growthbook VS jina

Why did we choose GrowthBook?

I would not adopt a platform that did not support exclusions. I think you should create a marketing page explaining the ways you are superior to the competition. Right now I would pick https://www.growthbook.io/

Seems that no-one mentioned my favorite feature flagging + A/B testing open source tool: https://www.growthbook.io/

Currently have the task of spiking a technical setup for A/B testing within our team application. I've already been looking at Growthbook and react-ab-test, what other tools / sources of info do people normally reach for in their own experience?

What are the differences to Flagr, GrowthBook or Flagsmith?

I work in the marketing analytics field, so I'm not that deep into product (even though I'm dabbling and will jump at the opportunity when one presents itself). Feature flags are being used to roll out experiments. Essentially, you publish code/experiments to the app source code, and based on the flag it shows a control or variant. The flag is fetched from a server and the rollout can easily be disabled if issues crop up. https://www.growthbook.io/ is an open-source tool that seems to be getting a bit of traction.

Jina mainly because of their use of neural networks and AI.

Jina - It’s an open-source project where you can build search engines. Well maybe not no code but it claims that you only need a few lines of code for creating projects. The project supports semantic, text, image, audio, and video search. What I’m also interested in is with their neural search and generative AI. I’m also interested in the amount of github repo that they have. I have this on my radar since this is also something I was interested in.

Do you guys have any ideas how we can match images on our database? We’re working on a project that about matching images on our database. We were trying to use SIFT and some other similar methods, but for some reason, nothing doesn’t seem to be working that well. Does anyone have any suggestions for the most effective way to do this? Maybe some open-source solutions like HuggingFace or Jina AI? We just want to make sure our image matching is correct and that part’s been a bit of a struggle on our part.

The tech lets you find 3D models without sifting through tons of text - An information retrieval framework does the heavy lifting and compares models to each other, no descriptions or keywords needed.

Jina AI -They offer a neural search solution that can help build smarter, more efficient search engines. They also have a list of cool github repos that you can check out. Similar to Vertex AI, they have image classification tools, NLPs, fine tuners etc.

Well, it's not exactly a new feature, but we've been working on early support for DocArray v2 in Jina.

Jina let’s you serve all of your models through the same Gateway while deploying them as individual microservices. You can also tie your models together in a pipeline if needed. Also some nice ML focussed features such as dynamic batching.