Fadhil Yaacob

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Fadhil Yaacob

Fadhil Yaacob

@sdil

Lousy Software Engineer. Building https://t.co/hNJbvNKtv1 & https://t.co/oUbDUoCEz1

utc+8 Katılım Haziran 2008
4.9K Takip Edilen1.6K Takipçiler
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Fadhil Yaacob
Fadhil Yaacob@sdil·
I never pinned a tweet until today
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Joran Dirk Greef
Joran Dirk Greef@jorandirkgreef·
We built an S3 client with 20x more throughput (and with a single core): youtu.be/-p-Xm7VEqSk
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SNEAKO
SNEAKO@sneako·
Muslims are taking over America
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Alex Veremeyenko
Alex Veremeyenko@alex_verem·
Anthropic admitted it in court.
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Hedgie@HedgieMarkets

🦔AI companies are bulk-buying rare books, scanning them through high-speed machines that cut the spines off, and shredding the originals. A service called ISBNdb facilitates orders of up to a million books and keeps buyers anonymous. Pre-2022 books are premium because they're free of AI-generated text. A federal judge ruled the practice is fair use because eliminating the original means only one copy exists at a time. Anthropic hired the former head of Google Books partnerships to obtain "all the books in the world." My Take This got to me. A bookseller told 404 Media that rare books with almost no surviving copies are being fed into this pipeline. Books that survived wars, fires, and centuries of handling are being shredded so an AI can learn to write a better marketing email. ISBNdb's website literally says "'AI company destroys two million books' is not a headline that generates sympathy," and they still built an entire business around making it happen quietly. They offer NDAs as a feature. They coach clients to call it "digital preservation." I've covered AI companies scraping the internet, torrenting libraries, and stealing music. This is worse because it's irreversible. You can re-upload a website. You can reprint a bestseller. You can't replace the last three copies of an 18th-century botanical text once someone shreds them for training data. And the judge said it's legal. So it's going to accelerate. "We shred rare books and offer NDAs so nobody finds out" is a legitimate business model in 2026. What a timeline. Hedgie🤗

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Shruti
Shruti@heyshrutimishra·
WTF AI companies are purchasing large quantities of used and rare books. Scanning their contents to train models. Then turning the originals to pulp. The sum of human thought, digitized and shredded. Every book that gets scanned disappears from the physical world permanently. The knowledge survives only as training data inside a system no one can hold, browse, or resell. What used to sit on a shelf for centuries now exists as weights in a model that might get deprecated next quarter.
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TigerBeetle
TigerBeetle@TigerBeetleDB·
And finally, how we engineered the engineering of this mission-critical OLTP system: TigerStyle, our methodology to ship safer software, faster. Static Allocation, Assertions, Deterministic Simulation Testing, and how to think of safety as a System property instead of a Language property.
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TigerBeetle@TigerBeetleDB

And now the architecture of a mission-critical OLTP system. TigerBeetle provides, preserves, and exploits durability for availability, by co-designing the global consensus protocol and local storage engine.

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ahmet alp balkan
ahmet alp balkan@ahmetb·
we're launching baseten-switch: it's a local gateway that diverts requests from Codex/Claude Code to models like Kimi K3/GLM 5.2 that we host. keep your harness and swap out the model for a more cost-efficient one. easy to turn it on/off when you don't like it. also has cost comparison UI. feedback appreciated.
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Alex Ker 🔭@thealexker

x.com/i/article/2082…

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Burak Karakan
Burak Karakan@burakkarakann·
ingestr is fast. Like, really fast. It is because we are obsessed with fast tools. The first version of ingestr, v0, was in Python. It was feature-complete and allowed us to got to the idea as quickly as we could, and we learned a lot from that experience. We understood the shape of the problem better, and it allowed us to grow the usecases we supported over the past year. However, it was slow. When we rewrote it in Go this year, with ingestr v1, we took performance as a core part of the platform. This meant that benchmarking was a part of our development lifecycle from the get-go. If there was anything that is faster than us in benchmarks, we would need to understand what they do better, and bring the learnings into ingestr. This included things like reducing allocations, building deeper integrations with source and destination platforms, and building a benchmark suite that allowed us to track the performance of our changes. I am very proud of where ingestr got to. There might be some tools that are faster here and there, and we'll continue chasing them, but I don't think there is any comparable alternative with 130+ built-in sources, 20+ destinations, with this performance.
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Fadhil Yaacob
Fadhil Yaacob@sdil·
Anyway, they claim to be faster than Redis, ValKey & Dragonfly, but it lacks a lot of features. It only support primitive commands like GET, SET & DEL atm.
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Fadhil Yaacob
Fadhil Yaacob@sdil·
github.com/Saxy/Tellstone… this codebase is so nice to read. A RESP-compatible in-memory KV store. It uses shard-per-core in Go, which scales linearly by num of cores; first time seeing the implementation in Go (skill issue). And it's zero-allocation on the hot path
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Paul Graham
Paul Graham@paulg·
I wonder if Google will have the advantage in preventing their models from being influenced by this kind of campaign from their decades of fighting black hat SEO.
Drop Site@DropSiteNews

⚡️NEW from @DropSiteNews: Israel Is Paying Millions to Train AI Chatbots How to Talk About Gaza. It's Working. Former Trump campaign manager Brad Parscale is overseeing an operation posting hundreds of blog posts on behalf of Israel, with the goal of infiltrating artificial intelligence. Story by @nick_clevelands dropsitenews.com/p/israel-brad-…

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The Saviour
The Saviour@TheSaviour·
This is what terrorists look like.
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Brandur
Brandur@brandur·
River Pro v0.26 ships today with active job rescue: • Jobs may become orphaned if the process running them crashes with no opportunity for graceful stop that'd set them back to available. • Traditional job rescue compares job timeout to job start time, adding a safety margin, and rescuing anything that should be finished. • River Pro tracks live clients/queues in an UNLOGGED table (no added WAL pressure) that's frequently heartbeated. • Active job rescue rescues any running jobs in a client/queue that's not reporting, reducing rescue delay from hours to minutes.
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GBC
GBC@GBC_Press·
🚨 BREAKING: ​US House Representative Mike Bost rebelled against Israel's genocide in Gaza: ​"Islam has nothing to do with this matter. To support Palestine, it is enough to be HUMAN." ​Notice to those who are HUMAN!
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𝐌𝐚𝐥𝐜𝐨𝐥𝐦
An American man shows his grandmother's passport and proudly says, "It will always be Palestine."
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