The best Hacker News stories from Show from the past day
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Show HN: Visual intuitive explanations of LLM concepts (LLM University)
Hi HN,<p>We've just published a lot of original, visual, and intuitive explanations of concepts to introduce people to large language models.<p>It's available for free with no sign-up needed and it includes text articles, some video explanations, and code examples/notebooks as well. And we're available to answer your questions in a dedicated Discord channel.<p>You can find it here: https://llm.university/<p>Having written https://jalammar.github.io/illustrated-transformer/, I've been thinking about these topics and how best to communicate them for half a decade. But this project is extra special to me because I got to collaborate on it with two of who I think of as some of the best ML educators out there. Luis Serrano of https://www.youtube.com/@SerranoAcademy and Meor Amer, author of "A Visual Introduction to Deep Learning" https://kdimensions.gumroad.com/l/visualdl<p>We're planning to roll out more content to it (let us know what concepts interest you). But as of now, it has the following structure (With some links for highlighted articles for you to audit):<p>---<p>Module 1: What are Large Language Models<p>- Text Embeddings (https://docs.cohere.com/docs/text-embeddings)<p>- Similarity between words and sentences (https://docs.cohere.com/docs/similarity-between-words-and-sentences)<p>- The attention mechanism<p>- Transformer models (https://docs.cohere.com/docs/transformer-models HN Discussion: https://news.ycombinator.com/item?id=35576918)<p>- Semantic search<p>---<p>Module 2: Text representation<p>- Classification models (https://docs.cohere.com/docs/classification-models)<p>- Classification Evaluation metrics (https://docs.cohere.com/docs/evaluation-metrics)<p>- Classification / Embedding API endpoints<p>- Semantic search<p>- Text clustering<p>- Topic modeling (goes over clustering Ask HN posts https://docs.cohere.com/docs/clustering-hacker-news-posts)<p>- Multilingual semantic search<p>- Multilingual sentiment analysis<p>---<p>Module 3: Text generation<p>- Prompt engineering (https://docs.cohere.com/docs/model-prompting)<p>- Use case ideation<p>- Chaining prompts<p>---<p>A lot of the content originates from common questions we get from users of the LLMs we serve at Cohere. So the focus is more on application of LLMs than theory or training LLMs.<p>Hope you enjoy it, open to all feedback and suggestions!
Show HN: Aimless.js – the missing js randomness library
Show HN: Gis.chat – a Geospatial Community
Hi folks! I'm excited to show you gis.chat, a geospatial chat platform in both senses: a platform about geospatial topics and a geospatial platform itself, referencing the location of our communities.<p>The setup is fairly simple and reproducible: a plain Zulip instance and a homepage with geospatial search capabilities.<p>It seems almost trivial but it has some very nice features. I guess you should be familiar with Zulips stream/topic model to follow along (<a href="https://zulip.com/help/streams-and-topics" rel="nofollow">https://zulip.com/help/streams-and-topics</a>).<p>The core idea is that there are city-specific streams (currently represented by a pin), but there could just as well be streams about points of interest, line geometries (e.g. a river) or polygons (e.g. national park).<p>- Every local stream can have the same topics, e.g. "general", "news", "meetups", "jobs" etc.
- With Zulip's search you can either search for a particular topic, e.g. "news" in a local stream or instead in all streams and have some kind of news feed of the community with "topic:news"
- Once more communities are added, specific filters could be added, e.g. country-wise or by drawing your own area of interest
- Eventually, for the ones who like, users could associate themselves with a local community in their profile or add there main location so one could not only search for the local communities but instead also for individuals<p>There are many nice features in Zulip's pipeline that would foster gis.chat:<p>- Further nesting of streams/topics
- Semantic search<p>If for example Zulip would allow for saving coordinates (or better an entire geometry) in the Postgres DB, with the help of PostGIS, Zulip's search could allow for bounding boxes (or custom geometries).<p>Let me know if you have any kind of other ideas or feedback!
Show HN: Gis.chat – a Geospatial Community
Hi folks! I'm excited to show you gis.chat, a geospatial chat platform in both senses: a platform about geospatial topics and a geospatial platform itself, referencing the location of our communities.<p>The setup is fairly simple and reproducible: a plain Zulip instance and a homepage with geospatial search capabilities.<p>It seems almost trivial but it has some very nice features. I guess you should be familiar with Zulips stream/topic model to follow along (<a href="https://zulip.com/help/streams-and-topics" rel="nofollow">https://zulip.com/help/streams-and-topics</a>).<p>The core idea is that there are city-specific streams (currently represented by a pin), but there could just as well be streams about points of interest, line geometries (e.g. a river) or polygons (e.g. national park).<p>- Every local stream can have the same topics, e.g. "general", "news", "meetups", "jobs" etc.
- With Zulip's search you can either search for a particular topic, e.g. "news" in a local stream or instead in all streams and have some kind of news feed of the community with "topic:news"
- Once more communities are added, specific filters could be added, e.g. country-wise or by drawing your own area of interest
- Eventually, for the ones who like, users could associate themselves with a local community in their profile or add there main location so one could not only search for the local communities but instead also for individuals<p>There are many nice features in Zulip's pipeline that would foster gis.chat:<p>- Further nesting of streams/topics
- Semantic search<p>If for example Zulip would allow for saving coordinates (or better an entire geometry) in the Postgres DB, with the help of PostGIS, Zulip's search could allow for bounding boxes (or custom geometries).<p>Let me know if you have any kind of other ideas or feedback!
Show HN: Gis.chat – a Geospatial Community
Hi folks! I'm excited to show you gis.chat, a geospatial chat platform in both senses: a platform about geospatial topics and a geospatial platform itself, referencing the location of our communities.<p>The setup is fairly simple and reproducible: a plain Zulip instance and a homepage with geospatial search capabilities.<p>It seems almost trivial but it has some very nice features. I guess you should be familiar with Zulips stream/topic model to follow along (<a href="https://zulip.com/help/streams-and-topics" rel="nofollow">https://zulip.com/help/streams-and-topics</a>).<p>The core idea is that there are city-specific streams (currently represented by a pin), but there could just as well be streams about points of interest, line geometries (e.g. a river) or polygons (e.g. national park).<p>- Every local stream can have the same topics, e.g. "general", "news", "meetups", "jobs" etc.
- With Zulip's search you can either search for a particular topic, e.g. "news" in a local stream or instead in all streams and have some kind of news feed of the community with "topic:news"
- Once more communities are added, specific filters could be added, e.g. country-wise or by drawing your own area of interest
- Eventually, for the ones who like, users could associate themselves with a local community in their profile or add there main location so one could not only search for the local communities but instead also for individuals<p>There are many nice features in Zulip's pipeline that would foster gis.chat:<p>- Further nesting of streams/topics
- Semantic search<p>If for example Zulip would allow for saving coordinates (or better an entire geometry) in the Postgres DB, with the help of PostGIS, Zulip's search could allow for bounding boxes (or custom geometries).<p>Let me know if you have any kind of other ideas or feedback!
Show HN: Honda Civic Infotainment Reverse-Engineering
I own a 2021 Honda Civic and have been annoyed by the lack of public documentation/hacking tools for the Android-based headunit. I hope to address this by publishing my research into the headunit and encouraging discussion and community contribution
Show HN: Honda Civic Infotainment Reverse-Engineering
I own a 2021 Honda Civic and have been annoyed by the lack of public documentation/hacking tools for the Android-based headunit. I hope to address this by publishing my research into the headunit and encouraging discussion and community contribution
Show HN: HelpHub – GPT chatbot for any site
Hi HN,<p>I’m the founder of a SaaS platform called CommandBar (YC S20). We’ve been mucking around with AI-related side quests for a while, but recently got excited enough about one to test it with some customers. Results were surprisingly good so we decided to launch it.<p>HelpHub is AI chat + semantic search for any website or web app.<p>You can add source content in 3 ways:
-Crawling any public site via a URL (e.g. your marketing site or blog)
-Syncing with a CMS (like Zendesk or Intercom)
-Add content manually<p>The chatbot is then “trained” on that content and will answer question’s based on that content only, not referencing directly the knowledge.<p>The output is an embeddable widget the contains two things: the chatbot interface for user’s to ask questions, and a search interface for users to search through the content the bot is trained on directly (as well as view source content).<p>You can play around with a demo on some popular sites here: <a href="https://helphub.commandbar.com">https://helphub.commandbar.com</a><p>Some features we added that make it better IMO than just chat:
-Suggested questions (based on the page the user is on and their chat history)
-Suggested follow-up questions in a chat response
-Ask a question about a specific doc
-Recommend content based on who the user is and where they are<p>Would love to hear feedback (not lost on me that there are other chatgpt-for-your-site products and we are probably missing a ton of functionality from there) and can also share details about how we built this. It’s not rocket science but does feel magic :)<p>-James
Show HN: HelpHub – GPT chatbot for any site
Hi HN,<p>I’m the founder of a SaaS platform called CommandBar (YC S20). We’ve been mucking around with AI-related side quests for a while, but recently got excited enough about one to test it with some customers. Results were surprisingly good so we decided to launch it.<p>HelpHub is AI chat + semantic search for any website or web app.<p>You can add source content in 3 ways:
-Crawling any public site via a URL (e.g. your marketing site or blog)
-Syncing with a CMS (like Zendesk or Intercom)
-Add content manually<p>The chatbot is then “trained” on that content and will answer question’s based on that content only, not referencing directly the knowledge.<p>The output is an embeddable widget the contains two things: the chatbot interface for user’s to ask questions, and a search interface for users to search through the content the bot is trained on directly (as well as view source content).<p>You can play around with a demo on some popular sites here: <a href="https://helphub.commandbar.com">https://helphub.commandbar.com</a><p>Some features we added that make it better IMO than just chat:
-Suggested questions (based on the page the user is on and their chat history)
-Suggested follow-up questions in a chat response
-Ask a question about a specific doc
-Recommend content based on who the user is and where they are<p>Would love to hear feedback (not lost on me that there are other chatgpt-for-your-site products and we are probably missing a ton of functionality from there) and can also share details about how we built this. It’s not rocket science but does feel magic :)<p>-James
Show HN: Image background removal without annoying subscriptions
Hi HN,<p>Removing the background from images is a surprisingly common image processing task, and AI has made it really easy. The technology has come a long way since segment leader remove.bg launched here on hn in Dec 2018 [1]. Chasing remove.bg's success, a legion of providers have come on the market offering varying levels of quality & service.<p>Despite there being a large number of competing services, most still price for very high (~95%?) gross margins. Furthermore, subscriptions make the effective unit price a lot higher than the list price for infrequent users, and requires effort & attention to ensure you're getting value for money. This has prevented a host of use cases (e.g. infrequent professional / hobbyist) and business models (e.g. ad-supported websites & mobile apps).<p>We see this as an opportunity where we can jump to the market's logical conclusion to gain market share and build goodwill: cost-plus PAYGO pricing, i.e. the "S3 pricing model".<p>So we've built yet-another image background removal service ( <a href="https://pixian.ai" rel="nofollow">https://pixian.ai</a> - introductory post 6 months ago [2], a ton has been improved since then) but with a couple of twists:<p>1. Quantified quality comparison (90-120% of remove.bg, depending on image category), free for you to check your own images so you can make an informed choice.<p>2. Customer-friendly pricing (PAYGO @ 1-10% of competitors' subscriptions) with a generous free tier (and free while in beta).<p>3. A novel API result format: Delta PNG [3], which offers excellent latency & bandwidth savings. Especially useful for mobile apps.<p>4. Operational transparency: actual volume & latency metrics public, with more coming soon (all API providers should be showing this).<p>There's of course more to it than just price and we see several sources of differentiation in this market: quality, price, capability, reliability, latency, and goodwill.<p>As a new entrant we're looking to meet-or-beat the quality bar; beat on price, capability, reliability and latency; and to build up goodwill over time.<p>Our goal is to make it a no-brainer for new accounts to choose us, and to provide the tools and guidance necessary for existing accounts to make the switch with confidence.<p>We'd love for you to try it out and to hear your thoughts!<p><a href="https://pixian.ai" rel="nofollow">https://pixian.ai</a><p>[1] <a href="https://news.ycombinator.com/item?id=18697601" rel="nofollow">https://news.ycombinator.com/item?id=18697601</a>
[2] <a href="https://news.ycombinator.com/item?id=33439405" rel="nofollow">https://news.ycombinator.com/item?id=33439405</a>
[3] <a href="https://pixian.ai/api/deltaPng" rel="nofollow">https://pixian.ai/api/deltaPng</a>
Show HN: Image background removal without annoying subscriptions
Hi HN,<p>Removing the background from images is a surprisingly common image processing task, and AI has made it really easy. The technology has come a long way since segment leader remove.bg launched here on hn in Dec 2018 [1]. Chasing remove.bg's success, a legion of providers have come on the market offering varying levels of quality & service.<p>Despite there being a large number of competing services, most still price for very high (~95%?) gross margins. Furthermore, subscriptions make the effective unit price a lot higher than the list price for infrequent users, and requires effort & attention to ensure you're getting value for money. This has prevented a host of use cases (e.g. infrequent professional / hobbyist) and business models (e.g. ad-supported websites & mobile apps).<p>We see this as an opportunity where we can jump to the market's logical conclusion to gain market share and build goodwill: cost-plus PAYGO pricing, i.e. the "S3 pricing model".<p>So we've built yet-another image background removal service ( <a href="https://pixian.ai" rel="nofollow">https://pixian.ai</a> - introductory post 6 months ago [2], a ton has been improved since then) but with a couple of twists:<p>1. Quantified quality comparison (90-120% of remove.bg, depending on image category), free for you to check your own images so you can make an informed choice.<p>2. Customer-friendly pricing (PAYGO @ 1-10% of competitors' subscriptions) with a generous free tier (and free while in beta).<p>3. A novel API result format: Delta PNG [3], which offers excellent latency & bandwidth savings. Especially useful for mobile apps.<p>4. Operational transparency: actual volume & latency metrics public, with more coming soon (all API providers should be showing this).<p>There's of course more to it than just price and we see several sources of differentiation in this market: quality, price, capability, reliability, latency, and goodwill.<p>As a new entrant we're looking to meet-or-beat the quality bar; beat on price, capability, reliability and latency; and to build up goodwill over time.<p>Our goal is to make it a no-brainer for new accounts to choose us, and to provide the tools and guidance necessary for existing accounts to make the switch with confidence.<p>We'd love for you to try it out and to hear your thoughts!<p><a href="https://pixian.ai" rel="nofollow">https://pixian.ai</a><p>[1] <a href="https://news.ycombinator.com/item?id=18697601" rel="nofollow">https://news.ycombinator.com/item?id=18697601</a>
[2] <a href="https://news.ycombinator.com/item?id=33439405" rel="nofollow">https://news.ycombinator.com/item?id=33439405</a>
[3] <a href="https://pixian.ai/api/deltaPng" rel="nofollow">https://pixian.ai/api/deltaPng</a>
Show HN: Image background removal without annoying subscriptions
Hi HN,<p>Removing the background from images is a surprisingly common image processing task, and AI has made it really easy. The technology has come a long way since segment leader remove.bg launched here on hn in Dec 2018 [1]. Chasing remove.bg's success, a legion of providers have come on the market offering varying levels of quality & service.<p>Despite there being a large number of competing services, most still price for very high (~95%?) gross margins. Furthermore, subscriptions make the effective unit price a lot higher than the list price for infrequent users, and requires effort & attention to ensure you're getting value for money. This has prevented a host of use cases (e.g. infrequent professional / hobbyist) and business models (e.g. ad-supported websites & mobile apps).<p>We see this as an opportunity where we can jump to the market's logical conclusion to gain market share and build goodwill: cost-plus PAYGO pricing, i.e. the "S3 pricing model".<p>So we've built yet-another image background removal service ( <a href="https://pixian.ai" rel="nofollow">https://pixian.ai</a> - introductory post 6 months ago [2], a ton has been improved since then) but with a couple of twists:<p>1. Quantified quality comparison (90-120% of remove.bg, depending on image category), free for you to check your own images so you can make an informed choice.<p>2. Customer-friendly pricing (PAYGO @ 1-10% of competitors' subscriptions) with a generous free tier (and free while in beta).<p>3. A novel API result format: Delta PNG [3], which offers excellent latency & bandwidth savings. Especially useful for mobile apps.<p>4. Operational transparency: actual volume & latency metrics public, with more coming soon (all API providers should be showing this).<p>There's of course more to it than just price and we see several sources of differentiation in this market: quality, price, capability, reliability, latency, and goodwill.<p>As a new entrant we're looking to meet-or-beat the quality bar; beat on price, capability, reliability and latency; and to build up goodwill over time.<p>Our goal is to make it a no-brainer for new accounts to choose us, and to provide the tools and guidance necessary for existing accounts to make the switch with confidence.<p>We'd love for you to try it out and to hear your thoughts!<p><a href="https://pixian.ai" rel="nofollow">https://pixian.ai</a><p>[1] <a href="https://news.ycombinator.com/item?id=18697601" rel="nofollow">https://news.ycombinator.com/item?id=18697601</a>
[2] <a href="https://news.ycombinator.com/item?id=33439405" rel="nofollow">https://news.ycombinator.com/item?id=33439405</a>
[3] <a href="https://pixian.ai/api/deltaPng" rel="nofollow">https://pixian.ai/api/deltaPng</a>
Show HN: Image background removal without annoying subscriptions
Hi HN,<p>Removing the background from images is a surprisingly common image processing task, and AI has made it really easy. The technology has come a long way since segment leader remove.bg launched here on hn in Dec 2018 [1]. Chasing remove.bg's success, a legion of providers have come on the market offering varying levels of quality & service.<p>Despite there being a large number of competing services, most still price for very high (~95%?) gross margins. Furthermore, subscriptions make the effective unit price a lot higher than the list price for infrequent users, and requires effort & attention to ensure you're getting value for money. This has prevented a host of use cases (e.g. infrequent professional / hobbyist) and business models (e.g. ad-supported websites & mobile apps).<p>We see this as an opportunity where we can jump to the market's logical conclusion to gain market share and build goodwill: cost-plus PAYGO pricing, i.e. the "S3 pricing model".<p>So we've built yet-another image background removal service ( <a href="https://pixian.ai" rel="nofollow">https://pixian.ai</a> - introductory post 6 months ago [2], a ton has been improved since then) but with a couple of twists:<p>1. Quantified quality comparison (90-120% of remove.bg, depending on image category), free for you to check your own images so you can make an informed choice.<p>2. Customer-friendly pricing (PAYGO @ 1-10% of competitors' subscriptions) with a generous free tier (and free while in beta).<p>3. A novel API result format: Delta PNG [3], which offers excellent latency & bandwidth savings. Especially useful for mobile apps.<p>4. Operational transparency: actual volume & latency metrics public, with more coming soon (all API providers should be showing this).<p>There's of course more to it than just price and we see several sources of differentiation in this market: quality, price, capability, reliability, latency, and goodwill.<p>As a new entrant we're looking to meet-or-beat the quality bar; beat on price, capability, reliability and latency; and to build up goodwill over time.<p>Our goal is to make it a no-brainer for new accounts to choose us, and to provide the tools and guidance necessary for existing accounts to make the switch with confidence.<p>We'd love for you to try it out and to hear your thoughts!<p><a href="https://pixian.ai" rel="nofollow">https://pixian.ai</a><p>[1] <a href="https://news.ycombinator.com/item?id=18697601" rel="nofollow">https://news.ycombinator.com/item?id=18697601</a>
[2] <a href="https://news.ycombinator.com/item?id=33439405" rel="nofollow">https://news.ycombinator.com/item?id=33439405</a>
[3] <a href="https://pixian.ai/api/deltaPng" rel="nofollow">https://pixian.ai/api/deltaPng</a>
Show HN: Image background removal without annoying subscriptions
Hi HN,<p>Removing the background from images is a surprisingly common image processing task, and AI has made it really easy. The technology has come a long way since segment leader remove.bg launched here on hn in Dec 2018 [1]. Chasing remove.bg's success, a legion of providers have come on the market offering varying levels of quality & service.<p>Despite there being a large number of competing services, most still price for very high (~95%?) gross margins. Furthermore, subscriptions make the effective unit price a lot higher than the list price for infrequent users, and requires effort & attention to ensure you're getting value for money. This has prevented a host of use cases (e.g. infrequent professional / hobbyist) and business models (e.g. ad-supported websites & mobile apps).<p>We see this as an opportunity where we can jump to the market's logical conclusion to gain market share and build goodwill: cost-plus PAYGO pricing, i.e. the "S3 pricing model".<p>So we've built yet-another image background removal service ( <a href="https://pixian.ai" rel="nofollow">https://pixian.ai</a> - introductory post 6 months ago [2], a ton has been improved since then) but with a couple of twists:<p>1. Quantified quality comparison (90-120% of remove.bg, depending on image category), free for you to check your own images so you can make an informed choice.<p>2. Customer-friendly pricing (PAYGO @ 1-10% of competitors' subscriptions) with a generous free tier (and free while in beta).<p>3. A novel API result format: Delta PNG [3], which offers excellent latency & bandwidth savings. Especially useful for mobile apps.<p>4. Operational transparency: actual volume & latency metrics public, with more coming soon (all API providers should be showing this).<p>There's of course more to it than just price and we see several sources of differentiation in this market: quality, price, capability, reliability, latency, and goodwill.<p>As a new entrant we're looking to meet-or-beat the quality bar; beat on price, capability, reliability and latency; and to build up goodwill over time.<p>Our goal is to make it a no-brainer for new accounts to choose us, and to provide the tools and guidance necessary for existing accounts to make the switch with confidence.<p>We'd love for you to try it out and to hear your thoughts!<p><a href="https://pixian.ai" rel="nofollow">https://pixian.ai</a><p>[1] <a href="https://news.ycombinator.com/item?id=18697601" rel="nofollow">https://news.ycombinator.com/item?id=18697601</a>
[2] <a href="https://news.ycombinator.com/item?id=33439405" rel="nofollow">https://news.ycombinator.com/item?id=33439405</a>
[3] <a href="https://pixian.ai/api/deltaPng" rel="nofollow">https://pixian.ai/api/deltaPng</a>
Show HN: Image background removal without annoying subscriptions
Hi HN,<p>Removing the background from images is a surprisingly common image processing task, and AI has made it really easy. The technology has come a long way since segment leader remove.bg launched here on hn in Dec 2018 [1]. Chasing remove.bg's success, a legion of providers have come on the market offering varying levels of quality & service.<p>Despite there being a large number of competing services, most still price for very high (~95%?) gross margins. Furthermore, subscriptions make the effective unit price a lot higher than the list price for infrequent users, and requires effort & attention to ensure you're getting value for money. This has prevented a host of use cases (e.g. infrequent professional / hobbyist) and business models (e.g. ad-supported websites & mobile apps).<p>We see this as an opportunity where we can jump to the market's logical conclusion to gain market share and build goodwill: cost-plus PAYGO pricing, i.e. the "S3 pricing model".<p>So we've built yet-another image background removal service ( <a href="https://pixian.ai" rel="nofollow">https://pixian.ai</a> - introductory post 6 months ago [2], a ton has been improved since then) but with a couple of twists:<p>1. Quantified quality comparison (90-120% of remove.bg, depending on image category), free for you to check your own images so you can make an informed choice.<p>2. Customer-friendly pricing (PAYGO @ 1-10% of competitors' subscriptions) with a generous free tier (and free while in beta).<p>3. A novel API result format: Delta PNG [3], which offers excellent latency & bandwidth savings. Especially useful for mobile apps.<p>4. Operational transparency: actual volume & latency metrics public, with more coming soon (all API providers should be showing this).<p>There's of course more to it than just price and we see several sources of differentiation in this market: quality, price, capability, reliability, latency, and goodwill.<p>As a new entrant we're looking to meet-or-beat the quality bar; beat on price, capability, reliability and latency; and to build up goodwill over time.<p>Our goal is to make it a no-brainer for new accounts to choose us, and to provide the tools and guidance necessary for existing accounts to make the switch with confidence.<p>We'd love for you to try it out and to hear your thoughts!<p><a href="https://pixian.ai" rel="nofollow">https://pixian.ai</a><p>[1] <a href="https://news.ycombinator.com/item?id=18697601" rel="nofollow">https://news.ycombinator.com/item?id=18697601</a>
[2] <a href="https://news.ycombinator.com/item?id=33439405" rel="nofollow">https://news.ycombinator.com/item?id=33439405</a>
[3] <a href="https://pixian.ai/api/deltaPng" rel="nofollow">https://pixian.ai/api/deltaPng</a>
Show HN: Accelerated Docker builds on your local machine with Depot (YC W23)
Hello HN! We just launched a new feature we built at Depot that accelerates Docker image builds on your local machine in a team environment, and we wanted to share some of the details with you all.<p>The launch blog post: https://depot.dev/blog/local-builds<p>Depot is a hosted container build service - we run fully managed Intel and Arm remote build machines in AWS, with large instance sizes and SSD cache disks. The machines run BuildKit, the build engine that powers Docker, so generally anything you can `docker build`, you can also `depot build`.<p>Most people use Depot in CI, and you could also run `depot build` from your local machine as well. That would perform the build using the remote builder, with associated fast hardware and extra fast datacenter network speeds.<p>But then to download the container back to your local machine, BuildKit would transfer the <i>entire</i> container back for every build, including base image layers, since BuildKit wasn’t aware of what layers already existed on your device.<p>The new release fixes this! To make it work, we replaced the BuildKit `--load` by making the Depot CLI itself serve the Docker registry API on a local port, then asking Docker to pull the image from that localhost registry. The CLI in turn intercepts the requests for layers and fetches them directly using BuildKit’s content API.<p>This means Docker only asks for the layers it needs! This actually speeds up both local builds, where you only need to download changed layers, as well as CI where it can skip building an expensive tarball of the whole image every time!<p>We ran into one major obstacle when first testing: the machine running the Docker daemon might not be the same machine running the `depot build` command. Notably, CircleCI has a remote Docker daemon, where asking it to pull from localhost does not reach the CLI’s temporary registry.<p>For this, we built a "helper" container that the CLI launches to run the HTTP server portion of the temporary registry - since it’s launched as a container, it does run on the same machine as the Docker daemon, and localhost is reachable. The Depot CLI then communicates with the helper container over stdio, receiving requests for layers and sending their contents back using a custom simple transport protocol.<p>This makes everything very efficient! One cool part about the remote build machines: you can share cache with anyone on your team who has access to the same project. This means that if your teammate already built all or part of the container, your build just reuses the result. This means that, in addition to using the fast remote builders instead of your local device, you can actually have cache hits on code you haven’t personally built yet.<p>We’d love for you to check it out, and are happy to answer any questions you have about technical details!<p>https://depot.dev/docs/guides/local-development
Show HN: File-by-file AI-generated comments for your codebase
My friends and I were complaining about having to decipher incomprehensible code one day and decided to pass the code through GPT to see if it could write easily understandable comments to help us out. It turns out that GPT can but it was still a hassle to generate comments for large files.<p>So we decided to develop a basic web application that automatically integrates with your Github repository, generate comments, create a pull request and send you an email when it is all done.<p>There is definitely a lot more that can be done but we wanted to gain feedback on whether this is a problem that you face too. Do you often find it challenging to understand complex code? Do you have difficulties in writing informative comments? And if so, would you find value in a tool that can automatically generate comments for your code?<p>Really appreciate any feedback and suggestions! Thanks in advance!
Show HN: File-by-file AI-generated comments for your codebase
My friends and I were complaining about having to decipher incomprehensible code one day and decided to pass the code through GPT to see if it could write easily understandable comments to help us out. It turns out that GPT can but it was still a hassle to generate comments for large files.<p>So we decided to develop a basic web application that automatically integrates with your Github repository, generate comments, create a pull request and send you an email when it is all done.<p>There is definitely a lot more that can be done but we wanted to gain feedback on whether this is a problem that you face too. Do you often find it challenging to understand complex code? Do you have difficulties in writing informative comments? And if so, would you find value in a tool that can automatically generate comments for your code?<p>Really appreciate any feedback and suggestions! Thanks in advance!
Show HN: DB-GPT, an LLM tool for database
Show HN: DB-GPT, an LLM tool for database