The best Hacker News stories from Show from the past day
Latest posts:
Show HN: Xc – A Markdown Defined Task Runner
Show HN: IngestAI – NoCode ChatGPT-bot creator from your knowledge base in Slack
Show HN: IngestAI – NoCode ChatGPT-bot creator from your knowledge base in Slack
Show HN: Parallax wallpaper engine for Linux and Windows
Show HN: Parallax wallpaper engine for Linux and Windows
Show HN: Parallax wallpaper engine for Linux and Windows
Show HN: Parallax wallpaper engine for Linux and Windows
Show HN: Mox - Modern full-featured low-maintenance self-hosted mail server
Show HN: Mox - Modern full-featured low-maintenance self-hosted mail server
Show HN: Mox - Modern full-featured low-maintenance self-hosted mail server
Show HN: Mox - Modern full-featured low-maintenance self-hosted mail server
Show HN: Graphic – A grammar of data visualization and Flutter charting library
Graphic is a grammar of data visualization and Flutter charting library, with there features:<p>- A Grammar of Graphics: Graphic derives from Leland Wilkinson's book The Grammar of Graphics, and tries to balance between theoretical beauty and practicability. It inherits most concepts, like the graphic algebra.
- Declarative and Reactive: As is encouraged in Flutter, the chart widget of Graphic is declarative and reactive. The grammar of data visualization is implemented by a declarative specification and the chart will reevaluate automatically on widget update.
- Interactive: With the signal and selection mechanism, the chart is highly interactive. It is easy to pop a tooltip or scale the coordinate.
- Customizable: With the shape and figure classes, it's easy to custom your own element, tooltip, annotation, etc.
- Dataflow Graph and Operators: Graphic has a internal structure of a dataflow graph and operators. That is how the reactive reevaluation and interaction is implemented.
Show HN: Vector icons, but for viral memes
Show HN: Vector icons, but for viral memes
Show HN: Graph-based AI for longform writing
Hey everyone, I wanted to share a new tool we've created called Jotte (<a href="https://jotte.ai" rel="nofollow">https://jotte.ai</a>) which we believe can be a game-changer for AI-generated longform writing like novels and research papers.<p>As you may know, current AI like ChatGPT and GPT-3 have a token limit of around 4000 tokens or 3000 words, which limits their effectiveness for longer writing tasks. With Jotte, we've developed a graph-based approach to summarize information and effectively give AI "unlimited" memory.<p>Jotte remembers recent details like the meal a character ate a page ago, while avoiding getting bogged down by irrelevant details like the blue curtains mentioned 5 chapters ago. We've created a proof of concept and would love to hear your thoughts on it.<p>Do you think this approach could lead to better longform writing by AI? Let us know in the comments!
Show HN: Graph-based AI for longform writing
Hey everyone, I wanted to share a new tool we've created called Jotte (<a href="https://jotte.ai" rel="nofollow">https://jotte.ai</a>) which we believe can be a game-changer for AI-generated longform writing like novels and research papers.<p>As you may know, current AI like ChatGPT and GPT-3 have a token limit of around 4000 tokens or 3000 words, which limits their effectiveness for longer writing tasks. With Jotte, we've developed a graph-based approach to summarize information and effectively give AI "unlimited" memory.<p>Jotte remembers recent details like the meal a character ate a page ago, while avoiding getting bogged down by irrelevant details like the blue curtains mentioned 5 chapters ago. We've created a proof of concept and would love to hear your thoughts on it.<p>Do you think this approach could lead to better longform writing by AI? Let us know in the comments!
Show HN: Graph-based AI for longform writing
Hey everyone, I wanted to share a new tool we've created called Jotte (<a href="https://jotte.ai" rel="nofollow">https://jotte.ai</a>) which we believe can be a game-changer for AI-generated longform writing like novels and research papers.<p>As you may know, current AI like ChatGPT and GPT-3 have a token limit of around 4000 tokens or 3000 words, which limits their effectiveness for longer writing tasks. With Jotte, we've developed a graph-based approach to summarize information and effectively give AI "unlimited" memory.<p>Jotte remembers recent details like the meal a character ate a page ago, while avoiding getting bogged down by irrelevant details like the blue curtains mentioned 5 chapters ago. We've created a proof of concept and would love to hear your thoughts on it.<p>Do you think this approach could lead to better longform writing by AI? Let us know in the comments!
Show HN: We’re open-sourcing our session replay tool
Hey HN! We’re open-sourcing highlight.io (<a href="https://github.com/highlight/highlight">https://github.com/highlight/highlight</a>), 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..).<p>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].<p>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.<p>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!<p>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!<p>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.<p>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.<p>[1]: <a href="https://www.highlight.io/docs/getting-started/frontend-backend-mapping">https://www.highlight.io/docs/getting-started/frontend-backe...</a><p>[2]: <a href="https://github.com/rrweb-io/rrweb">https://github.com/rrweb-io/rrweb</a><p>[3]: <a href="https://highlight.io/docs/general/product-features/session-replay/overview">https://highlight.io/docs/general/product-features/session-r...</a><p>[4]: <a href="https://opentelemetry.io/docs" rel="nofollow">https://opentelemetry.io/docs</a><p>[5]: <a href="https://www.highlight.io/docs/general/company/open-source/self-host-hobby">https://www.highlight.io/docs/general/company/open-source/se...</a>
Show HN: We’re open-sourcing our session replay tool
Hey HN! We’re open-sourcing highlight.io (<a href="https://github.com/highlight/highlight">https://github.com/highlight/highlight</a>), 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..).<p>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].<p>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.<p>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!<p>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!<p>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.<p>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.<p>[1]: <a href="https://www.highlight.io/docs/getting-started/frontend-backend-mapping">https://www.highlight.io/docs/getting-started/frontend-backe...</a><p>[2]: <a href="https://github.com/rrweb-io/rrweb">https://github.com/rrweb-io/rrweb</a><p>[3]: <a href="https://highlight.io/docs/general/product-features/session-replay/overview">https://highlight.io/docs/general/product-features/session-r...</a><p>[4]: <a href="https://opentelemetry.io/docs" rel="nofollow">https://opentelemetry.io/docs</a><p>[5]: <a href="https://www.highlight.io/docs/general/company/open-source/self-host-hobby">https://www.highlight.io/docs/general/company/open-source/se...</a>
Show HN: We’re open-sourcing our session replay tool
Hey HN! We’re open-sourcing highlight.io (<a href="https://github.com/highlight/highlight">https://github.com/highlight/highlight</a>), 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..).<p>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].<p>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.<p>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!<p>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!<p>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.<p>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.<p>[1]: <a href="https://www.highlight.io/docs/getting-started/frontend-backend-mapping">https://www.highlight.io/docs/getting-started/frontend-backe...</a><p>[2]: <a href="https://github.com/rrweb-io/rrweb">https://github.com/rrweb-io/rrweb</a><p>[3]: <a href="https://highlight.io/docs/general/product-features/session-replay/overview">https://highlight.io/docs/general/product-features/session-r...</a><p>[4]: <a href="https://opentelemetry.io/docs" rel="nofollow">https://opentelemetry.io/docs</a><p>[5]: <a href="https://www.highlight.io/docs/general/company/open-source/self-host-hobby">https://www.highlight.io/docs/general/company/open-source/se...</a>