Humor is safe from AI. For now.
SAFETY
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Meta’s Countermeasures Against Disinformation and Harmful Content
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Meta spends a considerable amount of efforts *preventing* people with nefarious intent from manipulating people on the platform. In fact, the countermeasures against disinformation, false accounts, hate speech, terrorist propaganda, calls to violence, and attempts to corrupt the
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Avoiding Awful Products: The Risk of Optimization Without Understanding
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Two easy steps for making an absolutely awful product: 1. Have no clue about what you are doing. 2. Optimize step number 1.
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Autoregressive Sampling: Language Models Generate Hallucinations by Design
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When we autoregressively sample from a language model, we are, by definition, seeing its hallucination. Users may think otherwise only when the LLM’s “dream” just so happens be an output that is acceptable to the user.
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Adversarial Training Framework Improves LLM Robustness
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Drop by the #EMNLP2023 Google booth today at 12:30 PM to learn about an adversarial training framework that uses limited human adversarial examples to generate and scale more useful synthetic examples that improve LLM robustness to unseen attacks.
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Regulators Determining LLM Compliance Standards Questioned
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Can’t wait for these people to be in charge of determining if your LLMs are compliant!
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Corporate Responsibility for Deceptive AI-Generated Video Content
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So it's the responsibility of the viewer to determine that they're lying to us and not the responsibility of the company that created the video? Sorry… But I whole-heartedly disagree with your take!
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AI Misrepresentation: Video Understanding Claims Under Scrutiny
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They gave the impression that the AI was responding to the video footage. I can understand the speeding up responses. But the implication that it was responding to the video footage it was seeing when it wasn't even close to doing that, feels wrong.
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ChatGPT needs more consistency and reliability improvements
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I’d like to see more consistency, reliability, and robustness from ChatGPT.

