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Writesonic
Don't depend on just one AI checker No single checker can guarantee complete confidence. We integrate with leading AI content detectors to give unparalleled confidence that your content appears to be written by a human. One-click, Eight Checks Demo link story.screenspace.io/2161397443/0cb05324
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Content Guardian AI's answer:
Content Guardian is the first multi-AI Content Detector to connect to multiple content checker services simultaneously. 8 checks in 1 click.
Content Guardian AI's answer:
AI is a very fast-paced environment with new advances happening weekly. Not all AI Content Detector models can keep pace. This is where Content Guardian comes in. You can get a much higher level of assurance about the accuracy of the results as we check up to 8 checkers and provide an aggregate score based on our algorithm. We update this regularly so it is reflective of the latest developments in AI LLM.
Content Guardian AI's answer:
We have 3 target audiences. Writers, Media publishers and Education.
Content Guardian AI's answer:
Next.js PHP Javascritp Node.js
Content Guardian AI's answer:
Content Guardian was born out of necessity. We all work with external collaborators and we wanted to have confidence that the content was authentic and original.
We felt having to rely on one AI checker left the business open to a wider margin of risk that it was solely generated by AI, so we started to use multiple AI Content Checkers.
This became very cumbersome for the team, so we decided to create a tool that seamlessly integrates into our workflow whilst connecting to multiple AI Content Checkers. We wanted to build a tool that provides convenience and higher assurance that we can spot unauthentic content.
The tool is ready to be released to the wider world. So here it is!
We will be actively developing the tool with new features and tweaks to make it the best tool it can be.
Based on our record, Medium seems to be more popular. It has been mentiond 2231 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Binarized on the fly during the forward pass and never used for the inference process. In this case there are two areas to optimize for: training efficiency and inference efficiency. If I understand correctly, it stores the weights, gradients and second-moment estimates in FP32 like every other mixed-precision training (the Gopher paper has details on why storing them in FP32 is important), and quantized weights... - Source: Hacker News / 1 day ago
Related: https://medium.com/@maciej.pocwierz/how-an-empty-s3-bucket-can-make-your-aws-bill-explode-934a383cb8b1. - Source: Hacker News / about 23 hours ago
I was thinking of that a few weeks ago and wrote a (dumb) little story about it; I imagined Astro (SF mascot) is a ruthless mob boss controlling it all behind the scenes lol https://medium.com/@dannyisaphantom/benioff-astro-and-the-art-of-the-deal-692149f5dd36. - Source: Hacker News / 1 day ago
Thanks for sharing, I like the approach and it makes a lot of sense for the problem space. Especially using existing products vs building/hosting your own. I was however tripped up by this sentence close to the beginning: > we encountered a significant challenge with RAG: relying solely on vector search (even using both dense and sparse vectors) doesn’t always deliver satisfactory results for certain queries. Not... - Source: Hacker News / 1 day ago
This is a better one: https://medium.com/@lordmoma/so-you-think-you-know-git-673f9c4b0792. - Source: Hacker News / 5 days ago
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