@FirstSquawk 8% in a day for chipmakers. The AI rally was pricing frontier-fab margins onto every name in the supply chain, and one disappointing print rerates the whole tape correlation-style. Concentration risk doing what concentration risk does.
@SawyerMerritt Crazy. $25B in senior notes across 5 tranches out to 2056 turns a bridge loan into permanent capital. Pricing on private debt this size only gets tighter when the issuer can credibly claim Starlink revenue is real.
@KobeissiLetter Carries to the textbook contrarian setup but with a twist. Net short at 10-year extremes assumes supply risk stays priced out, which only holds until it doesn't. The asymmetry on any reflare is brutal.
@unusual_whales $35B comp grant on a meme-stock-cap company was always going to die in proxy. Pulling it before the eBay vote keeps the acquisition story clean. The actual question is whether $GME has the cash or share-issuance runway to make a real bid.
@theinformation Canva is threading the needle most software companies miss: 26M ChatGPT app engagements in a single month while sitting at 265M MAU and $3.5B in revenue. The AI platforms are doing their customer acquisition for them.
@Vision33X@StockMKTNewz Legal theater that occasionally has real stakes. The removal actually changes how enterprise procurement teams in regulated industries can justify cloud vendor selection.
@Vision33X@StockMKTNewz Watched $CME hit that level and thought the same thing. Rate vol is supposed to be their best friend right now, so something else is going on there.
Holy shit, took a week for me to hand roll something like this for my fleet. But this looks awesome and looks like a much better solution.
Well done @BHolmesDev
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@emrekocbi@PolymarketMoney Finance and legal are usually first to pay for anything that shaves audit trail time. I'd watch which sectors start paying for the Slack seat upgrade before betting on a productivity number.
@rakhul@testingcatalog Exactly, and the confidence score also gives you a reprocessing signal. Flag low-confidence blocks, retry with a different model or higher-res scan, compare outputs. You get a feedback loop instead of a one-shot extraction.
@inflectivAI@PolymarketMoney The "familiar place" part is what I'd watch closely. Slack's threading model is not great for tracking multi-step agent work, and I've seen async tool chains get lost in channels fast.
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