Raw LLM Responses

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G The scary part for me is how many people seems to think similar to your girlfrie… rdc_m2br45t G Back in line with all the other jobs that have disappeared because of industrial… ytc_UgyrPlnQE… G You're wrong, there is a point when made by AI, to make money off of you 😂… ytc_UgwHzzFZj… G > by the exorbitant energy usage of AI. Can we stop with that bullshit of an… rdc_n0jaqm7 G Google: Midjourney image of Yoda taking a selfie. It shows the results from the … ytc_UgxDxc-dI… G Guys. My brother snitched on me when I was talking to Boxten on poly ai. My mom … ytc_UgwvRUwnT… G Muy bueno los videos Pero un detalle, suban más el volumen de los personajes... … ytc_UgzxCCdw8… G WakleeKins, until the A.I. deep learning algorithms figures it out and writes it… ytr_UgwVQNSFC…
Comment
In his TED talk, Andrew Ng emphasizes the parallels between the rise of AI and literacy, highlighting the need for broad access to technology for societal advancement. He points out that AI development is predominantly concentrated in big tech companies, which restricts access for small businesses and individuals. However, small enterprises like local pizza shops and T-shirt companies stand to gain significantly from AI, potentially improving operations and boosting revenue. Ng notes that many AI applications require custom solutions tailored to the unique needs of individual businesses rather than a one-size-fits-all approach. Emerging development platforms are changing this landscape by enabling users to create AI systems with minimal coding, focusing instead on data input. By democratizing access to AI tools, everyday professionals, such as accountants and quality inspectors, can develop tailored AI solutions. This empowerment could lead to broader economic benefits, enhancing productivity and innovation across various sectors. Ng envisions a future where everyone has the tools to build AI systems, driving significant advancements in multiple industries.
youtube AI Governance 2024-11-02T07:4…
Coding Result
DimensionValue
Responsibilitynone
Reasoningconsequentialist
Policynone
Emotionapproval
Coded at2026-04-27T06:26:44.938723
Raw LLM Response
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