Artificial intelligence powered an autonomous cargo ship for an full 500 miles

As it done its just about 500-mile journey from Tokyo Bay to Ise Bay, Suzaka, a 749 Gross Ton vessel became the world’s initially industrial cargo ship to be navigated completely by artificial intelligence (A.I), Electrek claimed.

As the globe moves in the direction of transportation automation, vessels at sea are not currently being remaining powering. Earlier this 12 months, we documented a large ferry in Japan becoming navigated autonomously, and now a business cargo ship has also realized the identical feat. The latter has been probable by way of maritime navigational application designed by an Israeli startup.

Orca AI

Established by a pair of naval specialists in 2018, Orca AI aims to automate cargo transportation by combining onboard security programs with a host of sensors. Very last yr, we reported Orca AI’s collaboration with the Japanese delivery organization NYK Line which boasts a fleet of in excess of 800 vessels. As section of this collaboration, Orca AI set up its Computerized Ship Concentrate on Recognition System on Suzaka as component of a study demo previous 12 months. The info gathered all through the ship’s preceding voyages was applied to coach the A.I. 

Also collaborating in the trials was Designing the Long term of Entire Autonomous Ships (DFFAS), a consortium of some 30 Japanese businesses and the Nippon Foundation, doing work towards automating maritime transport. 

The voyage

For the voyage, Orca’s safety navigation method consisting of the 18 onboard cameras was set up on Suzaka to provide as a watchkeeper and provide actual-time data detection, monitoring, classification, selection estimation, and 360-diploma views all through the day at night time. A fleet operations heart in Tokyo retained a tab on all the info coming in from the ship. 

Suzaka commenced its voyage from Tokyo Bay, a single of the

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Heliogen, Inc. Announces Full Year 2021 Financial and Operational Results

PASADENA, Calif., March 29, 2022–(BUSINESS WIRE)–Heliogen, Inc. (“Heliogen” or the “Company”) (NYSE: HLGN), a leading provider of AI-enabled concentrated solar energy, today announced full year 2021 financial and operational results.

Full-Year 2021 Highlights

  • Finalized $39 million U.S. Department of Energy award for deployment of AI-enabled concentrated solar technology

  • Completed first field test of autonomous robots designed to reduce installation and maintenance costs

  • Announced start of equipment procurement for first commercial-scale facility collaboration with Woodside Energy to deploy Heliogen’s power technology

  • Held successful demonstration of green hydrogen production using the Company’s core concentrated solar technology in partnership with Bloom Energy

  • Closed business combination with Athena Technology Acquisition Corp. (“Athena”); began trading on the NYSE on December 31, 2021

Recent Highlights

  • Began site preparation and setup for first full-scale manufacturing facility in Long Beach, California

  • Awarded exclusive lease rights to Brenda Solar Energy Zone by the U.S. Bureau of Land Management for the purposes of green hydrogen production

Executive Commentary

“Our mission is bold but simple,” said Bill Gross, Founder and Chief Executive Officer of Heliogen. “We aim to decarbonize heavy industry, using artificial intelligence, scalable, repeatable manufacturing techniques, and the power of the sun. Our patented closed-loop tracking system for our mirrors will allow us to generate temperatures up to 1,000 degrees Celsius, and efficiently store that heat to create industrial process steam, power and green hydrogen – without the intermittency problems of other renewable energy sources.”

Heliogen Progress in 2021 Continues into 2022

During 2021, Heliogen launched negotiations regarding deployment of its AI-enabled solar energy systems, and began engineering work on one of its first commercial scale facilities. The Company also continued to develop its infrastructure and set the foundation for its commercial-scale operations, to support its prospective project pipeline.

“The past year has been

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TPG RE Finance Trust, Inc. Reports Operating Results for the Fourth Quarter and Full Year Ended December 31, 2021

NEW YORK, February 22, 2022–(BUSINESS WIRE)–TPG RE Finance Trust, Inc. (NYSE: TRTX) (“TRTX” or the “Company”) reported its operating results for the fourth quarter and full year ended December 31, 2021.


  • Generated GAAP net income attributable to common stockholders of $41.4 million, or $0.51 per diluted common share based on a diluted weighted average share count of 82.0 million common shares, and book value per common share on December 31, 2021 of $16.37, an increase of $0.22 over the prior quarter.

  • Declared on December 13, 2021 a cash dividend of $0.24 per share of common stock and a non-recurring special cash dividend of $0.07 per share of common stock. The full cash dividend of $0.31 was paid on January 25, 2022 to common stockholders of record as of December 29, 2021. The Company paid on December 30, 2021, to stockholders of record as of December 20, 2021, a quarterly dividend on the Company’s 6.25% Series C Cumulative Redeemable Preferred Stock (“Series C Preferred Stock”) of $0.3906 per share.

  • Originated 10 first mortgage loans with total loan commitments of $651.6 million, an aggregate initial unpaid principal balance of $564.5 million, a weighted average credit spread of 3.77%, a weighted average interest rate floor of 0.10% and a weighted average loan-to-value ratio of 72.3%.

  • Received loan repayments of $428.1 million, including six full loan repayments totaling $420.9 million.

  • The weighted average risk rating of the Company’s loan portfolio improved to 3.0 as of December 31, 2021, compared to 3.1 in the preceding quarter.

  • Reduced the Company’s CECL reserve at quarter-end by $8.8 million, to $46.2 million or 85 basis points of total loan commitments, down from $55.0 million or 103 basis points as of September 30, 2021.

  • Sold a 17 acre undeveloped land parcel at

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