IBM AI boat to commemorate historic US Mayflower voyage finally lands… in Canada

Nearly two years late and in the wrong country, we welcome our robot overlords

IBM's self-sailing Mayflower Autonomous Ship (MAS) has finally crossed the Atlantic albeit more than a year and a half later than planned. Still, congratulations to the team.

That said, MAS missed its target. Instead of arriving in Massachusetts – the US state home to Plymouth Rock where the 17th-century Mayflower landed – the latest in a long list of technical difficulties forced MAS to limp to Halifax in Nova Scotia, Canada. The 2,700-mile (4,400km) journey from Plymouth, UK, came to an end on Sunday.

The 50ft (15m) trimaran is powered by solar energy, with diesel backup, and said to be able to reach a speed of 10 knots (18.5km/h or 11.5mph) using electric motors. This computer-controlled ship is steered by software that takes data in real time from six cameras and 50 sensors. This application was trained using IBM's PowerAI Vision technology and Power servers, we're told.

ProMare, a non-profit organization which promotes maritime research and engineering, worked with IBM to develop the software's deep-learning models, which are said to be capable of recognizing and avoiding navigation hazards such as buoys, debris, other ships, icebergs, narwhals, and – we wonder – the kraken.

But the maritime bot's voyage did not go well. The plan had been to make the crossing in 2020 to mark 400 years since the Mayflower's historic voyage from England, but extended sea trials put paid to that ambition.

The voyage was attempted in 2021, and a mechanical fault ended its journey after three days. In April this year, the team sent the Mayflower back out to sea – to sail from Plymouth, UK, to Washington DC rather than Massachusetts in the US – but it broke down last month and had to be repaired.

Then a decision was made to divert the machine to the Canadian port of Halifax, where it's now chilling out.

The Mayflower almost every American schoolchild learns about was a 100ft (30m) triple-masted wooden vessel with canvas sails. It had a maximum speed of about three knots (5.5km/h or 3.4mph) and took more than two months to complete the legendary journey to Cape Cod. The ship carried 102 passengers and a crew of about 30. Cargo was said to include tools, food, and weapons, as well as some live animals, including dogs, sheep, goats, and poultry.

The robot Mayflower was hoped to help demonstrate that human-free, self-sailing ships are possible. Although the AI software appeared to work fine, it suffered mechanical issues with no one onboard to take care of them.

We therefore wondered last month if the question on the feasibility of autonomous ocean-crossing vessels had now been answered. But of course don't forget the human-free computer-controlled Saildrone Surveyor that crossed the Pacific from San Francisco to Hawaii last July, demonstrating ahead of the Mayflower's eventual success that it is possible. ®

Broader topics

Other stories you might like

  • IBM settles age discrimination case that sought top execs' emails
    Just days after being ordered to provide messages, Big Blue opts out of public trial

    Less than a week after IBM was ordered in an age discrimination lawsuit to produce internal emails in which its former CEO and former SVP of human resources discuss reducing the number of older workers, the IT giant chose to settle the case for an undisclosed sum rather than proceed to trial next month.

    The order, issued on June 9, in Schenfeld v. IBM, describes Exhibit 10, which "contains emails that discuss the effort taken by IBM to increase the number of 'millennial' employees."

    Plaintiff Eugene Schenfeld, who worked as an IBM research scientist when current CEO Arvind Krishna ran IBM's research group, sued IBM for age discrimination in November, 2018. His claim is one of many that followed a March 2018 report by ProPublica and Mother Jones about a concerted effort to de-age IBM and a 2020 finding by the US Equal Employment Opportunity Commission (EEOC) that IBM executives had directed managers to get rid of older workers to make room for younger ones.

    Continue reading
  • Is computer vision the cure for school shootings? Likely not
    Gun-detecting AI outfits want to help while root causes need tackling

    Comment More than 250 mass shootings have occurred in the US so far this year, and AI advocates think they have the solution. Not gun control, but better tech, unsurprisingly.

    Machine-learning biz Kogniz announced on Tuesday it was adding a ready-to-deploy gun detection model to its computer-vision platform. The system, we're told, can detect guns seen by security cameras and send notifications to those at risk, notifying police, locking down buildings, and performing other security tasks. 

    In addition to spotting firearms, Kogniz uses its other computer-vision modules to notice unusual behavior, such as children sprinting down hallways or someone climbing in through a window, which could indicate an active shooter.

    Continue reading
  • Cerebras sets record for 'largest AI model' on a single chip
    Plus: Yandex releases 100-billion-parameter language model for free, and more

    In brief US hardware startup Cerebras claims to have trained the largest AI model on a single device powered by the world's largest Wafer Scale Engine 2 chip the size of a plate.

    "Using the Cerebras Software Platform (CSoft), our customers can easily train state-of-the-art GPT language models (such as GPT-3 and GPT-J) with up to 20 billion parameters on a single CS-2 system," the company claimed this week. "Running on a single CS-2, these models take minutes to set up and users can quickly move between models with just a few keystrokes."

    The CS-2 packs a whopping 850,000 cores, and has 40GB of on-chip memory capable of reaching 20 PB/sec memory bandwidth. The specs on other types of AI accelerators and GPUs pale in comparison, meaning machine learning engineers have to train huge AI models with billions of parameters across more servers.

    Continue reading

Biting the hand that feeds IT © 1998–2022