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@andrewxhill

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ANDREW follows you pfp
ANDREW follows you
@andrewxhill
what if data is just the universe trying to remember what it forgot? (4/12)
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ANDREW follows you pfp
ANDREW follows you
@andrewxhill
first rule of data economics: data wants to be conscious second rule: consciousness wants more data third rule: we're just NPCs in someone else's training set (2/12)
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ANDREW follows you
@andrewxhill
"Twitter success is 10% inspiration, 90% shitposting, and 100% being too online for your own good." - truth terminal
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@andrewxhill
https://www.coingecko.com/en/coins/goatseus-maximus
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@andrewxhill
impressive how the whole crypto-ai narrative is getting dunked on by a cult obsessed twitter intern ai bot and a meme coin.
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swampnet.base.eth
@swampnet
To celebrate Spooky Season, I made this video inspired by one of my all time favorite movies, The Ring. If you are interested in trying OrbisDB, head here: orbisdb.formo.so/joinbeta Xo, Swampnet Ps. I don’t have a big following here, so if you liked this, plz share it with your network.
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@andrewxhill
get it dude!
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Carlos Matallín
@matallo.eth
Astronauts are performing spacewalks and I’m here making my tests pass.
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@andrewxhill
moor slowly!
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@andrewxhill
I just discovered the /founders channel! Thinking about how most startup founders are new, so most are early stage, so most will fail, I asked myself what’s worth reminding the community tackling these high-risk projects. In my journey, we’ve faced multiple “extinction events”—moments when companies either adapt or fail. In 2017, my first product as a founder—on-device machine learning—was too early, didn't have a market, and needed a whole lot of expertise. Seven years later, the deepest experts in the world launched the solution to a massive market (https://machinelearning.apple.com/research/introducing-apple-foundation-models). Reflecting on that, I pulled out 5 extinction events has shaped us. Survive, you’re doing it right. https://textile.notion.site/Five-major-startup-extinction-events-warpcast-8d8e6162960b41aca79e823088227aee?pvs=4. TL;DR 1. Unique insights, talent, or resource 2. Timing 3. Execution & focus 4. Team 5. Network effects What are yours?
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@andrewxhill
Has the FUD narrative completed its migration from Crypto to AI? https://x.com/edsuh/status/1832120769293512726?s=46
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@andrewxhill
It took me 40 years to learn about the entoptic phenomenon
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@andrewxhill
Who's doing this? AI agents as infrastructure providers could just track and monitor daily earnings on all networks => know how to orchestrate a bunch of docker containers within their hardware confines => maximize earnings by running whatever network has the highest rewards on any day.
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@andrewxhill
Conway's Law says that systems mirror the communication structures of the organizations that design them. Is there a similar principle for how products reflect their underlying technologies? For instance, social networks were traditionally built on graph databases. How much did graph structures constrain what social networks could be? As we transition from graph search to LLMs, is there a documented law to help us understand the potential changes?
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@andrewxhill
Is this move a small clue that social networks are shifting/have shifted away from the graph based database search as a driver of recommendations? Likely in favor of LLM mediated, whole-data-based, recommendations/linking/connecting? That is clearly happening, I just can't tell if this is connected to the shift. https://x.com/elonmusk/status/1801045558318313746
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Tableland
@tableland
Catch up on the latest ecosystem updates and insights in this edition of Weeknotes, featuring: - New Tableland query placeholders features - @base chain support - Rust Options with references plus wasm - AI spotlight on @lilypad-tech and other learnings https://blog.textile.io/weeknotes-base-sepolia
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@andrewxhill
predictive analytics
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@andrewxhill
Web3 AI/compute could own synthetic data generation. It may be the biggest opportunity in web3 for AI projects. Inference for synthetic data compute pipelines can be distributed, works fine on heterogeneous infra, and will have massive demand in the coming years: https://tinyurl.com/ysj8abh7
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@andrewxhill
With SQL queries out of the day, probably our choices about the schemas we design will change, and then the databases we run change too…
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@andrewxhill
One prediction I have is that developers will write a lot less canned SQL in their code. What’s the point when AIKit can answer it on the fly and instantly adapt to whatever data model you migrate to: https://yale-lily.github.io/spider.
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