Seed2.1 Pro
Seed2.1 Pro is a next-generation AI productivity model built to handle complex, real-world work across general agents, code engineering, and multimodal understanding. It reliably executes multi-step tasks for high-value office work and everyday consultation, including project planning, file processing, research, tool use, spreadsheet analysis, lesson-plan slide generation, and industry report creation across tools and environments. In software development workflows, Seed2.1 Pro strengthens end-to-end delivery by improving requirement understanding, architecture design, coding, debugging, implementation, and validation. Its agent capabilities are designed to make steady progress on difficult tasks and return practical, verifiable results rather than isolated responses. The model also advances knowledge, reasoning, visual understanding, spatial reasoning, and long-context processing, giving agents a stronger foundation for complex decision-making and execution.
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Claude Fable 5.1
Claude Fable 5.1 is Anthropic’s advanced AI model for coding, knowledge work, research, and long-running agentic tasks. It is designed to improve on Claude Fable 5 with stronger performance across software engineering, scientific research, multidisciplinary reasoning, computer use, business workflows, and complex problem solving. The model can handle extended multi-step work, verify its own results, diagnose difficult software issues, and operate effectively across tool-heavy workflows. Anthropic also reduced cache-read pricing for Fable 5.1, lowering typical usage costs compared with Fable 5 and creating larger savings for highly agentic workloads. Fable 5.1 includes updated safeguards intended to reduce false positives while allowing more legitimate cybersecurity tasks such as vulnerability discovery for defensive purposes. The model is available through Claude products, the Claude API, Amazon Web Services, Google Cloud, and Microsoft Azure.
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Fugu Cyber
Fugu Cyber is a specialized multi-agent orchestration model purpose-built for modern cyber defense. It behaves like a single model through one API endpoint, but dynamically coordinates specialized agents to solve complex, multi-step security tasks without depending on one model provider. It focuses on two core defense workflows, analyzing complex codebases to verify real-world vulnerabilities and translating raw cyber threat intelligence into working detection rules. On CyberGym, which evaluates vulnerability analysis and verification, Fugu Cyber achieved an 86.9% success rate; on CTI-REALM, which measures detection-rule generation from threat reports, it reached 72.1%, placing it alongside leading cyber-focused frontier models. Fugu Cyber is intended to work as the reasoning engine inside broader security systems rather than as a standalone solution.
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Amazon Rekognition
Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial search capabilities that you can use to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases.
With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can build a model to classify specific machine parts on your assembly line or to detect unhealthy plants. Amazon Rekognition Custom Labels takes care of the heavy lifting of model development for you, so no machine learning experience is required.
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