The best Hacker News stories from Show from the past day
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Show HN: Gleek diagram maker – UML class, Sequence, ER diagrams, Flowcharts
Show HN: Gleek diagram maker – UML class, Sequence, ER diagrams, Flowcharts
Woice.me – async voice communication for teams: work, at your own pace
Show HN: We made a CLI and API to automate inbound email
Hi HN! We're a 5 person team working on simplifying the creation of email apps. Right now, most email services focus on outbound emails (newsletters, transactional, delivery), but that doesn't solve the fact that we all hate receiving them. You can try it at https://mailscript.com<p>Mailscript lets you create programmable email addresses. It works headless, via the CLI, API (we use Swagger to support most languages). You can even run it as a daemon on a server (to run functions when emails arrive).<p>Once you get username@mailscript.com, you can create as many aliases as you'd like (including on the fly support for *@username.mailscript.com). Just like in Gmail, we support adding . or +. Every address gets an SMTP key as well, so you can use your favourite email client e.g. Gmail...<p>We've been working hard on making the CLI and API easy to understand, and take a trigger/actions approach. We even have parsers for GitHub emails (so you can automate Issues, PRs, Actions). You can see what the code looks like in our templates: https://github.com/mailscript/cli/tree/main/packages/templates<p>Example use cases:
- send Zabbix alerts to SMS if 2 messages in one minute!
- post Github releases to Discord
- save pdf attachments to Google Drive
- create shared email addresses
You can even collaborate on your email infrastructure on GitHub by exporting it as a YAML file.<p>If you'd like to learn more:
Docs: https://docs.mailscript.com
API playground: https://api.mailscript.com<p>We'd really like to hear your feedback, especially the harsh criticism. If you'd like any help with building automations, we'll take the time to help you code them. Feel free to ask for help on our Discord (https://discord.gg/US24HAVYq2) or at contact@mailscript.com!
Show HN: Eraser — Excalidraw-based visual meeting canvas
Show HN: PhpOverWebsocket
Show HN: PhpOverWebsocket
Show HN: Static Site Authoring via SMS
Show HN: Static Site Authoring via SMS
Show HN: Static Site Authoring via SMS
Show HN: NNext.net – A Firebase-like managed vector storage for ML applications
Hi HN. Peter here. As a machine learning engineer, I mostly think in terms of feature vectors, embeddings, and matrices. One of the most useful byproducts of deep neural networks is embeddings because they allow us to represent high-dimensional data in terms of lower-dimensional latent vectors. These feature vectors can be used for downstream applications like similarly search, recommendation systems and near duplicate detection.<p>As an ML engineer, I was frustrated by the lack of a datastore in which vectors are first-class citizens. As a result, most ML engineers, including myself, end up using awkward workarounds to store vectors such as arrays in SQL/NoSQL databases, stringifying vectors and storing them as text in in-memory-based caching systems such as Redis ETC. Furthermore, these systems don't allow for vector-based query operations such as nearest neighbor search. Consequently, engineers have to deploy additional approximate nearest neighbor search systems such as Facebook's FAISS or Spotify's ANNOY. These systems, while nifty and fast, are difficult to install and are costly to maintain.
To address these issues, I built NNext, a managed vector datastore in which vectors are first class citizens. NNext, allows you to store vectors along with any json-blob metadata. Furthermore, NNext comes with a fast approximate nearest-neighbor (ANN) search capability.<p>I would love to get feedback on your experience as Data Scientist or ML engineer storing feature vectors and ANN systems. Please shoot me an email at p@nnext.net.<p>https://nnext.net
Show HN: NNext.net – A Firebase-like managed vector storage for ML applications
Hi HN. Peter here. As a machine learning engineer, I mostly think in terms of feature vectors, embeddings, and matrices. One of the most useful byproducts of deep neural networks is embeddings because they allow us to represent high-dimensional data in terms of lower-dimensional latent vectors. These feature vectors can be used for downstream applications like similarly search, recommendation systems and near duplicate detection.<p>As an ML engineer, I was frustrated by the lack of a datastore in which vectors are first-class citizens. As a result, most ML engineers, including myself, end up using awkward workarounds to store vectors such as arrays in SQL/NoSQL databases, stringifying vectors and storing them as text in in-memory-based caching systems such as Redis ETC. Furthermore, these systems don't allow for vector-based query operations such as nearest neighbor search. Consequently, engineers have to deploy additional approximate nearest neighbor search systems such as Facebook's FAISS or Spotify's ANNOY. These systems, while nifty and fast, are difficult to install and are costly to maintain.
To address these issues, I built NNext, a managed vector datastore in which vectors are first class citizens. NNext, allows you to store vectors along with any json-blob metadata. Furthermore, NNext comes with a fast approximate nearest-neighbor (ANN) search capability.<p>I would love to get feedback on your experience as Data Scientist or ML engineer storing feature vectors and ANN systems. Please shoot me an email at p@nnext.net.<p>https://nnext.net
Show HN: Recut, a native Mac app that automatically removes silence from videos
Show HN: Recut, a native Mac app that automatically removes silence from videos
Show HN: Recut, a native Mac app that automatically removes silence from videos
Show HN: Fast Rolling Quantiles for Python
Show HN: Fast Rolling Quantiles for Python
Show HN: A network of weather stations to help prevent pesticide spray drift
Show HN: A network of weather stations to help prevent pesticide spray drift
Show HN: A network of weather stations to help prevent pesticide spray drift