布雷特·法納夫是一位健談的美國中年企業家,今年感恩節前幾天,他在位于英國普利茅斯的一家咖啡館里對“五月花號”(The Mayflower)的航程和人們風險認知的變化發表了自己的看法。這家咖啡館距離1620年9月清教徒登上“五月花號”的地點沒有多遠。
“當這些人踏上征途的時候,不僅沒有人能夠保證航行成功,甚至沒有人可以保證他們能夠活下來,但為了走向新世界,他們還是義無反顧的接受了這種巨大的風險,這一點讓我感到備受鼓舞。”法納夫說。
現在,法納夫打算追隨前人的腳步,踏上屬于自己的征程。
過去五年,法納夫領導的非營利機構——ProMare一直致力于打造一款通過油電混合發動機和太陽能電池板供能的無人駕駛船舶,希望其可以像過往的清教徒一樣,從英格蘭普利茅斯橫渡大西洋抵達美國馬塞諸塞州普利茅斯。如果成功,這艘以著名航海先驅“五月花號”命名的“五月花號自動駕駛船舶”(The Mayflower Autonomous Ship,簡稱“MAS”)就將成為第一艘橫渡大西洋的無人船舶。
在計劃重現“五月花號”冒險橫渡大西洋的場景之時,法納夫發現,當前的文化對于“風險規避”的執著已經到了不合邏輯的地步。他說:“就整體社會而言,我們真的已經完全喪失了思考風險的能力。”他表示,在涉及人工智能等新技術的監管時,尤其如此,并稱“這就是對自動化和自主化的偏見。”
同時,法納夫認為,當前水面上最大的危險其實是那些缺乏經驗的游船愛好者。
“但卻沒有人說要把他們給禁了。”他說。
自動駕駛船舶的發展前景
按照設想,法納夫的現代版“五月花號”將扮演試驗平臺的角色,測試船舶實現自動駕駛所需的各種技術。預計到2030年年末,在集裝箱運輸、研究和軍事等領域,此類船舶的市場規模將超過1600億美元。
法納夫出生于波士頓地區,十年前到英國工作,長期以來,他一直在與美、英兩國的監管機構就“由人工智能軟件控制的船舶應該遵守何種規則”進行討論。法納夫經營的一家名為Marine AI的公司就在開發此類軟件。另外兩家由他領導的公司M Subs Ltd.和Submergence Group則負責制造供美、英兩國海軍使用載人潛水器和無人潛水器。在他看來,由人工智能操控的無人船舶的風險要遠小于人類駕駛的船舶。但他也表示,大多數監管機構并不認同他的觀點。
船隊無人化有助于緩解未來的供應鏈中斷問題,更不用說還能夠為航運業節省數以百萬美元計的人工成本。在此背景下,馬士基(Maersk)、赫伯羅特(Happag-Lloyd)等諸多航運業巨頭紛紛攜手軟件、機器人初創公司,合作探索無人船舶的制造也就不足為奇了。作為船舶發動機的主要制造商之一,勞斯萊斯(Rolls-Royce)也在大力開發人工智能船舶。一艘名為“MV Yara Birkeland”的挪威無人集裝箱船從今年11月開始在奧斯陸郊外峽灣進行測試。日本最大的航運公司日本郵船(Nippon Yusen)計劃于明年2月派遣一艘無人集裝箱船從東京灣前往伊勢市,進行一趟全長236英里的沿海航行。
但就距離和冒險程度而言,目前大型航運企業提出的方案都無法與法納夫為MAS制定的計劃相提并論。為紀念“五月花號”出航400周年,這艘49英尺長(約14.9352米)的鋁制三體船本應在2020年完成自己的跨大西洋航行,但受新冠疫情影響,該船未能及時完工。直到今年6月,MAS才終于踏上了從英國普利茅斯前往美國的旅程。這趟航行預計需要花費三周時間。但在出海三天之后,由于排氣管破裂,混動發電機無法正常運轉,MAS被迫借助備用電源艱難駛回臨近英吉利海峽西部的錫利島,之后,被ProMare團隊用拖車拖回了普利茅斯。
“船舶故障在所難免,我們的船也不例外,但這是船的問題,而不是人工智能部件的問題。”法納夫聳肩說道。
法納夫不是一位輕言放棄的人。“我們不能因為一次挫折就否定整個項目。”他說。畢竟,“五月花號”在完成66天橫渡大西洋的壯舉之前,也曾經被迫掉頭返修,而且還是兩次。于是,法納夫重新設計了船舶的發動機,Promare則對船上搭載的大部分軟件進行了升級。截至目前,MAS已經花費Promare約120萬美元,眾多合作企業也為其提供了更多設備、付出了大量勞力。按照計劃,該團隊將于明年春季再次嘗試橫渡大西洋。但首先,這艘正在普利茅斯附近水域進行廣泛測試船只還將進行一場距離更遠的試航——直接駛往鹿特丹,按照計劃,MAS將于明年2月重返普利茅斯。
前途光明
從理論上講,相較于制造無人駕駛汽車,建造無人船舶應當更為容易。即便是繁忙的航道,大洋也不會像大多數城市道路或高速公路那樣擁擠。在談到MAS的首次橫渡嘗試時,法納夫說:“上一次,我們駛出了500英里的距離,沒有一艘船曾經出現在我們10英里以內的地方。”除進出港口時外,船舶航行相較汽車通常更為自由。此外,在大多數情況下,船舶的航行速度也比汽車慢得多,這就意味著人工智能系統將有更多的時間來識別潛在危險,進而采取機動措施來規避危險。
不過唐·斯科特認為,無人船舶也面臨著一些獨特的挑戰,比如訓練人工智能系統識別浮標、航道標志、船舶和蟹籠、浮木等漂浮于水面上的各種物體就頗為不易,再考慮到船舶經常要在巨浪中顛簸,還要經受雨霧天氣的洗禮,要拿出穩定表現更是難上加難。斯科特是一位身材高大、滿臉胡須的加拿大人,也是MarineAI公司的首席技術官,負責監督MAS上的軟件系統開發工作。為了解決上述問題,斯科特開發了一個標簽化的數據庫,其中包含數百萬張各種海洋物體在不同光線和天氣條件下的圖像。為記錄相關活動、為MAS的人工智能系統創建一套訓練數據,他在普利茅斯港周圍各處安裝了許多攝像頭和傳感器。
MAS現在仍然靜靜地停靠在普利茅斯的碼頭邊,造型令人印象深刻:主船體和舷外支架均設有反向船艏,能夠提高切浪效率,同時也讓整個船體看起來更具科幻感。主船體中部是由四根支柱撐起來的中央平臺,天線、雷達、傳感器和攝像頭均布局其上,極為搶眼。
在船體上一眼就可以看到IBM的標志——IBM很早就對這個項目產生了興趣,也是ProMare的主要技術合作伙伴。借助IBM提供的軟件,MAS能夠“看到”周圍的物體,并在既定航道上出現其他船舶時及時調整航向。這套決策系統是IBM基于其為銀行和保險公司提供的軟件開發而來。IBM還為MAS提供了許多可以運行人工智能軟件的計算機,省去了船舶與岸上數據中心來回傳輸信息的麻煩。對MAS而言,能夠在不消耗太多船上有限電力的情況下“就地處理”這些計算需求可以說是一項“基本要求”。(因為在航行途中,)MAS可能需要快速進行航行決策,而在大洋之中,蜂窩通信網絡顯然鞭長莫及,衛星連接也可能無法提供足夠的網速和帶寬,甚至可能完全沒有信號。
船上還備有一些能夠收集科學數據的計算機。相較于載人科考船隊,無人船舶可以在海上停留更長時間,成本也低出許多;相較于傳感器浮標,無人船舶自身配有推進系統,能夠自主航行,可以覆蓋更大的地理區域,因此,法納夫認為,無人船舶將能夠幫助人類增進對海洋的認識,這也是其一大優勢。
IBM的研究人員設計了三個科研項目,交由MAS在橫渡大西洋時執行。其一是“水聽器”,用于持續聆聽水下聲音,并將數據提供給經過訓練的軟件,識別鯨歌。其二是“超級味覺”(Hypertaste),這是一種“電子舌頭”傳感器,每隔15分鐘會對MAS周圍的水體進行一次采樣并分析其中的化學成分。相關數據將會用于對海洋酸化進行研究,而海洋酸化又與氣候變化有關,在氣候變化的過程中,隨著大氣中二氧化碳含量的增加,海洋也會吸收越來越多的二氧化碳,導致其酸性越來越強。其三是研究人員會利用船上攝像機拍攝的視頻,結合船上慣性傳感器的數據,對人工智能系統進行訓練,使其可以根據海浪的外形來預測海浪所攜帶的能量。也許有一天,此項研究將會幫助科學家們更好地利用視頻來了解發生風暴和侵蝕的可能性,同時也將幫助未來的人類在穿越大洋時找到最安全、最高效的航線。
在其他方面,IBM也有貢獻,該公司旗下的The Weather Company負責向MAS傳輸氣象數據,幫助后者確定橫渡大西洋的最佳路線。(作為回報,MAS也會將船上傳感器收集到的天氣數據回傳給岸上的研究人員。)The Weather Company的氣象預報人員也會和ProMare溝通,幫助后者找到最佳的天氣窗口,從而最大限度地提高MAS橫渡成功的概率。
試航
這是一個寒氣逼人,但風平浪靜、陽光明媚的午后,斯科特和我登上了普利茅斯港的一艘小型游艇,旁邊停著的就是MAS,二者之間由一條繩索相連。作為MAS項目的總工程師,24歲的馬特·肖正坐在駕駛室中,他打開筆記本電腦,點開一個顯示著MAS上各種儀器讀數的數字儀表盤,直接用Xbox手柄和藍牙網絡開始了遠程操作。與此同時,MAS從我們面前平穩駛過,繩索也在陽光的照射下閃耀著金光。謹慎起見,當地官員要求MAS在進出港口時必須有人控制,并且需要與一艘載人的船舶連接在一起。
到達港口入口之外的考桑灣(Cawsand Bay)指定測試區域后,我們就解開了繩索,只看馬特敲擊了一下鍵盤,MAS就像脫韁的野馬一樣,以6.8節(約每小時8英里)的速度在預先設定的航點之間開始了自由航行。“以這個速度航行時,MAS的能效比最高。”馬特介紹說。與此同時,作為MAS上各項科學實驗的負責人之一,IBM研究中心的軟件工程師詹姆斯·薩頓則坐在一旁,通過膝蓋上放著的筆記本電腦查看MAS上各種科學儀器的讀數。
游艇先是在MAS旁伴行,隨后超到MAS前方,穿過了MAS的航線。斯科特說:“我們這么做是為了確保傳感器能夠正常看到我們,同時確保防撞軟件可以正常工作。”由于有關部門實際上并不允許MAS在距離海岸這么近的地方完全自主行動,所以MAS不會偏離既定航線。但在岸上碼頭邊的一座低矮紅磚建筑里,ProMare的其他員工能夠實時監控MAS攝像頭拍到的內容和雷達數據,還可以看到在自主操作的情況下,MAS的“人工智能船長”會做出何種決定來避免發生碰撞。他們用無線電通知馬特一切正常。“這就是海上的真實情況,什么問題都沒有。”斯科特說。
政府海事機構的謹慎讓法納夫憤憤不已,在他看來這毫無必要。他說:“正是這種夸張的安全文化為非理性監管提供了理由,這種行為最終將會阻礙行業的發展。”雖然西渡的清教徒一路遭受了許多苦難,但至少沒有遭受過度海事監管的折磨。(財富中文網)
譯者:梁宇
審校:夏林
布雷特·法納夫是一位健談的美國中年企業家,今年感恩節前幾天,他在位于英國普利茅斯的一家咖啡館里對“五月花號”(The Mayflower)的航程和人們風險認知的變化發表了自己的看法。這家咖啡館距離1620年9月清教徒登上“五月花號”的地點沒有多遠。
“當這些人踏上征途的時候,不僅沒有人能夠保證航行成功,甚至沒有人可以保證他們能夠活下來,但為了走向新世界,他們還是義無反顧的接受了這種巨大的風險,這一點讓我感到備受鼓舞。”法納夫說。
現在,法納夫打算追隨前人的腳步,踏上屬于自己的征程。
過去五年,法納夫領導的非營利機構——ProMare一直致力于打造一款通過油電混合發動機和太陽能電池板供能的無人駕駛船舶,希望其可以像過往的清教徒一樣,從英格蘭普利茅斯橫渡大西洋抵達美國馬塞諸塞州普利茅斯。如果成功,這艘以著名航海先驅“五月花號”命名的“五月花號自動駕駛船舶”(The Mayflower Autonomous Ship,簡稱“MAS”)就將成為第一艘橫渡大西洋的無人船舶。
在計劃重現“五月花號”冒險橫渡大西洋的場景之時,法納夫發現,當前的文化對于“風險規避”的執著已經到了不合邏輯的地步。他說:“就整體社會而言,我們真的已經完全喪失了思考風險的能力。”他表示,在涉及人工智能等新技術的監管時,尤其如此,并稱“這就是對自動化和自主化的偏見。”
同時,法納夫認為,當前水面上最大的危險其實是那些缺乏經驗的游船愛好者。
“但卻沒有人說要把他們給禁了。”他說。
自動駕駛船舶的發展前景
按照設想,法納夫的現代版“五月花號”將扮演試驗平臺的角色,測試船舶實現自動駕駛所需的各種技術。預計到2030年年末,在集裝箱運輸、研究和軍事等領域,此類船舶的市場規模將超過1600億美元。
法納夫出生于波士頓地區,十年前到英國工作,長期以來,他一直在與美、英兩國的監管機構就“由人工智能軟件控制的船舶應該遵守何種規則”進行討論。法納夫經營的一家名為Marine AI的公司就在開發此類軟件。另外兩家由他領導的公司M Subs Ltd.和Submergence Group則負責制造供美、英兩國海軍使用載人潛水器和無人潛水器。在他看來,由人工智能操控的無人船舶的風險要遠小于人類駕駛的船舶。但他也表示,大多數監管機構并不認同他的觀點。
船隊無人化有助于緩解未來的供應鏈中斷問題,更不用說還能夠為航運業節省數以百萬美元計的人工成本。在此背景下,馬士基(Maersk)、赫伯羅特(Happag-Lloyd)等諸多航運業巨頭紛紛攜手軟件、機器人初創公司,合作探索無人船舶的制造也就不足為奇了。作為船舶發動機的主要制造商之一,勞斯萊斯(Rolls-Royce)也在大力開發人工智能船舶。一艘名為“MV Yara Birkeland”的挪威無人集裝箱船從今年11月開始在奧斯陸郊外峽灣進行測試。日本最大的航運公司日本郵船(Nippon Yusen)計劃于明年2月派遣一艘無人集裝箱船從東京灣前往伊勢市,進行一趟全長236英里的沿海航行。
但就距離和冒險程度而言,目前大型航運企業提出的方案都無法與法納夫為MAS制定的計劃相提并論。為紀念“五月花號”出航400周年,這艘49英尺長(約14.9352米)的鋁制三體船本應在2020年完成自己的跨大西洋航行,但受新冠疫情影響,該船未能及時完工。直到今年6月,MAS才終于踏上了從英國普利茅斯前往美國的旅程。這趟航行預計需要花費三周時間。但在出海三天之后,由于排氣管破裂,混動發電機無法正常運轉,MAS被迫借助備用電源艱難駛回臨近英吉利海峽西部的錫利島,之后,被ProMare團隊用拖車拖回了普利茅斯。
“船舶故障在所難免,我們的船也不例外,但這是船的問題,而不是人工智能部件的問題。”法納夫聳肩說道。
法納夫不是一位輕言放棄的人。“我們不能因為一次挫折就否定整個項目。”他說。畢竟,“五月花號”在完成66天橫渡大西洋的壯舉之前,也曾經被迫掉頭返修,而且還是兩次。于是,法納夫重新設計了船舶的發動機,Promare則對船上搭載的大部分軟件進行了升級。截至目前,MAS已經花費Promare約120萬美元,眾多合作企業也為其提供了更多設備、付出了大量勞力。按照計劃,該團隊將于明年春季再次嘗試橫渡大西洋。但首先,這艘正在普利茅斯附近水域進行廣泛測試船只還將進行一場距離更遠的試航——直接駛往鹿特丹,按照計劃,MAS將于明年2月重返普利茅斯。
前途光明
從理論上講,相較于制造無人駕駛汽車,建造無人船舶應當更為容易。即便是繁忙的航道,大洋也不會像大多數城市道路或高速公路那樣擁擠。在談到MAS的首次橫渡嘗試時,法納夫說:“上一次,我們駛出了500英里的距離,沒有一艘船曾經出現在我們10英里以內的地方。”除進出港口時外,船舶航行相較汽車通常更為自由。此外,在大多數情況下,船舶的航行速度也比汽車慢得多,這就意味著人工智能系統將有更多的時間來識別潛在危險,進而采取機動措施來規避危險。
不過唐·斯科特認為,無人船舶也面臨著一些獨特的挑戰,比如訓練人工智能系統識別浮標、航道標志、船舶和蟹籠、浮木等漂浮于水面上的各種物體就頗為不易,再考慮到船舶經常要在巨浪中顛簸,還要經受雨霧天氣的洗禮,要拿出穩定表現更是難上加難。斯科特是一位身材高大、滿臉胡須的加拿大人,也是MarineAI公司的首席技術官,負責監督MAS上的軟件系統開發工作。為了解決上述問題,斯科特開發了一個標簽化的數據庫,其中包含數百萬張各種海洋物體在不同光線和天氣條件下的圖像。為記錄相關活動、為MAS的人工智能系統創建一套訓練數據,他在普利茅斯港周圍各處安裝了許多攝像頭和傳感器。
MAS現在仍然靜靜地停靠在普利茅斯的碼頭邊,造型令人印象深刻:主船體和舷外支架均設有反向船艏,能夠提高切浪效率,同時也讓整個船體看起來更具科幻感。主船體中部是由四根支柱撐起來的中央平臺,天線、雷達、傳感器和攝像頭均布局其上,極為搶眼。
在船體上一眼就可以看到IBM的標志——IBM很早就對這個項目產生了興趣,也是ProMare的主要技術合作伙伴。借助IBM提供的軟件,MAS能夠“看到”周圍的物體,并在既定航道上出現其他船舶時及時調整航向。這套決策系統是IBM基于其為銀行和保險公司提供的軟件開發而來。IBM還為MAS提供了許多可以運行人工智能軟件的計算機,省去了船舶與岸上數據中心來回傳輸信息的麻煩。對MAS而言,能夠在不消耗太多船上有限電力的情況下“就地處理”這些計算需求可以說是一項“基本要求”。(因為在航行途中,)MAS可能需要快速進行航行決策,而在大洋之中,蜂窩通信網絡顯然鞭長莫及,衛星連接也可能無法提供足夠的網速和帶寬,甚至可能完全沒有信號。
船上還備有一些能夠收集科學數據的計算機。相較于載人科考船隊,無人船舶可以在海上停留更長時間,成本也低出許多;相較于傳感器浮標,無人船舶自身配有推進系統,能夠自主航行,可以覆蓋更大的地理區域,因此,法納夫認為,無人船舶將能夠幫助人類增進對海洋的認識,這也是其一大優勢。
IBM的研究人員設計了三個科研項目,交由MAS在橫渡大西洋時執行。其一是“水聽器”,用于持續聆聽水下聲音,并將數據提供給經過訓練的軟件,識別鯨歌。其二是“超級味覺”(Hypertaste),這是一種“電子舌頭”傳感器,每隔15分鐘會對MAS周圍的水體進行一次采樣并分析其中的化學成分。相關數據將會用于對海洋酸化進行研究,而海洋酸化又與氣候變化有關,在氣候變化的過程中,隨著大氣中二氧化碳含量的增加,海洋也會吸收越來越多的二氧化碳,導致其酸性越來越強。其三是研究人員會利用船上攝像機拍攝的視頻,結合船上慣性傳感器的數據,對人工智能系統進行訓練,使其可以根據海浪的外形來預測海浪所攜帶的能量。也許有一天,此項研究將會幫助科學家們更好地利用視頻來了解發生風暴和侵蝕的可能性,同時也將幫助未來的人類在穿越大洋時找到最安全、最高效的航線。
在其他方面,IBM也有貢獻,該公司旗下的The Weather Company負責向MAS傳輸氣象數據,幫助后者確定橫渡大西洋的最佳路線。(作為回報,MAS也會將船上傳感器收集到的天氣數據回傳給岸上的研究人員。)The Weather Company的氣象預報人員也會和ProMare溝通,幫助后者找到最佳的天氣窗口,從而最大限度地提高MAS橫渡成功的概率。
試航
這是一個寒氣逼人,但風平浪靜、陽光明媚的午后,斯科特和我登上了普利茅斯港的一艘小型游艇,旁邊停著的就是MAS,二者之間由一條繩索相連。作為MAS項目的總工程師,24歲的馬特·肖正坐在駕駛室中,他打開筆記本電腦,點開一個顯示著MAS上各種儀器讀數的數字儀表盤,直接用Xbox手柄和藍牙網絡開始了遠程操作。與此同時,MAS從我們面前平穩駛過,繩索也在陽光的照射下閃耀著金光。謹慎起見,當地官員要求MAS在進出港口時必須有人控制,并且需要與一艘載人的船舶連接在一起。
到達港口入口之外的考桑灣(Cawsand Bay)指定測試區域后,我們就解開了繩索,只看馬特敲擊了一下鍵盤,MAS就像脫韁的野馬一樣,以6.8節(約每小時8英里)的速度在預先設定的航點之間開始了自由航行。“以這個速度航行時,MAS的能效比最高。”馬特介紹說。與此同時,作為MAS上各項科學實驗的負責人之一,IBM研究中心的軟件工程師詹姆斯·薩頓則坐在一旁,通過膝蓋上放著的筆記本電腦查看MAS上各種科學儀器的讀數。
游艇先是在MAS旁伴行,隨后超到MAS前方,穿過了MAS的航線。斯科特說:“我們這么做是為了確保傳感器能夠正常看到我們,同時確保防撞軟件可以正常工作。”由于有關部門實際上并不允許MAS在距離海岸這么近的地方完全自主行動,所以MAS不會偏離既定航線。但在岸上碼頭邊的一座低矮紅磚建筑里,ProMare的其他員工能夠實時監控MAS攝像頭拍到的內容和雷達數據,還可以看到在自主操作的情況下,MAS的“人工智能船長”會做出何種決定來避免發生碰撞。他們用無線電通知馬特一切正常。“這就是海上的真實情況,什么問題都沒有。”斯科特說。
政府海事機構的謹慎讓法納夫憤憤不已,在他看來這毫無必要。他說:“正是這種夸張的安全文化為非理性監管提供了理由,這種行為最終將會阻礙行業的發展。”雖然西渡的清教徒一路遭受了許多苦難,但至少沒有遭受過度海事監管的折磨。(財富中文網)
譯者:梁宇
審校:夏林
Just days before Thanksgiving, Brett Phaneuf, a voluble middle-aged American entrepreneur, sat in a café in Plymouth, England, not far from the spot where the Pilgrims embarked on The Mayflower in September 1620, and talked about their voyage and changing perceptions of risk.
“What I find inspirational, is that these people were willing to take such an incredible risk to sort of jump off into something new, with not just no guarantee of success, but, like, no guarantee of survival,” Phaneuf says.
Now Phaneuf plans to follow them—in a sense.
For the past five years, a non-profit Phaneuf heads, ProMare, has been building an unmanned autonomous ship, powered by a hybrid diesel-electric motor and solar panels, which it hopes will follow in the Pilgrims’ wake, crossing the Atlantic from Plymouth, England, to Plymouth, Massachusetts. If successful, The Mayflower Autonomous Ship, named in honor of its famous nautical forebearer and known as MAS for short, will be the first such trans-Atlantic voyage by an autonomous vessel.
As he plans to recreate the pilgrims' risky crossing, Phaneuf finds today’s culture illogically risk-adverse. “As a society, we really simply have completely lost the ability to think about risk,” he says. This is particularly true, he says, when it comes to the regulation of new technology, such as artificial intelligence. “There’s just this bias against automation and autonomy,” he said.
Meanwhile, says Phaneuf, the biggest hazards on the water today are inexperienced pleasure boaters.
“But no one talks about banning them,” he said.
The promise of autonomous ships
Phaneuf's modern Mayflower was envisioned as a testbed for the technology needed to make autonomous ships viable. The market for such vessels, for container transport, research and military applications, is expected to reach more than $160 billion by the end of the decade.
Phaneuf, a Boston-area native who moved to Britain a decade ago for work, has been in discussions with regulators in both the U.S. and the U.K. about what rules should govern ships piloted by artificial intelligence software. One company Phaneuf runs, Marine AI, makes such software. Two other companies he also heads, M Subs Ltd. and The Submergence Group, build manned and unmanned submersibles for use by the U.S. and British Navy. In his view, uncrewed ships captained by A.I. pose far less risk than those helmed by human skippers—but most regulators don’t see it that way, he says.
Dispensing with crews could help ease future supply chain disruptions, not to mention saving the shipping industry millions in labor costs. So it’s not surprising that a number of maritime industry giants, including Maersk and Happag-Lloyd, have been teaming up with software and robotics startups to explore the creation of autonomous ships. Rolls-Royce, a major producer of ships’ engines, is making a big push to develop A.I.-captained vessels too. A Norwegian autonomous container ship, MV Yara Birkeland, began testing in the fjord outside Oslo in November. And Japan’s largest shipping company, Nippon Yusen, plans to send a captainless containership on a 236-mile coastal voyage from Tokyo Bay to the Japanese city of Ise in February.
But so far, none of big league shipping companies has proposed a journey as lengthy and audacious as what Phaneuf has planned for MAS. The 49-foot long, aluminum trimaran was supposed to have made its trans-Atlantic voyage to commemorate the 400th Anniversary of the Pilgrims’ journey, in 2020, but the COVID-19 pandemic delayed the vessel’s completion. In June this year, MAS belatedly embarked from Plymouth bound for America. The journey was expected to take about three weeks. But, after three days at sea, an exhaust pipe broke, preventing the hybrid electric generator from operating. MAS was forced to limp back under reserve power to the Isles of Scilly, which lie just west of the English Channel, and then the ProMare team towed her home to Plymouth.
“Boats always break, so our boat broke—but not the A.I. part,” Phaneuf shrugged.
Phaneuf isn’t one to give up easily. “One setback doesn’t define the whole project,” he said. After all, the original Mayflower also had to turn around—twice—for repairs before it eventually completed its 66-day Atlantic crossing. So Phaneuf redesigned the ship’s engine, Promare upgraded much of the boat’s software for good measure, and the group is planning another attempt to cross The Atlantic this spring. But first, the boat—which has cost Promare about $1.2 million so far, with a variety of corporate partners donating more in equipment and labor—is undergoing extensive testing in the waters near Plymouth, with a longer shake-down cruise to Rotterdam and back planned for February.
It should be easy
In theory, building an autonomous ship ought to be easier than creating a self-driving car. Even in busy shipping lanes, the oceans are less congested than most city roads or highways. “Last time, we travelled 500 miles offshore and we never came within 10 miles of another vessel,” Phaneuf said of MAS’s maiden crossing attempt. Except when coming in and out of port, ships generally have a lot of more freedom to navigate than cars do. Also, in most cases, ships travel much more slowly than cars, meaning there is a lot more time for A.I.-systems to identify potential hazards and maneuver to avoid them.
But training an A.I. system to identify buoys, channel markers, boats and all sorts of other things that float in the sea, from crab pots to logs—and to do so reliably in rain or fog while the ship is also pitching in heavy swells—that is a bit of a trick, says Don Scott, the tall, bearded Canadian, who is the chief technology officer at MarineAI and who oversaw the development of the software systems deployed on MAS. To do so, Scott developed a labelled database of millions of images of marine objects in different light and weather conditions. He installed cameras and sensors at various points around Plymouth Harbor to record activity and create a set of training data for MAS's A.I.
Sitting still alongside the pier in Plymouth, MAS cuts an impressive figure: its main hull and outriggers have reverse bows, designed to cut through the waves more efficiently, giving the ship the profile of some exotic spacecraft. A central platform rises on four struts rises from the middle of the main hull, sporting an impressive array of antennas, radars, sensors and cameras.
IBM took an early interest in the project and became ProMare’s principal technology partner, its corporate logo prominently displayed on the ship’s hull. The company provided some of the software the ship uses to “see” objects around it as well as the software the ship uses to decide how to steer when other vessels obstruct its path. This decision-making system was adapted from software IBM first used to help banks and insurance companies. IBM has also provided MAS with computers that can run A.I. software without needing to send information back and forth to on-shore datacenters. Being able to handle these computing demands “on the edge” without consuming too much of MAS’s limited electric power was an essential requirement. MAS may need to be make quick navigational decisions while in the middle of the ocean, beyond the reach of cellular communications and where satellite connectivity can be slow and bandwidth limited, or sometimes nonexistent.
Other computers onboard the ship will be helping to gather scientific data. One of the big advantages of autonomous ships, as Phaneuf sees it, is their ability to advance human understanding of the oceans. An unmanned vessel can remain at sea longer, at a tiny fraction of the cost, of a human-crewed research ship. With its own propulsion and the ability to navigate independently, it can also cover a wider geographic area than a sensor-laden buoy.
IBM researchers have designed three science projects that MAS will conduct while it is crossing the Atlantic. One is a hydrophone that will be used to listen continuously to sounds underwater, feeding the data to software that has been trained to identify whale songs. Another sensor, called Hypertaste, is an “electronic tongue” that will sample the water around MAS at 15 minute intervals, identifying its chemical composition. The data will be used to study ocean acidification, a process, linked to climate change, in which, as the amount of carbon dioxide in the atmosphere increases, the oceans also absorbs larger and larger amounts of carbon dioxide, becoming more acidic. Finally, researchers will be using video from the ship’s cameras, combined with data from inertial sensors onboard, to train an A.I. system to predict the energy a wave carries based on its appearance. This might one day help scientists make better use of video to understand the potential for storms and erosion, as well helping future autonomous ships steer the safest, most efficient path, through high seas.
Big Blue has contributed in other ways too. IBM owns The Weather Company, which transmits meteorological data to MAS that it will use to help determine the best route across the Atlantic. (In return, the ship is also relaying weather data from its own sensors back to shore-based researchers.) Weather company forecasters are also consulting with the ProMare team to help them find the best weather window for maximizing MAS’s chance of having a successful crossing.
Test drive
It’s a chilly, but calm and sunny early afternoon as Scott and I step aboard a small cabin cruiser in Plymouth Harbor. We watch as Matt Shaw, the 24-year old who serves as chief engineer on the MAS project, opens a laptop inside the pilot house and pulls up a digital dashboard displaying readouts from MAS’s instruments. Using an Xbox controller and a Bluetooth network, Shaw remotely pilots MAS as she motors placidly in front of us, attached to the cabin cruiser by a slack, day-glow orange line. As a precaution, local officials have mandated that MAS be under human control and tethered to a manned boat while navigating in and out of the harbor.
Once we reach a designated testing area in Cawsand Bay, just outside the harbor entrance, the tether is released, Shaw taps a key on the keyboard and MAS is off, making her own way between preprogrammed waypoints at a speed of 6.8 knots (about eight miles per hour). “This is her optimal speed for fuel consumption efficiency,” Shaw said. Meanwhile, James Sutton, a software engineer from IBM Research who has worked on the science experiments MAS carries, sits with a laptop perched on his knees, watching the readouts from the scientific instruments onboard.
The cruiser motors along next to MAS and then, pulling slightly ahead, crosses her path. “We’re testing to make sure the sensors can correctly see us and that the collision-avoidance software is working properly,” Scott said. The authorities won’t actually let MAS operate fully autonomously this close to shore, so MAS doesn’t deviate from its set course. But back on shore, in a squat redbrick building right alongside the wharf, other ProMare employees can monitor MAS’s camera feeds and radar data in real-time and also see what decision MAS’s A.I. captain would have taken to avoid a collision if it had been operating autonomously. They radio Shaw to tell him everything appears to be working. “This is the reality of being at sea, nothing much happens,” Scott said.
Phaneuf grates at what he sees at the needless caution of government maritime authorities. “It's just this sort of hyperbolic sort of safety culture that is being used to justify irrational attempts to regulate things in a way that will retard the growth of the industry,” he said. Of all the many hardships the Pilgrims had to bear, at least excessive maritime regulation wasn’t one of them.