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ai-modelsClear
Microsoft Paint and Photos Embed Server-Issued GUIDs as Invisible Watermarks in Locally-Generated Images
microsoftimage-generationai-modelsdigital-watermarking
Research

MS Paint and Photos inivisibly watermark even locally generated output with GUID

Microsoft Paint embeds an invisible, server-issued GUID watermark in images generated locally through its Cocreator feature on Copilot+ PCs. Before local NPU-based Stable Diffusion inference begins, Paint sends the prompt and style to a Microsoft Azure moderation endpoint. The response includes a revised prompt, a promptGenerationId, a watermarkId, and a human-reference classification. Paint encodes the 16-byte watermarkId into image pixels through Watermarker.dll; generation fails if that watermarking step fails. The watermark encoder requires images at least 192 by 192 pixels and converts the GUID into a 144-bit payload with a prefix and checksum. Paint also sends the generated image and promptGenerationId to an online signing service, which returns a signed C2PA Content Credentials manifest. Testing found that the manifest’s Microsoft InvisMark soft-binding value matched the GUID embedded in the image pixels. Paint limits AI-generated image saves to C2PA-preserving PNG, JPEG, GIF, and .paint formats. Microsoft Photos includes the same Watermarker.dll for locally generated Image Creator and Restyle Image results, although its code appears to return an image even when watermarking fails. Microsoft discloses remote content filtering and C2PA manifests, but the research found no Microsoft disclosure describing the prompt-moderation-issued GUID or its embedding in pixels.

xusheng.dev

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

14 min

8/24/2026

DeepSeek V4 Flash 0731 Intelligence, Performance and Price Analysis

DeepSeek V4 Flash 0731 offers enhanced intelligence, improved performance metrics, and competitive pricing analysis. The model aims to optimize efficiency and effectiveness in AI applications.

artificialanalysis.ai

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

1 min

7/31/2026

Opus 5 is currently #1 on Artificial Analysis Intelligence Leaderboard

A comparison of AI models evaluates their intelligence, performance, and pricing, focusing on metrics such as output speed, latency, and context window. The analysis includes various evaluations such as agentic real-world tasks, tool use, coding capabilities, and reasoning across different domains.

artificialanalysis.ai

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

3 min

7/24/2026

GLM 5.2 is nearly as accurate as a human book keeper

GLM 5.2 achieves accuracy comparable to a human book-keeper in preparing quarterly VAT returns for small UK businesses. The cost of using GLM 5.2 is less than 1% of traditional accounting services.

toot-books.pages.dev

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

9 min

7/9/2026

Disagreement among frontier LLMs on real-world fact-checks

67% of real fact-checks show that top AI models disagree on the answers. Five frontier LLMs evaluated 1,000 user-submitted claims, resulting in significant discrepancies among their verdicts.

lenz.io

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

22 min

5/28/2026

Study: Back-to-basics approach can match or outperform AI in language analysis

A grammar-based method called LambdaG can match or outperform advanced AI systems in identifying text authorship. This method utilizes patterns in grammar and sentence construction, providing comparable accuracy with greater transparency and lower computational costs.

manchester.ac.uk

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

3 min

4/15/2026

Why AI systems don't learn – On autonomous learning from cognitive science

Current AI models struggle with autonomous learning due to inherent limitations. A new learning architecture is proposed, inspired by human and animal cognition, which incorporates learning from observation and active behavior.

arxiv.org

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

1 min

3/17/2026

Towards Autonomous Mathematics Research

Recent advancements in foundational models have produced reasoning systems that can achieve gold-medal standards at the International Mathematical Olympiad. Transitioning from competition-level problem-solving to professional research necessitates the ability to navigate extensive literature and construct long-form mathematical arguments.

arxiv.org

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

2 min

2/15/2026

MS Paint and Photos inivisibly watermark even locally generated output with GUID

Microsoft Paint embeds an invisible, server-issued GUID watermark in images generated locally through its Cocreator feature on Copilot+ PCs. Before local NPU-based Stable Diffusion inference begins, Paint sends the prompt and style to a Microsoft Azure moderation endpoint. The response includes a revised prompt, a promptGenerationId, a watermarkId, and a human-reference classification. Paint encodes the 16-byte watermarkId into image pixels through Watermarker.dll; generation fails if that watermarking step fails. The watermark encoder requires images at least 192 by 192 pixels and converts the GUID into a 144-bit payload with a prefix and checksum. Paint also sends the generated image and promptGenerationId to an online signing service, which returns a signed C2PA Content Credentials manifest. Testing found that the manifest’s Microsoft InvisMark soft-binding value matched the GUID embedded in the image pixels. Paint limits AI-generated image saves to C2PA-preserving PNG, JPEG, GIF, and .paint formats. Microsoft Photos includes the same Watermarker.dll for locally generated Image Creator and Restyle Image results, although its code appears to return an image even when watermarking fails. Microsoft discloses remote content filtering and C2PA manifests, but the research found no Microsoft disclosure describing the prompt-moderation-issued GUID or its embedding in pixels.

xusheng.dev

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

14 min

8/24/2026

Opus 5 is currently #1 on Artificial Analysis Intelligence Leaderboard

A comparison of AI models evaluates their intelligence, performance, and pricing, focusing on metrics such as output speed, latency, and context window. The analysis includes various evaluations such as agentic real-world tasks, tool use, coding capabilities, and reasoning across different domains.

artificialanalysis.ai

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

3 min

7/24/2026

Disagreement among frontier LLMs on real-world fact-checks

67% of real fact-checks show that top AI models disagree on the answers. Five frontier LLMs evaluated 1,000 user-submitted claims, resulting in significant discrepancies among their verdicts.

lenz.io

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

22 min

5/28/2026

Why AI systems don't learn – On autonomous learning from cognitive science

Current AI models struggle with autonomous learning due to inherent limitations. A new learning architecture is proposed, inspired by human and animal cognition, which incorporates learning from observation and active behavior.

arxiv.org

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

1 min

3/17/2026

DeepSeek V4 Flash 0731 Intelligence, Performance and Price Analysis

DeepSeek V4 Flash 0731 offers enhanced intelligence, improved performance metrics, and competitive pricing analysis. The model aims to optimize efficiency and effectiveness in AI applications.

artificialanalysis.ai

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

1 min

7/31/2026

GLM 5.2 is nearly as accurate as a human book keeper

GLM 5.2 achieves accuracy comparable to a human book-keeper in preparing quarterly VAT returns for small UK businesses. The cost of using GLM 5.2 is less than 1% of traditional accounting services.

toot-books.pages.dev

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

9 min

7/9/2026

Study: Back-to-basics approach can match or outperform AI in language analysis

A grammar-based method called LambdaG can match or outperform advanced AI systems in identifying text authorship. This method utilizes patterns in grammar and sentence construction, providing comparable accuracy with greater transparency and lower computational costs.

manchester.ac.uk

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

3 min

4/15/2026

Towards Autonomous Mathematics Research

Recent advancements in foundational models have produced reasoning systems that can achieve gold-medal standards at the International Mathematical Olympiad. Transitioning from competition-level problem-solving to professional research necessitates the ability to navigate extensive literature and construct long-form mathematical arguments.

arxiv.org

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

2 min

2/15/2026

MS Paint and Photos inivisibly watermark even locally generated output with GUID

Microsoft Paint embeds an invisible, server-issued GUID watermark in images generated locally through its Cocreator feature on Copilot+ PCs. Before local NPU-based Stable Diffusion inference begins, Paint sends the prompt and style to a Microsoft Azure moderation endpoint. The response includes a revised prompt, a promptGenerationId, a watermarkId, and a human-reference classification. Paint encodes the 16-byte watermarkId into image pixels through Watermarker.dll; generation fails if that watermarking step fails. The watermark encoder requires images at least 192 by 192 pixels and converts the GUID into a 144-bit payload with a prefix and checksum. Paint also sends the generated image and promptGenerationId to an online signing service, which returns a signed C2PA Content Credentials manifest. Testing found that the manifest’s Microsoft InvisMark soft-binding value matched the GUID embedded in the image pixels. Paint limits AI-generated image saves to C2PA-preserving PNG, JPEG, GIF, and .paint formats. Microsoft Photos includes the same Watermarker.dll for locally generated Image Creator and Restyle Image results, although its code appears to return an image even when watermarking fails. Microsoft discloses remote content filtering and C2PA manifests, but the research found no Microsoft disclosure describing the prompt-moderation-issued GUID or its embedding in pixels.

xusheng.dev

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

14 min

8/24/2026

GLM 5.2 is nearly as accurate as a human book keeper

GLM 5.2 achieves accuracy comparable to a human book-keeper in preparing quarterly VAT returns for small UK businesses. The cost of using GLM 5.2 is less than 1% of traditional accounting services.

toot-books.pages.dev

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

9 min

7/9/2026

Why AI systems don't learn – On autonomous learning from cognitive science

Current AI models struggle with autonomous learning due to inherent limitations. A new learning architecture is proposed, inspired by human and animal cognition, which incorporates learning from observation and active behavior.

arxiv.org

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

1 min

3/17/2026

DeepSeek V4 Flash 0731 Intelligence, Performance and Price Analysis

DeepSeek V4 Flash 0731 offers enhanced intelligence, improved performance metrics, and competitive pricing analysis. The model aims to optimize efficiency and effectiveness in AI applications.

artificialanalysis.ai

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

1 min

7/31/2026

Disagreement among frontier LLMs on real-world fact-checks

67% of real fact-checks show that top AI models disagree on the answers. Five frontier LLMs evaluated 1,000 user-submitted claims, resulting in significant discrepancies among their verdicts.

lenz.io

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

22 min

5/28/2026

Towards Autonomous Mathematics Research

Recent advancements in foundational models have produced reasoning systems that can achieve gold-medal standards at the International Mathematical Olympiad. Transitioning from competition-level problem-solving to professional research necessitates the ability to navigate extensive literature and construct long-form mathematical arguments.

arxiv.org

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

2 min

2/15/2026

Opus 5 is currently #1 on Artificial Analysis Intelligence Leaderboard

A comparison of AI models evaluates their intelligence, performance, and pricing, focusing on metrics such as output speed, latency, and context window. The analysis includes various evaluations such as agentic real-world tasks, tool use, coding capabilities, and reasoning across different domains.

artificialanalysis.ai

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

3 min

7/24/2026

Study: Back-to-basics approach can match or outperform AI in language analysis

A grammar-based method called LambdaG can match or outperform advanced AI systems in identifying text authorship. This method utilizes patterns in grammar and sentence construction, providing comparable accuracy with greater transparency and lower computational costs.

manchester.ac.uk

πŸ”₯πŸ”₯πŸ”₯πŸ”₯πŸ”₯

3 min

4/15/2026

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