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ai-skepticismClear
The 100,000 whys of AI
llmsai-generated-texthuman-ai-distinctionai-skepticism
Opinion

The 100k Whys of AI

Distinguishing between human-written and AI-generated text remains a contentious issue among tech experts. Large language models (LLMs) operate as advanced statistical models that mimic human language, making their output potentially indistinguishable from human writing in statistical assessments.

lcamtuf.substack.com

🔥🔥🔥🔥🔥

2 min

6/21/2026

No, everyone is not using AI for everything

AI adoption varies significantly among individuals, with some fully embracing it, others limiting their use, and some avoiding it entirely. A perception exists that once people try AI, they will consistently use it, which is proving to be inaccurate.

gabrielweinberg.com

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7 min

6/14/2026

GitHub - davegoldblatt/marcus-claims-dataset: Systematic extraction and analysis of every testable AI claim Gary Marcus made on his Substack (2022-2026). Dual-pipeline analysis by Claude and ChatGPT with hybrid reconciliation.Research

Marcus AI Claims Dataset

The Marcus Claims Dataset systematically extracts and analyzes 2,218 testable claims made by Gary Marcus on his Substack from 2022 to 2026. Among claims with checkable evidence, 59.9% were supported, 33.7% were mixed, and 6.4% were contradicted.

github.com

🔥🔥🔥🔥🔥

2 min

3/4/2026

The 100k Whys of AI

Distinguishing between human-written and AI-generated text remains a contentious issue among tech experts. Large language models (LLMs) operate as advanced statistical models that mimic human language, making their output potentially indistinguishable from human writing in statistical assessments.

lcamtuf.substack.com

🔥🔥🔥🔥🔥

2 min

6/21/2026

Marcus AI Claims Dataset

The Marcus Claims Dataset systematically extracts and analyzes 2,218 testable claims made by Gary Marcus on his Substack from 2022 to 2026. Among claims with checkable evidence, 59.9% were supported, 33.7% were mixed, and 6.4% were contradicted.

github.com

🔥🔥🔥🔥🔥

2 min

3/4/2026

No, everyone is not using AI for everything

AI adoption varies significantly among individuals, with some fully embracing it, others limiting their use, and some avoiding it entirely. A perception exists that once people try AI, they will consistently use it, which is proving to be inaccurate.

gabrielweinberg.com

🔥🔥🔥🔥🔥

7 min

6/14/2026

The 100k Whys of AI

Distinguishing between human-written and AI-generated text remains a contentious issue among tech experts. Large language models (LLMs) operate as advanced statistical models that mimic human language, making their output potentially indistinguishable from human writing in statistical assessments.

lcamtuf.substack.com

🔥🔥🔥🔥🔥

2 min

6/21/2026

No, everyone is not using AI for everything

AI adoption varies significantly among individuals, with some fully embracing it, others limiting their use, and some avoiding it entirely. A perception exists that once people try AI, they will consistently use it, which is proving to be inaccurate.

gabrielweinberg.com

🔥🔥🔥🔥🔥

7 min

6/14/2026

Marcus AI Claims Dataset

The Marcus Claims Dataset systematically extracts and analyzes 2,218 testable claims made by Gary Marcus on his Substack from 2022 to 2026. Among claims with checkable evidence, 59.9% were supported, 33.7% were mixed, and 6.4% were contradicted.

github.com

🔥🔥🔥🔥🔥

2 min

3/4/2026

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