Since we work extensively with Dockerfiles to enable smooth deployment of our user's projects at work, I had the chance to spend a day comparing the latest AI models to understand their efficiency.
TL;DR:
- If you have time: iterate with GPT-4o-mini, you will have almost the same results as the bigger models for wayyyy cheaper
- Claude 3.5 Sonnet is on top, as usual
- I've created a CLI tool if you want to easily generate a Dockerfile for your project
Watson AI: Open Source Meeting Assistant
I've built Watson AI, an open-source tool that makes meetings more productive. It:
Records your system audio and microphone
Transcribes the meeting in real-time
Summarizes the discussion
Extracts action items
Key benefits:
Save time on note-taking
Never miss important details
Easily share outcomes with your team
It's open source, so you can customize it to your needs.
GitHub repo: www.github.com/latentdream/watson.ai
What do you think? How do you handle meeting notes?
We've developed a free, open-source alternative to TestStand for running various Python tests (Pytest, Python scripts). Easily import Pytest projects and Python scripts, visualize their output, and add logic to them. We also provide a visual programming interface with support for SCPI and the most popular instrument brands (NI, Keysight, Tektronix, Rhode & Schwarz, etc.).
We're seeking beta users and feedback to enhance this desktop app's utility. It's completely free! In particular, we're interested in hearing how this early version of Flojoy compares to LabVIEW and TestStand.
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