Hacker News

Article URL: https://www.youtube.com/watch?v=4S5uJ7VKsdE

Comments URL: https://news.ycombinator.com/item?id=43603484

Points: 1

# Comments: 0

Article URL: https://www.lesswrong.com/posts/4mvphwx5pdsZLMmpY/recent-ai-model-progress-feels-mostly-like-bullshit

Comments URL: https://news.ycombinator.com/item?id=43603453

Points: 2

# Comments: 0

Article URL: https://tulon.github.io/spline-fitting/

Comments URL: https://news.ycombinator.com/item?id=43603450

Points: 1

# Comments: 0

Article URL: https://www.nytimes.com/athletic/6258313/2025/04/06/alex-ovechkin-nhl-goals-record-wayne-gretzky/

Comments URL: https://news.ycombinator.com/item?id=43603447

Points: 2

# Comments: 2

Hi HN,

Gabriel here, one of the developers at Latitude.sh (we're a bare metal cloud provider).

Over the past year or so, I've been the primary developer building Latitude.sh Databases – our take on a managed PostgreSQL service. The core idea was to offer a straightforward and competitively priced option for developers who need reliable PostgreSQL without overly complex configurations, leveraging the performance benefits of running directly on bare metal.

It runs on our global bare metal infrastructure. Key features we've implemented include:

* Built-in monitoring & connection pooling

* IP Address Whitelisting (Trusted Sources)

* Automated backups configured directly to your own S3 bucket (giving you control over storage and potentially costs)

* An optional integration with Supabase, allowing you to use parts of their dashboard for enhanced usability with your database.

Under the hood, it's built on Kubernetes running on our bare metal servers, using the CloudNativePG operator to manage the PostgreSQL instances. We've found this operator approach works well for handling stateful database workloads in K8s, challenging the old notion that databases don't belong there.

The service stemmed from internal needs and early interest gathered from a waitlist (~300 signups). It's currently live and available for use.

We're launching it here on HN because we'd genuinely appreciate your feedback on:

* The overall developer experience and UI simplicity.

* The current feature set (especially the S3 backup and Supabase integration).

* Performance perceptions (given the bare metal base).

* Our pricing model's competitiveness and clarity.

* Any technical aspects of the implementation (running PG on K8s/bare metal).

Happy to answer any questions you have!

You can check out the product page here: https://www.latitude.sh/databases

Thanks for looking!

Comments URL: https://news.ycombinator.com/item?id=43603441

Points: 1

# Comments: 0

Article URL: https://www.overcomingbias.com/p/unleash-capitalism

Comments URL: https://news.ycombinator.com/item?id=43603439

Points: 1

# Comments: 0

Article URL: https://old.reddit.com/r/shopifyDev/comments/1jszw56/ever_wonder_which_influencers_are_actually_worth/

Comments URL: https://news.ycombinator.com/item?id=43603394

Points: 1

# Comments: 0

Article URL: https://blog.rust-lang.org/2025/04/04/vision-doc-survey.html

Comments URL: https://news.ycombinator.com/item?id=43603393

Points: 2

# Comments: 0

Article URL: https://www.politico.eu/article/france-suggest-to-regulate-data-in-response-to-trump-tariffs/

Comments URL: https://news.ycombinator.com/item?id=43603378

Points: 4

# Comments: 3

I just read about how, to train AIML to do sentiment analysis, some projects use Amazon reviews for data.

See, every Amazon review has to be accompanied by a star rating. if the star rating is poor, then the accompanying text is likely to be negative. And vice versa.

Blew my mind.

It's totally self-contained. No need to hire humans in Kenya or India to rate a piece of text to determine and label its sentiment.

I thought this was a highly creative way to approach the "data problem".

I want to learn more about such creative solutions to the "data problem".

Please share what you know about such creative solutions (or your ideas on creative solutions to the "data problem") on this page so we can have a resource to reference.

Thank you.

Comments URL: https://news.ycombinator.com/item?id=43603374

Points: 1

# Comments: 0

Article URL: https://english.elpais.com/technology/2025-04-05/the-computer-that-runs-on-human-neurons.html

Comments URL: https://news.ycombinator.com/item?id=43603342

Points: 1

# Comments: 2

Article URL: https://www.youtube.com/watch?v=YkjrEXtZoWM

Comments URL: https://news.ycombinator.com/item?id=43603334

Points: 1

# Comments: 1

Article URL: https://techcrunch.com/2025/04/05/sf-mayor-lurie-to-tech-ceos-how-can-we-get-you-back/

Comments URL: https://news.ycombinator.com/item?id=43603333

Points: 1

# Comments: 0

If you've tried building AI agentic systems on top of Model Context Protocol (MCP), you've likely run into the same issues we did: integration complexity, lack of UI support, high token costs, and hallucination-prone outputs. That’s why we built something better—Oqlous AI’s RAG Agentic Framework, designed from the ground up to be practical, scalable, and user-friendly.

Let me break it down.

What’s Wrong with MCP?

While MCP introduced an interesting idea around managing AI context and action workflows, it suffers from some critical

limitations:

No UI/End-User Layer

MCP provides no native UI support. You prompt it to create a JIRA ticket, and you get a text response. That’s it. No interactive layer, no native app UIs.

Token Inefficiency

MCP agents burn through tokens quickly, leading to higher cost and slower throughput. Not scalable for real-time or production use.

Shallow Execution

There’s no real multi-app, multi-hop reasoning. MCP can’t take a task, pull data from three apps, synthesize a decision, and then execute downstream actions. It just doesn't go that deep.

Hallucinations and Fragility

Output quality is unreliable. Responses can be vague, hallucinated, or misaligned with business context. Customization is minimal.

Oqlous AI RAG Agentic Framework: Built for Real Execution We built Oqlous AI to solve all of the above—and more.

One-Click App Integrations

No need for manual config files or external orchestrators. You can connect to tools like Gmail, JIRA, Notion, Drive, and more with a click having 100+ integrations.

End-to-End UI Support

When you prompt the agent to "create a JIRA task," you don’t get just text—you get a full JIRA UI component within the workflow. You can interact with it, update fields, drag tickets, and more, like you would in the native app.

Efficient LLM Usage

Thanks to smart token management and modular RAG strategies, Oqlous AI consumes significantly fewer tokens per operation. That means up to three times faster execution and lower costs, while keeping responses grounded.

Deep Agentic Workflows

Oqlous AI agents can reason across multiple tools. Say you ask, "Schedule a meeting with Alice, summarize the latest engineering report, and create follow-up tasks in Asana." Oqlous agents will fetch the report from Notion, parse action items, schedule via Calendar, and push tasks—all autonomously.

Customizable to Enterprise Workflows

Every enterprise has unique needs. Oqlous AI’s framework allows easy customization of agent behavior, integrations, and guardrails. You’re not stuck with rigid chains or black-box flows.

Grounded, Reliable Output

With RAG plus fine-tuned execution layers, hallucinations are drastically reduced. Agents don’t guess—they check, verify, and act based on actual data.

Summary

MCP had promise but isn't built for real-world execution at scale. Oqlous AI’s RAG Agentic Framework is.

If you're looking for an enterprise-ready, highly efficient, and deeply interactive AI agent system, Oqlous AI is the upgrade MCP never became.

We're opening this up for developers, startups, and enterprises building the next generation of agentic applications. Happy to connect with anyone working in this space.

Happy to give you acess: https://www.oqlous.com/get-started

Comments URL: https://news.ycombinator.com/item?id=43603324

Points: 1

# Comments: 1

Article URL: https://arstechnica.com/tech-policy/2025/04/eu-may-make-an-example-of-x-by-issuing-1-billion-fine-to-musks-social-network/

Comments URL: https://news.ycombinator.com/item?id=43603307

Points: 9

# Comments: 1

Article URL: https://www.economist.com/business/2025/04/04/tiktoks-bizarre-sale-process-gets-even-weirder

Comments URL: https://news.ycombinator.com/item?id=43603304

Points: 2

# Comments: 0

Article URL: https://twitter.com/rauchg/status/1907132415560335674

Comments URL: https://news.ycombinator.com/item?id=43603299

Points: 1

# Comments: 0

Article URL: https://mattsayar.com/how-i-vibe-coded-a-math-game-in-ten-minutes/

Comments URL: https://news.ycombinator.com/item?id=43603275

Points: 1

# Comments: 0

Article URL: https://www.khi.co.jp/expo2025/concept01/index.html

Comments URL: https://news.ycombinator.com/item?id=43603273

Points: 1

# Comments: 1

I don’t want to build another notes app

Comments URL: https://news.ycombinator.com/item?id=43603264

Points: 1

# Comments: 0