seth bloomberg
@bloomberg_seth
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Investment Partner @UnsupervisedCap | prev: @CrucibleLabs, research @MessariCrypto | Woo Pig 🐽
Joined September 2019
Starting a telegram channel. It'll be a collection of things I find interesting at the moment, coupled with some writing, eventually. Link is in my bio and the next tweet.
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Seems we've hit the time of the market cycle where everyone is questioning whether we need tokens in crypto.
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This seems relevant again today. Expect it will continue to be throughout 2026.
Becoming clear now to everyone that solving the token vs equity problem is one of the biggest opportunities within crypto. On par with stablecoins, DeFi, etc. It's also clear that L1 tokens like SOL, ETH, etc existentially depend on solving this problem too.
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NSF is launching one of the most ambitious experiments in federal science funding in 75 years. The program is called Tech Labs, and the goal is to invest ~$1 billion to seed new institutions of science and technology for the 21st century. Instead of funding projects, the NSF
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Becoming clear now to everyone that solving the token vs equity problem is one of the biggest opportunities within crypto. On par with stablecoins, DeFi, etc. It's also clear that L1 tokens like SOL, ETH, etc existentially depend on solving this problem too.
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I'll never understand our industry. We'll jump through endless, nonsensical hoops to come up with the next narrative to chase, but after 10 years we still don't know if Ethereum is massively under/over valued.
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Saying you don’t believe in crypto-AI is saying you dont believe in Bitcoin Here’s the proof of work That is all
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1/ Re: confusion about TAO emissions and TAOflow A visual explanation of what it means for subnet token prices 👇
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Love to see the bear market bringing back the L1 debate. To state the obvious: -- Yes, they have moats -- Yes, the outcomes will look binary + exponential It is interesting, though, that no one will really tell you how to value them.
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Today, we are announcing the launch of Training at Home, our effort to democratise the creation of AI models to allow the many to participate, not just the few. Training at Home is an easy to use application that allows anyone with a Macbook to contribute to creating AI models.
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steady lads. Adoption is coming. @bitmind has experienced 10x more enterprise interest than ever. Fake documents, scam pictures to use as returns, financial fraud. semantic search of our traffic so ppl can lookup all the deepfakes of them. fundamentals across bittensor look
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Diffusion models just seem cooler, glad to see their time is coming
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