💼 Replacing Human Workers with AI is more Expensive.Plus: Are Chokepoints the only way to control AI? - ChatGPT has been Updated and is allegedly “less Lazy.”
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ChatGPT has been Updated and is allegedly “less Lazy.”OpenAI's GPT-4 Turbo addresses 'laziness' in task completion with an update trained on data up to April 2023. Over 70% of GPT-4 API users have migrated to this version for its improved capabilities. Upcoming features include vision capabilities for multimodal interactions. Additionally, OpenAI introduced 'embeddings' models—'text-embedding-3-small' and 'text-embedding-3-large'—to enhance AI's understanding of content relationships, marking significant progress in AI technology.
The US Data Privacy ChecklistScale your consumer data privacy program with ease. Vanta’s exclusive US Data Privacy (USDP) framework is all you need to comply with state-level consumer privacy laws. By covering all state privacy laws with one comprehensive set of controls, this unlocks a fast, scalable way to keep you ahead of ever changing privacy laws across the US. Do the work once and ensure your business simultaneously adheres to CCPA/CPRA, CPA, CTDPA, UCPA, and VCDPA. The framework is constantly being updated to keep up with new and evolving regulations. Download the US Data Privacy checklist to learn more. Replacing Human Workers with AI is more ExpensiveMIT researchers found that replacing human workers with AI in visual inspection tasks is often more expensive than keeping human labor. Their study across 800 occupations showed only 23% of tasks are cost-effective to automate due to high AI system costs. This finding suggests that AI-driven job displacement will be significant but gradual, allowing time for policy development and workforce retraining. Despite the rapid growth of AI technologies like ChatGPT and Bard, and recent tech sector layoffs, experts believe this shift could lead to new types of jobs. The study, supported by IBM's Watson AI Lab, highlights that while automation may become more economically feasible over time, it currently remains limited and requires thoughtful regulatory preparation. Are Chokepoints the only way to control AI?In the realm of AI development, researchers are exploring the concept of embedding restrictions within crucial components like GPUs to regulate AI's power and prevent dangerous applications. This approach, which ties AI's capabilities to its hardware, aims to offer a more enforceable solution than conventional laws or treaties. Modern devices already employ similar security measures, like iPhones' secure enclaves for biometric data. The proposal, while theoretically sound, faces significant challenges in technical implementation and political acceptance. It draws parallels to nuclear nonproliferation methods, suggesting a new frontier in AI governance. However, the tech industry has shown resistance to such hardware-based controls, citing ethical and complexity issues. The U.S. government has expressed interest, indicating a potential shift in how AI capabilities might be regulated in the future. 💰 Follow The Money
🤔 What Does that even Mean? Term of the DayOverfitting: A modeling error in machine learning that occurs when a function is too closely fit to a limited set of data points. Example: A weather prediction model is trained with a very specific set of data from a short period. It performs exceptionally well on this training data but fails to accurately predict weather when given data from a different time frame or location. This is because it has learned the peculiarities of the training data too well, at the expense of its ability to generalize to new data. 📰 Publications I am currently reading and recommending:
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Friday, January 26, 2024
πΌ Replacing Human Workers with AI is more Expensive.
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