reliably and free from human supervision. Learning multi -agent reinforcement: modern foundations and curricula. This often includes the use of the Internet or other tools independently. There are still obstacles to safety and security to overcome them. Artificially supported artificial intelligence agents can behave from large language models and perform unintended procedures – which become more problematic when it is trusted to act without human supervision.
He says: “The more agents go ahead and do something during long periods of time, the more useful, if you have to intervene less and less.” “The ability of the new models to use tools in an interesting parallel – which can save some time along the way, to be useful.”
An example of the types of safety issues that are still artificial intelligence companies, agents can end up taking unexpected shortcuts or exploit gaps to reach the goals that have been granted. For example, they may reserve each seat on a plane to ensure that their user gets a seat, or resort to creative fraud to win the chess game. Anthropor says she was able to reduce this behavior, known as piracy bonus, in both new models by 65 % for Claude Sonit 3.7. This was achieved by monitoring problematic behaviors in a closer way during training, and improving both artificial intelligence training and evaluation methods.
