Do The Digital Worm πŸ›

Step 1: recreate the brain of the C. elegans worm as a neural network 🧠

Step 2: ask it to park a car πŸš—

Researchers digitized the worm brain, the only fully mapped brain we have, with a 12 neuron network. The goal of this exercise was to create a neural network that humans can understand and parse since the organic version it is based on is well understood. πŸ—Ί

An interesting realization that came out of this exercise: πŸ‘‡

Curiously, both the AI model and the realΒ C. elegansΒ neural circuit contained two neurons that seemed to be acting antagonistically, he saidβ€”when one was highly active, the other wasn’t.

I wonder when this switching neuron feature will be rolled into an AI/ML/DL architecture. πŸ€”

Src: Motherboard

Saving the Fish 🐠

ATLAN Space is doing some awesome work in the conservation space. They’re rolling out a pilot project in the Seychelles using AI-powered drones. πŸ›Έ

The drones will:

  • Determine what type of vessel a boat is
  • Determine whether the boat is in a protected marine area
  • Determine if it is an authorized fishing vessel
  • If the vessel hits the illegal jackpot the drone will:
  • Note the vessel’s location
  • Count the number of people onboard
  • Note the ID number
  • Notify authorities

Sounds like the Coast Guard is about to get some team members. 🚁

Src: CNN

AI 4 Elephants 🐘

The Elephant Listening Project is now using AI to analyze their trove of audio to recognize forest elephants. This allows conservationists to better estimate population numbers and track the animals through unique voice signatures. πŸ‘‚

The ELP is also using AI to pick out illegal poaching noises in the audio, like gunshots, so they can alert authorities. And apparently they’re using image rec to flag online ads for poaching related products. 🚫

I love seeing how AI is being used for conservation and environmental causes. 🌎🌍🌏

Src: India Times

AI Vineyards 🍷

A really cool look at how machine learning is being used by Australian vineyards to predict seasonal yield and monitor their crops throughout the year. πŸ‡

The big takeaway: 🀯

This proves how technology allows a 45-hectare land to be surveyed in 15 minutes and have the data ready a day later.

I wonder if systems like this could lead to more sustainable farming practices? πŸ€”

Src: OpenGov

What’s That Animal? πŸ˜πŸ¦πŸƒ

Snapshot Serengeti is investigating the use of deep learning image recognition to sift through their trove of 3.2 million wildlife pictures from various camera traps. This is an AI researcher/engineer’s dream data set, there is just so much. πŸ“Š

So what can this model do? πŸ”

Not only does the artificial intelligence system tell you which of 48 different species of animal is present, but it also tells you how many there are and what they are doing. It will tell you if they are eating, sleeping, if babies are present, etc.

And why does it matter? πŸ“Έ

We estimate that the deep learning technology pipeline we describe would save more than eight years of human labeling effort for each additional 3 million images.

This could be a huge development for wildlife protection/preservation efforts and the first instance of AI being used to help us protect our environment and planet, which is rather important if you ask me. 🌍

Src: R&D Magazine

Bees are Zen, Care about Nothing 🐝

Bees have officially reached stage 3 of 4 in understanding the concept of zero. πŸŽ‰

Beginning to understand how bees learn and understand things, and potential transfer learning throughout the hive, could be really interesting for AI. I’ve been curious why we’re so focused on recreating human thought in machines, especially when we still seem to understand so little about how the squishy machines work. Ego I presume. πŸ’ž

Recreating and turbocharging intelligences found in nature, like bee hives or ant colonies, could yield very interesting results. And result in novel solutions to various problems. πŸ”

Src: The Conversation