Alternatives
Products that do what ATAR does
Retrofit AI weed detection for any boom sprayer.
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Hey HN! We’ve forked Jupyter Lab and added AI code generation features that feel native and have all the context about your notebook. You can see a demo video (2 min) here: https://www.tella.tv/video/clxt7ei4v00rr09i5gt1laop6/view Try a hosted version here: https://pretzelai.app Jupyter is by far the most used Data Science tool. Despite its popularity, it still lacks good code-generation extensions. The flagship AI extension jupyter-ai lags far behind in features and UX compared to modern AI code generation and understanding tools (like…
2024 · github.com
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I’m building a robot that can track nerf darts and shoot them out of the air. I’ve worked on other projects in robotics and object tracking (perception for self driving cars), but this has a whole different set of challenges. Nerf rival rounds travel at over 100 feet per second and shooting them out of the air requires aiming systems that are precise to less than half the width of a human hair and timing precision of 600 times faster than the blink of an eye. This is the first part of the series of me building the project (and my first video!) so I’d love to hear what you think!
2022 · youtube.com
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I built Axe because I got tired of every AI tool trying to be a chatbot. Most frameworks want a long-lived session with a massive context window doing everything at once. That's expensive, slow, and fragile. Good software is small, focused, and composable... AI agents should be too. Axe treats LLM agents like Unix programs. Each agent is a TOML config with a focused job. Such as code reviewer, log analyzer, commit message writer. You can run them from the CLI, pipe data in, get results out. You can use pipes to chain them together. Or trigger from cron, git hooks, CI. What Axe is: - 12MB…
Mar 2026 · github.com
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2024 · github.com
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2021 · cotl.com.au
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Write a task in plain English. An AI agent runs it on a simulator on your Mac and tells you if a real user could complete it. Save the successful run as a regression check you can replay later.
23d ago · app.deltix.ai
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Jun 2026 · github.com
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We’re open-sourcing a simple way to add “canary tools” to AI agents via MCP honeypots. These are functions your agent should never call during normal operation. If a canary is invoked, you get a high-fidelity signal of prompt-injection, tool hijacking, or lateralization—no heuristics, no extra model calls. What it is: - Go framework exposing decoy tools over MCP that look legitimate (names/params/descriptions), return safe dummy output, and emit telemetry when invoked. - Runs alongside your real tools; ship events to stdout/webhook or your pipeline (Prometheus/Grafana,…
Sep 2025
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