Alternatives
Products that do what IngaBoard does
A Simpler Way to Build Causal Diagrams.
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Directed acyclic graphs are muched discussed in comp-sci, but octopus appears to be the first reusable, turnkey, ready-to-wear, off-the-shelf implementation of a DAG for application development, in any language, that I'm aware of. This is remarkable because DAGs hit a sweet spot in the middle of the three common programming paradigms (OO, event-driven, functional). Let's have a DAG as the top-level structure of our applications. Data-fetching and onChange handlers live in DAG nodes, next to the data they act on. The UI flows out from the DAG with fine-grained reactivity. Our app state is…
2023 · github.com
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Creating high-quality scientific figures can be time-consuming and challenging, even though sketching ideas on paper is relatively easy. Furthermore, recreating existing figures that are not stored in formats preserving semantic information is equally complex. To tackle this problem, we introduce DeTikZify, a novel multimodal language model that automatically synthesizes scientific figures as semantics-preserving TikZ graphics programs based on sketches and existing figures. We also introduce a Monte Carlo Tree Search-based inference algorithm that enables DeTikZify to iteratively refine its…
2024 · github.com
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Hi HN! I'm Gabriel, the author of dep-tree (https://github.com/gabotechs/dep-tree), and I wanted to show off this tool and explain why it's being really useful at my current org for dealing with code complexity. I work at a startup where business evolves really fast, and requirements change frequently, so it's easy to end up with big piles of code stacked together without a clear structure, specially with tight deadlines. I made dep-tree [1] to help us maintain a clean code architecture and a logical separation of concerns between parts of the application, which is…
2024 · github.com
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2019 · clearbrain.com
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Made a tool to organize thoughts. Actually it is a mind tree, but in a more web-friendly form. It has pivoted from what I originally started building at evryca.com. Some years ago I got the idea of fractal conversation, instead of old-school tree/ladder-like comments. I wanted to see only comments related to the current level. I started making "something" with fractal comments. This "something" was a project discussion platform. But it turned out that even I myself don't use it, and the idea of fractal comments stuck there unused. And recently it dawned on me that it may be a…
2022 · evryca.com
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ThoughtDAG indexes local agent conversations across tools, finds the turns relevant to your work, and turns them into editable context graphs.
23d ago · chenxiachan.github.io
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2015 · en.arguman.org
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2024 · medium.com
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Turn codebases into interactive maps, graphs, and governance
Jul 2026 · dev-swat.com
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2014 · emergentmind.com
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Hey, HN Community! I'm a Brazilian software engineer, and my educational journey led to a significant discovery. During my master's degree, I often struggled to recall foundational concepts studied years earlier, which were crucial for my current studies. This challenge sparked a reevaluation of traditional note-taking and inspired the creation of cmaps.io. Human thinking is inherently associative, not linear. We often draw connections between learned concepts unconsciously. To leverage this natural process, making these connections explicit is essential – and that's precisely what cmaps.io…
2023 · cmaps.io
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2020 · app.ilograph.com
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Together with a friend, we were developing a golf application. Our codebase grew rapidly and became split between multiple repositories: the iOS app, Android app, backend, front-end, and extra tooling. Both of us also work in larger scale-ups, and we saw the same problem: understanding large distributed codebases becomes progressively harder. Yay for microservices. It takes time to understand and answer questions like: - What calls this function? - What is the impact of changing this interface? - Is this code actually reachable and used? Not a secret that both of us embrace the leverage AI…
Jul 2026 · github.com
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2021 · gleek.io
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Everything that would be here is in the README. I hope this gets big, it has tons of potential.
2013 · github.com
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2015 · omniflow.io
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2020 · github.com
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2020 · muzejs.org
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TLDR: A small, vendor-agnostic inference loop that turns token logprobs/perplexity/entropy into an extra pass and reasoning for LLMs. - Captures logprobs/top-k during generation, computes perplexity and token-level entropy. - Triggers at most one refine when simple thresholds fire; passes a compact “uncertainty report” (uncertain tokens + top-k alts + local context) back to the model. - In our tests on technical Q&A / math / code, a small model recovered much of “reasoning” quality at ~⅓ the cost while refining ~⅓ of outputs. I kept seeing “reasoning” models behave…
2025 · github.com
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2024 · columns.ai
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Jul 2026 · github.com
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2015 · david-peter.de
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