Our statement on Governor Newsom's AI Working Group Draft Report:
ETHICS
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Sam Altman’s Senate Testimony on AI Engagement and Monetization
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Two @sama quotes I think about often from the Senate Judiciary Committee's AI hearing in 2023: The 1st answer is when @ossoff expressed concern about tech companies maximizing engagement. The 2nd is when @CoryBooker asked if OpenAI would ever consider ads.
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Tech Monetization and AI: Senate Judiciary Hearing Insights
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I always think about the 2023 Senate Judiciary Committee's hearing on AI when @ossoff noted tech companies' tendency of monetizing engagement. Here's how @sama answered, and I've always wondered how long this would hold up:
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COBOL Unlearning and AI Model Training Implications
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“How could unlearning COBOL lead to this?” I’m crying
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Five Critical Cybersecurity Mistakes Companies Make With AI
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5 Mistakes Companies Will Make This Year With Cybersecurity #Businesses are facing unprecedented #cybersecurity threats from #AI-powered attacks, unprepared employees, and insider #vulnerabilities that could devastate their bottom line. Bernard Marr reveals the five critical
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Responsible AI Governance and Business Impact with Ryan Carrier
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Can responsible AI drive better business? Ryan Carrier, Executive Director of ForHumanity, cuts through the noise on AI governance, auditing and why informed consumers hold the power. Listen now http://
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Compute Power Increases Model Confidence and Overconfidence Risks
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– And good news! More compute = more confidence as well. (However, more compute made one model become more confident in wrong answers too. Something to keep an eye to make sure model confidence doesn’t tip into overconfidence.)
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Model Confidence Critical for High-Stakes AI Applications
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– Higher compute and confidence were extra important for model performance when wrong answers had serious consequences (like when they were weighted 20x). You wouldn't want a 51%-sure diagnosis of a terminal illness.
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Johns Hopkins: LLMs Must Know When to Abstain
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You can't just be right, you have to know you're right. Good advice for LLMs, according to new Johns Hopkins research. Sometimes no answer is better than a wrong one – life or death choices in medicine, for example, or big financial decisions.