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"M*A*S*H" ran for 11 seasons, even though the Korean War, during which the CBS series was set, lasted three years. When the show finally signed off 40 years ago -- with a special 2.5-hour episode titled "Goodbye, Farewell and Amen" -- it set a ratings record that will never be equaled, and indeed, has become virtually impossible in the fragmented media market that exists today.

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Hi HN, we’re Carl and Nic, the creators of crul (https://www.crul.com), and we’ve been hard at work for the last year and a half building our dream of turning the web into a dataset. In a nutshell crul is a tool for querying and building web and api data feeds from anywhere to anywhere.

With crul you can crawl and transform web pages into csv tables, explore and dynamically query APIs, filter and organize data, and push data sets to third party data lakes and analytics tools. Here’s a demo video, we’ve been told Nic sounds like John Mayer (lol) (https://www.crul.com/demo-video)

We’ve personally struggled wrangling data from the web using puppeteer/playwright/selenium, jq or cobbling together python scripts, client libraries, and schedulers to consume APIs. The reality is that shit is hard, doesn’t scale (classic blocking for-loop or async saturation), and comes with thorny maintenance/security issues. The tools we love to hate.

Crul’s value prop is simple: Query any Webpage or API for free.

At its core, crul is based on the foundational linked nature of Web/API content. It consists of a purpose built map/expand/reduce engine for hierarchical Web/API content (kind of like postman but with a membership to Gold's Gym) with a familiar parser expression grammar that naturally gets the job done (and layered caching to make it quick to fix when it doesn’t on the first try). There’s a boatload of other features like domain policies, scheduler, checkpoints, templates, REST API, Web UI, vault, OAuth for third parties and 20+ stores to send your data to.

Our goal is to open source crul as time and resources permit. At the end of the day it’s just the two of us trying to figure things out as we go! We’re just getting started.

Crul is one bad mother#^@%*& and the web is finally yours!

Download crul for free as a Mac OS desktop application or as a Docker image (https://www.crul.com) and let us know if you love it or hate it. (https://forms.gle/5BXb5bLC1D5QG7i99) And come say hello to us on our slack channel - we’re a friendly bunch! (https://crulinc.slack.com/)

Nic and Carl (https://www.crul.com/early-days)


Comments URL: https://news.ycombinator.com/item?id=34970917

Points: 34

# Comments: 6



from Hacker News: Front Page https://www.crul.com/
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The US Department of Energy has assessed that the Covid-19 pandemic most likely came from a laboratory leak in China, according to a newly updated classified intelligence report. The assessment further adds to the divide in the US government over whether the pandemic began in China in 2019 as the result of a lab leak or whether it emerged naturally.

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Read CNN's Ratko Mladic Fast Facts for a look at the life of former leader of the Bosnian Serb army, indicted for genocide and other war crimes.

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Hey HN! We’re open-sourcing highlight.io (https://github.com/highlight/highlight), a session replay and error monitoring tool. Highlight.io gives you a high-precision video-like replay of what users are doing when an error or exception occurs in your web app, along with a full-fledged error monitoring experience (similar to bugsnag, rollbar, etc..).

The main value prop of highlight.io is that we help you understand the full context surrounding an error and allow you to drill down to the code path that a user invoked (i.e user clicked button X, sent network request Y, and backend code Z was executed). Some of our customers compare this to a “web debugger” of sorts. A picture of what this looks like in our app is here [1].

For some background, when we worked at our previous companies as engineers, we encountered hard-to-reproduce issues spanning across both the frontend and backend. The main issues were (1) if a customer complained about a problem, it was hard to reproduce the issue without asking for a screen-share or jumping on a video call; and (2) when viewing errors caught by tools like BugSnag or Rollbar, understanding the triggered code path required stitching together logs, errors, and trace; all from different sources.

Highlight.io is completely open source and written in Go and Typescript. To build the replay capability, we use an open source project called rrweb [2] and have worked closely with their team to add support for features like canvas recording, shadow dom recording, and more [3]. Beyond that, we use the OpenTelemetry spec for our SDKs [4], which has made it pretty straight forward to support several languages, even with our small 4-person engineering team!

Our product is completely self-serve at app.highlight.io. Installing it is as easy as a npm/yarn import and installing the backend sdk of your choosing. In addition, given the privacy-centric nature of session replay, we also offer the option to self-host [5]. Highlight.io currently makes money off of our hosted offering, and our self-hosted deployment is completely free. We’re also toying with the idea of an “enterprise” self-hosted deployment, similar to gitlab’s billing model, and thoughts from the community on this front would be appreciated!

And as far as what’s next for us: Our customers are asking to render logs and traces on a highlight.io session (and vice versa), and we’re excited to be going deeper into a developer’s debugging stack. The long term goal is to build a platform that connects replay, errors, logs and more so that engineers can “playback” the full state of a web application.

Overall, we’re quite new to the open source scene and would love the HN community to share their feedback on what we’re building. If anyone has opinions on where we’re going, or what they’d like to see in an open source monitoring product, we’re all ears. Check us out at highlight.io and at github.com/highlight/highlight to give us a shot.

[1]: https://www.highlight.io/docs/getting-started/frontend-backe...

[2]: https://github.com/rrweb-io/rrweb

[3]: https://highlight.io/docs/general/product-features/session-r...

[4]: https://opentelemetry.io/docs

[5]: https://www.highlight.io/docs/general/company/open-source/se...


Comments URL: https://news.ycombinator.com/item?id=34897645

Points: 19

# Comments: 2



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Hi HN,

Today we're launching phind.com, a developer-focused search engine that uses generative AI to browse the web and answer technical questions, complete with code examples and detailed explanations. It's version 1.0 of what was previously known as Hello (beta.sayhello.so) and has been completely reworked to be more accurate and reliable.

Because it's connected to the internet, Phind is always up-to-date and has access to docs, issues, and bugs that ChatGPT hasn't seen. Like ChatGPT, you can ask followup questions. Phind is smart enough to perform a new search and join it with the existing conversation context. We're merging the best of ChatGPT with the best of Google.

You're probably wondering how it's different from the new Bing. For one, we don't dumb down a user's query the way that the new Bing does. We feed your question into the model exactly as it was asked, and are laser-focused on providing developers the most detailed and comprehensive explanations to code-related questions. Secondly, we've focused the model on providing answers instead of chatbot small talk. This is one of the major improvements we've made since exiting beta.

Phind has the creative abilities to generate code, write essays, and even compose some poems/raps but isn't interested in having a conversation for conversation's sake. It should refuse to state its own opinion and rather provide a comprehensive summary of what it found online. When it isn't sure, it's designed to say so. It's not perfect yet, and misinterprets answers ~5% of the time. An example of Phind's adversarial question answering ability is https://phind.com/search?q=why+is+replacing+NaCL+with+NaCN+i....

ChatGPT became useful by learning to generate answers it thinks humans will find helpful, via a technique called Reinforcement Learning from Human Feedback (RLHF). In RLHF, a model generates multiple candidate answers for a given question and a human rates which one is better. The comparison data is then fed back into the model through an algorithm such as PPO. To improve answer quality, we're deploying RLAIF — an improvement over RLHF where the AI itself generates comparison data instead of humans. Generative LLMs have already reached the point where they can review the quality of their own answers as good or better than an average human rater tasked with annotating data for RLHF.

We still have a long way to go, but Phind is state-of-the-art at answering complex technical questions and writing intricate guides all while citing its sources. We'd love to hear your feedback.

Examples:

https://phind.com/search?q=How+to+set+up+a+CI%2FCD+pipeline+...

https://phind.com/search?q=how+to+debug+pthread+race+conditi...

https://phind.com/search?q=example+of+a+c%2B%2B+semaphore

https://phind.com/search?q=What+is+the+best+way+to+deploy+a+...

https://phind.com/search?q=show+me+when+to+use+defaultdicts+...

Discord: https://discord.gg/qHj8pwYCNg


Comments URL: https://news.ycombinator.com/item?id=34884338

Points: 46

# Comments: 10



from Hacker News: Front Page https://phind.com
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I'm wondering is there a monthly or periodically post on HN where we could actually learn about other people's ideas or people who are just in development phase or maybe just researching and are looking for co-founders.

I'm wondering what everyone thinks.


Comments URL: https://news.ycombinator.com/item?id=34883106

Points: 18

# Comments: 11



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The manslaughter charges against Alec Baldwin relating to the 2021 fatal shooting on the set of the movie "Rust" have been downgraded by prosecutors in New Mexico, which will reduce the prison time the actor could face in the death of the movie's cinematographer, Halyna Hutchins.

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Hi HN. I've been working on a new browser-based design tool that's ready for you to try.

The idea is you work on your design in low fidelity wireframes, while still getting a high fidelity output that you can share or use as a reference for your implementation. The way it works is by mapping low fidelity blocks you draw into high fidelity design system & React components.

I spent several years working on design tools at companies like Airbnb, and I think the ideas behind many of the tools we built for designing at scale could really help startups and small teams as well. I would love any feedback you have!

PS: Most of Noya is open source at https://github.com/noya-app/noya


Comments URL: https://news.ycombinator.com/item?id=34848583

Points: 4

# Comments: 0



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Gun violence, at its highest level in the US since the early 1990s, has become one of the top concerns for many American voters. Jens Ludwig and Chico Tillmon argue that our main concern should be the gaping holes in the social safety net for the group at greatest risk of gun violence — young men.

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Google searches = used for training AI models

Apple notes = private

Google docs = ?

Siri requests = used for training models

Emails you send in gmail = ?

I'm seeking to understand what things people might think are private, because they're not posted on the open web, but where they're used for training AI models.


Comments URL: https://news.ycombinator.com/item?id=34807687

Points: 35

# Comments: 31



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US intelligence officials are assessing the possibility that the suspected Chinese spy balloon was not deliberately maneuvered into the continental US by the Chinese government and are examining whether it was diverted off course by strong winds, multiple people briefed on the intelligence tell CNN.

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Applies to ALL employees within 40 miles of an office.

Announced internally in what’s known as V2MOM, which is an internal top-down KPIs. All managers will be judged based on this metric.

This applies to employees at all organisations under its umbrella, including Slack. Includes engineers.


Comments URL: https://news.ycombinator.com/item?id=34776243

Points: 65

# Comments: 40



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The Consumer Product Safety Commission reiterated its warning about the hazards of some popular Baby Trend-brand strollers and sharply criticized the stroller manufacturer for issuing "a clearly inaccurate statement" about the safety of its products and the agency's position on them.

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Republican Rep. Brian Fitzpatrick, a co-chair of the House Problem Solvers Caucus, said Sunday that GOP members of his bipartisan group are ready to break with their party leadership on some aspects of the debt ceiling negotiations but they remain committed to attaching some spending cuts.

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After getting frustrated with Siri's inability to answer pretty basic questions with actual answers instead of "I searched the web for you", I figured out how to get GPT-3 integrated pretty seamlessly with Siri. Sharing it here in case it's useful for anyone else!

You can see the short writeup with instructions here: https://ift.tt/475m0tK

The Siri shortcut is here: https://ift.tt/iLqXJf8 (You'll need to add your OpenAI API key to the shortcut and update your Siri accessibility settings to get it to work smoothly – see the above-linked blog post for more detailed instructions.)


Comments URL: https://news.ycombinator.com/item?id=34646178

Points: 23

# Comments: 3



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makejinja can be used to automatically generate files from Jinja templates. This allows you to load variables from external files or create repeating patterns via loops. A very interesting use case for this tool is generating config files for Home Assistant: Using the same language that the built-in templates use, you can greatly simplify your configuration. When creating for example dashboards, it allows you to create a view for each room based on a single common template, dramatically reducing the maintenance overhead of complex dashboards. I originally developed this for my smarthome setup, but thought it may be useful for others as well!

A concrete example for Home Assistant can be found in the tests directory: https://github.com/mirkolenz/makejinja/blob/main/tests/data

For more information like detailed features or installation/usage instructions, please visit the GitHub repo.


Comments URL: https://news.ycombinator.com/item?id=34645370

Points: 3

# Comments: 0



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