Latest stranger creatures spotted in marine

What is the newest deep sea creature discovered?

Fish Pyrolycus Jaco  

                   Pyrolycus jaco is the first eelpout species to be seen on the Jacó Scar methane seep, an extreme environment that exhibits hydrothermal vent-like characteristics, including elevated temperatures up to 5.2°C (41.4°F), which is several degrees warmer than the surrounding areas in the deep sea

Are there strange creatures in the ocean?

From monstrous crabs to goblins of the sea, there are some thrilling ocean dwellers out there. Here are some fascinating facts about some of the most mysterious animals in the sea. A massive crab that looks like a spider. No need to be scared, they usually sit around 1000 feet deep.

What is the new deep sea creature in the Indian Ocean?

Of the many species the scientists photographed aboard the RV Investigator, the deep-sea batfish made one of the biggest splashes across social media:

Batfishes have expansive, level heads and thin bodies and are covered with hard lumps and spines. A few animal categories have a prolonged, improved nose. Batfishes develop all things considered around 36 cm (14 inches) long. They are unfortunate swimmers and for the most part stroll on the base on thickened lamblike pectoral and pelvic blades.

What is the new animal in the ocean?

Named after two other entities this new species is—and one of them is Yoda! This odd, deep-sea animal is a type of acorn worm. Acorn worms live above or buried in the sea floor, where they feed on sediment or particles that settle on their bodies. They range in size from just 1 millimeter to over 2 meters long.

Yoda purpurata is a type of acorn worm found 2.5 km (around 1.5 miles) beneath the outer layer of the Atlantic Sea and was the first of the variety Yoda found. Going from 12 to 19 cm (4.7 to 7.5 in) long, it was named after the imaginary person Yoda from the Star Wars establishment.

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AI technologies are revolutionizing the agriculture industry

Artificial Intelligence (AI) has been making significant advancements in various fields, and agriculture is no exception. AI technologies are revolutionizing the agriculture industry, providing innovative solutions to improve productivity, efficiency, and sustainability. Here are some ways AI is being used in agriculture:

Precision Agriculture: AI is used to collect and analyze data from various sources like drones, satellites, and IoT sensors. This data helps farmers make informed decisions about irrigation, fertilization, and pest control. Precision agriculture ensures that resources are used efficiently, leading to higher yields and reduced environmental impact.

Crop Monitoring and Disease Detection: AI-powered systems can monitor crops in real-time using image recognition and computer vision technologies. They can identify early signs of diseases, nutrient deficiencies, and other issues, allowing farmers to take prompt actions and prevent large-scale crop losses.

Autonomous Farming Equipment: AI enables the development of autonomous tractors, harvesters, and other farming equipment. These machines can perform tasks more precisely, work 24/7, and reduce the need for human labor.

Crop Yield Prediction: AI models trained on historical data and environmental factors can predict crop yields for a given season. This information helps farmers plan their resources, logistics, and marketing strategies.

Climate and Weather Forecasting: AI algorithms can analyze historical weather patterns and provide more accurate short-term and long-term weather forecasts. This information is crucial for optimizing planting schedules and making decisions related to irrigation and pest control.

Robotics and Farm Automation: AI-powered robots are being used in agriculture to perform tasks such as planting, weeding, and harvesting. These robots can work autonomously and adapt to different terrains and crop types.

Livestock Monitoring: AI and IoT technologies are used to monitor livestock health and behavior. Sensors can track vital signs and detect early signs of illness, enabling timely veterinary intervention.

Market and Price Analysis: AI can analyze market trends, commodity prices, and consumer demand. This helps farmers make better decisions regarding crop selection and timing of sales to maximize profits.

Soil Health Assessment: AI-based soil analysis provides insights into soil quality, fertility, and nutrient levels. This information guides farmers in applying the right amount of fertilizers and soil amendments.

Supply Chain Optimization: AI algorithms optimize supply chain logistics, reducing waste and ensuring timely delivery of agricultural products to the market.

Conclusion

By leveraging AI technologies, agriculture is becoming more efficient, sustainable, and productive. However, it's essential to address challenges such as data privacy, integration with existing farming practices, and ensuring accessibility to small-scale farmers to maximize the benefits of AI in agriculture.