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Will Trump Toss Out the SAVE Student Loan Repayment Plan? Here's What Experts Say
Defeasible Reasoning
Article URL: https://plato.stanford.edu/entries/reasoning-defeasible/
Comments URL: https://news.ycombinator.com/item?id=42864911
Points: 1
# Comments: 0
Comparing Two Types of Meditation – Samatha and Vipassana (2018)
Article URL: https://emdrhealing.com/samatha-vs-vipassana-meditation/
Comments URL: https://news.ycombinator.com/item?id=42864907
Points: 1
# Comments: 0
One Project at a Time, or a Dozen (2024)
Article URL: https://hackaday.com/2024/02/10/one-project-at-a-time-or-a-dozen/
Comments URL: https://news.ycombinator.com/item?id=42864898
Points: 1
# Comments: 0
2024 YR4
Article URL: https://en.wikipedia.org/wiki/2024_YR4
Comments URL: https://news.ycombinator.com/item?id=42864866
Points: 1
# Comments: 0
Adversarial Misuse of Generative AI
Article URL: https://cloud.google.com/blog/topics/threat-intelligence/adversarial-misuse-generative-ai
Comments URL: https://news.ycombinator.com/item?id=42864861
Points: 2
# Comments: 0
C++26: Attributes in Structured Bindings
Article URL: https://www.sandordargo.com/blog/2025/01/29/cpp26-attributes-structured-bindings
Comments URL: https://news.ycombinator.com/item?id=42864860
Points: 1
# Comments: 0
I do not want AI to "polish" me
Article URL: https://thebloggess.com/2025/01/28/no-i-do-not-want-ai-to-polish-me/
Comments URL: https://news.ycombinator.com/item?id=42864854
Points: 3
# Comments: 0
Cloudy Forecast: How Predictable Is Communication Latency in the Cloud?
Article URL: https://arxiv.org/abs/2309.13169
Comments URL: https://news.ycombinator.com/item?id=42864819
Points: 1
# Comments: 0
Baguette bandits strike again with ransomware and a side of mockery
Article URL: https://www.theregister.com/2025/01/28/baguettes_bandits_strike_again/
Comments URL: https://news.ycombinator.com/item?id=42864808
Points: 1
# Comments: 0
Show HN: TailwindResume – Modern Resume Builder for Tech Professionals
There are already many resume tools in the market. If you search for resume tools, you’ll find many similar ones. I’ve researched and used their features, but they don’t fully meet my needs. I believe that resumes for internet professionals should start to differ from resumes in other industries. They should reflect technical characteristics and rigor in both content and format.
So I made TailwindResume: A resume builder for tech professionals. All templates are crafted with Tailwind CSS, enhanced with DeepSeek LLM for content generation.
Link: https://tailwindresume.co Docs: https://docs.tailwindresume.co
Features: - Clean, responsive templates built with Tailwind CSS - AI resume generation using DeepSeek LLM - Real tech resume examples (Frontend/Backend/DevOps) - Export as PDF or share as web page - Free resume writing guidelines
Looking forward to your feedback!
Comments URL: https://news.ycombinator.com/item?id=42864806
Points: 1
# Comments: 0
AppleCare+ claim denied after MacBook Pro was destroyed in a car crash
Article URL: https://9to5mac.com/2025/01/28/applecare-claim-denied-after-macbook-pro-was-destroyed-in-a-car-crash/
Comments URL: https://news.ycombinator.com/item?id=42864796
Points: 7
# Comments: 0
Seagate: 'new' hard drives used for tens of thousands of hours
Ruby Falcon is 2x faster than asynchronous Python, as fast as Node.js
Article URL: https://old.reddit.com/r/ruby/comments/1ic3z2e/ruby_falcon_is_2x_faster_than_asynchronous_python/
Comments URL: https://news.ycombinator.com/item?id=42864786
Points: 1
# Comments: 0
INOP Expands into B2B AI Driven Workforce Solutions
Article URL: https://inop.ai/inop-expands-into-b2b-workforce-solutions/
Comments URL: https://news.ycombinator.com/item?id=42864771
Points: 1
# Comments: 1
Building AI Apps with Ruby on Rails and Outropy
Article URL: https://outropy.ai/blog/2025-01-24-building_apps_with_ruby_on_rails/
Comments URL: https://news.ycombinator.com/item?id=42864769
Points: 1
# Comments: 0
Show HN: Open Source AI Playground for Prompt Engineers
Hi HN,
We're a small team building AI tutors out of India, and as you might guess, this means we spend a ton of time writing, testing, and refining prompts for LLMs. When we started out, we were using the OpenAI playground but things became tedious when we wanted to compare responses from different models. We tried a bunch of other playgrounds but found them lacking in some features so we built our own.
Quick Links:
Github: https://github.com/supernova-app/ai-playground
Hosted demo: http://playground.getsupernova.ai
Demo video: https://www.youtube.com/watch?v=I01_t75FT-c
TLDR:
Main features are:
- Monaco editor for writing prompts.
- Variable support in prompts {{}}.
- Syntax highlighting for tags like XML.
- Save prompt and conversations as JSON.
- Easy to self host.
Key Features:
1. Monaco Editor for Writing Prompts
When we were working on long, detailed prompts, writing them in plain text felt clunky and error-prone. Small issues—like missing a tag or having weird formatting—could break things.
So, we integrated the Monaco editor (used in VS Code). It gives us:
- Line numbers (so we don't get lost in long prompts).
- White space detection to catch formatting issues early.
- Syntax highlighting for tags like XML.
- Code folding to collapse parts of a prompt we're not actively working on.
These might sound like small things, but they've been a huge help when we're dealing with large, complex prompts that need constant tweaking.
2. Variable Support for Dynamic Prompts
You can define placeholders in your prompt using double curly braces ({{ }}) and fill them in via a friendly UI.
3. Testing for Consistency Across Completions
One of the hardest parts of building AI tutors has been ensuring reliable outputs. Even when a prompt seems fine, it can fail unexpectedly—or worse, it works sometimes but not always.
To address this, we made it easy to generate multiple completions from the same model at once. This lets us quickly see:
- If the prompt is consistently producing good results.
- Where the AI might misinterpret our intent.
For example, we'd often run 5–6 completions to see if the AI consistently understood our instructions, rather than getting lucky once or twice.
4. Comparing Models Side by Side
The main reason we built the playground in the first place. You can set up API keys for multiple providers and see how different models handle the same task. This helped us:
- Optimize prompts for specific models.
- Choose the best model for a particular use case.
5. Saving Conversations as Test Cases
Another pain point was testing how a prompt or conversation would evolve over time. Sometimes, we'd go back and forth with the AI to simulate real user interactions, but we had no way to save that conversation for future reference.
Now, with the playground, we can save these conversations as test cases. Here's how it works: 1. We create a conversation (or simulate a long interaction). 2. At any point, we can save it as a JSON file. 3. The JSON includes the full conversation, the system prompt, and any variables we used.
We then use this JSON file and use it in our code for running test cases or run evals.
6. Simple Self-Hosting
Finally, we wanted to make sure the playground was easy for others to set up. The only dependencies are:
- A Postgres database.
- API keys for the AI providers you want to use.
It supports Google login, so you can setup OAuth and can restrict access to only your domain.
The app is open source and we are running a hosted version of it here: http://playground.getsupernova.ai.
You can check out the repo here: https://github.com/supernova-app/ai-playground. It's easy to self-host, and we're actively working on new features.
If you give it a try, let us know what you think! Feedback, feature ideas, and contributions are all welcome.
Comments URL: https://news.ycombinator.com/item?id=42864727
Points: 3
# Comments: 0
Alibaba releases AI model it claims surpasses DeepSeek-V3
Article URL: https://ca.finance.yahoo.com/news/alibaba-releases-ai-model-claims-051704499.html
Comments URL: https://news.ycombinator.com/item?id=42864725
Points: 2
# Comments: 0
Show HN: I built an OSS abstraction over Stripe to embed any pricing model
Hey HN,
We just finished the YC batch and saw how long founders spent implementing pricing.
A few years ago SaaS pricing was just a monthly subscription. But AI companies today have many pricing options they want to experiment with: eg credit systems, usage based systems, top ups etc.
Building this in-house, with upgrades, downgrades, pro-ration, free trials, just sucks.
Similar to how Clerk 'solved' Auth for people that don't want to waste time building non-core features, I think we can do something similar for pricing.
I built an abstraction over Stripe to create any price model (subscriptions, usage-based, credits, trials etc), then embed it in a couple lines of code.
1. use /attach when a customer purchases a plan. A Stripe checkout URL is returned if needed. 2. use /entitled to check if a customer has access to a plan or specific features. This means no more dealing with webhooks, syncing subscription states etc. It's all open source and I'd love to hear your feedback!
Comments URL: https://news.ycombinator.com/item?id=42864717
Points: 3
# Comments: 0
A Proposed Silicon Valley Between Oxford and Cambridge
Article URL: https://www.theguardian.com/business/2025/jan/28/reeves-plans-to-create-silicon-valley-between-oxford-and-cambridge
Comments URL: https://news.ycombinator.com/item?id=42864695
Points: 3
# Comments: 0