Cristian Pereyra (@kshmir) header
Cristian Pereyra (@kshmir) profile picture

Making @kaptionai - among other things.

Austin, TX
Joined November 2008
Photo by Cristian Pereyra (@kshmir)Photo by Cristian Pereyra (@kshmir)Photo by Cristian Pereyra (@kshmir)Photo by Cristian Pereyra (@kshmir)Photo by Cristian Pereyra (@kshmir)Photo by Cristian Pereyra (@kshmir)Photo by Cristian Pereyra (@kshmir)Photo by Cristian Pereyra (@kshmir)Photo by Cristian Pereyra (@kshmir)Photo by Cristian Pereyra (@kshmir)
Replying to @SomosAnalistas_
En 7 meses Trump le pone la medallita a Lionel.
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Cristian Pereyra retweeted
Timeless career advice:
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Mejor auto del mundo en el mejor pais del mundo!
Llegamos a Argentina el 20 de Noviembre
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Qué fruta noble la RTX 5090
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My jaw dropped I'm still trying to pick it up
I'm not even sounding the claxon for this it's just horrible. Any text > 256chars is a valid root password, holy shit sshhole.com/
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Amen
One universal truth to leading a company: When it’s all said and done, the revenue is always somehow less than you expected, and the expenses are more.
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Cristian Pereyra retweeted
I built this thing called Kairon It's an MCP that sells for you from Claude, ChatGPT, or GrokBot It finds qualified leads daily, and keeps conversations going until the meeting is booked I've been using it for the last 3 months, and it got me 60+ companies at 4.5k MRR. Try it!
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Some you win some you lose...
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1/ Sam Altman argued this week that AI running on everyone's own computer is a misallocation of the world's limited memory and chips, which do more good shared in data centers. I checked the numbers on a real, free AI model. Here it is in plain English. 🧵
sam: local inference is a terrible allocation of scarce resources “a lot of people want local inference, and somehow they assume that the problem is solved now because we have open-source models, we're going to be able to run them on our computers, and so we're not going to need all the stuff in the data centre but from a global allocation perspective, actually it's quite terrible to have everybody, like, have a bunch of the world's limited supply of DRAM sitting in their own computer and being used five percent of the time you want maximum utilisation in the cloud if you're trying to deal with this very supply-constrained environment somehow many people's intuition is the opposite of that”
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7/ So the numbers back his allocation point. Easy to mix up: "open" AI and "local" AI aren't the same. Open: anyone can use and inspect the model. Great. Local: everyone buys their own machine to run it. That's the waste.
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Something we can agree on! Except for audio… that is 100% solved.
sam: local inference is a terrible allocation of scarce resources “a lot of people want local inference, and somehow they assume that the problem is solved now because we have open-source models, we're going to be able to run them on our computers, and so we're not going to need all the stuff in the data centre but from a global allocation perspective, actually it's quite terrible to have everybody, like, have a bunch of the world's limited supply of DRAM sitting in their own computer and being used five percent of the time you want maximum utilisation in the cloud if you're trying to deal with this very supply-constrained environment somehow many people's intuition is the opposite of that”
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Decime que dependés de BRL<>USD sin decirlo.
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