Category: Open source
-
Comparing NotebookLM with Open NotebookLM
This post compares Google’s NotebookLM with the open-source Open NotebookLM. While NotebookLM impresses with its detailed output, Open NotebookLM lags behind in performance. However, I think I probably still prefer Open NotebookLM due to its potential for local use, addressing concerns about Google’s product longevity and data privacy.
-
Open NotebookLM is the open-source version of Google’s NotebookLM
Open NotebookLM is an open-source version of Google’s NotebookLM, which converts PDFs into podcast conversations.
-
Flux.1 for image creation
Flux.1 by Black Forest Labs is a new, open-source image generation model. Deeply rooted in the generative AI research community, our mission is to develop and advance state-of-the-art generative deep learning models for media such as images and videos, and to push the boundaries of creativity, efficiency and diversity… By making our models available to…
-
Improve online reading with Reader view in Firefox
This post describes the Reader View feature in Firefox, which allows users to read web pages in a clutter-free, distraction-free mode with customisable text and background settings, making it ideal for online reading.
-
Zettlr is an open-source writing platform for academics
I’ve always been fascinated with the tools people use to write (I should write a follow-up to that post), and over the last couple of years that interest has been focused on what I think of as . Your one-stop publication workbench. From idea to publication in one app: Zettlr accompanies you while writing your…
-
Automated page translation in Firefox
Firefox’s page translation feature allows users to translate web pages directly in the browser, ensuring privacy by running the language model locally. While the translations are not perfect, it’s a convenient option for simple browsing activities, without relying on cloud services or sending data to servers.
-
Defining open source AI
Open Source has proven immensely beneficial by removing barriers to learning, using, sharing and improving software systems. These benefits – autonomy, transparency, frictionless reuse, and collaborative improvement – are needed for AI. We need essential freedoms to build and deploy reliable, transparent AI systems. Currently, only a few models qualify as truly open source.