This is an edition of The Atlantic Daily, a newsletter that guides you through the biggest stories of the day, helps you discover new ideas, and recommends the best in culture. The tech world's most attention-grabbing man had a very busy week. Elon Musk launched a rocket, dealt with bad news at Tesla, stoked fear that AI could end humankind, and rolled out another controversial change on Twitter. Through it all, Musk exemplifies the danger of what happens when technology and ego collide. Earlier today, a SpaceX rocket exploded in the skies over the Gulf of Mexico, detonating itself after the booster failed to separate from the upper portion of the vehicle after launch.

In one experiment, the team used these methods to determine if radar signals from Earth's Global Navigation Satellite System (GNSS), which were reflected over the ocean and received by GNSS receivers located at towns offshore in the Gulf of Mexico, could be used to track hurricane evolution by measuring rising sea levels after landfall. Between 2020 and 2021, the team studied how seven storms, such as Hurricane Hana and Hurricane Delta, affected coastal sea levels before they made landfall in the Gulf of Mexico. By monitoring these complex changes, they found a positive correlation between higher sea levels and how intense the storm surges were.

Out in the deep waters of the Gulf of Mexico, a young woman named Rachel clings to the side of an oil rig. The wind whips her auburn hair into a wild tangle, and ocean spray drenches her jeans, but she climbs on, determined to uncover evidence of illegal drilling. When she arrives on board, however, she finds something far more sinister at play. This is a snippet of Oil and Darkness, a horror movie set on an oil rig. It features environmental activist Rachel, guilt-ridden rig foreman Jack, and shady corporate executive Ryan, who has been conducting dangerous research on a "new type of highly flammable oil." It's the kind of movie you could swear you caught the second half of once while late-night channel-hopping or dozed blearily through on a long-haul flight.

Out in the deep waters of the Gulf of Mexico, a young woman named Rachel clings to the side of an oil rig. The wind whips her auburn hair into a wild tangle, and ocean spray drenches her jeans, but she climbs on, determined to uncover evidence of illegal drilling. When she arrives on board, however, she finds something far more sinister at play. This is a snippet of Oil and Darkness, a horror movie set on an oil rig. It features environmental activist Rachel, guilt-ridden rig foreman Jack, and shady corporate executive Ryan, who has been conducting dangerous research on a "new type of highly flammable oil." It's the kind of movie you could swear you caught the second half of once while late-night channel-hopping or dozed blearily through on a long-haul flight.

Autonomous ships just took a small but important step forward. Hyundai's Avikus subsidiary says it has completed the world's first autonomous navigation of a large ship across the ocean. The Prism Courage (pictured) left Freeport in the Gulf of Mexico on May 1st, and used Avikus' AI-powered HiNAS 2.0 system to steer the vessel for half of its roughly 12,427-mile journey to the Boryeong LNG Terminal in South Korea's western Chungcheong Province. The Level 2 self-steering tech was good enough to account for other ships, the weather and differing wave heights. The autonomy spared the crew some work, of course, but it may also have helped the planet. Avikus claims HiNAS' optimal route planning improved the Prism Courage's fuel efficiency by about seven percent, and reduced emissions by five percent.

Deep learning is on the frontline in a new age of piracy, outwitting attacks with pre-emptive tech, explains Yarden Gross, CEO and co-founder of Orca AI. Almost a decade has passed since piracy raged off Somalia, and yet the danger posed by maritime hijackings is as present as ever. The global pandemic last year sparked a resurgence of attacks, with piracy incidents doubling across Asia, in a worrying uptick also seen in the Gulf of Mexico and West Africa. The fallout from coronavirus, including the loss of key security personnel, turned quarantined vessels into easy targets. This wave has since receded a little, with the International Maritime Bureau reporting a 44 per cent YoY dip in piracy and armed robbery incidents in 2021.

Traditional seismic processing workflows (SPW) are expensive, requiring over a year of human and computational effort. Deep learning (DL) based data-driven seismic workflows (DSPW) hold the potential to reduce these timelines to a few minutes. Raw seismic data (terabytes) and required subsurface prediction (gigabytes) are enormous. This large-scale, spatially irregular time-series data poses seismic data ingestion (SDI) as an unconventional yet fundamental problem in DSPW. Current DL research is limited to small-scale simplified synthetic datasets as they treat seismic data like images and process them with convolution networks. Real seismic data, however, is at least 5D. Applying 5D convolutions to this scale is computationally prohibitive. Moreover, raw seismic data is highly unstructured and hence inherently non-image like. We propose a fundamental shift to move away from convolutions and introduce SESDI: Set Embedding based SDI approach. SESDI first breaks down the mammoth task of large-scale prediction into an efficient compact auxiliary task. SESDI gracefully incorporates irregularities in data with its novel model architecture. We believe SESDI is the first successful demonstration of end-to-end learning on real seismic data. SESDI achieves SSIM of over 0.8 on velocity inversion task on real proprietary data from the Gulf of Mexico and outperforms the state-of-the-art U-Net model on synthetic datasets.

Every day, it seems that there is another innovation regarding how artificial intelligence can be used to do things humans couldn't do on their own. Several weeks ago, it was reported that scientists can now use AI to listen to conversations that dolphins are having with each other; an algorithm assists a research team go through millions of echolocation clicks made by these marine mammals found in the Gulf of Mexico.