HN user
Work: https://newsloth.com
Blog: https://www.nilkanth.com
Social: https://x.com/voidmonk
I wouldn't limit it to RSS. They need any structured data (JSON, XML/RSS, CSV etc.).
Systems and agents need to monitor and extract public web content into fresh structured data for their ingestion, intelligence workflows and analysis.
* Shameless plug * Our data infrastructure layer for businesses and AI turns continuously updated websites into a stream of structured data.
Imo, ease and multi-line HTML readability of CDATA outweighs that one edge case (it cannot directly contain its own terminator).
Rundown AI newsletter: https://www.therundown.ai
Linux Mint.
I would have liked the option of non-touch display, and although the display is variable rate (30-120Hz) it's not going to be as optimal as the 1-120Hz panel in the Dell XPS 14 getting it to 40+ hours (https://x.com/dhh/status/2040139744445673938).
That is not the same extension OP is referencing/discussing: https://chromewebstore.google.com/detail/json-formatter/bcji...
Very cool.
Now why didn't an AI think of that? :)
Partnership confirmed by Moonshot:
Cursor accesses Kimi-k2.5 via FireworksAI_HQ hosted RL and inference platform as part of an authorized commercial partnership.
https://x.com/Kimi_Moonshot/status/2035074972943831491
Cursor teams take:
Only ~1/4 of the compute spent on the final model came from the base, the rest is from our training. This is why evals are very different.
Am I understanding it right that for each new text (tweet) you generate its embedding first, try to match across existing vector embeddings for all other text (full text or bag of words), and then send the text to the LLM for tag classification only if no match is found or otherwise classify it to the same tag for which a match was found.
Will it be any better if you sent a list of existing tags with each new text to the LLM, and asked it to classify to one of them or generate a new tag? Possibly even skipping embeddings and vector search altogether.
I'm trying to like Bluesky. X has a large tech community and some deep thoughts/discussions on tech and philosophy matters, but I can't find similar people or groups on Bluesky yet.
Landing pages can still save time to validate an idea/concept, build a leads list, and with cold outreach even.
Dev tools or B2C: landing page (collect email) with app/product tour video or mockup screenshots
B2B: landing page with video or mockup screenshots, and 'book a demo' link/form (collect as much info)
Before starting tasks, developers forecast that allowing AI will reduce completion time by 24%. After completing the study, developers estimate that allowing AI reduced completion time by 20%. Surprisingly, we find that allowing AI actually increases completion time by 19%—AI tooling slowed developers down.
Here's a good summary of the study: https://x.com/RubenHssd/status/1934968317627998534
In short, workers don't want full automation. They want partnership.
Heard someone say the other day "AI coding is just advanced scaffolding right now." Made me wonder if we're expecting too much out of it, at-least for now.
From the article: " The authors are currently running a new study to deepen the understanding of the dog-human relationship. Dog owners across the world are invited to answer the following questionnaire: https://tally.so/r/nPXKPb "
Haven't noticed any billing issue. Maybe try reaching out to them at https://x.com/CloudflareHelp
Really! Is there an official mention anywhere by Stripe?
If Stripe Radar (has a small fee per transaction) is enabled in an account, then an early warning (before chargeback) is sent via the `radar.early_fraud_warning.created` webhook event, which can be used for a pre-emptive manual review, or an automatic refund and cancellation. No dispute fee on a refunded transaction!
There are services like Chargeblast, ByeDispute etc. which also help avoid disputes and chargebacks.
Related: just today came across this post on X..
"Sri Lanka will become next Bali as long as it gets fiber."
* Shameless plug * Our feed builder combines a web scraper, AI-powered content auto-detection and data transformer to generate custom JSON and RSS feeds for any public webpage.
Bearblog is simple and easy for personal blogging. For something more advanced, you can't go wrong with Ghost (self-hosted or cloud).
To block AI bots, you'll need to add known AI bots[1] to your blog's robots.txt file [2].
[1] https://github.com/ai-robots-txt/ai.robots.txt/blob/main/rob...
[2] https://docs.bearblog.dev/neat-bear-features/#edit-robotstxt or https://ghost.org/help/modifying-robots-txt/
Can't you just use PayPal for accepting one-time or subscription payments?
Paddle and Rebill also seem to support Argentina.
https://www.paddle.com/help/legal/sanctions/which-countries-... https://www.rebill.com/en/payment-and-subscription-solutions...
Looks good!
I wonder if there's a way to combine a simple tool like yours (or Balsamiq, which I've used for many years) with generative AI to create plain HTML/CSS pages from mockups/wireframes. Figma seems bloated, v0 is React/Tailwind only.
Been hearing great things about Cursor, and its been impressive in my few days of use.
Imo, it depends on the nature of the app you're trying to build. It can be a good early-stage approach to build a simple prototype or MVP using no-code builders (combo of Glide and Make is great for CRUD apps with low-complexity workflows).
Spend as little as two weeks to build the prototype or MVP, and start showing it to potential users/customers. If it solves a real problem for them, they use it daily and commit to pay for it, then you can think about enhancing the no-code app or moving to a hybrid or all-code approach.
Test the idea first with least time and effort, which is surely possible using no-code builders.
> I'd love a RSS reader that groups items on the same topic.
We had the same concern with everyday industry news, and so did some of our customers, so we built it a while back!
Our Newsroom feed reader uses NLP and ML to group similar articles for low-noise research/reading:
https://newsloth.com/#features
Currently, it detects and groups articles from a few hundred popular global news sites, and gradually growing to cover more sources.
We also have a feed builder/generator that turns unstructured public webpages into structured RSS feeds, to make it a flexible and unified feeds platform:
Nice, but this seems to only detect some existing RSS feeds on a given website.
* Shameless plug * Our feed generator can detect existing RSS feeds, and combines a scraper and data transformer to help create custom RSS feeds for any public webpage.