Anthropic Says New Model Can Code on Its Own for 30 Hours Straight.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Anthropic Says New Model Can Code on Its Own for 30 Hours Straight.
Συγγραφείς: Ghaffary, Shirin (AUTHOR)
Πηγή: Bloomberg.com. 9/29/2025, pN.PAG-N.PAG. 1p.
Θεματικοί όροι: *Artificial intelligence, *Computer software developers, *Computer security, Machine learning, Subroutines (Computer programs)
Περίληψη: The article focuses on Anthropic's release of a new artificial intelligence model, Claude Sonnet 4.5, which is designed to enhance coding capabilities for software developers. This model can autonomously code for up to 30 hours, surpassing the previous model, Claude Opus 4, which could code for seven hours. Anthropic, valued at $183 billion, aims to address practical business needs, particularly in sectors like cybersecurity and financial services, while competing with other companies like OpenAI and Google. The company acknowledges that for AI to deliver significant benefits, improvements in AI models and adaptations in workflows are necessary. [Extracted from the article]
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Βάση Δεδομένων: Business Source Index
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  Data: The article focuses on Anthropic's release of a new artificial intelligence model, Claude Sonnet 4.5, which is designed to enhance coding capabilities for software developers. This model can autonomously code for up to 30 hours, surpassing the previous model, Claude Opus 4, which could code for seven hours. Anthropic, valued at $183 billion, aims to address practical business needs, particularly in sectors like cybersecurity and financial services, while competing with other companies like OpenAI and Google. The company acknowledges that for AI to deliver significant benefits, improvements in AI models and adaptations in workflows are necessary. [Extracted from the article]
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  Data: <i>Copyright of Bloomberg.com is the property of Bloomberg, L.P. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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