- Pascal's Chatbot Q&As
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Archive
The insights from the article "Where do Healthcare Budgets Match AI Hype? A 10-Year Lookback of Funding Data" provide valuable lessons for AI makers, investors, healthcare organizations and regulators
By focusing on areas with demonstrated value, aligning with proven ROI, and fostering collaborative regulatory frameworks, each group can contribute to AI’s successful and responsible integration.
GPT-4o: An ideal opt-in/opt-out approach focuses on user empowerment, simplicity, and protection. The company should avoid placing the burden of proof on the user...
...ensure that data is handled with transparency, and prioritize minimizing the collection of sensitive information when users exercise their rights.
The article "Microsoft’s Hypocrisy on AI" by Karen Hao, explores the contradiction between Microsoft’s public climate commitments and its ongoing business relationships with fossil-fuel companies.
While Microsoft is making these public pledges, it is also marketing its AI technologies to major oil and gas companies to help them discover and extract new fossil-fuel reserves more efficiently.
GPT-4o: While AI could be a tool for societal good, in the hands of corporations, it is contributing to environmental degradation, labor exploitation, and increased militarization.
The article’s critique of AI as a force that is increasing inequality and environmental harm while being used for militaristic purposes offers a fresh, controversial, and provocative view.
Grok: While Musk publicly supports the idea of responsible AI, his actions suggest a more complex relationship with the actual practice of these principles...
...where commercial interests or the push for rapid innovation might sometimes overshadow strict adherence to responsible AI ethics. His adherence to these principles in practice appears inconsistent.
GPT-4o: No matter how big you make an AI model or how much data you give it, there's a limit to how good it can get, and we're not entirely sure why this happens yet.
This means that industries requiring high accuracy, like healthcare, autonomous driving, or legal sectors, need to understand that AI won't become perfectly accurate.
Mollick highlights key issues in the performance of OpenAI's "Strawberry" (o1-preview) that are unlikely to be resolved soon. Below are the problematic issues & their potential long-term consequences.
Without such improvements, AI systems like Strawberry may reach a performance ceiling, unable to fully integrate into domains that require trust, adaptability, and nuanced reasoning.
The jailbreak seems to expose a way of forcing the AI to engage with restricted content by using "leetspeak" (altered text), which may have been designed to bypass certain filters or monitoring tools.
The second post expresses anger at being locked out of the O1 models, implying a possible temporary or permanent suspension after engaging with the jailbreak or illicit content generation.
GPT-4o: I agree with the author’s nuanced and practical approach to using AI as a supportive tool in peer review, rather than a disruptive force.
The goal should be to leverage AI’s strengths to complement human expertise, without compromising the integrity of the peer review process or overloading reviewers with additional tasks.
GPT-4o: Yes, people can end up acting, talking, and writing like "drones" due to several factors. The combined effect of AI systems funneling similar information to large groups of people...
...encouraging a lack of independent thought, and being used by commercial entities to influence behavior creates a significant risk of people behaving more like "drones."
GPT-o1 about itself vs 4o: I can remember and reference earlier parts of our conversation more effectively. I can better recognize and respond appropriately to the emotional tone of your messages.
To avoid conflating the term "reasoning" as used for humans with the processes performed by AI language models like myself, you might use alternative terms such as: Pattern Recognition...