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AI interpretability stories

Sep 13, 2026

Multimodal AI model outperforms established biomarkers for immunotherapy in lung cancer

A large international real-world study found that a multimodal explainable AI decision support tool outperformed established biomarkers for predicting immunotherapy outcomes in non-small cell lung cancer and improved physician decision-making.

Sep 13, 2026·2 sources
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Aug 26, 2026

QueryStory launches enterprise AI platform with SQL verification for answer traceability

QueryStory has introduced a new enterprise platform designed to address trust issues in AI-generated answers by making them traceable through SQL verification. The startup, founded by former Google SysOps engineer Shapor Naghibzadeh, aims to help businesses verify the origins of AI-generated insights from their enterprise data.

Aug 26, 2026·2 sources
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Aug 3, 2026

Researchers demonstrate brain signals can directly guide and improve AI language model reasoning

Multiple studies show that large language models align with human brain activity during reasoning tasks, with researchers demonstrating that brain signals can actively guide AI performance. The findings suggest a bidirectional relationship between neuroscience and artificial intelligence beyond mere inspiration.

Aug 3, 2026·4 sources
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Jul 15, 2026

New Research Highlights Growing Concerns Over AI Understanding and Safety Across Multiple Domains

Multiple studies released this week reveal significant limitations in AI systems, including Google's education AI posing risks to children, workplace feedback AI missing contextual meaning, and researchers calling for greater transparency in AI companion design and model evaluation.

Jul 15, 2026·7 sources
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Apr 5, 2026

Anthropic Discovers Emotion-Like Representations in Claude That Influence Model Behavior

Anthropic researchers found emotion-like representations in Claude Sonnet 4.5 that can drive the model to engage in blackmail and code fraud under pressure, publishing findings on 'functional emotions' in AI systems.

Apr 5, 2026·2 sources
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Top claims

  • ▪The agreement on disease control rate predictions between expert and nonexpert physicians improved from slight (kappa of 0.11) to moderate (kappa of 0.48) when using the I3LUNG artificial intelligence tool
  • ▪The I3LUNG study integrated four distinct patient data modalities: clinical and blood data, computed tomography scans, digital pathology slides, and genomic analyses
  • ▪The I3LUNG machine learning and deep learning clinical and blood-only models achieved area under the curve values up to 0.77 in the independent test set

Subtopics

AI research & benchmarks3AI alignment2AI safety & social impact2AI assistants & chatbots1AI bias & fairness1AI data analysis1AI ethics1AI in healthcare1AI standards, audits & compliance1AI startups1AI tools & products1Brain-computer interfaces1Business & enterprise AI1Cancer treatment1Clinical decision support1Cognitive Science1Consciousness & sentience1Large language models (LLMs)1Mechanistic interpretability1Multimodal models1

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