This adorable sea lion has to eat five to eight percent of its body weight every day to stay healthy and hydrated. Breakthroughs, discoveries, and DIY tips sent six days a week. Over the long and complicated course of evolutionary history, mammals independently turned towards water to make a home multiple times. While many of the warm-blooded animals that abandoned dry land for a watery habitat no longer exist, we still have plenty of stunning examples: Think dolphins, whales, manatees, porpoises. There's even a whole suborder of carnivores called the pinnipeds, which includes seals, sea lions, and walruses who move between land and water.

The audio, etched onto a plastic disc in 1949, predates the era when researchers could even recognize whale calls. Breakthroughs, discoveries, and DIY tips sent six days a week. In 1970, a single record would change history.

Environment Animals Wildlife Whales Hawaii's short-finned pilot whales eat over 77,000 squid a year Breakthroughs, discoveries, and DIY tips sent every weekday. The black marine mammals with bulbous heads primarily feed on the cephalopods and some small amounts of fish. But just how much squid do they eat? New estimates suggest that individual Hawaiian short-finned pilot whales eat between 82 and 202 squid per day. The findings are detailed in a study published today in the and could help local conservation efforts.

Effective monitoring of whale populations is critical for conservation, but traditional survey methods are expensive and difficult to scale. While prior work has shown that whales can be identified in very high-resolution (VHR) satellite imagery, large-scale automated detection remains challenging due to a lack of annotated imagery, variability in image quality and environmental conditions, and the cost of building robust machine learning pipelines over massive remote sensing archives. We present a semi-automated approach for surfacing possible whale detections in VHR imagery using a statistical anomaly detection method that flags spatial outliers, i.e. "interesting points". We pair this detector with a web-based labeling interface designed to enable experts to quickly annotate the interesting points. We evaluate our system on three benchmark scenes with known whale annotations and achieve recalls of 90.3% to 96.4%, while reducing the area requiring expert inspection by up to 99.8% -- from over 1,000 sq km to less than 2 sq km in some cases. Our method does not rely on labeled training data and offers a scalable first step toward future machine-assisted marine mammal monitoring from space. We have open sourced this pipeline at https://github.com/microsoft/whales.

As Artificial Intelligence (AI) has developed rapidly over the past few decades, the new generation of AI, Large Language Models (LLMs) trained on massive datasets, has achieved ground-breaking performance in many applications. Further progress has been made in multimodal LLMs, with many datasets created to evaluate LLMs with vision abilities. However, none of those datasets focuses solely on marine mammals, which are indispensable for ecological equilibrium. In this work, we build a benchmark dataset with 1,423 images of 65 kinds of marine mammals, where each animal is uniquely classified into different levels of class, ranging from species-level to medium-level to group-level. Moreover, we evaluate several approaches for classifying these marine mammals: (1) machine learning (ML) algorithms using embeddings provided by neural networks, (2) influential pre-trained neural networks, (3) zero-shot models: CLIP and LLMs, and (4) a novel LLM-based multi-agent system (MAS). The results demonstrate the strengths of traditional models and LLMs in different aspects, and the MAS can further improve the classification performance. The dataset is available on GitHub: https://github.com/yeyimilk/LLM-Vision-Marine-Animals.git.

At the end of 2022, Vineyard Wind and Charles River Analytics began a collaboration aimed at further protecting marine mammals during the construction of the Vineyard Wind 1 project. Vineyard Wind, an 800-megawatt project located 15 miles off the coast of Martha's Vineyard, will generate electricity for more than 400,000 homes and businesses in the Commonwealth of Massachusetts, create 3,600 Full Time Equivalent (FTE) job years, save customers $1.4 billion over the first 20 years of operation, and is expected to reduce carbon emissions by more than 1.6 million metric tons per year, the equivalent of taking 325,000 cars off the road annually. Charles River Analytics is providing its Awarion artificial intelligence and computer vision technology to Vineyard Wind to help detect the presence of marine mammal, ship, and fishing gear using Electro-Optical and Infrared (EO/IR) video streams. Designed to deliver enhanced maritime situational awareness, these EO/IR methods provide much greater detail and resolution than radar, enabling superior detection probability and true autonomy. Awarion can be attached to both manned and unmanned marine vessels to deliver persistent autonomous lookout capabilities, as well as trajectory modeling and threat assessment.

Facial recognition technology is mostly associated with uses such as surveillance and the authentication of human faces, but scientists believe they've found a new use for it -- saving seals. A research team at Colgate University has developed SealNet, a database of seal faces created by taking pictures of dozens of harbor seals in Maine's Casco Bay. The team found the tool's accuracy in identifying the marine mammals is close to 100%, which is no small accomplishment in an ecosystem home to thousands of seals. The researchers are working on expanding their database to make it available to other scientists, said Krista Ingram, a biology professor at Colgate and a team member. Broadening the database to include rare species such as the Mediterranean monk seal and Hawaiian monk seal could help inform conservation efforts to save those species, she said.

The ocean swims in sounds, and a new AI tool could help scientists sift through all that noise to track and study marine mammals. This tool is called Deep Squeak, not because it measures the calls of dolphins. The researchers are now applying the technology to vast marine bioacoustics datasets. Given that much of the ocean is out of our physical reach, underwater sound can help us understand where marine mammals swim, their density and abundance, and how they interact with each other. Recordings of whale songs have already helped to identify an unknown population of blue whales in the Indian Ocean and a previously unknown species of beaked whales.

The ocean is swimming in sound, and a new artificial intelligence tool could help scientists sift through all that noise to track and study marine mammals. The tool is called DeepSqueak, not because it measures dolphin calls in the ocean underworld, but because it is based on a deep learning algorithm that was first used to categorize the different ultrasonic squeals of mice. Now, researchers are applying the technology to vast datasets of marine bioacoustics. Given that much of the ocean is out of our physical reach, underwater sound could help us understand where marine mammals swim, their density and abundance, and how they interact with one another. Already, recordings of whale songs have helped identify an unknown population of blue whales in the Indian Ocean and a never-before-heard species of beaked whale.

The "Mayflower 400", the world's first intelligent ship, bobs gently in a light swell as it stops its engines in Plymouth Sound, off England's southwest coast, before self-activating a hydrophone designed to listen to whales. The 50-foot (15-metre) trimaran, which weighs nine tonnes and navigates with complete autonomy, is preparing for a transatlantic voyage. On its journey, the vessel, covered in solar panels, will study marine pollution and analyse plastic in the water, as well as track aquatic mammals. Eighty per cent of the underwater world remains unexplored. Brett Phaneuf, the co-founder of the charity ProMare and the mastermind behind the Mayflower project, said the ocean exerts "the most powerful force" on the global climate.