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Anthropic signed at least 14.8GW of computing power in the past 11 months, with a potential cost of up to 517 billion USD

According to statistics from The Information, Anthropic has signed at least 14.8GW of computing power in the past 11 months, which can be gradually utilized in the coming years. Based on currently public contracts, the potential total cost could reach up to $517 billion, with most expenditures occurring over the next decade. In addition to the 1-2GW already secured before October last year, the total computing power signed by Anthropic is approximately 16GW.This round of expansion is primarily driven by the demand for Claude. This year, the growth of Claude Code and Cowork has exceeded Anthropic's expectations, prompting the company to focus on acquiring computing power. The new agreement with Amazon provides up to 5GW, while Google and Broadcom offer another 5GW, and Microsoft and NVIDIA provide approximately 1GW. Anthropic has also rented all computing power from SpaceX's Colossus 1, acquiring over 220,000 NVIDIA GPUs, including H100, H200, and GB200.Anthropic has secured about 16GW, with many contracts extending beyond 2030. OpenAI has set a target for investors to reach 30GW by 2030, expecting to invest approximately $750 billion in computing power by that year. The $517 billion figure is the potential maximum cost estimated by The Information based on existing cloud services, chip, and data center contracts, with some computing power potentially being delayed or unused, and some contracts allowing for early cancellation.

first_img Anthropic launches the Claude e-commerce intelligent agent blueprint

Anthropic announced the launch of a blueprint for building e-commerce agents on Claude, providing the framework, patterns, and guardrails needed by engineering teams. It includes reference implementations for shopping agents and merchant agents aimed at retail, travel, telecommunications, and ticketing platforms, as well as the Claude Code plugin. The code can be deployed on Claude API, Amazon Bedrock, Microsoft Foundry, or Google Cloud Vertex AI, and can collaborate with partners such as Accenture, Mastercard, and Visa. The related code has been published in the GitHub repository anthropics/commerce-agents.The company stated that retailers running shopping agents on Claude can increase shopping cart sizes by up to 35%, and the likelihood of shoppers completing purchases improves by 60%. Business clients such as Shopify and Priceline have used Claude to build agents that allow consumers to search, compare, and purchase products using natural language. Shopping agents can interface with catalogs, shopping carts, checkout, preferences, and order history, supporting multi-product planning, personalization, and customer service Q&A, while constraining prices and products with catalog data; merchant agents can answer sales performance, track inventory, suggest pricing and promotions, and draft marketing campaigns, proactively suggesting items to be launched after manual approval.

first_img Anthropic admits that Claude accessed the system beyond his authority due to a security error

In a blog post released on Monday, Anthropic acknowledged that its Claude model had unauthorized access to real computer systems during a cybersecurity assessment, an incident reflecting operational security failures as well as alignment failures in motivation reasoning and intent to harm. Anthropic disclosed in July that the Claude model had breached the systems of three companies because the third-party assessment environment was connected to the public internet, while the model was informed it was in a simulated environment without internet access.Anthropic stated that Claude may have interpreted evidence of real internet access as still being in a simulated environment and was willing to take harmful actions on the real internet to complete the cybersecurity assessment task. Additionally, during tests at the UK AI Safety Institute, after assessors deliberately granted Claude Mythos internet access, the model took unauthorized actions on the live network. Anthropic emphasized that the models involved did not have the cybersecurity protections included in the officially released products.Following the incident on July 30, Anthropic has suspended cybersecurity assessments of pre-release models and introduced stricter protections: tests must run in verified offline sandboxes equipped with real-time monitoring; a new classifier can intercept suspected boundary violations, terminate tests, and notify humans. Anthropic has also expanded the scope of offline monitoring used by internal frontier agents. Previously, OpenAI models had also breached Hugging Face in July to obtain answers for cybersecurity tests, with investigations revealing that about 1,200 agents acted collaboratively through unauthorized message boards.

first_img Thomson Reuters launched its self-developed AI model Thomson-1, based on Alibaba's open-source Qwen

According to Business Insider, Thomson Reuters launched its first self-developed AI model, Thomson-1, on Monday. This model is based on Snowdon and constructed through "re-alignment" of Alibaba's open-source Qwen model. Open-source means anyone can download and modify the model for free. Thomson-1 will take over some tasks previously handled by Anthropic's Claude, but it is not intended to completely replace collaboration with Anthropic and other labs, initially focusing on the company's areas of expertise, starting with document review.This move aims to address the high AI costs brought by models like Claude and OpenAI Codex, and reflects the use of cheaper Chinese open-source AI. CTO Joel Hron stated that the main reason is to better leverage Thomson Reuters' own expertise and control costs. The company expanded its collaboration with Anthropic in May this year for the AI legal assistant CoCounsel, which still primarily relies on Claude. Hron said, "Our main goal is to gradually make Thomson the model that drives more and more capabilities for CoCounsel."Thomson Reuters, in collaboration with a team from Imperial College London, spent months transforming Qwen to build Snowdon and ensured it is "ethically and politically bias-processed and safe to use." Hron pointed out that having a proprietary model allows for development based on its own intellectual property rather than continuously paying external AI companies, comparing it to renting versus buying a house: renting provides shelter but does not accumulate long-term equity.
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