Browse Comments — Clean (de-noised)
Close reading of the corpus at each pipeline stage: raw → clean → relevant → coded.
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The 'who benefits' framing exposes the governance gap. I see companies rushing to deploy agents without defining ownership of the output or liability for errors. Speed beats scrutiny every time. How are you seeing leadership teams actually structure accountability for autonomous AI decisions?
The concentration of data and compute infrastructure makes equity the biggest hurdle, not the code itself...
History shows: technology rarely destroys societies. But bad coordination, weak institutions, and concentrated value sometimes do.
The banned words list also trains your own awareness. It teaches you to catch them in your own drafts before Claude even has to filter them out.
Pumped for 3.5 flash
I have developed a set of prompts that assist students with the workflow of a research paper, giving inspiration in the areas of topics and research questions, getting them to generate content with AI and then use AI to help critique and improve on the ideas and analysis. Students so far seem to think that it’s the best of both worlds. They do produce better work but they feel they’re in control and are learning by going through the process. It’s a work in progress but I would be happy to share the prompts with anyone interested
Just like with all things technology ever: those who blindly walk the broad path before them will find themselves farther away from themselves than those who walk the tight path, knowing and feeling their way closer to who they are. AI is no exception. It’s a catalyst like they all are. What choice will you make?
Day four connect Gmail. Read last ten emails with contact. Draft answer send ready. No more copy paste.
Most enterprise AI failures happen because companies focus on making the brain smarter while ignoring the wiring, permissions, and decision structure around it. Luís Rodrigues
This is one of the oldest arguments in political economy. The pattern is still the same: a new resource comes along, a window opens, a small group moves fast, and then the widow closes. That small group that moved fast controls now the resource. Now, the question is, what comes next for those who do not belong to that small group?
Paolo Spada In the context, that makes sense.
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Greetings Demis, I have attempted contacting you via email as several people have suggested that we talk. Having been sent ‘The Thinking Game’, and then yesterday a link to an interview between Sebastian Mallaby and Michael Walker of Novara Media, I understand why people wish for us to speak. I am not a threat to you, or your work, I do however possibly hold the answer for how to make AI safe. If this is a genuine concern, as is being said, please respond to my email, or reach out on here. I have already been asked by cognitive scientists I work with to write about the future of AI. And have written a chapter for another academic book on the subject. I will write a thesis and ensure it is well-documented the ways I have tried to reach you. With respect and kind regards, I hope to hear from you soon.
I am afraid it is a little too late. It is naive to think we can go back and start again on the right path this AI journey.
Pascal BORNET Your emphasis on 'who decides and benefits' is a powerful point. The real impact of AI hinges on intentional design and responsible governance, ensuring its advanced capabilities genuinely serve broader human outcomes.
Tamer Chowdhury thank you
the data loop one hits different when you're building something with real user-contributed data. that moat grows every single day and nobody can just copy it overnight
Day 6 is where most people quietly miss the real ROI. Going from 'I prompt Claude' to 'Claude runs my recurring workflows' is the inflection point — scheduled tasks plus connectors turn it from an assistant you visit into infrastructure that compounds in the background. Solid breakdown, especially the .md voice file on Day 3 — underrated step.
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Liked for the shirt