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AI Safety

Artificial intelligence alignment

July 26, 2026 | Artificial Intelligence | Joaquimma Anna

Artificial intelligence alignment refers to the challenge of ensuring that AI systems act in ways that are consistent with human values, intentions, and ethical principles. It involves designing AI behaviors that are beneficial and safe, particularly as AI systems become more autonomous and capable.

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Anthropic (company)

July 24, 2026 | Artificial Intelligence | Joaquimma Anna

Anthropic is an American artificial intelligence research company focused on developing AI systems with an emphasis on safety and interpretability. Founded in 2021 by former OpenAI employees, the company aims to create reliable and steerable AI technologies.

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Eliezer Yudkowsky

July 9, 2026 | Artificial Intelligence | Joaquimma Anna

Eliezer Yudkowsky is a researcher and writer known for his work on artificial intelligence and rationality. He is a co-founder of the Machine Intelligence Research Institute.

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Conservative Q-learning (CQL)

June 28, 2026 | Artificial Intelligence | Joaquimma Anna

Conservative Q-learning (CQL) is a reinforcement learning algorithm designed to enhance the stability and reliability of learning in complex environments.

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TruthfulQA

June 17, 2026 | Artificial Intelligence | Joaquimma Anna

TruthfulQA is a benchmark designed to evaluate the truthfulness of language models by testing their ability to provide accurate and truthful answers to questions that may induce false or misleading responses.

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Claude (language model)

June 13, 2026 | Artificial Intelligence | Joaquimma Anna

Claude is a series of large language models developed by Anthropic, designed for natural language understanding and generation. It aims to provide safer and more controllable AI assistant capabilities through advanced machine learning techniques.

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Asilomar AI Principles

May 30, 2026 | Artificial Intelligence | Joaquimma Anna

The Asilomar AI Principles are a set of guidelines designed to promote the safe, ethical, and beneficial development of artificial intelligence. Created in 2017, they address issues such as research transparency, value alignment, and long-term safety.

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Recent Articles

  • Learning to adapt (meta-learning for domain shift)
  • PolyCoder
  • SPLADE (sparse lexical and dense)
  • How Long Does It Take to Get Your Nails Done? Salon Time Guide
  • CoQA (Conversational Question Answering)
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