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AI for Conservation / Feed

Artificial intelligence is increasingly being used in the field to analyse information collected by wildlife conservationists, from camera trap and satellite images to audio recordings. AI can learn how to identify which photos out of thousands contain rare species; or pinpoint an animal call out of hours of field recordings - hugely reducing the manual labour required to collect vital conservation data.

discussion

Looking for bird and bat audio datasets and related research for biodiversity AI project

Hi everyone,I'm working on a project funded by the PNRR and selected by NBFC, focused on tracking biodiversity in Italy, with potential expansion to other countries. The goal is...

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ICLR 2025

The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but...

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careers

Senior Firmware & Systems Engineer

Arribada is looking for a proactive Senior Firmware & Systems Engineer to join Arribada's experienced and passionate team of field conservationists and engineers. You will write and develop firmware and advise on...

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discussion

Thesis Collaboration

Hello everyone, I am an experienced Data Scientist and I am currently studying a second master in Environment Management (ULB - Belgium). I am currently looking for a master...

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Hi Simon,
Did you already contact INBO? Both biologging and citizen science are big themes at INBO. Last year we had a master thesis on camera trapping invasive muntjac. You can send me a private message for more info!

Hi Simon,

We're a biologging start-up based in Antwerp and are definitely open to collaborate if you're interested. We've got some programs going on with local zoo's. Feel free to send me a DM if you'd like to know more.

Hi Simon,
We (Reneco International Wildlife Consultants) have an ongoing collaboration with a local University (Abu Dhabi, UAE)  for developing AI tools (cameratrap/drone images and video analyses) and biomimetic robots applied to conservation (e.g  https://www.sciencedirect.com/science/article/pii/S1574954124004813 ). We also have a genetic team working on eDNA.    Field experience could be possible, in UAE or Morocco.
Feel free to write me back if you may be interested and would like to know more
 

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discussion

State of the art thermal imaging core and the zoo

First of all I would like to extend my thanks and gratitude to Minke Geense from Gaiazoo, Limburg, The Netherlands for making this test possible.I recently obtained a couple of...

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I would also be interested - looking at starting a project that need observation of large african animals with nocturnal habits... Holy grail with unlimited funding would be a grid of 100's of cameras :-)

@HeinrichS there’s still time for you or anyone else to make a funding submission to the wildlabs 2025 grants ❤️❤️❤️

I haven't applied for wildlabs funding, but I would love for others to apply that want to use my systems. My preference goes to those who want to use the most units :-)

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discussion

Which LLMs are most valuable for coding/debugging?

Hello! I'm curious to get folks' impressions on the most useful LLMs for helping with data analysis/debugging code? I've been using chatgpt, which is at times helpful and at times...

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When it comes to coding and debugging, several large language models (LLMs) stand out for their value. Here are a few of the most valuable LLMs for these tasks:

1. OpenAI's Codex: This model is specifically trained for programming tasks, making it excellent for generating code snippets, suggesting improvements, and even debugging existing code. It powers tools like GitHub Copilot, which developers find immensely helpful.

2. Google's PaLM: Known for its versatility, PaLM excels in understanding complex queries, making it suitable for coding-related tasks as well. Its ability to generate and refine code snippets is particularly useful for developers.

3. Meta's LLaMA: This model is designed to be adaptable and can be fine-tuned for specific coding tasks. Its open-source nature allows developers to customize it according to their needs, making it a flexible option for coding and debugging.

4. Mistral: Another emerging model that shows promise in various tasks, including programming. It’s being recognized for its capabilities in generating and understanding code.

These LLMs are gaining traction not just for their coding capabilities but also for their potential to streamline the debugging process, saving developers time and effort. If you want to dive deeper into the features and strengths of these models, you can check out the full article here: Best Open Source Large Language Models  LLMs

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discussion

What the mice get up to at night

Last night I set up the following rig to see if there were any mice in the kitchen at night. It consists of my StalkedByTheState smart camera trap system and a 640x512 resolution...

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And I see now they can walk vertically up walls like Spider-Man.


Walking up walls

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discussion

Ai for soil nutrient analysis

My team has observed that restoration practitioners seldom consider the health of soils at their restoration sites before seedlings are planted. They tend to witness mortalities...

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We'd love to see this added to The Inventory, our wiki-style databse of conservation tech tools, R&D projects, and organizations! Check out the user guide to learn more about how to add a page for your app. Give a shout with any questions!

Thank you for the comments. The app is not made available on the app or google store yet. It is applicable on android systems and does not need a high level skill to operate however one would need to be taught how to use the app and make meaning of the data. 

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careers

New PhD - Drones, seaweeds & climate change

A PhD opportunity for anyone interested in coastal drone surveys, seaweeds, climate change and the chance to do a whole bunch of different computer modelling including AI-driven species distribution modelling to assess...

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discussion

Pytorch Wildlife v5 detection in thermal

Hope everyone had a nice Christmas. I'd like to share my experiment with Pytorch Wildlife V5 and a high res (640x512) thermal core, connected to a Raspberry Pi 5. The thermal...

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I added plain old motion detection because megadetector v5 was not working well with the smaller rat images and in thermal.

This works really well:
 

Rat in thermal
 

Also, I can see really easily where the rat comes into the shed, see this series:

Before

Just visible

 

Just visible



Clearly visible.
 

Clearly visible

So now I have a way to build up a create thermal dataset for training :-)
 

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article

Horizon scan of AI in nature conservation

Comments on Reynolds, S.A et all (2024) 'The potential for AI to revolutionize conservation: a horizon scan'. A very interesting read, perhaps more for the discussion on negative effects of AI and consequences for the...

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Thank you for this excellent summary, Frank. I agree with you that not enough is being developed on the implementation side, which is what is needed most. Last year, I ...
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