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In the myth about the Tower of Babel, people conspired to build a city and tower that would reach heaven. Their creator observed, “And now nothing will be restrained from them, which they have imagined to do.” According to the myth, God thwarted this effort by creating diverse languages so that they could no longer collaborate.
In our modern times, we’re experiencing a state of unprecedented connectivity thanks to technology. However, we’re still living under the shadow of the Tower of Babel. Language remains a barrier in business and marketing. Even though technological devices can quickly and easily connect, humans from different parts of the world often can’t.
Translation agencies step in, making presentations, contracts, outsourcing instructions, and advertisements comprehensible to all intended recipients. Some agencies also offer “localization” expertise. For instance, if a company is marketing in Quebec, the advertisements need to be in Québécois French, not European French. Risk-averse companies may be reluctant to invest in these translations. Consequently, these ventures haven’t achieved full market penetration.
Global markets are waiting, but AI-powered language translation isn’t ready yet, despite recent advancements in natural language processing and sentiment analysis. AI still has difficulties processing requests in one language, without the additional complications of translation. In November 2016, Google added a neural network to its translation tool. However, some of its translations are still socially and grammatically odd. I spoke to technologists and a language professor to find out why.
“To Google’s credit, they made a pretty massive improvement that appeared almost overnight. You know, I don’t use it as much. I will say this. Language is hard,” said Michael Housman, chief data science officer at RapportBoost.AI and faculty member of Singularity University.
He explained that the ideal scenario for machine learning and artificial intelligence is something with fixed rules and a clear-cut measure of success or failure. He named chess as an obvious example, and noted machines were able to beat the best human Go player. This happened faster than anyone anticipated because of the game’s very clear rules and limited set of moves.
Housman elaborated, “Language is almost the opposite of that. There aren’t as clearly-cut and defined rules. The conversation can go in an infinite number of different directions. And then of course, you need labeled data. You need to tell the machine to do it right or wrong.”
Housman noted that it’s inherently difficult to assign these informative labels. “Two translators won’t even agree on whether it was translated properly or not,” he said. “Language is kind of the wild west, in terms of data.”
Google’s technology is now able to consider the entirety of a sentence, as opposed to merely translating individual words. Still, the glitches linger. I asked Dr. Jorge Majfud, Associate Professor of Spanish, Latin American Literature, and International Studies at Jacksonville University, to explain why consistently accurate language translation has thus far eluded AI.
He replied, “The problem is that considering the ‘entire’ sentence is still not enough. The same way the meaning of a word depends on the rest of the sentence (more in English than in Spanish), the meaning of a sentence depends on the rest of the paragraph and the rest of the text, as the meaning of a text depends on a larger context called culture, speaker intentions, etc.”
He noted that sarcasm and irony only make sense within this widened context. Similarly, idioms can be problematic for automated translations.
“Google translation is a good tool if you use it as a tool, that is, not to substitute human learning or understanding,” he said, before offering examples of mistranslations that could occur.
“Months ago, I went to buy a drill at Home Depot and I read a sign under a machine: ‘Saw machine.’ Right below it, the Spanish translation: ‘La máquina vió,’ which means, ‘The machine did see it.’ Saw, not as a noun but as a verb in the preterit form,” he explained.
Dr. Majfud warned, “We should be aware of the fragility of their ‘interpretation.’ Because to translate is basically to interpret, not just an idea but a feeling. Human feelings and ideas that only humans can understand—and sometimes not even we, humans, understand other humans.”
He noted that cultures, gender, and even age can pose barriers to this understanding and also contended that an over-reliance on technology is leading to our cultural and political decline. Dr. Majfud mentioned that Argentinean writer Julio Cortázar used to refer to dictionaries as “cemeteries.” He suggested that automatic translators could be called “zombies.”
Erik Cambria is an academic AI researcher and assistant professor at Nanyang Technological University in Singapore. He mostly focuses on natural language processing, which is at the core of AI-powered language translation. Like Dr. Majfud, he sees the complexity and associated risks. “There are so many things that we unconsciously do when we read a piece of text,” he told me. Reading comprehension requires multiple interrelated tasks, which haven’t been accounted for in past attempts to automate translation.
Cambria continued, “The biggest issue with machine translation today is that we tend to go from the syntactic form of a sentence in the input language to the syntactic form of that sentence in the target language. That’s not what we humans do. We first decode the meaning of the sentence in the input language and then we encode that meaning into the target language.”
Additionally, there are cultural risks involved with these translations. Dr. Ramesh Srinivasan, Director of UCLA’s Digital Cultures Lab, said that new technological tools sometimes reflect underlying biases.
“There tend to be two parameters that shape how we design ‘intelligent systems.’ One is the values and you might say biases of those that create the systems. And the second is the world if you will that they learn from,” he told me. “If you build AI systems that reflect the biases of their creators and of the world more largely, you get some, occasionally, spectacular failures.”
Dr. Srinivasan said translation tools should be transparent about their capabilities and limitations. He said, “You know, the idea that a single system can take languages that I believe are very diverse semantically and syntactically from one another and claim to unite them or universalize them, or essentially make them sort of a singular entity, it’s a misnomer, right?”
Mary Cochran, co-founder of Launching Labs Marketing, sees the commercial upside. She mentioned that listings in online marketplaces such as Amazon could potentially be auto-translated and optimized for buyers in other countries.
She said, “I believe that we’re just at the tip of the iceberg, so to speak, with what AI can do with marketing. And with better translation, and more globalization around the world, AI can’t help but lead to exploding markets.”
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Swarms of drones buzz overhead, while robotic vehicles crawl across the landscape. Orbiting satellites snap high-resolution images of the scene far below. Not one human being can be seen in the pre-dawn glow spreading across the land.
This isn’t some post-apocalyptic vision of the future à la The Terminator. This is a snapshot of the farm of the future. Every phase of the operation—from seed to harvest—may someday be automated, without the need to ever get one’s fingernails dirty.
In fact, it’s science fiction already being engineered into reality. Today, robots empowered with artificial intelligence can zap weeds with preternatural precision, while autonomous tractors move with tireless efficiency across the farmland. Satellites can assess crop health from outer space, providing gobs of data to help produce the sort of business intelligence once accessible only to Fortune 500 companies.
“Precision agriculture is on the brink of a new phase of development involving smart machines that can operate by themselves, which will allow production agriculture to become significantly more efficient. Precision agriculture is becoming robotic agriculture,” said professor Simon Blackmore last year during a conference in Asia on the latest developments in robotic agriculture. Blackmore is head of engineering at Harper Adams University and head of the National Centre for Precision Farming in the UK.
It’s Blackmore’s university that recently showcased what may someday be possible. The project, dubbed Hands Free Hectare and led by researchers from Harper Adams and private industry, farmed one hectare (about 2.5 acres) of spring barley without one person ever setting foot in the field.
The team re-purposed, re-wired and roboticized farm equipment ranging from a Japanese tractor to a 25-year-old combine. Drones served as scouts to survey the operation and collect samples to help the team monitor the progress of the barley. At the end of the season, the robo farmers harvested about 4.5 tons of barley at a price tag of £200,000.
“This project aimed to prove that there’s no technological reason why a field can’t be farmed without humans working the land directly now, and we’ve done that,” said Martin Abell, mechatronics researcher for Precision Decisions, which partnered with Harper Adams, in a press release.
I, Robot Farmer
The Harper Adams experiment is the latest example of how machines are disrupting the agricultural industry. Around the same time that the Hands Free Hectare combine was harvesting barley, Deere & Company announced it would acquire a startup called Blue River Technology for a reported $305 million.
Blue River has developed a “see-and-spray” system that combines computer vision and artificial intelligence to discriminate between crops and weeds. It hits the former with fertilizer and blasts the latter with herbicides with such precision that it can eliminate 90 percent of the chemicals used in conventional agriculture.
It’s not just farmland that’s getting a helping hand from robots. A California company called Abundant Robotics, spun out of the nonprofit research institute SRI International, is developing robots capable of picking apples with vacuum-like arms that suck the fruit straight off the trees in the orchards.
“Traditional robots were designed to perform very specific tasks over and over again. But the robots that will be used in food and agricultural applications will have to be much more flexible than what we’ve seen in automotive manufacturing plants in order to deal with natural variation in food products or the outdoor environment,” Dan Harburg, an associate at venture capital firm Anterra Capital who previously worked at a Massachusetts-based startup making a robotic arm capable of grabbing fruit, told AgFunder News.
“This means ag-focused robotics startups have to design systems from the ground up, which can take time and money, and their robots have to be able to complete multiple tasks to avoid sitting on the shelf for a significant portion of the year,” he noted.
Eyes in the Sky
It will take more than an army of robotic tractors to grow a successful crop. The farm of the future will rely on drones, satellites, and other airborne instruments to provide data about their crops on the ground.
Companies like Descartes Labs, for instance, employ machine learning to analyze satellite imagery to forecast soy and corn yields. The Los Alamos, New Mexico startup collects five terabytes of data every day from multiple satellite constellations, including NASA and the European Space Agency. Combined with weather readings and other real-time inputs, Descartes Labs can predict cornfield yields with 99 percent accuracy. Its AI platform can even assess crop health from infrared readings.
The US agency DARPA recently granted Descartes Labs $1.5 million to monitor and analyze wheat yields in the Middle East and Africa. The idea is that accurate forecasts may help identify regions at risk of crop failure, which could lead to famine and political unrest. Another company called TellusLabs out of Somerville, Massachusetts also employs machine learning algorithms to predict corn and soy yields with similar accuracy from satellite imagery.
Farmers don’t have to reach orbit to get insights on their cropland. A startup in Oakland, Ceres Imaging, produces high-resolution imagery from multispectral cameras flown across fields aboard small planes. The snapshots capture the landscape at different wavelengths, identifying insights into problems like water stress, as well as providing estimates of chlorophyll and nitrogen levels. The geo-tagged images mean farmers can easily locate areas that need to be addressed.
Growing From the Inside
Even the best intelligence—whether from drones, satellites, or machine learning algorithms—will be challenged to predict the unpredictable issues posed by climate change. That’s one reason more and more companies are betting the farm on what’s called controlled environment agriculture. Today, that doesn’t just mean fancy greenhouses, but everything from warehouse-sized, automated vertical farms to grow rooms run by robots, located not in the emptiness of Kansas or Nebraska but smack dab in the middle of the main streets of America.
Proponents of these new concepts argue these high-tech indoor farms can produce much higher yields while drastically reducing water usage and synthetic inputs like fertilizer and herbicides.
Iron Ox, out of San Francisco, is developing one-acre urban greenhouses that will be operated by robots and reportedly capable of producing the equivalent of 30 acres of farmland. Powered by artificial intelligence, a team of three robots will run the entire operation of planting, nurturing, and harvesting the crops.
Vertical farming startup Plenty, also based in San Francisco, uses AI to automate its operations, and got a $200 million vote of confidence from the SoftBank Vision Fund earlier this year. The company claims its system uses only 1 percent of the water consumed in conventional agriculture while producing 350 times as much produce. Plenty is part of a new crop of urban-oriented farms, including Bowery Farming and AeroFarms.
“What I can envision is locating a larger scale indoor farm in the economically disadvantaged food desert, in order to stimulate a broader economic impact that could create jobs and generate income for that area,” said Dr. Gary Stutte, an expert in space agriculture and controlled environment agriculture, in an interview with AgFunder News. “The indoor agriculture model is adaptable to becoming an engine for economic growth and food security in both rural and urban food deserts.”
Still, the model is not without its own challenges and criticisms. Most of what these farms can produce falls into the “leafy greens” category and often comes with a premium price, which seems antithetical to the proposed mission of creating oases in the food deserts of cities. While water usage may be minimized, the electricity required to power the operation, especially the LEDs (which played a huge part in revolutionizing indoor agriculture), are not cheap.
Still, all of these advances, from robo farmers to automated greenhouses, may need to be part of a future where nearly 10 billion people will inhabit the planet by 2050. An oft-quoted statistic from the Food and Agriculture Organization of the United Nations says the world must boost food production by 70 percent to meet the needs of the population. Technology may not save the world, but it will help feed it.
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The two main pitfalls of robots that imitate the human body are control and cost. Researchers from the MoCoTi European project have designed a prototype of a robot that learns how to actuate its own limbs, and that can be easily duplicated. The device, consisting of a control system and a tendon-driven robotic arm, might be the first step toward low-cost humanoid robotics. Continue reading
Cimcorp Selected to Supply Turnkey Automated Handling System to Large Turkish Tire Manufacturer, Petlas
The leading tire handling specialist’s system will handle tires in the tire-finishing and palletizing areas in Turkish manufacturer’s expanded facility
Ulvila, Finland – November 9, 2016 – Cimcorp, leading global supplier of turnkey automation for intralogistics and tire-handling solutions, announces it has been selected to implement a fully automated handling system in Petlas Tire Corporation’s (Petlas) factory in Kirsehir, Turkey. Based on Cimcorp’s Dream Factory solution, the automation will take care of the handling of passenger car radial (PCR) finished tires in the tire-finishing and palletizing areas. Work on the order is already underway and the’ turnkey material handling system will become fully operational in fall 2017.
The order, Cimcorp’s first project for Petlas, is part of a huge investment program to expand the Kirsehir plant in order to increase Petlas’ PCR production capacity and meet growing demand.
Turkey achieved record car production and export levels in 2015, with production up by 16 percent and exports up 12 percent over the preceding year. This growth rate is higher than in any other European country and, with its automotive plants rolling out 1.36 million vehicles in 2015, Turkey is now the seventh largest automotive producer in Europe.
With the production equipment – the tire-building machines, presses and testing machines – already installed, Petlas is commencing the automation of the plant’s material handling. This comprises Cimcorp’s robotic buffer stores, tire conveyors and control software – Cimcorp WCS (Warehouse Control Software) – to take care of all material flows. Using linear robots operating on overhead gantries, the system will automate the handling and transfer of finished tires from the trimming stations, through visual inspection and uniformity testing, to palletizing.
Yahya Ertem, general manager, Petlas Tire Corporation, said, “We think highly of Cimcorp’s software, which integrates the machines into one entity and keeps the flow of material and data under complete control. Cimcorp’s Dream Factory solution fits with our vision to achieve ‘excellence in business’ and will help us to achieve our strategic goals.”
Tero Peltomäki, vice president of sales and projects, Cimcorp, said, “It has been fantastic to work with the Petlas team, honing our design into the best possible solution for the Kirsehir plant. The automation will help Petlas to enhance its market position as a leading tire manufacturer and distributor and we look forward to working on future automation projects with the company.”
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Cimcorp Group – part of Murata Machinery, Ltd. (Muratec) – is a leading global supplier of turnkey automation for intralogistics, using advanced robotics and software technologies. As well as being a manufacturer and integrator of pioneering material handling systems for the tire industry, Cimcorp has developed unique robotic solutions for order fulfillment and storage that are being used in the food & beverage, retail, e-commerce, FMCG and postal services sectors. With locations in Finland, Canada and the United States, the group has around 300 employees and has delivered over 2,000 logistics automation solutions. Designed to reduce operating costs, ensure traceability and improve efficiency, these systems are used within manufacturing and distribution centers in 40 countries across five continents. For more information, visit www.cimcorp.com.
About Petlas Tire Corporation (Petlas)
Founded in 1976, Petlas Tire Corporation has operations in 98 countries worldwide and employs 2,150 people. The company’s plant in Kirsehir currently has the capacity to produce 8 million PCR (passenger car radial) tires, 2 million agricultural tires, 500,000 TBR (truck & bus radial) tires and 300,000 OTR (off-the-road) tires per year. For more information, visit www.petlas.com.
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Fusion for Energy signs multi-million deal with Airbus Safran Launchers, Nuvia Limited and Cegelec CEM to develop robotics equipment for ITER
The contract for a value of nearly 100 million EUR is considered to be the single biggest robotics deal to date in the field of fusion energy. The state of the art equipment will form part of ITER, the world’s largest experimental fusion facility and the first in history to produce 500 MW. The prestigious project brings together seven parties (China, Europe, Japan, India, the Republic of Korea, the Russian Federation and the USA) which represent 50% of the world’s population and 80% of the global GDP.
The collaboration between Fusion for Energy (F4E), the EU organisation managing Europe’s contribution to ITER, with a consortium of companies consisting of Airbus Safran Launchers (France-Germany), Nuvia Limited (UK) and Cegelec CEM (France), companies of the VINCI Group, will run for a period of seven years. The UK Atomic Energy Authority (UK), Instituto Superior Tecnico (Portugal), AVT Europe NV (Belgium) and Millennium (France) will also be part of this deal which will deliver remotely operated systems for the transportation and confinement of components located in the ITER vacuum vessel.
The contract carries also a symbolic importance marking the signature all procurement packages managed by Europe in the field of remote handling. Carlo Damiani, F4E’s Project Manager for ITER Remote Handling Systems, explained that “F4E’s stake in ITER offers an unparalleled opportunity to companies and laboratories to develop expertise and an industrial culture in fusion reactors’ maintenance.”
Cut-away image of the ITER machine showing the casks at the three levels of the ITER machine. ITER IO © (Remote1 web). Photo Credit: f4e.europa.euIllustration of lorry next to an ITER cask. F4E © (Remote 2 web). Photo Credit: f4e.europa.euAerial view of the ITER construction site, October 2016. F4E © (ITER site aerial Oct). Photo Credit: f4e.europa.eu
Why ITER requires Remote Handling?
Remote handling refers to the high-tech systems that will help us maintain and repair the ITER machine. The space where the bulky equipment will operate is limited and the exposure of some of the components to radioactivity, prohibit any manual intervention inside the vacuum vessel.
What will be delivered through this contract?
The transfer of components from the ITER vacuum vessel to the Hot Cell building, where they will be deposited for maintenance, will need to be carried out with the help of massive double-door containers known as casks. According to current estimates, 15 of these casks will need to be manufactured and in their largest configuration they will measure 8.5 m x 3.7 m x 2.6 m approaching 100 tonnes when transporting the heaviest components. These enormous “boxes”, resembling to a conventional lorry container, will be remotely operated as they move between the different levels and buildings of the machine. Apart from the transportation and confinement of components, the ITER Cask and Plug Remote Handling System will also ensure the installation of the remote handling equipment entering into the vacuum vessel to pick up the components to be removed. The technologies underpinning this system will encompass a variety of high-tech skills and comply with nuclear safety requirements. A proven manufacturing experience in similar fields and the development of bespoke systems to perform mechanical transfers will be essential.
MEMO: Fusion for Energy signs multi-million deal with Airbus Safran Launchers, Nuvia Limited and Cegelec CEM to develop robotics equipment for ITER
To see how the ITER Remote Handling System will operate click on clip 1 and clip 2
To see the progress of the ITER construction site click here
To take a virtual tour on the ITER construction site click here
Cut-away image of the ITER machine showing the casks at the three levels of the ITER machine. ITER IO © (Remote1 web)
Illustration of lorry next to an ITER cask. F4E © (Remote 2 web)
Aerial view of the ITER construction site, October 2016. F4E © (ITER site aerial Oct)
The consortium of companies
The consortium combines the space expertise of Airbus Safran Launchers, adapted to this extreme environment to ensure safe conditions for the ITER teams; with Nuvia comes a wealth of nuclear experience dating back to the beginnings of the UK Nuclear industry. Nuvia has delivered solutions to some of the world’s most complex nuclear challenges; and with Cegelec CEM as a specialist in mechanical projects for French nuclear sector, which contributes over 30 years in the nuclear arena, including turnkey projects for large scientific installations, as well as the realisation of complex mechanical systems.
Fusion for Energy
Fusion for Energy (F4E) is the European Union’s organisation for Europe’s contribution to ITER.
One of the main tasks of F4E is to work together with European industry, SMEs and research organisations to develop and provide a wide range of high technology components together with engineering, maintenance and support services for the ITER project.
F4E supports fusion R&D initiatives through the Broader Approach Agreement signed with Japan and prepares for the construction of demonstration fusion reactors (DEMO).
F4E was created by a decision of the Council of the European Union as an independent legal entity and was established in April 2007 for a period of 35 years.
Its offices are in Barcelona, Spain.
ITER is a first-of-a-kind global collaboration. It will be the world’s largest experimental fusion facility and is designed to demonstrate the scientific and technological feasibility of fusion power. It is expected to produce a significant amount of fusion power (500 MW) for about seven minutes. Fusion is the process which powers the sun and the stars. When light atomic nuclei fuse together form heavier ones, a large amount of energy is released. Fusion research is aimed at developing a safe, limitless and environmentally responsible energy source.
Europe will contribute almost half of the costs of its construction, while the other six parties to this joint international venture (China, Japan, India, the Republic of Korea, the Russian Federation and the USA), will contribute equally to the rest.
The site of the ITER project is in Cadarache, in the South of France.
For Fusion for Energy media enquiries contact:
Tel: + 34 93 3201833 + 34 649 179 42
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