by sushrut1058 ·
I am building an AI powered escrow service for software projects that intends to protect both freelancers and the clients.
- Freelancers: your IP (code/repo) always stays private
- Clients: you get sandboxed link + detailed report (specs, best practices) + prompt the hidden code (within guardrails)
- Fast AI-powered turnaround
Payments only release on mutual agreement.
Join the waitlist for early access: https://bit.ly/4sTuPHe
by chalshik ·
I currently use claude code, I am curios what if instead use other open source tool with pay as you go api, would be it cheaper while keeping same outcome ?
Sharing interactive scientific visualizations is hard. I don’t want my colleagues to have to install specialized software. I just want to email them a link which they can click on and see the full interactive visualization and explore my (potentially large) dataset and results. I want figures to be long-term archivable (Zenodo, etc). And local first (no upload required to view).
I created Figpack to solve these problems by creating self-contained HTML bundles for rich interactive scientific viz.
How it works. You import figpack in your Python project, pass numpy data (large time series, images, domain-specific data) to a figpack view object (many existing types, extensible via custom javascript/react), and then the show() command creates a completely self-contained HTML bundle with rich interactive visualization in a temporary directory and spins up a local web server to view it in the browser. The data and rendering code are all in one stand-alone directory. Easy!
To share with a colleague, just set upload=True and it uploads to the cloud. You get a url to send to your friend and they can see the exact same thing without any login.
I know… how is this different from Plotly, Bokeh, Observable, etc? Happy to discuss!
Please try it out and let me know what you think!
Open source (Apache 2.0).
China’s AI ecosystem moves fast. But news on the latest in China’s AI is slow and fragmented.
Overnight AI is a daily 10-minute briefing on China’s AI, curated from 200+ Chinese-language sources. It covers everything from technical breakthroughs like new attention mechanisms to product adoption updates.
The newsletter runs on a daily pipeline. The first phase is information ingestion. It uses RSSHub + WeWe RSS to fetch daily news feeds from social media platforms and news sites. The news items are batched for processing. Claude summarizes each item and groups related stories into topics. Next, it scores each topic based on a rubric. Finally, Claude turns the top scoring stories into a newsletter.
The pipeline is simple. Most of my time went into tuning the scoring rubric and composition taste. I believe for pure factual news reporting, AI can now do better than human editors.
Any feedback is welcomed. I’m especially interested in hearing your thoughts on AI news curation. Thanks!
by Profazia ·
I am 15 years old and have spent the last 7 months building this. And the thing I noticed about every planner was that it always expects you to stick to your schedule as you originally created it. But this is impossible because life happens.
IntelliRoutine is capable of changing your schedule automatically if there is even the slightest shift in your plans due to delays, meetings moving, or your own energy levels. There is no need for any manual planning. Key functionalities available now include: - Intelligent scheduling system within 2 minutes - Schedule adaption - Integration with Google Calendar - E-mail integration: just forward an e-mail to get your schedule updated
Free 7-day trial, no card required: https://www.intelliroutine.com
Would love brutal feedback from HN
by curtisblaine ·
by MichaelRazum ·
This is already the second time I’ve observed this. People coming from highly respected universities are doing everything with AI. It’s even hard to argue with them, since it’s all cross-checked with ChatGPT and similar tools.
The picture of software development also looks completely different. Code that used to be readable in a few lines becomes 100 lines—overblown because, well, code is cheap. Now, I could argue that it makes things unreadable and so on, but honestly, who cares? Right? The AI can fix it if it breaks...
So what do you guys think? Is this the future? Maybe the skill to focus on is orchestrating AI, and if you don’t do that, you become a legacy developer—someone with COBOL-like skills—still needed, but from the past millennium.