The best Hacker News stories from Show from the past day
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Show HN: A website that tracks US food prices every day
The US Department of Agriculture (USDA) publishes daily food price data for about 290 commodities on:<p>- what growers were paid at shipping point<p>- what buyers paid at the big city wholesale markets<p>- what prices supermarkets advertised in their weekly ads<p>This data comes out as dozens of separate text reports and PDFs, one per market, with no history and no way to see how prices change over time.<p>I think this should be public data that is easy to access and understand, so I built an open-source tracker for it.<p>Github: <a href="https://github.com/kadoa-org/food-price-monitor" rel="nofollow">https://github.com/kadoa-org/food-price-monitor</a>
Show HN: jevals – replacing LLM judges with typed Jev decisions
Show HN: Foremerge – Catch intent conflicts between parallel coding agents
At, GPTree, we run several coding agents across our team on one repo using parallel worktrees. Apart from wasted time reviewing and fixing conflicts at PR time, the failures that hurt the most are when multiple plans or tickets cause architecture changes that cannot both be true. Ex. one agent replaces a class while another one is in the process of extending it. Git only notices if the resulting patches happen to touch the same lines and the review only catches it if they are familiar with both tickets.<p>Foremerge is a local "git like" coordination layer that sits above git (ie. does not interact with or change the way git and worktrees function), Before editing each agent publishes an intent and the scopes it will change, with the operation it plans to complete on each one.<p><pre><code> foremerge intent publish --agent "$A" \
--summary "Replace PaymentService with StripePaymentService" \
--scope symbol:PaymentService=replace
foremerge intent publish --agent "$B" \
--summary "Add PayPal support to PaymentService" \
--scope symbol:PaymentService=extend
</code></pre>
The publish by the 2nd agent returns a HIGH destructive_vs_additive finding before writing any code. Agents keep their own worktrees and the shared state is one SQLite file in gits common direectory. No hooks, no merge drivers, nothing rewrites your history.<p>It ships as one Rust binary with a CLI and MCP server with 18 tools and `foremerge setup all` wires it into Claude Code, Codex and Cursor. Because the protocol has nothing provider specific, a Claude agent and a Codex agent coordinate through the same store. Before any work is accepted, Foremerge runs a named check that you configured against the exact git state of the change. An agent that says tests pass is recorded but it dosnt satisfy the acceptance gate without running the check itself.<p>Detection is deterministic, no judge model reading your code. HIGH conflicts are only asserted for declared operations, ie. matches inferred from prose cap out below high. Claims are advisory leases, not locks so two agents can still hold the same scope without deadlock. The open source version is single matching and so not a distributed consensus.<p>We have tested this up to 98 parallel agents all working on the same repo with zero conflicts (was supposed to be 100 but 2 agents failed to run due to resource limitations)<p>I replayed 76 intents on my own agents from a build last week in the order they happened. The sample had exactly 1 conflict (which was flagged) and the review found a blind spot where one agent claimed scope by class name and the other claimed it by an internal method. We are working on fixing that for the next release.<p>Setup is a 30s install by pasting the quickstart instructions from the readme.md into your agent or manually:
`curl -fsSL <a href="https://foremerge.com/install.sh" rel="nofollow">https://foremerge.com/install.sh</a> | sh` or `cargo install
--locked foremerge`, then `foremerge init && foremerge setup all` in a repo.
Apache-2.0.<p>The feedback I want most is which conflicts between your agents plans would you actually want flagged and which would you tollerate as noise?<p>Repo here: <a href="https://github.com/naw103/foremerge" rel="nofollow">https://github.com/naw103/foremerge</a>
Website: <a href="https://foremerge.com" rel="nofollow">https://foremerge.com</a><p>More information on the problems this solves: <a href="https://foremerge.com/blog/" rel="nofollow">https://foremerge.com/blog/</a>
Show HN: Lossless-memory – a personal AI memory that never summarizes
Show HN: Mini-AGI – Dynamic continual learning model trained on 8GB VRAM
Sorry for the pretentious name, I know, I know.. It just contains all the pieces I would like to see a AGI model to have, and I can't stand the temptation. Before throwing rocks at me, please take a glance at the Readme, and I hope it will cover your mood a little bit.<p>So, first of all it does work and you can see the sample from the whole training run here: <a href="https://raw.githubusercontent.com/volotat/mini-AGI/refs/heads/main/runs/samples.txt" rel="nofollow">https://raw.githubusercontent.com/volotat/mini-AGI/refs/head...</a><p>Here is the scaling law graph I have so far, and it looks very promising:
<a href="https://github.com/volotat/mini-AGI/blob/main/assets/scaling.png" rel="nofollow">https://github.com/volotat/mini-AGI/blob/main/assets/scaling...</a><p>The model was built under my deep dissatisfaction so we cannot really train even moderately big models (1B+ scale) on the consumer's hardware. We can inference and fine-tune them for sure, but I would like to have full control over what the model sees over the training run, so it is fully aligned with my interests, not some corporations.<p>I was thinking about for some time and come up with two interesting ideas I thought worth pursuing: MoE with a lot of experts that gets added and pruned from the model while it trains, where only a small subset of of experts are actually in use at any particular moment + batch 1 training on the single continuous stream of data.<p>First allows us to be bounded only by the disk space in terms of number of parameters and load and unload experts only when they are needed. The second (if figured out and it turns out to be doable) allows us to get aways with small VRAM capacity because we do not need to store big randomized batches and their respective gradients.<p>I started brainstorming with Claude and after some time we found an approach that seems to be promising, and low and behold, a few weeks pass and you can see the results yourself.<p>Obviously, I did use AI in the process of making this project and I am pretty sure it would be completely impossible for me to do something like this without it, so I hope it is more than justified.<p>The model is still running over the first of 7.8B characters corpus I selected for training, so the weights are not out yet, and it's about a couple weeks of waiting until they are cooked at the current reading speed. And yeah, the model just read continuous interleaved passages from the dataset, each by 32K characters long each as a single stream. Just as you or I would do.<p>The set up seems to be really simple so you can git clone the project, run it and observe everything for yourself.<p>Thanks for your attention.
Show HN: Rubrol – Sub-10ms PDF engine using Typst instead of Headless Chrome
Show HN: Three genlocked RP2350B make a console – 3k sprite pixels per line)
Show HN: I created an open source locally usable full fledged AI platform
hi to all the readers this post is for my recent opensource project called ENZO<p>now answering what is enzo so enzo is an opensource platform where i clubbed all the free available api for anyone use under one hood with more than 2000 models available to use for chatting coding researching and much more now answering the most common question of why you should put your time looking the project so it has few distinct feature meaning<p>it has a dedicated agents tab where you can describe your need and create a special agent just for one specific task with master ability in that domain<p>second it has the ability to connect your gmail drive and calendar and then you can ask it to perform some specific tasks like reading you the most important mail of the day or finding recruiter mails and creating personalized reply based on your data which it stores locally on your device<p>third the coding mode offers a dedicated preview window where you can see your code running and have a look of it feels and edit it in realtime as well as all the modes are packed with dedicated skills which delivers promising results<p>fourth the ui features some additional things such as music tab where you can listen to any music want and it has a custom personalized feature which runs in background and an llm understands your taste and recommends similar kind of music you like<p>fifth the most important why your trust it with your api key then to explain i would say enzo a dedicated vault which manages all your api and to secure it the vault as aes 256 bit encryption which prevents any person or any middle man to look at your api key and since the whole program runs locally on your device you have complete freedom to oversee all the backend work happening and it also features password lock which if you enable saves a backup key and then locks your whole platform work behind a pass screen though it is not foolproof as any third party or malware containing extension can still fetch login tokens from your browser so its security also depends upon how you access it concluding all of it.<p>i urge to anyone who reads this to have a look at the platform even if you hate it just curse it in the comment its fine or if you would like to drop any feedback i would highly encourage that and since its my first work open source platform i know it has a lot of errors and bugs so i apologize upfront for it and if you consider my work worthy please drop a star on the repo that'll make my day
Show HN: A competition for small neural networks that play strategy games
Show HN: A competition for small neural networks that play strategy games
Show HN: Sigabrt.dev – cronjob monitor with an SSH TUI
Hello HN. I built this mostly to monitor the things I host myself. I know it's nothing too exciting.<p>Anyway, the TL;DR is: Create an endpoint, and if your script/cronjob fails to regularly ping it, you get notified (by email or ntfy). E.g.:<p><pre><code> 0 * * * * ./script.sh && curl -fsS https://sigabrt.dev/pulse/<id>/beat
</code></pre>
It also has an SSH TUI which is currently experimental and read-only, mostly because I'm not sure whether it is actually useful or just a gimmick :):<p><pre><code> ssh sigabrt.dev
</code></pre>
To use it, simply add your SSH public key in your account settings.<p>Yes, there are services like this already, and this is minimalistic by comparison. Feedback is welcome.
Show HN: Sigabrt.dev – cronjob monitor with an SSH TUI
Hello HN. I built this mostly to monitor the things I host myself. I know it's nothing too exciting.<p>Anyway, the TL;DR is: Create an endpoint, and if your script/cronjob fails to regularly ping it, you get notified (by email or ntfy). E.g.:<p><pre><code> 0 * * * * ./script.sh && curl -fsS https://sigabrt.dev/pulse/<id>/beat
</code></pre>
It also has an SSH TUI which is currently experimental and read-only, mostly because I'm not sure whether it is actually useful or just a gimmick :):<p><pre><code> ssh sigabrt.dev
</code></pre>
To use it, simply add your SSH public key in your account settings.<p>Yes, there are services like this already, and this is minimalistic by comparison. Feedback is welcome.
Show HN: Radius – A Meetup.com Alternative
Hello HN!<p>I'm relaunching Radius [1] - far too long after the original Show HN [2] (I'll blame the day job for that).<p>Radius started out from my frustration with not knowing what was going on around me. The initial plan was to "show all and every type of event" from big to small, but over time I narrowed the focus to communities, groups, events, and helping people connect through them.<p>The initial Show HN gave me 150+ comments (surprising, looking back, given how terrible the plain Bootstrap UI was...) with a huge amount of useful feedback and feature requests. I've spent the time since then working through that, along with additional requests from groups using Radius, and it finally feels ready for a proper relaunch.<p>I've also recently added "Activities" [3] - which are lightweight events, independent of groups, intended to help people find others to do things with - for example:<p>> John is going for a cycle and a coffee in New York at 10am<p>People can join and vote for a time that works for them.<p>I've got a bunch of ideas for where to go next with this, including things like open sourcing and federation, but those are for another day!<p>Any feedback would be greatly appreciated!<p>P.S. it's built with Ruby on Rails, for those interested. I highly suspect it would have taken me 2 more years to get to this point without Rails!<p>[1] <a href="https://radius.to/" rel="nofollow">https://radius.to/</a><p>[2] <a href="https://news.ycombinator.com/item?id=40717398">https://news.ycombinator.com/item?id=40717398</a><p>[3] <a href="https://radius.to/documentation/activities/post-an-activity" rel="nofollow">https://radius.to/documentation/activities/post-an-activity</a>
Show HN: Radius – A Meetup.com Alternative
Hello HN!<p>I'm relaunching Radius [1] - far too long after the original Show HN [2] (I'll blame the day job for that).<p>Radius started out from my frustration with not knowing what was going on around me. The initial plan was to "show all and every type of event" from big to small, but over time I narrowed the focus to communities, groups, events, and helping people connect through them.<p>The initial Show HN gave me 150+ comments (surprising, looking back, given how terrible the plain Bootstrap UI was...) with a huge amount of useful feedback and feature requests. I've spent the time since then working through that, along with additional requests from groups using Radius, and it finally feels ready for a proper relaunch.<p>I've also recently added "Activities" [3] - which are lightweight events, independent of groups, intended to help people find others to do things with - for example:<p>> John is going for a cycle and a coffee in New York at 10am<p>People can join and vote for a time that works for them.<p>I've got a bunch of ideas for where to go next with this, including things like open sourcing and federation, but those are for another day!<p>Any feedback would be greatly appreciated!<p>P.S. it's built with Ruby on Rails, for those interested. I highly suspect it would have taken me 2 more years to get to this point without Rails!<p>[1] <a href="https://radius.to/" rel="nofollow">https://radius.to/</a><p>[2] <a href="https://news.ycombinator.com/item?id=40717398">https://news.ycombinator.com/item?id=40717398</a><p>[3] <a href="https://radius.to/documentation/activities/post-an-activity" rel="nofollow">https://radius.to/documentation/activities/post-an-activity</a>
Show HN: I wrote a custom assembler for CHIP-8 in C++
I'm writing a custom assembler for CHIP-8 and just finished adding support for the DB/.byte directive so I can embed sprites in the ROM and finally get something drawn on the screen. It SHOULD support all OG CHIP-8 instructions, but still a ton of rough edges that I'm ironing out.<p>This is my first ever C++ project, just like the CHIP-8 emulator was my first ever C (and emudev) project. It's so satisfying to write assembly and have your program spit out a ROM that actually runs in the emulator you wrote.<p>All code is written by me (a lot of it livestreaming) as evident by the quality, no AI.
Show HN: CUA-S1 – A System One Model for Computer Use
Hello HN! We're Dillon and Francesco from Cua.<p>We were wondering how many computer use tasks actually need a full general purpose LLM (e.g. gpt-6-astra, claude-opus-5 etc.) to think through all their decisions and steps. Some tasks require thinking about a plan, exploring different paths, recovering from failure. Other tasks are a question of making local decisions, like this value should go in this box, or should I check this box, or this element should be ignored.<p>We wondered how far we could go with a small model trained to only make these kinds of decisions.<p>Our inspiration was Typesafe's Jev and its System One Model framing. This is a nod to the dichotomy between thinking quickly, automatically, and intuitively (system 1) vs. thinking slowly, analytically (system 2), as described by Daniel Kahneman.<p>The interesting question for us was: what happens if you give a model an interface of current context, and a set of possible choices, and you ask it to return a probability for each choice? This kind of model does not generate output token by token like most LLMs do, but rather scores the options you give it, which you can check, trust, and use to drive your app's behavior.<p>CUA-S1 is our answer for narrow, specialized decision models for computer use. Our first release is CUA-S1-FORMS. We built this from ideas and code in jevlike, and then trained a second model just to handle form interactions. It has 706k parameters, and the original checkpoint is 2.8 MB.<p>The first training iteration took less than 30 minutes on synthetic data. Given a set of structured elements and values extracted from a document, it predicts whether to use the given value, CHECK, CLICK, or SKIP for each element. It does not predict new values for text fields, and does not consider screenshots. Element decisions are scored together, and your code can order the actions, and Cua Driver will execute them one at a time.<p>A first evaluation of this specialist vs. hosted Jev on our form task:<p>- For the whole decision set: 99.7% correct vs 83.6%.<p>- For the subset of steps that require an action: 100% correct vs 96%.<p>- For the subset of steps that are just leaving already-filled fields alone: 100% correct vs 74%.<p>The specialist was trained specifically for this task and convention (just press skip for already filled boxes), while hosted Jev has not been fine-tuned for it, so this is an experiment in scoped specialization.<p>We measured 7-9 ms to score a form locally vs. 260-280 ms per call to hosted Jev including network latency, though those samples measure different things and are not end-to-end form completion times.<p>Our interest here is in the space between a brittle script and a general agent loop. The content and layout of form fields vary enough that scripts get unwieldy, but the set of available decisions can remain narrow and well scoped. We want to explore the possibility of a general agent encountering something novel, and passing well understood decisions over to specialists like this.<p>That is a direction we are looking into. The current release is for forms only. We're open sourced the synthetic data generation, training, evaluation, and Driver integration under libs/cua-s1 with an MIT license.<p>Comments welcome! Especially if you are building computer-use agents and have run into a recurring decision that is too variable to script but is too narrow to call another LLM for.
Show HN: CUA-S1 – A System One Model for Computer Use
Hello HN! We're Dillon and Francesco from Cua.<p>We were wondering how many computer use tasks actually need a full general purpose LLM (e.g. gpt-6-astra, claude-opus-5 etc.) to think through all their decisions and steps. Some tasks require thinking about a plan, exploring different paths, recovering from failure. Other tasks are a question of making local decisions, like this value should go in this box, or should I check this box, or this element should be ignored.<p>We wondered how far we could go with a small model trained to only make these kinds of decisions.<p>Our inspiration was Typesafe's Jev and its System One Model framing. This is a nod to the dichotomy between thinking quickly, automatically, and intuitively (system 1) vs. thinking slowly, analytically (system 2), as described by Daniel Kahneman.<p>The interesting question for us was: what happens if you give a model an interface of current context, and a set of possible choices, and you ask it to return a probability for each choice? This kind of model does not generate output token by token like most LLMs do, but rather scores the options you give it, which you can check, trust, and use to drive your app's behavior.<p>CUA-S1 is our answer for narrow, specialized decision models for computer use. Our first release is CUA-S1-FORMS. We built this from ideas and code in jevlike, and then trained a second model just to handle form interactions. It has 706k parameters, and the original checkpoint is 2.8 MB.<p>The first training iteration took less than 30 minutes on synthetic data. Given a set of structured elements and values extracted from a document, it predicts whether to use the given value, CHECK, CLICK, or SKIP for each element. It does not predict new values for text fields, and does not consider screenshots. Element decisions are scored together, and your code can order the actions, and Cua Driver will execute them one at a time.<p>A first evaluation of this specialist vs. hosted Jev on our form task:<p>- For the whole decision set: 99.7% correct vs 83.6%.<p>- For the subset of steps that require an action: 100% correct vs 96%.<p>- For the subset of steps that are just leaving already-filled fields alone: 100% correct vs 74%.<p>The specialist was trained specifically for this task and convention (just press skip for already filled boxes), while hosted Jev has not been fine-tuned for it, so this is an experiment in scoped specialization.<p>We measured 7-9 ms to score a form locally vs. 260-280 ms per call to hosted Jev including network latency, though those samples measure different things and are not end-to-end form completion times.<p>Our interest here is in the space between a brittle script and a general agent loop. The content and layout of form fields vary enough that scripts get unwieldy, but the set of available decisions can remain narrow and well scoped. We want to explore the possibility of a general agent encountering something novel, and passing well understood decisions over to specialists like this.<p>That is a direction we are looking into. The current release is for forms only. We're open sourced the synthetic data generation, training, evaluation, and Driver integration under libs/cua-s1 with an MIT license.<p>Comments welcome! Especially if you are building computer-use agents and have run into a recurring decision that is too variable to script but is too narrow to call another LLM for.
Show HN: CUA-S1 – A System One Model for Computer Use
Hello HN! We're Dillon and Francesco from Cua.<p>We were wondering how many computer use tasks actually need a full general purpose LLM (e.g. gpt-6-astra, claude-opus-5 etc.) to think through all their decisions and steps. Some tasks require thinking about a plan, exploring different paths, recovering from failure. Other tasks are a question of making local decisions, like this value should go in this box, or should I check this box, or this element should be ignored.<p>We wondered how far we could go with a small model trained to only make these kinds of decisions.<p>Our inspiration was Typesafe's Jev and its System One Model framing. This is a nod to the dichotomy between thinking quickly, automatically, and intuitively (system 1) vs. thinking slowly, analytically (system 2), as described by Daniel Kahneman.<p>The interesting question for us was: what happens if you give a model an interface of current context, and a set of possible choices, and you ask it to return a probability for each choice? This kind of model does not generate output token by token like most LLMs do, but rather scores the options you give it, which you can check, trust, and use to drive your app's behavior.<p>CUA-S1 is our answer for narrow, specialized decision models for computer use. Our first release is CUA-S1-FORMS. We built this from ideas and code in jevlike, and then trained a second model just to handle form interactions. It has 706k parameters, and the original checkpoint is 2.8 MB.<p>The first training iteration took less than 30 minutes on synthetic data. Given a set of structured elements and values extracted from a document, it predicts whether to use the given value, CHECK, CLICK, or SKIP for each element. It does not predict new values for text fields, and does not consider screenshots. Element decisions are scored together, and your code can order the actions, and Cua Driver will execute them one at a time.<p>A first evaluation of this specialist vs. hosted Jev on our form task:<p>- For the whole decision set: 99.7% correct vs 83.6%.<p>- For the subset of steps that require an action: 100% correct vs 96%.<p>- For the subset of steps that are just leaving already-filled fields alone: 100% correct vs 74%.<p>The specialist was trained specifically for this task and convention (just press skip for already filled boxes), while hosted Jev has not been fine-tuned for it, so this is an experiment in scoped specialization.<p>We measured 7-9 ms to score a form locally vs. 260-280 ms per call to hosted Jev including network latency, though those samples measure different things and are not end-to-end form completion times.<p>Our interest here is in the space between a brittle script and a general agent loop. The content and layout of form fields vary enough that scripts get unwieldy, but the set of available decisions can remain narrow and well scoped. We want to explore the possibility of a general agent encountering something novel, and passing well understood decisions over to specialists like this.<p>That is a direction we are looking into. The current release is for forms only. We're open sourced the synthetic data generation, training, evaluation, and Driver integration under libs/cua-s1 with an MIT license.<p>Comments welcome! Especially if you are building computer-use agents and have run into a recurring decision that is too variable to script but is too narrow to call another LLM for.
Show HN: LiveWorld – Every 24/7 YouTube live camera on one globe
Show HN: Aclif – Agent CLI framework: one grammar, canonical names across SaaS
Simple discovery of the provider's default schemas is possible without any credentials (since they are built into the binary). If you want it to fetch customizations of your specific instance, give it credentials to your org.<p>The repo has more details. <a href="https://github.com/agent-cli-framework/aclif" rel="nofollow">https://github.com/agent-cli-framework/aclif</a>