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Re:How we made claude.ai 3x faster in two weeks on Thursday September 24, 2026 @07:15AM (#49829017)
Claude.ai's UI itself isn't that complex, and making it fast isn't some engineering marvel that requires such an announcement IMO.

Nevertheless a good takeaway on how Ai can relentlessly pursue a target.

My other takeaway: vibing your way to a product can apparently generate a lot of tech debt along the way.

Ai created problem Ai solves said problems

Re: on Friday September 18, 2026 @11:43AM (#49756064)
Hi HN, I wrote this as an exploration of how Causal ML could be used for better observability. Happy to hear your thoughts!
Reactive access to incrementally parsed JSON for Python. Consume fields and array items as they arrive — no need to wait for the full payload.

jsontap builds a reactive node tree on top of ijson's streaming parser. You await scalar/object values and async for over arrays while the JSON is still being fed in, one chunk at a time. This makes it ideal for LLM token streams, chunked HTTP responses, or any scenario where JSON arrives incrementally.

Re:How we rebuilt Next.js with AI in one week on Wednesday February 25, 2026 @11:19PM (#47161794)
Makes me wonder how the hell all the tests passed?!
FauxSpark is a discrete event simulator built with SimPy whose objective is to model the internals of Apache Spark. It lets you experiment with Apache Spark workloads under various cluster configurations without spinning up a real cluster – perfect for testing failures, different job schedules, or capacity planning to observe the impact it has on your workload.

The current version includes:

- DAG scheduling with stages, tasks, and dependencies (but perhaps, designing around "RDD" would've been the right call)

- Modeling the input, output, shuffle partition sizes as probability distributions.

- Automatic retries on executor or shuffle-fetch failures

- Single-job execution

- Simple CLI to tweak cluster configuration, simulate failures, and scaling up executors

This tool might be relevant to the following folks:

- Data & Infrastructure engineers running Apache Spark who want to experiment with cluster configurations

- Anyone curious about Spark internals

I'd appreciate feedback from anyone with experience in discrete event simulation, particularly regarding the planned features as well as from anyone who may find this useful to shape its development.

A walkthrough section in the README demonstrates how it can be used.

GH repo https://github.com/fhalde/fauxspark

Show HN: FauxSpark – An Apache Spark Simulator Using SimPy

https://github.com/fhalde/fauxspark

Hi HN,I've built FauxSpark. A discrete event simulation of Apache Spark, built with SimPy.It's designed to let users experiment with and understand the runtime characteristics of Apache Spark workloads under different cluster configurations, failures & job schedules without spawning a real cluster.In this initial version, FauxSpark implements a simplified version of Apache Spark which...

( Read More... | no comments | on HN )
Pardon the rapists, murderers and jail the Tesla vandals! Sigh
Enjoy all cars equally
Re:Doge.gov site has been hacked on Friday February 14, 2025 @03:52AM (#43046301)
It's ok for data to leak from the sacred soil of America but China is bad
it's arxiv what were we expecting
Jensen: 1000$

Customers: 10$

Jensen: 500$ :(

Customers: 20$

Jensen: 250$

Customer: 10$ + your jacket

Jensen: :'((

Re:OpenAI Fails to Deliver Opt-Out System for Photographers on Wednesday January 15, 2025 @07:49PM (#42719487)
The tool was called "Media Manager" LMFAO. A name so uninspired it perfectly reflected how little they cared.