Journey from Entrepreneur to Employee
21 by vortex_ape | 6 comments on Hacker News.
Tuesday, December 31, 2024
Monday, December 30, 2024
New top story on Hacker News: Tell HN: John Friel my father, internet pioneer and creator of QModem, has died
Tell HN: John Friel my father, internet pioneer and creator of QModem, has died
173 by AaronFriel | 17 comments on Hacker News.
If you knew him in life or remember his contribution to the world, please share your stories.
173 by AaronFriel | 17 comments on Hacker News.
If you knew him in life or remember his contribution to the world, please share your stories.
Sunday, December 29, 2024
New top story on Hacker News: Show HN: Kando – A cross-platform pie menu for your desktop
Show HN: Kando – A cross-platform pie menu for your desktop
47 by schneegans | 15 comments on Hacker News.
Kando is a cross-platform open source pie menu which I am currently developing! It offers an unconventional, fast, highly efficient, and fun way of interacting with your computer! You can use it to launch applications, simulate keyboard shortcuts, open files, and much more. Let me know what you think about it!
47 by schneegans | 15 comments on Hacker News.
Kando is a cross-platform open source pie menu which I am currently developing! It offers an unconventional, fast, highly efficient, and fun way of interacting with your computer! You can use it to launch applications, simulate keyboard shortcuts, open files, and much more. Let me know what you think about it!
Saturday, December 28, 2024
Friday, December 27, 2024
Thursday, December 26, 2024
Wednesday, December 25, 2024
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Monday, December 23, 2024
New top story on Hacker News: Show HN: Otto-m8 – A low code AI/ML API deployment Platform
Show HN: Otto-m8 – A low code AI/ML API deployment Platform
3 by farhan0167 | 0 comments on Hacker News.
Hi all, so I've been working on this low to no code platform that allows you to spin up deep learning workloads(I'm talking LLM's, Huggingface models, etc), interconnect a bunch of them, and deploy them as API's. The idea essentially came up early in September, when experimenting with combining a Huggingface based BERT model with an LLM at work, and I realized it would be cool if I could do that instantly(especially since it was a prototype). At the time, I was considering a platform that could essentially help you train deep learning models without any code. It was my observation that much of the code required to train or even run inference on HF models have matured significantly. But before I solved that problem, I wanted to solve inference. Initially inspired by n8n and AWS Cloudformation, I built out otto-m8 (translates to automate). Given a json payload that lists out all the resources, and how each model is interconnected, launch it as one-off API the user can query. And thanks to Reactflow, the UI was just something I couldn't just not implement. And as I built it out, I did not want to miss out on the LLM and Agent bit. With otto-m8, today, you can launch complex workflows by interconnecting HF models and LLM's(currently it supports OpenAI and Ollama only). But I like to see it being more than that. At the core, every workflow is an input process output model. Inputs get processed and there's an output. Therefore, with the way things are setup, one can integrate almost anything and make it interconnectable. Project Link: https://ift.tt/uKAnlLT Let me know what you guys think. I really would love feedback!
3 by farhan0167 | 0 comments on Hacker News.
Hi all, so I've been working on this low to no code platform that allows you to spin up deep learning workloads(I'm talking LLM's, Huggingface models, etc), interconnect a bunch of them, and deploy them as API's. The idea essentially came up early in September, when experimenting with combining a Huggingface based BERT model with an LLM at work, and I realized it would be cool if I could do that instantly(especially since it was a prototype). At the time, I was considering a platform that could essentially help you train deep learning models without any code. It was my observation that much of the code required to train or even run inference on HF models have matured significantly. But before I solved that problem, I wanted to solve inference. Initially inspired by n8n and AWS Cloudformation, I built out otto-m8 (translates to automate). Given a json payload that lists out all the resources, and how each model is interconnected, launch it as one-off API the user can query. And thanks to Reactflow, the UI was just something I couldn't just not implement. And as I built it out, I did not want to miss out on the LLM and Agent bit. With otto-m8, today, you can launch complex workflows by interconnecting HF models and LLM's(currently it supports OpenAI and Ollama only). But I like to see it being more than that. At the core, every workflow is an input process output model. Inputs get processed and there's an output. Therefore, with the way things are setup, one can integrate almost anything and make it interconnectable. Project Link: https://ift.tt/uKAnlLT Let me know what you guys think. I really would love feedback!
Sunday, December 22, 2024
Saturday, December 21, 2024
Friday, December 20, 2024
Thursday, December 19, 2024
Wednesday, December 18, 2024
Tuesday, December 17, 2024
Monday, December 16, 2024
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Thursday, December 12, 2024
New top story on Hacker News: Show HN: Gentrace – connect to your LLM app code and run/eval it from a UI
Show HN: Gentrace – connect to your LLM app code and run/eval it from a UI
10 by dsaffy | 0 comments on Hacker News.
Hey HN - Doug from Gentrace here. We originally launched via Show HN in August of 2023 as evaluation and observability for generative AI: https://ift.tt/cteSWHj Since then, everyone from the model providers to LLM ops companies built a prompt playground. We had one too, until we realized this was totally the wrong approach: - It's not connected to your application code - They don't support all models - You have to rebuild evals for just this one prompt (can't use your end-to-end evals) In other words, it was a ton of work and time to use these to actually make your app better. So, we built a new experience and are relaunching around this idea: Gentrace is a collaborative LLM app testing and experimentation platform that brings together engineers, PMs, subject matter experts, and more to run and test your actual end-to-end app. To do this, use our SDK to: - connect your app to Gentrace as a live runner over websocket (local) / via webhook (staging, prod) - wrap your parameters (eg prompt, model, top-k) so they become tunable knobs in the front end - edit the parameters and then run / evaluate the actual app code with datasets and evals in Gentrace We think it's great for tuning retrieval systems, upgrading models, and iterating on prompts. It's free to trial. Would love to hear your feedback / what you think!
10 by dsaffy | 0 comments on Hacker News.
Hey HN - Doug from Gentrace here. We originally launched via Show HN in August of 2023 as evaluation and observability for generative AI: https://ift.tt/cteSWHj Since then, everyone from the model providers to LLM ops companies built a prompt playground. We had one too, until we realized this was totally the wrong approach: - It's not connected to your application code - They don't support all models - You have to rebuild evals for just this one prompt (can't use your end-to-end evals) In other words, it was a ton of work and time to use these to actually make your app better. So, we built a new experience and are relaunching around this idea: Gentrace is a collaborative LLM app testing and experimentation platform that brings together engineers, PMs, subject matter experts, and more to run and test your actual end-to-end app. To do this, use our SDK to: - connect your app to Gentrace as a live runner over websocket (local) / via webhook (staging, prod) - wrap your parameters (eg prompt, model, top-k) so they become tunable knobs in the front end - edit the parameters and then run / evaluate the actual app code with datasets and evals in Gentrace We think it's great for tuning retrieval systems, upgrading models, and iterating on prompts. It's free to trial. Would love to hear your feedback / what you think!
Wednesday, December 11, 2024
Tuesday, December 10, 2024
Monday, December 9, 2024
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Sunday, December 1, 2024
New top story on Hacker News: Show HN: Vicinity – Fast, Lightweight Nearest Neighbors with Flexible Back Ends
Show HN: Vicinity – Fast, Lightweight Nearest Neighbors with Flexible Back Ends
9 by Pringled | 0 comments on Hacker News.
We’ve just open-sourced Vicinity, a lightweight approximate nearest neighbors (ANN) search package that allows for fast experimentation and comparison of a larger number of well known algorithms. Main features: - Lightweight: the base package only uses Numpy - Unified interface: use any of the supported algorithms and backends with a single interface: HNSW, Annoy, FAISS, and many more algorithms and libraries are supported - Easy evaluation: evaluate the performance of your backend with a simple function to measure queries per second vs recall - Serialization: save and load your index for persistence After working with a large number of ANN libraries over the years, we found it increasingly cumbersome to learn the interface, features, quirks, and limitations of every library. After writing custom evaluation code to measure the speed and performance for the 100th time to compare libraries, we decided to build this as a way to easily use a large number of algorithms and libraries with a unified, simple interface that allows for quick comparison and evaluation. We are curious to hear your feedback! Are there any algorithms that are missing that you use? Any extra evaluation metrics that are useful?
9 by Pringled | 0 comments on Hacker News.
We’ve just open-sourced Vicinity, a lightweight approximate nearest neighbors (ANN) search package that allows for fast experimentation and comparison of a larger number of well known algorithms. Main features: - Lightweight: the base package only uses Numpy - Unified interface: use any of the supported algorithms and backends with a single interface: HNSW, Annoy, FAISS, and many more algorithms and libraries are supported - Easy evaluation: evaluate the performance of your backend with a simple function to measure queries per second vs recall - Serialization: save and load your index for persistence After working with a large number of ANN libraries over the years, we found it increasingly cumbersome to learn the interface, features, quirks, and limitations of every library. After writing custom evaluation code to measure the speed and performance for the 100th time to compare libraries, we decided to build this as a way to easily use a large number of algorithms and libraries with a unified, simple interface that allows for quick comparison and evaluation. We are curious to hear your feedback! Are there any algorithms that are missing that you use? Any extra evaluation metrics that are useful?
Saturday, November 30, 2024
New top story on Hacker News: Show HN: Jinbase – Multi-model transactional embedded database
Show HN: Jinbase – Multi-model transactional embedded database
3 by alexrustic | 0 comments on Hacker News.
Hi HN ! Alex here. I'm excited to show you Jinbase ( https://ift.tt/WfLuy8H ), my multi-model transactional embedded database. Almost a year ago, I introduced Paradict [1], my take on multi-format streaming serialization. Given its readability, the Paradict text format appears de facto as an interesting data format for config files. But using Paradict to manage config files would end up cluttering its programming interface and making it confusing for users who still have choices of alternative libraries (TOML, INI File, etc.) dedicated to config files. So I used Paradict as a dependency for KvF (Key-value file format) [2], a new project of mine that focuses on config files with sections. With its compact binary format, I thought Paradict would be an efficient dependency for a new project that would rely on I/O functions (such as Open, Read, Write, Seek, Tell and Close) to implement a minimalistic yet reliable persistence solution. But that was before I learned that "files are hard" [3]. SQLite with its transactions, BLOB data type and incremental I/O for BLOBs seemed like the right giant to stand on for my new project. Jinbase started small as a key-value store and ended up as a multi-model embedded database that pushes the boundaries of what we usually do with SQLite. The first transition to the second data model (the depot) happened when I realized that the key-value store was not well suited for cases where a unique identifier is supposed to be automatically generated for each new record, saving the user the burden of providing an identifier that could accidentally be subject to a collision and thus overwrite an existing record. After that, I implemented a search capability that accepts UID ranges for the depot store, timespans (records are automatically timestamped) for both the depot and key-value stores and GLOB patterns and number ranges for string and integer keys in the key-value store. The queue and stack data models emerged as solutions for use cases where records must be consumed in a specific order. A typical record would be retrieved and deleted from the database in a single transaction unit. Since SQLite is used as the storage engine, Jinbase supports the relational model de facto. For convenience, all tables related to Jinbase internals are prefixed with "jinbase_", making Jinbase a useful tool for opening legacy SQLite files to add new data models that will safely coexist with the ad hoc relational model. All four main data models (key-value, depot, queue, stack) support Paradict-compatible data types, such as dictionaries, strings, binary data, integers, datetimes, etc. Under the hood, when the user initiates a write operation, Jinbase serializes (except for binary data), chunks, and stores the data iteratively. A record can be accessed not only in bulk, but also with two levels of partial access granularity: the byte-level and the field-level. While SQLite's incremental I/O for BLOBs is designed to target an individual BLOB column in a row, Jinbase extends this so that for each record, incremental reads cover all chunks as if they were a single unified BLOB. For dictionary records only, Jinbase automatically creates and maintains a lightweight index consisting of pointers to root fields, which then allows extracting from an arbitrary record the contents of a field automatically deserialized before being returned. The most obvious use cases for Jinbase are storing user preferences, persisting session data before exit, order-based processing of data streams, exposing data for other processes, upgrading legacy SQLite files with new data models and bespoke data persistence solutions. Jinbase is written in Python, is available on PyPI and you can play with the examples on the README. Let me know what you think about this project. [1] https://ift.tt/85sMINy [2] https://ift.tt/lKuvTRe [3] https://ift.tt/z9qsjuD
3 by alexrustic | 0 comments on Hacker News.
Hi HN ! Alex here. I'm excited to show you Jinbase ( https://ift.tt/WfLuy8H ), my multi-model transactional embedded database. Almost a year ago, I introduced Paradict [1], my take on multi-format streaming serialization. Given its readability, the Paradict text format appears de facto as an interesting data format for config files. But using Paradict to manage config files would end up cluttering its programming interface and making it confusing for users who still have choices of alternative libraries (TOML, INI File, etc.) dedicated to config files. So I used Paradict as a dependency for KvF (Key-value file format) [2], a new project of mine that focuses on config files with sections. With its compact binary format, I thought Paradict would be an efficient dependency for a new project that would rely on I/O functions (such as Open, Read, Write, Seek, Tell and Close) to implement a minimalistic yet reliable persistence solution. But that was before I learned that "files are hard" [3]. SQLite with its transactions, BLOB data type and incremental I/O for BLOBs seemed like the right giant to stand on for my new project. Jinbase started small as a key-value store and ended up as a multi-model embedded database that pushes the boundaries of what we usually do with SQLite. The first transition to the second data model (the depot) happened when I realized that the key-value store was not well suited for cases where a unique identifier is supposed to be automatically generated for each new record, saving the user the burden of providing an identifier that could accidentally be subject to a collision and thus overwrite an existing record. After that, I implemented a search capability that accepts UID ranges for the depot store, timespans (records are automatically timestamped) for both the depot and key-value stores and GLOB patterns and number ranges for string and integer keys in the key-value store. The queue and stack data models emerged as solutions for use cases where records must be consumed in a specific order. A typical record would be retrieved and deleted from the database in a single transaction unit. Since SQLite is used as the storage engine, Jinbase supports the relational model de facto. For convenience, all tables related to Jinbase internals are prefixed with "jinbase_", making Jinbase a useful tool for opening legacy SQLite files to add new data models that will safely coexist with the ad hoc relational model. All four main data models (key-value, depot, queue, stack) support Paradict-compatible data types, such as dictionaries, strings, binary data, integers, datetimes, etc. Under the hood, when the user initiates a write operation, Jinbase serializes (except for binary data), chunks, and stores the data iteratively. A record can be accessed not only in bulk, but also with two levels of partial access granularity: the byte-level and the field-level. While SQLite's incremental I/O for BLOBs is designed to target an individual BLOB column in a row, Jinbase extends this so that for each record, incremental reads cover all chunks as if they were a single unified BLOB. For dictionary records only, Jinbase automatically creates and maintains a lightweight index consisting of pointers to root fields, which then allows extracting from an arbitrary record the contents of a field automatically deserialized before being returned. The most obvious use cases for Jinbase are storing user preferences, persisting session data before exit, order-based processing of data streams, exposing data for other processes, upgrading legacy SQLite files with new data models and bespoke data persistence solutions. Jinbase is written in Python, is available on PyPI and you can play with the examples on the README. Let me know what you think about this project. [1] https://ift.tt/85sMINy [2] https://ift.tt/lKuvTRe [3] https://ift.tt/z9qsjuD
Friday, November 29, 2024
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New top story on Hacker News: Launch HN: Midship (YC S24) – Turn unstructured documents into usable data
Launch HN: Midship (YC S24) – Turn unstructured documents into usable data
9 by maxmaio | 9 comments on Hacker News.
Hey HN, we are Max, Kieran, and Aahel from Midship ( https://midship.ai ). Midship makes it easy to extract data from unstructured documents like pdfs and images. Here’s a video showing it in action: https://ift.tt/Jv8fASy?... , and a demo playground (no signup required!) to test it out: https://ift.tt/metpDza We started 5 months ago initially trying to make an AI natural language workflow builder that would be a simpler alternative to Zapier or Make.com. However, most of our users seemed to be much more interested in the basic (and not very good) document extraction feature we had. Seeing how people were spending hours a day manually extracting data from pdfs inspired us to build what has become Midship! The problem is that despite all our progress in software, huge amounts of business data still lives in PDFs and images. Sure, you can OCR them, but getting clean, structured data out is still painful. Most existing tools just give you a blob of markdown - leaving you to figure out which parts matter and how they relate. We've found that combining OCR with language models lets us do something more useful: extract specific fields and tables that users actually care about. The LLMs help correct OCR mistakes and understand context (like knowing that "Inv#" and "Invoice Number" mean the same thing). We have two main kinds of users today, non-technical users that extract data via our web app and developers who use our extraction api. We were initially focused on the first one as they seemed like an underserved part of the market, but we’ve received a lot of interest from developers who face the same issues. For pricing, we currently charge a monthly Saas fee per seat for the web app and a volume based pricing for the API. We’re really excited to share what we’ve built so far and look forward to any feedback from the community!
9 by maxmaio | 9 comments on Hacker News.
Hey HN, we are Max, Kieran, and Aahel from Midship ( https://midship.ai ). Midship makes it easy to extract data from unstructured documents like pdfs and images. Here’s a video showing it in action: https://ift.tt/Jv8fASy?... , and a demo playground (no signup required!) to test it out: https://ift.tt/metpDza We started 5 months ago initially trying to make an AI natural language workflow builder that would be a simpler alternative to Zapier or Make.com. However, most of our users seemed to be much more interested in the basic (and not very good) document extraction feature we had. Seeing how people were spending hours a day manually extracting data from pdfs inspired us to build what has become Midship! The problem is that despite all our progress in software, huge amounts of business data still lives in PDFs and images. Sure, you can OCR them, but getting clean, structured data out is still painful. Most existing tools just give you a blob of markdown - leaving you to figure out which parts matter and how they relate. We've found that combining OCR with language models lets us do something more useful: extract specific fields and tables that users actually care about. The LLMs help correct OCR mistakes and understand context (like knowing that "Inv#" and "Invoice Number" mean the same thing). We have two main kinds of users today, non-technical users that extract data via our web app and developers who use our extraction api. We were initially focused on the first one as they seemed like an underserved part of the market, but we’ve received a lot of interest from developers who face the same issues. For pricing, we currently charge a monthly Saas fee per seat for the web app and a volume based pricing for the API. We’re really excited to share what we’ve built so far and look forward to any feedback from the community!
Tuesday, November 5, 2024
New top story on Hacker News: Rd-TableBench – Accurately evaluating table extraction
Rd-TableBench – Accurately evaluating table extraction
20 by raunakchowdhuri | 4 comments on Hacker News.
Hey HN! A ton of document parsing solutions have been coming out lately, each claiming SOTA with little evidence. A lot of these turned out to be LLM or LVM wrappers that hallucinate frequently on complex tables. We just released RD-TableBench, an open benchmark to help teams evaluate extraction performance for complex tables. The benchmark includes a variety of challenging scenarios including scanned tables, handwriting, language detection, merged cells, and more. We employed an independent team of PhD-level human labelers who manually annotated 1000 complex table images from a diverse set of publicly available documents. Alongside this, we also release a new bioinformatics inspired algorithm for grading table similarity. Would love to hear any feedback! -Raunak
20 by raunakchowdhuri | 4 comments on Hacker News.
Hey HN! A ton of document parsing solutions have been coming out lately, each claiming SOTA with little evidence. A lot of these turned out to be LLM or LVM wrappers that hallucinate frequently on complex tables. We just released RD-TableBench, an open benchmark to help teams evaluate extraction performance for complex tables. The benchmark includes a variety of challenging scenarios including scanned tables, handwriting, language detection, merged cells, and more. We employed an independent team of PhD-level human labelers who manually annotated 1000 complex table images from a diverse set of publicly available documents. Alongside this, we also release a new bioinformatics inspired algorithm for grading table similarity. Would love to hear any feedback! -Raunak
Monday, November 4, 2024
Sunday, November 3, 2024
Saturday, November 2, 2024
Friday, November 1, 2024
Thursday, October 31, 2024
New top story on Hacker News: Show HN: Shimmer – ADHD-adapted body doubling
Show HN: Shimmer – ADHD-adapted body doubling
12 by christalwang | 1 comments on Hacker News.
I’m Chris, one of the co-founders of Shimmer. In 2022, following my ADHD diagnosis, I launched Shimmer ( https://shimmer.care ), a 1:1 ADHD Coaching for adults (HN launch here: https://ift.tt/jdiogB1 ). One problem we discovered while running 1:1 coaching is that people weren’t able to actually follow through (in real life) on the ideas they came up with during their weekly sessions with their coach. There is a concept called body doubling that’s popular within the ADHD community—it’s basically getting things done in the presence of other people. The positive accountability is proven to work. However, our members told us they tried other body doubling solutions or attempted to organize it themselves in real life but none of the solutions stuck. So we reverse engineered productive moments our members described, paired with scientific backing of what motivates ADHD-ers, and designed an online body doubling experience for our coaching members that provides a safe but productive space for them to get things done between weekly sessions. A few of the motivators we infused into the traditional body doubling experience were 1) newness/novelty — each session has a different guided experience in the break like breathwork or stretching, 2) urgency — there’s a large visible pomodoro timer on the top left that counts down from 25 min, 3) community — the shared space is ADHD-friendly, and has a mood check-in & sharing functionality built in so you don’t feel alone, 4) accountability — there’s a task list where each time you check something off, it notifies the group, and you can view others’ as well if they opt in. Here’s a video walking through the product experience: https://ift.tt/AMGKRhq Our body doubling was created and iterated alongside thousands of people with ADHD on our coaching platform over 9+ months of building & iterating with them. We’re excited to unveil this experience. If you have ADHD (or executive functioning challenges), we’d love for you to check out coaching & body doubling and give us critical feedback. Shimmer’s pricing: $140/mo. for Essentials plan (15-min weekly sessions), $230/mo. for Standard plan (30-min weekly sessions), $345/mo. for Immersive plan (45-min weekly sessions); all plans start with an additional 25% off the first month, HSA/FSA-eligible. The reason why the price is so high is that this is not a self-guided app or SaaS tool. You’re matched with a real, credentialed coach (not AI) and since ADHD coaching is not reimbursed in the US, the price is hard for us to bring down because the largest cost component is the coach’s compensation. *We know these prices are still expensive for many people with ADHD. Here are the actions we’re taking: (1) we offer needs-based scholarships and aim to have 5% of members on them at any time, (2) we often run fully sponsored scholarships with our partners—over 60 full ride scholarships and 100 group coaching spots have been disbursed alongside Asian Mental Health Project, Government of Canada, and more, and (3) we have aligned our coaching model alongside Health & Wellness Coaching, which is expected to be reimbursed in the next years. If there are ways we can further drive down the cost, please reach out to me directly at chris@shimmer.care.
12 by christalwang | 1 comments on Hacker News.
I’m Chris, one of the co-founders of Shimmer. In 2022, following my ADHD diagnosis, I launched Shimmer ( https://shimmer.care ), a 1:1 ADHD Coaching for adults (HN launch here: https://ift.tt/jdiogB1 ). One problem we discovered while running 1:1 coaching is that people weren’t able to actually follow through (in real life) on the ideas they came up with during their weekly sessions with their coach. There is a concept called body doubling that’s popular within the ADHD community—it’s basically getting things done in the presence of other people. The positive accountability is proven to work. However, our members told us they tried other body doubling solutions or attempted to organize it themselves in real life but none of the solutions stuck. So we reverse engineered productive moments our members described, paired with scientific backing of what motivates ADHD-ers, and designed an online body doubling experience for our coaching members that provides a safe but productive space for them to get things done between weekly sessions. A few of the motivators we infused into the traditional body doubling experience were 1) newness/novelty — each session has a different guided experience in the break like breathwork or stretching, 2) urgency — there’s a large visible pomodoro timer on the top left that counts down from 25 min, 3) community — the shared space is ADHD-friendly, and has a mood check-in & sharing functionality built in so you don’t feel alone, 4) accountability — there’s a task list where each time you check something off, it notifies the group, and you can view others’ as well if they opt in. Here’s a video walking through the product experience: https://ift.tt/AMGKRhq Our body doubling was created and iterated alongside thousands of people with ADHD on our coaching platform over 9+ months of building & iterating with them. We’re excited to unveil this experience. If you have ADHD (or executive functioning challenges), we’d love for you to check out coaching & body doubling and give us critical feedback. Shimmer’s pricing: $140/mo. for Essentials plan (15-min weekly sessions), $230/mo. for Standard plan (30-min weekly sessions), $345/mo. for Immersive plan (45-min weekly sessions); all plans start with an additional 25% off the first month, HSA/FSA-eligible. The reason why the price is so high is that this is not a self-guided app or SaaS tool. You’re matched with a real, credentialed coach (not AI) and since ADHD coaching is not reimbursed in the US, the price is hard for us to bring down because the largest cost component is the coach’s compensation. *We know these prices are still expensive for many people with ADHD. Here are the actions we’re taking: (1) we offer needs-based scholarships and aim to have 5% of members on them at any time, (2) we often run fully sponsored scholarships with our partners—over 60 full ride scholarships and 100 group coaching spots have been disbursed alongside Asian Mental Health Project, Government of Canada, and more, and (3) we have aligned our coaching model alongside Health & Wellness Coaching, which is expected to be reimbursed in the next years. If there are ways we can further drive down the cost, please reach out to me directly at chris@shimmer.care.
Wednesday, October 30, 2024
New top story on Hacker News: Show HN: AI OmniGen – AI Image Generator with Consistent Visuals
Show HN: AI OmniGen – AI Image Generator with Consistent Visuals
15 by lcorinst | 3 comments on Hacker News.
AI OmniGen is an advanced AI image generator, offering identity preservation for consistent subject representation and seamless image editing for refined, customized visuals.
15 by lcorinst | 3 comments on Hacker News.
AI OmniGen is an advanced AI image generator, offering identity preservation for consistent subject representation and seamless image editing for refined, customized visuals.
Tuesday, October 29, 2024
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New top story on Hacker News: Show HN: Client Side anti-RAG solution
Show HN: Client Side anti-RAG solution
6 by foxhop | 2 comments on Hacker News.
Client Side Only Example, chat with this page. Because we don't use API keys we don't have any real need for a server. view the page source, it's _all_ there! The program doesn't take history into account & yet is has surprising coherence. View Source and start on line 258.
6 by foxhop | 2 comments on Hacker News.
Client Side Only Example, chat with this page. Because we don't use API keys we don't have any real need for a server. view the page source, it's _all_ there! The program doesn't take history into account & yet is has surprising coherence. View Source and start on line 258.
Saturday, October 19, 2024
Friday, October 18, 2024
Thursday, October 17, 2024
New top story on Hacker News: Arithmetic is an underrated world-modeling technology
Arithmetic is an underrated world-modeling technology
11 by crescit_eundo | 1 comments on Hacker News.
11 by crescit_eundo | 1 comments on Hacker News.
Wednesday, October 16, 2024
Tuesday, October 15, 2024
Monday, October 14, 2024
Sunday, October 13, 2024
Saturday, October 12, 2024
Friday, October 11, 2024
Thursday, October 10, 2024
Wednesday, October 9, 2024
New top story on Hacker News: Show HN: Donobu – Mac App for Web Automation and Testing
Show HN: Donobu – Mac App for Web Automation and Testing
16 by wewtyflakes | 0 comments on Hacker News.
Been working on a desktop app for Mac that lets you create web flows and rerun them ( https://www.donobu.com/ ). You can optionally use AI (BYOK: bring your own keys) to create flows for you and to do other interesting things, like making vision-based semantic assertions. Also, your data lives on your own filesystem, and we do not see any of it (further still, there is no phoning home at all). A nice benefit of this being a desktop app rather than a SAAS product, is that if you happen to be developing/iterating on a webpage locally, this has no problem hooking into it. What this intends to be a good fit for: - Testing web pages, especially locally. - Exploring random webpages with a stated objective. - Automating tedious flows. Rerunning a flow won't get caught up on using a single selector (many websites randomize element IDs, for instance), there is smart failover using a prioritized list of selectors. - Getting a quick draft of an end-to-end test in Javascript. What this is a bad fit for: - Mass web scraping (too slow). - Adversarial websites. What we are still working out: - Click-and-drag operations. - Websites that are primarily controlled from canvas. - Smoothing out UI/UX (we are two backend engineers trying our best, and are handedly outgunned by real frontend engineers). Fun things to try: - Asking it to assert that a webpage has a certain theme. - Asking it to run an accessibility report for a page (uses https://ift.tt/YS62q4A ). - Asking it to run a cookie report for a page. The tech: - Java 21 for the main business logic. - Javalin 6 for the web framework ( https://javalin.io/ ). - Playwright for controlling the browser ( https://ift.tt/31uRzpq ). - Axe for running accessibility reports ( https://ift.tt/YS62q4A ). Critical feedback is welcome. Thanks for trying it out! Cheers, -Justin and Vaz
16 by wewtyflakes | 0 comments on Hacker News.
Been working on a desktop app for Mac that lets you create web flows and rerun them ( https://www.donobu.com/ ). You can optionally use AI (BYOK: bring your own keys) to create flows for you and to do other interesting things, like making vision-based semantic assertions. Also, your data lives on your own filesystem, and we do not see any of it (further still, there is no phoning home at all). A nice benefit of this being a desktop app rather than a SAAS product, is that if you happen to be developing/iterating on a webpage locally, this has no problem hooking into it. What this intends to be a good fit for: - Testing web pages, especially locally. - Exploring random webpages with a stated objective. - Automating tedious flows. Rerunning a flow won't get caught up on using a single selector (many websites randomize element IDs, for instance), there is smart failover using a prioritized list of selectors. - Getting a quick draft of an end-to-end test in Javascript. What this is a bad fit for: - Mass web scraping (too slow). - Adversarial websites. What we are still working out: - Click-and-drag operations. - Websites that are primarily controlled from canvas. - Smoothing out UI/UX (we are two backend engineers trying our best, and are handedly outgunned by real frontend engineers). Fun things to try: - Asking it to assert that a webpage has a certain theme. - Asking it to run an accessibility report for a page (uses https://ift.tt/YS62q4A ). - Asking it to run a cookie report for a page. The tech: - Java 21 for the main business logic. - Javalin 6 for the web framework ( https://javalin.io/ ). - Playwright for controlling the browser ( https://ift.tt/31uRzpq ). - Axe for running accessibility reports ( https://ift.tt/YS62q4A ). Critical feedback is welcome. Thanks for trying it out! Cheers, -Justin and Vaz
Tuesday, October 8, 2024
Monday, October 7, 2024
Sunday, October 6, 2024
Saturday, October 5, 2024
New top story on Hacker News: Show HN: Open-source real-time talk-to-AI wearable device for few $
Show HN: Open-source real-time talk-to-AI wearable device for few $
19 by zq2240 | 4 comments on Hacker News.
1. In the US, about 1/5 children are hospitalized each year that don’t have a caregiver. Caregiver such as play therapists and parents’ stress can also affect children's emotions. 2. Not everyone is good at making friends and not everyone has a BFF to talk to. Imagine you're having a hard time in life or at work, and you can't tell your parents or friends. So, we built an open-source project Starmoon and are using affordable hardware components to bring AI characters to real-word objects like toys and plushies to help people emotional growth. We believe this is a complement tool and it is not intended to replace anyone. Please leave any opinion.
19 by zq2240 | 4 comments on Hacker News.
1. In the US, about 1/5 children are hospitalized each year that don’t have a caregiver. Caregiver such as play therapists and parents’ stress can also affect children's emotions. 2. Not everyone is good at making friends and not everyone has a BFF to talk to. Imagine you're having a hard time in life or at work, and you can't tell your parents or friends. So, we built an open-source project Starmoon and are using affordable hardware components to bring AI characters to real-word objects like toys and plushies to help people emotional growth. We believe this is a complement tool and it is not intended to replace anyone. Please leave any opinion.
New top story on Hacker News: Ask HN: What type of Auth are you using on your side projects?
Ask HN: What type of Auth are you using on your side projects?
10 by honksillet | 7 comments on Hacker News.
I was looking at the Supabase docs and it was nice to see a long list of Auth work flows supported/documented. So my question is, here in October 2024, what are y'all using for Auth on your side projects. Password based, social, email, something else? If you are using social, which social do you support? Is there any public data on which types of Auth have the best conversion/bounce rates? And for you, which Auth is just easy to support long term and which just ends up being a drag? TY
10 by honksillet | 7 comments on Hacker News.
I was looking at the Supabase docs and it was nice to see a long list of Auth work flows supported/documented. So my question is, here in October 2024, what are y'all using for Auth on your side projects. Password based, social, email, something else? If you are using social, which social do you support? Is there any public data on which types of Auth have the best conversion/bounce rates? And for you, which Auth is just easy to support long term and which just ends up being a drag? TY
Friday, October 4, 2024
Thursday, October 3, 2024
Wednesday, October 2, 2024
New top story on Hacker News: Show HN: Kameo – a Rust library for building fault-tolerant, async actors
Show HN: Kameo – a Rust library for building fault-tolerant, async actors
12 by tqwewe | 2 comments on Hacker News.
Hi HN, I’m excited to share Kameo, a lightweight Rust library that helps you build fault-tolerant, distributed, and asynchronous actors. If you're working on distributed systems, microservices, or real-time applications, Kameo offers a simple yet powerful API for handling concurrency, panic recovery, and remote messaging between nodes. Key Features: - Async Rust: Each actor runs as a separate Tokio task, making concurrency management simple. - Remote Messaging: Seamlessly send messages to actors across different nodes. - Supervision and Fault Tolerance: Create self-healing systems with actor hierarchies. - Backpressure Support: Supports bounded and unbounded mpsc messaging. I built Kameo because I wanted a more intuitive, scalable solution for distributed Rust applications. I’d love feedback from the HN community and contributions from anyone interested in Rust and actor-based systems. Check out the project on GitHub: https://ift.tt/RZFqO0p Looking forward to hearing your thoughts!
12 by tqwewe | 2 comments on Hacker News.
Hi HN, I’m excited to share Kameo, a lightweight Rust library that helps you build fault-tolerant, distributed, and asynchronous actors. If you're working on distributed systems, microservices, or real-time applications, Kameo offers a simple yet powerful API for handling concurrency, panic recovery, and remote messaging between nodes. Key Features: - Async Rust: Each actor runs as a separate Tokio task, making concurrency management simple. - Remote Messaging: Seamlessly send messages to actors across different nodes. - Supervision and Fault Tolerance: Create self-healing systems with actor hierarchies. - Backpressure Support: Supports bounded and unbounded mpsc messaging. I built Kameo because I wanted a more intuitive, scalable solution for distributed Rust applications. I’d love feedback from the HN community and contributions from anyone interested in Rust and actor-based systems. Check out the project on GitHub: https://ift.tt/RZFqO0p Looking forward to hearing your thoughts!
Tuesday, October 1, 2024
Monday, September 30, 2024
Sunday, September 29, 2024
Saturday, September 28, 2024
New top story on Hacker News: Show HN: Bringing multithreading to Python's async event loop
Show HN: Bringing multithreading to Python's async event loop
15 by nbsande | 2 comments on Hacker News.
This project explores the integration of multithreading into the asyncio event loop in Python. While this was initially built with enhancing CPU utilization for FastAPI servers in mind, the approach can be used with more general async programs too. If you’re interested in diving deeper into the details, I’ve written a blog post about it here: https://ift.tt/ITStjm8
15 by nbsande | 2 comments on Hacker News.
This project explores the integration of multithreading into the asyncio event loop in Python. While this was initially built with enhancing CPU utilization for FastAPI servers in mind, the approach can be used with more general async programs too. If you’re interested in diving deeper into the details, I’ve written a blog post about it here: https://ift.tt/ITStjm8
Friday, September 27, 2024
Thursday, September 26, 2024
Wednesday, September 25, 2024
Tuesday, September 24, 2024
Monday, September 23, 2024
Sunday, September 22, 2024
Saturday, September 21, 2024
Friday, September 20, 2024
New top story on Hacker News: Show HN: EloqKV – Scalable distributed ACID key-value database with Redis API
Show HN: EloqKV – Scalable distributed ACID key-value database with Redis API
12 by hubertzhang | 19 comments on Hacker News.
We're thrilled to unveil EloqKV, a lightning-fast distributed key-value store with a Redis-compatible API. Built on a new database architecture called the Data Substrate, EloqKV brings significant innovations to database design. Here’s the unique features that makes it stand out: - Flexible Deployment: Run it as a single-node in-memory KV cache, a larger-than-memory database or scale to a highly available, distributed transactional database with ease. - High Performance: Achieves performance levels comparable to top in-memory databases like Redis and DragonflyDB, while significantly outperforming durable KV stores like KVRocks. - Full ACID Transactions: Ensures complete transactional integrity, even in distributed environments. - Independent Resource Scaling: Scale CPU, memory, storage, and logging resources independently to meet your needs. We’d love to hear your thoughts and feedback!
12 by hubertzhang | 19 comments on Hacker News.
We're thrilled to unveil EloqKV, a lightning-fast distributed key-value store with a Redis-compatible API. Built on a new database architecture called the Data Substrate, EloqKV brings significant innovations to database design. Here’s the unique features that makes it stand out: - Flexible Deployment: Run it as a single-node in-memory KV cache, a larger-than-memory database or scale to a highly available, distributed transactional database with ease. - High Performance: Achieves performance levels comparable to top in-memory databases like Redis and DragonflyDB, while significantly outperforming durable KV stores like KVRocks. - Full ACID Transactions: Ensures complete transactional integrity, even in distributed environments. - Independent Resource Scaling: Scale CPU, memory, storage, and logging resources independently to meet your needs. We’d love to hear your thoughts and feedback!
New top story on Hacker News: Show HN: Inngest 1.0 – Open-source durable workflows on every platform
Show HN: Inngest 1.0 – Open-source durable workflows on every platform
20 by tonyhb | 0 comments on Hacker News.
Hi HN! I’m Tony, one of the co-founders of Inngest ( https://inngest.com/ ) Inngest is an open-source durable workflow platform that works on any cloud. Durable workflows are stateful, long running step functions written in code, which automatically retry on failure. It abstracts everything about queues, event streams and state for you, letting you focus on code. Some examples of uses: managing stateful AI chained step functions; managing search/rag indexes and data pipelines; integrations and webhooks; billing and payment flows. Technical details: unlike other solutions, we put lots of effort into designing our SDK’s step.run APIs to make them extremely easy to use — developer experience is the most important thing for us. We had to design and build our own queueing system to work with multi-tenancy, batching, and debouncing, and we’re iterating on this as we move to FoundationDB. It’s largely all Go in the backend, with a bunch of caching, clickhouse, event streams, and coordination on our behalf. Workers are shared nothing, and run based off of the queue and execution state. We did a post last year as we iterated on our TS SDK. The product has changed a lot since then and wanted to show the community what’s changed as we reach 1.0: * Golang, Java, and Python SDKs with cross-language function invocation (across clouds, too) * Multi-tenant aware flow control (concurrency, throttling, debounce) * Batching, grouping many events into a single function call * Much improved dashboard, with tracing and metrics built in * Advanced recovery tools like function replay, temporary pausing, bulk cancellation (with optional expressions). No more dead letter queues! * Branch deploys built in, with staging env support out of the box * Full local testing with production parity There's a ton on the roadmap, with more launching next week. We’re hiring systems & infra engineers, too — it’s a fun job with lots of challenges! Wanted to say thank you to the HN community for feedback so far! Happy Friday :)
20 by tonyhb | 0 comments on Hacker News.
Hi HN! I’m Tony, one of the co-founders of Inngest ( https://inngest.com/ ) Inngest is an open-source durable workflow platform that works on any cloud. Durable workflows are stateful, long running step functions written in code, which automatically retry on failure. It abstracts everything about queues, event streams and state for you, letting you focus on code. Some examples of uses: managing stateful AI chained step functions; managing search/rag indexes and data pipelines; integrations and webhooks; billing and payment flows. Technical details: unlike other solutions, we put lots of effort into designing our SDK’s step.run APIs to make them extremely easy to use — developer experience is the most important thing for us. We had to design and build our own queueing system to work with multi-tenancy, batching, and debouncing, and we’re iterating on this as we move to FoundationDB. It’s largely all Go in the backend, with a bunch of caching, clickhouse, event streams, and coordination on our behalf. Workers are shared nothing, and run based off of the queue and execution state. We did a post last year as we iterated on our TS SDK. The product has changed a lot since then and wanted to show the community what’s changed as we reach 1.0: * Golang, Java, and Python SDKs with cross-language function invocation (across clouds, too) * Multi-tenant aware flow control (concurrency, throttling, debounce) * Batching, grouping many events into a single function call * Much improved dashboard, with tracing and metrics built in * Advanced recovery tools like function replay, temporary pausing, bulk cancellation (with optional expressions). No more dead letter queues! * Branch deploys built in, with staging env support out of the box * Full local testing with production parity There's a ton on the roadmap, with more launching next week. We’re hiring systems & infra engineers, too — it’s a fun job with lots of challenges! Wanted to say thank you to the HN community for feedback so far! Happy Friday :)
Thursday, September 19, 2024
Wednesday, September 18, 2024
Tuesday, September 17, 2024
Monday, September 16, 2024
Sunday, September 15, 2024
New top story on Hacker News: Ask HN: Former gifted children with hard lives, how did you turn out?
Ask HN: Former gifted children with hard lives, how did you turn out?
60 by askHN2024 | 50 comments on Hacker News.
For various life reasons, I developed depression, and I am autistic and have ADHD (diagnosed, treated). I didn’t get treatment for my ADHD till after college. The point of this Ask HN isn’t to start a pity party, but I am just getting some data on how others like me are doing. I have an ACE score of 6. Currently, I look accomplished to people, but I don’t feel accomplished. My estimated networth is maybe 300K or more with home equity. My biggest concern with my quality of life is I don’t feel safe (don’t ask). So what’s your ACE score, and how satisfied are you with your life? ACE quiz: https://ift.tt/T0WwEoB...
60 by askHN2024 | 50 comments on Hacker News.
For various life reasons, I developed depression, and I am autistic and have ADHD (diagnosed, treated). I didn’t get treatment for my ADHD till after college. The point of this Ask HN isn’t to start a pity party, but I am just getting some data on how others like me are doing. I have an ACE score of 6. Currently, I look accomplished to people, but I don’t feel accomplished. My estimated networth is maybe 300K or more with home equity. My biggest concern with my quality of life is I don’t feel safe (don’t ask). So what’s your ACE score, and how satisfied are you with your life? ACE quiz: https://ift.tt/T0WwEoB...
Saturday, September 14, 2024
Friday, September 13, 2024
Thursday, September 12, 2024
Wednesday, September 11, 2024
Tuesday, September 10, 2024
Monday, September 9, 2024
New top story on Hacker News: Ask HN: How do you manage your prompts in ChatGPT?
Ask HN: How do you manage your prompts in ChatGPT?
20 by nabi_nafio | 12 comments on Hacker News.
I use ChatGPT regularly for a lot of different tasks. For example, coding, health Q&A, and summarizing docs. The different prompts stack up in the sidebar which becomes very difficult to manage. For example, I frequently have to refer back to a prompt that I wrote previously. But I usually give up looking for it because of the tedious scroll and search process. I was wondering if there is an easier way. How do you manage your prompts in ChatGPT?
20 by nabi_nafio | 12 comments on Hacker News.
I use ChatGPT regularly for a lot of different tasks. For example, coding, health Q&A, and summarizing docs. The different prompts stack up in the sidebar which becomes very difficult to manage. For example, I frequently have to refer back to a prompt that I wrote previously. But I usually give up looking for it because of the tedious scroll and search process. I was wondering if there is an easier way. How do you manage your prompts in ChatGPT?
Sunday, September 8, 2024
Saturday, September 7, 2024
Friday, September 6, 2024
Thursday, September 5, 2024
Wednesday, September 4, 2024
Tuesday, September 3, 2024
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Saturday, August 31, 2024
Friday, August 30, 2024
Thursday, August 29, 2024
Wednesday, August 28, 2024
New top story on Hacker News: Show HN: Claude Artifacts" but creating real web apps
Show HN: Claude Artifacts" but creating real web apps
18 by antonoo | 8 comments on Hacker News.
Hey Hacker News! Launching gptengineer.app into beta today. It's like Claude Artifacts, but: - you can edit the code in your fav IDE (two-way github sync) - installs npm packages - automatically picks up build and runtime errors and fixes them - very fast, built with rust The full stack capabilities are built on supabase (prefer to not have to handle auth + user data at this point so this is owned by the user) The seed for this project was an open source experiment, posted about that previously here: https://ift.tt/1E6wLn5 Would love feedback if you give it a try!
18 by antonoo | 8 comments on Hacker News.
Hey Hacker News! Launching gptengineer.app into beta today. It's like Claude Artifacts, but: - you can edit the code in your fav IDE (two-way github sync) - installs npm packages - automatically picks up build and runtime errors and fixes them - very fast, built with rust The full stack capabilities are built on supabase (prefer to not have to handle auth + user data at this point so this is owned by the user) The seed for this project was an open source experiment, posted about that previously here: https://ift.tt/1E6wLn5 Would love feedback if you give it a try!
Tuesday, August 27, 2024
Monday, August 26, 2024
New top story on Hacker News: In 2024, it really is better to run a startup in SF
In 2024, it really is better to run a startup in SF
21 by iancmceachern | 18 comments on Hacker News.
21 by iancmceachern | 18 comments on Hacker News.
Sunday, August 25, 2024
New top story on Hacker News: Why don't we have personalized search engines?
Why don't we have personalized search engines?
15 by enether | 15 comments on Hacker News.
- Search as it is today sucks - Google is an ad-engine, not a search engine - SEO is gamed all the time The end result is a search result that isn't that valuable. Why isn't there a tool that allows me to: - search good content I've read - search curated (from other people I trust) content - search books and other paid material I have bought - search my notes (that are scattered throughout 5 apps) All in one?
15 by enether | 15 comments on Hacker News.
- Search as it is today sucks - Google is an ad-engine, not a search engine - SEO is gamed all the time The end result is a search result that isn't that valuable. Why isn't there a tool that allows me to: - search good content I've read - search curated (from other people I trust) content - search books and other paid material I have bought - search my notes (that are scattered throughout 5 apps) All in one?
Saturday, August 24, 2024
Friday, August 23, 2024
Thursday, August 22, 2024
Wednesday, August 21, 2024
Tuesday, August 20, 2024
New top story on Hacker News: Show HN: Tree-sitter Integration for Swift
Show HN: Tree-sitter Integration for Swift
4 by daspoon | 0 comments on Hacker News.
I have created a Swift package ( https://ift.tt/6pwUsJq ) enabling tree-sitter parsers to be written in Swift; specifically, as an array of production rules which map symbol types to pairings of syntax expression and type constructor. A member macro derives a tree-sitter grammar and embeds the generated parser in its expansion. This project is a work in progress, and I will be grateful for any feedback. Thanks, Dave
4 by daspoon | 0 comments on Hacker News.
I have created a Swift package ( https://ift.tt/6pwUsJq ) enabling tree-sitter parsers to be written in Swift; specifically, as an array of production rules which map symbol types to pairings of syntax expression and type constructor. A member macro derives a tree-sitter grammar and embeds the generated parser in its expansion. This project is a work in progress, and I will be grateful for any feedback. Thanks, Dave
Monday, August 19, 2024
New top story on Hacker News: Ask HN: Google Ads Rejected My SaaS as Compromised Site
Ask HN: Google Ads Rejected My SaaS as Compromised Site
17 by madjam002 | 12 comments on Hacker News.
I’m a solo founder and really struggling to get Google Ads running for my website. My site always gets flagged as Compromised Site and Malicious Software, even though I’ve done several checks that shows it’s clean. Even Google’s own Safe Browsing shows it as clean. Their latest feedback after appealing suggests I change from a .co.uk to .com to resolve the issue which seems like complete nonsense. Does anyone have any suggestions on how I can fix this? All of my competitors are running ads and it’s extremely frustrating as a solo founder that I am unable to do so. Will post my website on request as I’m not sure if I’m allowed to post it.
17 by madjam002 | 12 comments on Hacker News.
I’m a solo founder and really struggling to get Google Ads running for my website. My site always gets flagged as Compromised Site and Malicious Software, even though I’ve done several checks that shows it’s clean. Even Google’s own Safe Browsing shows it as clean. Their latest feedback after appealing suggests I change from a .co.uk to .com to resolve the issue which seems like complete nonsense. Does anyone have any suggestions on how I can fix this? All of my competitors are running ads and it’s extremely frustrating as a solo founder that I am unable to do so. Will post my website on request as I’m not sure if I’m allowed to post it.
Sunday, August 18, 2024
Saturday, August 17, 2024
Friday, August 16, 2024
New top story on Hacker News: Banks Are Now Accused of Cheating Customers Billions
Banks Are Now Accused of Cheating Customers Billions
50 by randycupertino | 10 comments on Hacker News.
50 by randycupertino | 10 comments on Hacker News.
Thursday, August 15, 2024
Wednesday, August 14, 2024
Tuesday, August 13, 2024
Monday, August 12, 2024
New top story on Hacker News: Postgres.new: In-browser Postgres with an AI interface
Postgres.new: In-browser Postgres with an AI interface
51 by kiwicopple | 64 comments on Hacker News.
hey HN, supabase ceo here This is a new service that we're experimenting with that uses PGLite[0], a WASM build of Postgres that runs in the browser. You might remember an earlier WASM build[1] that was around ~30MB. The Electric team [2] have gone one step further and created a complete build of Postgres that’s under 3MB. Their implementation is technically interesting. Postgres is normally multi-process - each client connection is handed to a child process by the postmaster process. In WASM there’s limited/no support for process forking and threads. Fortunately, Postgres has a relatively unknown built-in “single user mode” [3] primarily designed for bootstrapping a new database and disaster recovery. Single-user mode only supports a minimal cancel REPL, so PGlite adds wire-protocol support which enables parametrised queries etc. We have created https://postgres.new as an experiment. You can think of it like a love-child between Postgres and ChatGPT: in-browser Postgres sandbox with AI assistance. You can spin up as many new Postgres databases as you want because they all live inside your browser. We pair PGlite with an LLM (currently GPT-4o) and give it full reign over the database with unrestricted permissions. This is an important detail - giving an LLM full autonomy means that it can run multiple operations back-to-back: any SQL errors from Postgres are fed back to the language model so that it can have a few more attempts to solve the problem. Since it’s in-browser it’s low risk. Some other features include: - CSV upload: you can upload a CSV and it will automatically create a Postgres table which you can query with natural language. - Charts: you can ask the LLM to create a chart with the data and change the colors of the charts. - RAG / pgvector: PGLite supports pgvector, so you can ask the LLM to create embeddings for RAG. The site uses transformers.js [4] to create embeddings inside the browser. We’re working on an update to deploy your databases and serve them from S3 using pg-gateway [5]. We expect to have a read-only deployments ready by the end of the week. You can access them using any postgres-compatible tool (eg: psql). Everything is open source. A huge shout-out to the Electric team who have been a pleasure to build with. [0] PGLite: https://ift.tt/LPbFKie [1] Postgres-wasm: https://ift.tt/EPZqtD4 [2] Electric: https://ift.tt/DyEH0FB [3] Single user mode: https://ift.tt/3WTVnJ4... [4] transformers.js: https://ift.tt/TwNPvIx [5] pg-gateway: https://ift.tt/iDMzGol
51 by kiwicopple | 64 comments on Hacker News.
hey HN, supabase ceo here This is a new service that we're experimenting with that uses PGLite[0], a WASM build of Postgres that runs in the browser. You might remember an earlier WASM build[1] that was around ~30MB. The Electric team [2] have gone one step further and created a complete build of Postgres that’s under 3MB. Their implementation is technically interesting. Postgres is normally multi-process - each client connection is handed to a child process by the postmaster process. In WASM there’s limited/no support for process forking and threads. Fortunately, Postgres has a relatively unknown built-in “single user mode” [3] primarily designed for bootstrapping a new database and disaster recovery. Single-user mode only supports a minimal cancel REPL, so PGlite adds wire-protocol support which enables parametrised queries etc. We have created https://postgres.new as an experiment. You can think of it like a love-child between Postgres and ChatGPT: in-browser Postgres sandbox with AI assistance. You can spin up as many new Postgres databases as you want because they all live inside your browser. We pair PGlite with an LLM (currently GPT-4o) and give it full reign over the database with unrestricted permissions. This is an important detail - giving an LLM full autonomy means that it can run multiple operations back-to-back: any SQL errors from Postgres are fed back to the language model so that it can have a few more attempts to solve the problem. Since it’s in-browser it’s low risk. Some other features include: - CSV upload: you can upload a CSV and it will automatically create a Postgres table which you can query with natural language. - Charts: you can ask the LLM to create a chart with the data and change the colors of the charts. - RAG / pgvector: PGLite supports pgvector, so you can ask the LLM to create embeddings for RAG. The site uses transformers.js [4] to create embeddings inside the browser. We’re working on an update to deploy your databases and serve them from S3 using pg-gateway [5]. We expect to have a read-only deployments ready by the end of the week. You can access them using any postgres-compatible tool (eg: psql). Everything is open source. A huge shout-out to the Electric team who have been a pleasure to build with. [0] PGLite: https://ift.tt/LPbFKie [1] Postgres-wasm: https://ift.tt/EPZqtD4 [2] Electric: https://ift.tt/DyEH0FB [3] Single user mode: https://ift.tt/3WTVnJ4... [4] transformers.js: https://ift.tt/TwNPvIx [5] pg-gateway: https://ift.tt/iDMzGol
Sunday, August 11, 2024
Saturday, August 10, 2024
Friday, August 9, 2024
Thursday, August 8, 2024
Wednesday, August 7, 2024
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Thursday, August 1, 2024
Wednesday, July 31, 2024
New top story on Hacker News: Ask HN: Best Tools for Monorepo?
Ask HN: Best Tools for Monorepo?
12 by bradhe | 15 comments on Hacker News.
I've got a monorepo I'm working in that has a Golang backend with a couple services and a Next.js front-end. Everything lives in a monorepo together. My tooling is super weak, though! For instance, for process management in development I'm using Goreman, which is a Foreman alternative in Goalng. Wondering what's the state of the art for managing the processes in local dev in monorepos in 2024? Or other tools for managing a monorepo I might be missing in general!
12 by bradhe | 15 comments on Hacker News.
I've got a monorepo I'm working in that has a Golang backend with a couple services and a Next.js front-end. Everything lives in a monorepo together. My tooling is super weak, though! For instance, for process management in development I'm using Goreman, which is a Foreman alternative in Goalng. Wondering what's the state of the art for managing the processes in local dev in monorepos in 2024? Or other tools for managing a monorepo I might be missing in general!
Tuesday, July 30, 2024
Monday, July 29, 2024
New top story on Hacker News: Can the moon influence human health? New research
Can the moon influence human health? New research
22 by sabrina_ramonov | 11 comments on Hacker News.
22 by sabrina_ramonov | 11 comments on Hacker News.
Sunday, July 28, 2024
New top story on Hacker News: Show HN: I built an open-source tool to make on-call suck less
Show HN: I built an open-source tool to make on-call suck less
16 by aray07 | 1 comments on Hacker News.
Hey HN, I am building an open source platform to make on-call better and less stressful for engineers. We are building a tool that can silence alerts and help with debugging and root cause analysis. We also want to automate tedious parts of being on-call (running runbooks manually, answering questions on Slack, dealing with Pagerduty). Here is a quick video of how it works: https://youtu.be/m_K9Dq1kZDw I hated being on-call for a couple of reasons: * Alert volume: The number of alerts kept increasing over time. It was hard to maintain existing alerts. This would lead to a lot of noisy and unactionable alerts. I have lost count of the number of times I got woken up by alert that auto-resolved 5 minutes later. * Debugging: Debugging an alert or a customer support ticket would need me to gain context on a service that I might not have worked on before. These companies used many observability tools that would make debugging challenging. There are always a time pressure to resolve issues quickly. There were some more tangential issues that used to take up a lot of on-call time * Support: Answering questions from other teams. A lot of times these questions were repetitive and have been answered before. * Dealing with PagerDuty: These tools are hard to use. e.g. It was hard to schedule an override in PD or do holiday schedules. I am building an on-call tool that is Slack-native since that has become the de-facto tool for on-call engineers. We heard from a lot of engineers that maintaining good alert hygiene is a challenge. To start off, Opslane integrates with Datadog and can classify alerts as actionable or noisy. We analyze your alert history across various signals: 1. Alert frequency 2. How quickly the alerts have resolved in the past 3. Alert priority 4. Alert response history Our classification is conservative and it can be tuned as teams get more confidence in the predictions. We want to make sure that you aren't accidentally missing a critical alert. Additionally, we generate a weekly report based on all your alerts to give you a picture of your overall alert hygiene. What’s next? 1. Building more integrations (Prometheus, Splunk, Sentry, PagerDuty) to continue making on-call quality of life better 2. Help make debugging and root cause analysis easier. 3. Runbook automation We’re still pretty early in development and we want to make on-call quality of life better. Any feedback would be much appreciated!
16 by aray07 | 1 comments on Hacker News.
Hey HN, I am building an open source platform to make on-call better and less stressful for engineers. We are building a tool that can silence alerts and help with debugging and root cause analysis. We also want to automate tedious parts of being on-call (running runbooks manually, answering questions on Slack, dealing with Pagerduty). Here is a quick video of how it works: https://youtu.be/m_K9Dq1kZDw I hated being on-call for a couple of reasons: * Alert volume: The number of alerts kept increasing over time. It was hard to maintain existing alerts. This would lead to a lot of noisy and unactionable alerts. I have lost count of the number of times I got woken up by alert that auto-resolved 5 minutes later. * Debugging: Debugging an alert or a customer support ticket would need me to gain context on a service that I might not have worked on before. These companies used many observability tools that would make debugging challenging. There are always a time pressure to resolve issues quickly. There were some more tangential issues that used to take up a lot of on-call time * Support: Answering questions from other teams. A lot of times these questions were repetitive and have been answered before. * Dealing with PagerDuty: These tools are hard to use. e.g. It was hard to schedule an override in PD or do holiday schedules. I am building an on-call tool that is Slack-native since that has become the de-facto tool for on-call engineers. We heard from a lot of engineers that maintaining good alert hygiene is a challenge. To start off, Opslane integrates with Datadog and can classify alerts as actionable or noisy. We analyze your alert history across various signals: 1. Alert frequency 2. How quickly the alerts have resolved in the past 3. Alert priority 4. Alert response history Our classification is conservative and it can be tuned as teams get more confidence in the predictions. We want to make sure that you aren't accidentally missing a critical alert. Additionally, we generate a weekly report based on all your alerts to give you a picture of your overall alert hygiene. What’s next? 1. Building more integrations (Prometheus, Splunk, Sentry, PagerDuty) to continue making on-call quality of life better 2. Help make debugging and root cause analysis easier. 3. Runbook automation We’re still pretty early in development and we want to make on-call quality of life better. Any feedback would be much appreciated!
Saturday, July 27, 2024
New top story on Hacker News: Show HN: Semantic Grep – A Word2Vec-powered search tool
Show HN: Semantic Grep – A Word2Vec-powered search tool
8 by arunsupe | 1 comments on Hacker News.
Much improved new version. Search for words similar to the query. For example, "death" will find "death", "dying", "dead", "killing"... Incredibly useful for exploring large text datasets where exact matches are too restrictive.
8 by arunsupe | 1 comments on Hacker News.
Much improved new version. Search for words similar to the query. For example, "death" will find "death", "dying", "dead", "killing"... Incredibly useful for exploring large text datasets where exact matches are too restrictive.
Friday, July 26, 2024
Thursday, July 25, 2024
Wednesday, July 24, 2024
Tuesday, July 23, 2024
New top story on Hacker News: Show HN: Zerox – document OCR with GPT-mini
Show HN: Zerox – document OCR with GPT-mini
12 by themanmaran | 3 comments on Hacker News.
This started out as a weekend hack with gpt-4-mini, using the very basic strategy of "just ask the ai to ocr the document". But this turned out to be better performing than our current implementation of Unstructured/Textract. At pretty much the same cost. I've tested almost every variant of document OCR over the past year, especially trying things like table / chart extraction. I've found the rules based extraction has always been lacking. Documents are meant to be a visual representation after all. With weird layouts, tables, charts, etc. Using a vision model just make sense! In general, I'd categorize this solution as slow, expensive, and non deterministic. But 6 months ago it was impossible. And 6 months from now it'll be fast, cheap, and probably more reliable!
12 by themanmaran | 3 comments on Hacker News.
This started out as a weekend hack with gpt-4-mini, using the very basic strategy of "just ask the ai to ocr the document". But this turned out to be better performing than our current implementation of Unstructured/Textract. At pretty much the same cost. I've tested almost every variant of document OCR over the past year, especially trying things like table / chart extraction. I've found the rules based extraction has always been lacking. Documents are meant to be a visual representation after all. With weird layouts, tables, charts, etc. Using a vision model just make sense! In general, I'd categorize this solution as slow, expensive, and non deterministic. But 6 months ago it was impossible. And 6 months from now it'll be fast, cheap, and probably more reliable!
Monday, July 22, 2024
Sunday, July 21, 2024
Saturday, July 20, 2024
Friday, July 19, 2024
Thursday, July 18, 2024
Wednesday, July 17, 2024
New top story on Hacker News: Show HN: VisCircuit – A Note-Taking Website for Electronics and Circuits
Show HN: VisCircuit – A Note-Taking Website for Electronics and Circuits
6 by darrenyaoyaoyao | 0 comments on Hacker News.
Hi, everyone. I created a note-taking website for electronics and circuits where you can draw circuit diagrams and write text notes at the same time. I am a Digital IC designer, and I self-study different types of analog and digital circuits a lot. However, I found a problem. Circuits have many different architectures and are hard to memorize due to numerous experiential tips. I want to document what I learn in my note app, but I found there is no method for me to easily draw circuit and block diagrams alongside text notes. This issue has bothered me for a long time, from my master's school to my current working life. I decided to solve it, so I created a note-taking website specifically for electronics and circuits, called VisCircuit. With VisCircuit, you can easily draw circuit diagrams, block diagrams, and write text notes simultaneously. I have already used it for two weeks and have noted down things I find hard to remember, such as SRAM, amplifier circuits, and PCB components of Arduino and Raspberry Pi. I found this tool really useful for memorizing knowledge about electronics and circuits. Currently, I have opened VisCircuit for alpha testing, and I want to let some people use it and give me feedback. Feel free to try it, and I will really appreciate what you think about this project. Leave any suggestions for improvement. Thank you very much.
6 by darrenyaoyaoyao | 0 comments on Hacker News.
Hi, everyone. I created a note-taking website for electronics and circuits where you can draw circuit diagrams and write text notes at the same time. I am a Digital IC designer, and I self-study different types of analog and digital circuits a lot. However, I found a problem. Circuits have many different architectures and are hard to memorize due to numerous experiential tips. I want to document what I learn in my note app, but I found there is no method for me to easily draw circuit and block diagrams alongside text notes. This issue has bothered me for a long time, from my master's school to my current working life. I decided to solve it, so I created a note-taking website specifically for electronics and circuits, called VisCircuit. With VisCircuit, you can easily draw circuit diagrams, block diagrams, and write text notes simultaneously. I have already used it for two weeks and have noted down things I find hard to remember, such as SRAM, amplifier circuits, and PCB components of Arduino and Raspberry Pi. I found this tool really useful for memorizing knowledge about electronics and circuits. Currently, I have opened VisCircuit for alpha testing, and I want to let some people use it and give me feedback. Feel free to try it, and I will really appreciate what you think about this project. Leave any suggestions for improvement. Thank you very much.
Tuesday, July 16, 2024
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