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Anthropic CEO Dario Amodei An essay was published Thursday, the researchers stressed how the world’s leading AI models understand. To solve this, Amodii, an ambitious goal set for anthropic, is allegedly among the 2027 AI model problems.
Amodei acknowledges the upcoming problem. Early improvements in watching the anthropical and the relevance of the relevance of the relevance of the relevance of the relevance of the models “- but stressed the need for more research to decipher whenever these systems grow stronger.
“I am very worried about the placement of such systems without a better arm with the interpretation.” “These systems will be completely central for economics, technology and national security, I think it will be able to influence so that humanity does not know how to do so.
It is one of the leading companies in an area that understands the black box of anthropic, mechanismal interpretation, AI models and why they do their decisions. Despite the improvement of the rapid performance of the Tech industry’s AI models, we still have a relatively little idea how these systems come to the decisions.
For example, Openai recently gave better results for both AI models, O3 and O4-mini, which are better performed in some positions more hallucinat than other models. The company does not know why it happened.
“When a generative AI system generalizes a financial document, a certain or precise level, why he chooses these options, why he has chosen these options, or why he is generally accurate.”
Amodei says that the anthropical co-founder Chris Olah said that the AI models of anthropist Olah “grew more than they were built.” In other words, the AI researchers found ways to improve the AI model intelligence, but they do not complete the reason.
In Essei, Amodei says it can be dangerous to reach AGI – or when calling it “the country of genius in a data center“- Without understanding how these models work. It claims that such a stage could reach such a stage by 2026 or 2027 of the technological industry, but it believes that we fully understand the AI models.
In a long run, Amodei, Anthropic, “Brain Scans” or “Brain Scans” or “brain scans” or “brain scans” or “MRI” wanted. These examinations said there were information about this, including AI models, including lies or strengths or inclinations for other weaknesses. It can take five to 10 years to achieve, but these measures will need to try and place the future AI models of anthropy.
Anthropik made several research progress, which allows you to better understand how AI models work. For example, the company recently found the way Watch the ways of the AI modelWhat calls for the company. Anthropic, AI models have identified a period that helps us to understand what cities of the United States. The company only found several of these circuits, but calculations have millions of AI models.
Anthropic translation capability himself and recently invested in the comments First investment in a beginner work on interpretation. Today, the interpretation is seen as a security inquiry today, the Amodei celebrates that the result may present a commercial advantage that describes how the AI models come to the answers.
Essaya called Amodei, Openai and Google Deepmind to increase research efforts in the field. Outside of the friendly nude, the Director General of Anthropik asked the governments to promote the rules of “lightweight”, companies to promote interpreting research such as requirements for their security and safety experiences. Amodei in the Essei should also put export control over the US chips to limit the probability of an informal, global AI race in the United States.
Anthropic has always been off Openai and Google as it is directed to safety. Other technological companies are controversial AI Security Bill, SB 1047, Recommendations for anthropic released modest support and billThis will determine what security reporting standards are determined by security reporting standards for the border AI model developers.
In this case, the anthropic, only increasing its capabilities, trying to make an industrial effort to better understand the AI models.
