there’s a way of thinking I’ve adopted in the last year or so where I’ve started to believe everything is my fault, without the self judgement it comes with. Even for things outside my control. Bad market? My fault for picking it.
Bad output? Skill issue if I did it myself or
@waitin4agi_
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Taking Ownership: Adopting Personal Responsibility Without Self-Judgment
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Early AI Model Adoption as Competitive Arbitrage Opportunity
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there’s a massive arbitrage just trying and using the models before everybody else.
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Commercializing AI Research: The Symbiotic Relationship Between Innovation and Funding
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it’s misguided. Researchers need people who can commercialise the technology. It’s very high risk but some of these people will generate enough money to fund more research. The wrappers all start small of course. It’s a symbiotic relationship — the two sides need each other.
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Building Defensible Competitive Edges in Business Strategy
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Actually it doesn’t matter in business unless it gives you a defensible edge against your competitors (key word being defensible)
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Wrappers vs Foundational Models: Business Strategy Guide
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I have a book recommendation for people who keep arguing about wrappers versus foundational models. Especially if your goal is to build a business instead of doing research. Wonderful biz book in general
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Open sourcing fine-tuned video models: balancing access and safety
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if we train a fine tuned video model on my face, should I open source it? I can add good faith guardrails to prevent abuse maybe.
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60% Right Strategy for Risk Taking and Performance
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I think it’s generally better to be like 60% right on the things you do/work on. It’s like Dota MMR: you need close to 52-60% win rate to climb. Aiming for 90-100% will mean you’re too risk averse and probably not play at all and not have fun either. If you’re 60% right over the
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AI-Generated Content Becomes Indistinguishable From Human Work
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will also be a very good exercise while watching the video for you is to spot where the AI stuff starts and where it ends. I really don’t think most people will be able to tell.
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Budget Constraints and Organizational Bureaucracy Growth
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I’m relearning some age old budgeting lore — unlimited taps eventually leak (no incentive to shut down unused subscriptions etc), but when you set a clear unmoving subscription budget that changes. Even if it looks too stiff. Is this how companies become bureaucratic?
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Learning Image LoRA Tuning Through Practical Experimentation and Datasets
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my own learning from using tuners is that you learn by doing. like we know to some degree what will happen to the output of an image Lora depending on what params we change and we’ve found it to be more intuition than science. Also, dataset.