GradientJ
Build complex LLM applications fast and manage them at scale
What it does
GradientJ lets you build LLM-powered applications in minutes by describing them in natural language. Once built, our app lets you experiment with LLM prompts, upload proprietary data, regression test prompts in production, and fine-tune on your data.
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I have been working in AI space for a while now, first at FAANG with ML since 2021, then with LLM in start-ups since early 2023. I think LLM Application development is extremely iterative, more so than any other types of development. This is because to improve an LLM application performance (accuracy, hallucinations, latency, cost), you need to try various combinations of LLM models, prompt templates (e.g., few-shot, chain-of-thought), prompt context with different RAG architecture, different agent architecture, and more. There are thousands of possible combinations and you need a process…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Source: Product Hunt launch ↗
Launched alongside, May 2023
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In today's world, catchy headlines and articles often distract readers from the facts and relevant information. By utilizing OpenAI's language models, Boring Report processes sensationalist news articles, transforms them into the content you see, and helps readers focus on the essential details. We recently updated our iOS app experience, so any and all feedback would be appreciated. App Link: https://apps.apple.com/us/app/boring-report-news-by-ai/id644...
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