The best Hacker News stories from All from the past day
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Cystic fibrosis breakthrough has given patients a chance to live longer
Downpour is the game creation tool I have been working on for the past few years
OpenAI board reappoints Altman and adds three other directors
Monodraw
Monodraw
Bruno: Fast and Git-friendly open-source API client (Postman alternative)
Bruno: Fast and Git-friendly open-source API client (Postman alternative)
Show HN: Wallstreetlocal – View investments from America's biggest companies
Hello Hacker News! My name is Anonyo, and I am a seventeen-year-old from Southeast Michigan. This is wallstreetlocal, my passion project for the last year (and a half). I've posted this before, but I've finally open-sourced this entire project, so I thought I'd post it again.<p>Heres the short pitch.<p>The Securities and Exchange Commission (SEC) keeps record of every company in the United States. Companies whose holdings surpass $100 million though, are required to file a special type of form: the 13F form. This form, filed quarterly, discloses the filer's holdings, providing transparency into their investment activities and allowing the public and other market participants to monitor them.<p>The problem though, is that these holdings are often cumbersome to access, and valuable analysis is often hidden behind a paywall. Through wallstreetlocal, the SEC's 13F filers become more accessible and open.<p>By exploring the website (and the code), you can see the resources I used, check out some notable money managers I listed, and download any data that suits you. All for free. (Note, the mobile site likely needs work.)<p>I made this project to better democratize SEC filings, and also to get some experience on my hands. I love computers, and one day hope to get involved with startups. In the comments, I'd appreciate any and all advice, as well as feedback on how to improve the site.
Autogenerating a Book Series from Three Years of iMessages
Show HN: Hatchet – Open-source distributed task queue
Hello HN, we're Gabe and Alexander from Hatchet (<a href="https://hatchet.run">https://hatchet.run</a>), we're working on an open-source, distributed task queue. It's an alternative to tools like Celery for Python and BullMQ for Node.js, primarily focused on reliability and observability. It uses Postgres for the underlying queue.<p>Why build another managed queue? We wanted to build something with the benefits of full transactional enqueueing - particularly for dependent, DAG-style execution - and felt strongly that Postgres solves for 99.9% of queueing use-cases better than most alternatives (Celery uses Redis or RabbitMQ as a broker, BullMQ uses Redis). Since the introduction of SKIP LOCKED and the milestones of recent PG releases (like active-active replication), it's becoming more feasible to horizontally scale Postgres across multiple regions and vertically scale to 10k TPS or more. Many queues (like BullMQ) are built on Redis and data loss can occur when suffering OOM if you're not careful, and using PG helps avoid an entire class of problems.<p>We also wanted something that was significantly easier to use and debug for application developers. A lot of times the burden of building task observability falls on the infra/platform team (for example, asking the infra team to build a Grafana view for their tasks based on exported prom metrics). We're building this type of observability directly into Hatchet.<p>What do we mean by "distributed"? You can run workers (the instances which run tasks) across multiple VMs, clusters and regions - they are remotely invoked via a long-lived gRPC connection with the Hatchet queue. We've attempted to optimize our latency to get our task start times down to 25-50ms and much more optimization is on the roadmap.<p>We also support a number of extra features that you'd expect, like retries, timeouts, cron schedules, dependent tasks. A few things we're currently working on - we use RabbitMQ (confusing, yes) for pub/sub between engine components and would prefer to just use Postgres, but didn't want to spend additional time on the exchange logic until we built a stable underlying queue. We are also considering the use of NATS for engine-engine and engine-worker connections.<p>We'd greatly appreciate any feedback you have and hope you get the chance to try out Hatchet.
Show HN: Hatchet – Open-source distributed task queue
Hello HN, we're Gabe and Alexander from Hatchet (<a href="https://hatchet.run">https://hatchet.run</a>), we're working on an open-source, distributed task queue. It's an alternative to tools like Celery for Python and BullMQ for Node.js, primarily focused on reliability and observability. It uses Postgres for the underlying queue.<p>Why build another managed queue? We wanted to build something with the benefits of full transactional enqueueing - particularly for dependent, DAG-style execution - and felt strongly that Postgres solves for 99.9% of queueing use-cases better than most alternatives (Celery uses Redis or RabbitMQ as a broker, BullMQ uses Redis). Since the introduction of SKIP LOCKED and the milestones of recent PG releases (like active-active replication), it's becoming more feasible to horizontally scale Postgres across multiple regions and vertically scale to 10k TPS or more. Many queues (like BullMQ) are built on Redis and data loss can occur when suffering OOM if you're not careful, and using PG helps avoid an entire class of problems.<p>We also wanted something that was significantly easier to use and debug for application developers. A lot of times the burden of building task observability falls on the infra/platform team (for example, asking the infra team to build a Grafana view for their tasks based on exported prom metrics). We're building this type of observability directly into Hatchet.<p>What do we mean by "distributed"? You can run workers (the instances which run tasks) across multiple VMs, clusters and regions - they are remotely invoked via a long-lived gRPC connection with the Hatchet queue. We've attempted to optimize our latency to get our task start times down to 25-50ms and much more optimization is on the roadmap.<p>We also support a number of extra features that you'd expect, like retries, timeouts, cron schedules, dependent tasks. A few things we're currently working on - we use RabbitMQ (confusing, yes) for pub/sub between engine components and would prefer to just use Postgres, but didn't want to spend additional time on the exchange logic until we built a stable underlying queue. We are also considering the use of NATS for engine-engine and engine-worker connections.<p>We'd greatly appreciate any feedback you have and hope you get the chance to try out Hatchet.
Home Lab Beginners guide
Fine tune a 70B language model at home
Jeremy from Answer.AI here. This is our first project since launching our new R&D lab at the start of this year.<p>It's the #1 most requested thing I've been hearing from open source model builders: the ability to use multiple GPUs with QLoRA training. So that's why we decided to make it our first project.<p>Huge thanks to Tim Dettmers for helping us get started to this -- and of course for creating QLoRA in the first place!<p>Let me know if you have any questions or thoughts.
My favourite animation trick: exponential smoothing (2023)
Epic says Apple will reinstate developer account
Epic says Apple will reinstate developer account
Don't fuck with paste
Akira Toriyama has died
The Pile is a 825 GiB diverse, open-source language modelling data set (2020)
Bob_cassette_rewinder