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askr

@heyaskr • 1,907 subscribers

Use AI together in chats of 100 people. Every AI model is waiting to help you, just tag askr. No subscriptions, pay for what you use with card or crypto.

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What a crazy 24 hours since the doors opened to the public. We never anticipated this overnight platform adoption. On launch we accumulated robinhood:0xa92768863a55d8a0591709f7f5e594a249d36ea3 to help control a successful launch, and to use towards marketing. With creator fees and platform adoption within the first 24 hours exploding, the supply isn’t needed. Everything is being funded in ETH. So we did what they were bought for... marketing! $315,000 of robinhood:0xa92768863a55d8a0591709f7f5e594a249d36ea3 tokens have been burned removing just over 7% from circulation 🔥 >

What a crazy 24 hours since the doors opened to the public. We never anticipated this overnight platform adoption. On launch we accumulated robinhood:0xa92768863a55d8a0591709f7f5e594a249d36ea3 to help control a successful launch, and to use towards marketing. With creator fees and platform adoption within the first 24 hours exploding, the supply isn’t needed. Everything is being funded in ETH. So we did what they were bought for... marketing! $315,000 of robinhood:0xa92768863a55d8a0591709f7f5e594a249d36ea3 tokens have been burned removing just over 7% from circulation 🔥 >

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Fusion Models by robinhood:0xa92768863a55d8a0591709f7f5e594a249d36ea3, explained properly. Why a panel beats one model: Ask three models the same hard question and they disagree. The disagreement is the information, where they contradict each other is where one of them is wrong, and a judge can see it. OpenRouter shipped exactly this in June and their panels beat any single frontier model. Credit to them and their $10B sale to stripe. Why the same panel for everyone is the wrong shape: You don't have one best model. You have a best model per job. The one you trust for code is not the one you trust for writing, and neither is the one you'd pick for a five-line reply. A panel chosen per request, identical for every user, can't know that. A panel arranged around you can. The number that matters isn't price: It's cost per answer that works. Model A costs $4 per million tokens and gets your job right one time in four. Model B costs $10 and gets it right three times in four. Per answer you actually keep, A costs $16 and B costs $13. The cheap model was the expensive one. Everyone comparing price lists is measuring the wrong thing. You never rate anything: Stopping an answer halfway is a rating. Regenerating is a rating. Switching model and asking again is the loudest rating there is. Every one of those already writes a row we can learn from. The router learns which models earn your credits, per job, and tries a cheaper one now and then to check. Fusion only when it pays: Cost mode tries the cheap model first and escalates only if a judge says it failed. Performance mode fans out to your panel and merges. Most simple prompts never fuse. That's why it costs less, not more. Put it together and you have a personal model: Not trained. Assembled. Your profile from a two-minute questionnaire and everything you've imported from Claude or ChatGPT. Your memory, shared across every model so switching never starts from zero. Your skills, workflows you build once and run on any model. Your scorecard, which models earn your credits per job. One per person. Nobody else has yours. Every model is someone else's; the arrangement is you, and it leaves with you. People aren't loyal to models. They're loyal to results. A moat can't be a commodity, but it can be our own creation.

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