Category Archives: Artificial Intelligence
Manufacturing Leaders’ Summit: Realising the promise of Artificial Intelligence – Manufacturer.com
Manufacturing plays a central role in the global economy, and its a field where the promise of artificial intelligence (AI) is clear driving productivity, growth and employment.
But with the manufacturing sector among the first to reap the benefits of AI at scale, industrial businesses will also find themselves at the forefront of responding to some of the challenges of AI, from skills and culture, to ethics and responsibility.
It is these responses that will define our collective and individual success. Chris Harries, worldwide manufacturing industry solutions director for Microsoft, took to the main stage at Manufacturing Leaders Summit 2019 to explain more.
He began by charting the start of the First Industrial Revolution when the steam engine first appearance on the scene and changed the course of human history.
Almost everything we understand about how goods are produced, how societies are organised and how economies operate can be traced back to that moment, Harries noted.
Today, we are in the early stages of another technology-driven transformation; the catalyst this time is artificial intelligence (AI).
Harries described AI as a collective term for technologies that can sense their environment, think, learn and take action in response to what theyre sensing and their objectives.
At the granular level, AI can be built into processes we already run today, such as HSE compliance (see image right), as well as to create completely new solutions and capabilities, he continued.
Taken collectively the potential for change is vast, and like the First Industrial Revolution, manufacturing is again leading the way in adopting a new technology to create new products and services, transform processes, and revolutionise productivity.
Unlike with the First Industrial Generation, we wont need to wait a century to feel the full effects.
Over just the past couple of years, AI has already transformed how we work, live, learn, and play in dramatic ways. And the pace of change is accelerating.
The promise of AI in manufacturing hasnt been definitively calculated, with various studies and projections offering a wide spectrum of potential:
With our customers, were seeing the early signs of realising benefits through AI, most often through improved product quality, production and supply chain efficiencies, and the effectiveness of their service operations, Harries explained.
But as the sector starts to reap the benefits of AI, manufacturers also find themselves at the forefront of responding to some of the challenges.
Earlier this year, Microsoft collaborated with author Greg Shaw to publish The Future Computed: AI for Manufacturing.
In researching for the book, Shaw interviewed dozens of customers, policy makers, labor representatives and other stakeholders from around the world to find the story behind the impact of AI on the manufacturing sector and its workforce.
Through the course of these interviews, six themes began to emerge:
1. Manufacturers around the world are already seizing the AI opportunity.
More than that, they are seeing that the value of AI extends beyond productivity to include everything from workplace safety to process efficiencies, predictive maintenance, intelligent supply chains, and higher value, higher quality products.
2. To take full advantage of AI, companies are undergoing a cultural transformation that requires strong, committed leaders and engaged workers who are involved in decisions-making and implementation at every level of the process.
Companies seeing the greatest gains from AI today are those that are embracing change and eliminating the barriers between information systems and people, so they could create a seamless information supply chain that utilises their entire digital estate.
Removing these barriers is just as much about corporate culture as it is about technology implementation.
3. The managers inside production operations who are closest to the workforce care the most about AIs impact on employees.
Their focus on creating a better company translates to a commitment to create safer work environments, and to increasing productivity through providing better opportunities and fewer repetitive and unsatisfying jobs.
And because they put their people first, they are eager to adopt technologies that will have a positive impact on workers.
4. There is widespread optimism that AI will lead to more and better jobs over the long term; but disruption and dislocation are inevitable.
Everyone is concerned that manufacturing will face a significant talent shortage and wonders where the next generation of bright students with the right skills and training will come from.
Therefore, there is a very real need to create a talent pipeline filled with people who have the knowledge and capabilities to fill tomorrows manufacturing jobs.
Businesses, governments, educational institutions and labor organisations will all need to work together to forge new partnerships that are focused on skills and workforce development.
5. Its not just about digital skills, this new generation of technologies will also need a new generation of policies and laws.
It is clear that as manufacturers implement AI into their processes and incorporate it in their products, they are looking for new guidelines and updated legal frameworks that will clarify their obligations and help them anticipate potential issues.
To encourage the adoption of AI technologies in ways that strengthen worker safety, create more jobs, and promote economic growth and national competitiveness, regulators are eager to update existing laws so that they reflect the realities of our digital world.
6. AI is a journey and it will be different for everyone. And deploying AI is fundamentally different than implementing traditional software solutions.
This is not a build once, roll out worldwide technology that can be left in the hands of the IT team. For companies to reap the full benefits, AI systems need to continuously learn.
They must also be trained, monitored, evaluated and improved to guard against unconscious bias, and to avoid privacy violations and safety issues.
To ease the way forward, Microsoft has produced a framework to help companies assess their needs and determine what AI solutions to implement, and when.
This operational model begins at the foundational level for companies that are just beginning to explore what AI really is and how it can help them become a data-driven organisation.
It then moves through increasing levels of knowledge, culture change, and digital expertise until companies reach the level of maturity and tech intensity needed to apply AI ethically, responsibly, and successfully across their organisation.
Earlier this year, Microsoft in partnership with INSEAD also launched the AI Business School, a free, on-demand, masterclass series designed specifically for business leaders to empower them to get results from AI.
The course covers setting an AI strategy, enabling an AI-ready culture, fostering responsible and trustworthy AI, and finally an introduction to the full range of AI technologies that you could use to transform your organisation and ecosystem,
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Manufacturing Leaders' Summit: Realising the promise of Artificial Intelligence - Manufacturer.com
PNNL researchers working to improve doctor-patient care through artificial intelligence – NBC Right Now
RICHLAND, WA - Researchers at the Pacific Northwest National Laboratory are working on improving doctor-patient relationships through new technology.
A team of scientists has been working on this for the past few years. The goal is not to replace a doctor, but to assist them in accurately diagnosing a patient based on their symptoms.
Imagine walking into a doctor's office and using technology like Siri or Google Assistant to help determine a diagnosis based on your symptoms. That's how PNNL scientists envision future doctor-patient care.
"We will have this conversational interface with a system that will help the doctor to collect all different data sources and provide information that will help the doctor have a more precise diagnostic," computer scientist Robert Rallo said.
Creating that conversational interface tool begins with building artificial intelligence models. Doctors' medical knowledge and anonymous patient data is combined, then translated into computer speak.
"With this tool what they can better process all this information and better leverage all the knowledge that this information is providing to them." Rallo said.
The goal is to mimic a doctor's ability to create links between symptoms and diseases. The technology will have more data and connections than can be stored in any human brain.
"You can think of this as a tool that can help doctors process all the information that they have in a much more efficient way," Rallo said.
It could be years before we see this at our next doctor appointment. But, scientists like Rallo believe it has the potential to forever change the medical care system.
"To me, one of the most important aspects of this work is that we are working with real people and we are helping them have much more improved health and health care in general," he said.
In the next phase of research, the PNNL team will work with a new data set. It's part of a collaboration between the Veterans Administration and the Department of Energy.
For more information on this project, you can visit this article on PNNL's website.
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How Augmented Reality and Artificial Intelligence Are Helping Entrepreneurs Create a Better Customer Experience – CTOvision
Read Madison Semarjian explain how augmented reality (AR) and artificial intelligence (AI) are helping companies create better customer service engines on Entrepreneur :
Michael Bower helps companies provide cool experiences to their customers on the web. As CEO of Sellry, an ecommerce solutions company, he combines creativity with the latest technology to propel brands into the future. Alongside clients, Sellry works to reimagine and design the future of ecommerce. AR is going to completely change many industries. Weve seen applications where you can just point your phone at something and itll tell you about it. Weve also seen smart mirrors. Theres even APIs where itll measure your body from a photograph with a degree of accuracy. A lot of these APIs are nearly real-time. Some of them can even look at multiple different subjects at the same time and figure out many things about them. Its the future.
Read her full article here.
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IT chiefs recognise the risks of artificial intelligence bias – ComputerWeekly.com
A survey of 350 US and UK-based CIOs, chief financial officers (CTOs), vice-presidents and IT managers has reported that IT decision-makers are becoming increasingly aware of artificial intelligence (AI) bias.
Nearly half (42%) of AI professionals across the US and UK say they are very to extremely concerned about AI bias, according to research from Data Robot.
DataRobots The State of AI bias 2019 study found that most organisations (71%) currently rely on AI to execute up to 19 business functions.
More organisations are deploying AI as they recognise the technology as a critical success factor for competing in todays business climate, said Ted Kwartler, vice-president of trusted AI at DataRobot.
Almost a fifth of the IT decision-makers surveyed said that AI is used to complete 20 to 49 business functions, and 10% said they use AI to complete more than 50 business functions.
DataRobots research found that AI is used by organisations to execute functions across departments, including operations (76%), finance and accounting (54%), marketing (49%), sales (47%), and human resources (35%).
Weve observed that AI maturity varies widely, with many organisations still using untrustworthy AI systems, Kwartler added.
The biggest AI bias concerns for the IT executives surveyed include compromised brand reputation and loss of customer trust.
Colin Priest, vice-president of AI Strategy at DataRobot, said: While many organisations have started to take the right steps to mitigate AI bias such as moving away from black box systems and establishing internal AI guidelines theres more to be done to win the trust of businesses and consumers.
Every business must make AI bias education a priority so they can implement critical strategies in their AI systems that will help prevent it from happening.
Respondents said they faced challenges in developing unbiased AI algorithms, determining what data to train AI models on, and understanding how input data relates to AI decisions.
The survey found that 65% of IT decision-makers are using tools to explore why AI makes negative decisions. Almost two-thirds said they are also using tools to check which input data has the greatest effect on an AI decision. Just over half said they use word clouds to look at how text input is associated with AI decisions.
The survey reported that 94% of US IT leaders and 86% of UK IT leaders plan to invest more in AI bias prevention initiatives in the next 12 months.
To enhance AI bias prevention efforts moving forward, 59% of the IT decision-makers surveyed said they plan to invest in more sophisticated white box systems, where AI decisions are explainable. More than half (54%) said they will hire internal personnel to manage AI trust, and 48% said they intend to enlist third-party firms to oversee AI trust.
The survey also reported that 85% of IT leaders who took part in the survey believe that AI regulation would be helpful for better defining what constitutes AI bias and how it should be prevented.
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IT chiefs recognise the risks of artificial intelligence bias - ComputerWeekly.com
Is St. Louis ready for artificial intelligence? It will steal white-collar jobs here, too – STLtoday.com
St. Louis workforce wont be on the front lines of the artificial intelligence revolution, a new report says, but it wont be immune either.
The Brookings Institution study looks at patent applications for artificial intelligence and compares them with occupational descriptions. For instance, a patent containing the phrase diagnose disease would affect a physicians job.
This method allowed researchers to zero in on artificial intelligence, or AI, in a way that hadnt been done before. Previous studies on the future of work defined automation broadly and tended to focus on more established technologies like computers and industrial robots.
Forecasts about AI, the fast-developing technology in which machines can learn and make decisions for themselves, have tended toward the sensational. Tesla founder Elon Musk famously called AI a fundamental risk to the existence of human civilization.
The patent study let researchers avoid scare stories and see which jobs the new technology might actually change.
Those most affected fell into two broad groups: production workers, in fields such as agriculture and manufacturing, and white-collar knowledge workers. AI will take over tasks where human judgment was once essential, from spotting defects to managing procurement.
Where earlier research found automation to have the biggest effect on young, unskilled workers, the people dealing with AI in the workplace will include highly paid professionals in their prime working years.
An interesting part of the story is this heavy orientation to better-educated, better-paid occupations in everything from business management to finance to technology to medicine, said Mark Muro, a Brookings senior fellow and co-author of the report. Factory automation has been more of a blue-collar phenomenon, but AI clearly has a very noteworthy white-collar look.
Women are less exposed than men because theyre over-represented in fields such as nursing and education that arent often mentioned in AI patents.
Cities most exposed to AI include technology hubs like San Jose and Seattle, agricultural towns like Bakersfield, California, and manufacturing centers such as Detroit and Louisville.
The St. Louis area shows up slightly below average, with 17% of jobs here highly exposed to AI. The metropolitan area has relatively high numbers of health care personnel, personal care workers and food preparers, all of which have low exposure.
That doesnt mean St. Louis can ignore the advance of AI. Some of the industries on which the region is staking its future, including medicine, finance and agriculture, will be transformed by the new technologies.
In general your science base and business sector concentrate your exposure, Muro explained. That you dont have a ton of manufacturing left reduces it.
The research, he cautioned, should be read with a couple of caveats. One is that its a study of potential exposure, not a forecast of any specific impact.
The other is that just because a job is affected by AI, it doesnt mean the workers will become obsolete. Some jobs could disappear, but AI could make other workers more productive and raise their pay.
Tasks that once seemed valuable, like the ability to glean insights from a spreadsheet, may become less so. Other skills, such as the ability to connect emotionally with a customer, may become more important.
As this revolution happens, well need government and educational institutions that can help workers adapt. Those dont exist today, in Muros opinion, and the need is becoming urgent.
Part of the reason all of this is frightening to people is because our training and adjustment systems are not all that good, he said.
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DesignCon Expands Into Artificial Intelligence, Automotive, 5G, IoT, and More For 2020 Edition – I-Connect007
DesignCon, the nations largest event for chip, board, and systems design engineers, today announced new areas of focus for the 2020 edition highlighting advances in the fields of5G, artificial intelligence (AI),automotive, andIoT, producing the most in-demandelectronicsemerging today. Topics will be examined through a 14-track conference schedule spanning technical sessions, boot camps, tutorials, and more to fit the needs of the hardware design engineering community. DesignCon returns to Silicon Valley for its 25thyear, taking place from January 28-30, 2020 at the Santa Clara Convention Center.
The DesignCon conference and expo reflects the design engineering industrys growing need for breakthroughs in the development of5Gconnectivity, AI,automotiveelectronics, and IoT. With worldwide spending on AI systems forecasted to reach$79.2 billion in 2022, sales ofautomotiveelectronic systems at itshighest growth rateon-record, expected worldwide spending on IoT projected to surpass$1 trillion in 2022, and the5Ginfrastructure market estimated to reach$4.2 billion in value by 2020, DesignCon is the ideal forum for attendees across these interlaced industries to exchange ideas and develop solutions to meet consumer demand.
The market and value for connected, especially fast connected products, is on the rise, said Suzanne Deffree, brand director, Intelligent Systems & Design, Informa Markets. DesignCon is the most comprehensive event available to the design engineer community, enabling attendees to collaborate toward these growing opportunities and innovate beyond current demand. We pride ourselves on being the industrys leading educational event, helping the brightest minds understand and master the latest technology and applications on the market.
The DesignCon premier educational conference is curated by theTechnical Program Committee (TPC), an expert panel of more than 90 industry professionals who review and update the curriculum each year to meet the needs of the ever-evolving high-speed communications and semiconductor industry.
Featured conference content of interest at DesignCon 2020 include:
Electronic Design Automation Roadmap for Machine Learning & AI StandardizationCurrently, EDA has no roadmap for machine learning (ML) and AI with a timetable to meet design and manufacturing needs. A roadmap would provide a framework to study targeted ML/AI functions and describe dependencies between industry organizations. Defining functional needs with business goals will identify methodology gaps for new R&D from industry and academia. In this panel, industry and academic experts will discuss and debate the following areas critical to developing an EDA ML/AI roadmap: concept unification, software interoperability, high-volume data handling and exchange, and learning from other disciplines.
A System-Level Power Integrity Study of Multi-Domain Power Supply Noise CouplingDuring this technical session, Dmitry Klokotov, staff signalintegrityengineer at Xilinx, will present a system-level study of power supply noise coupling between different power distribution networks. The system is built around a large programmable SoC device, which is currently used in a variety of cutting-edge applications such as AI, Cloud, IoT, etc. An SoC chip hosts many different blocks with different power demands, restrictions, and requirements. Different blocks need to operate side by side and interact with each other. Insuring powerintegrityof such a system becomes challenging and it is particularly difficult to manage noise coupling via a shared return path. Klokotovs powerintegritystudy covers pre-silicon modeling, hardware verification, and correlation steps.
Electronic/Photonic IC Design for5GRF ApplicationsPhotonic integrated circuits are rapidly advancing in several applications, such as datacom and telecom, virtual reality, sensors,automotive, and medical applications. Validated, unified Electronic/Photonic Design Automation (EPDA) tool flows are key to bringing standardization and scalability to silicon photonics, including implementing5Gand WiGig. This tutorial will introduce a PDK-based design flow enabling RF designs for5Gand WiGig. Experts from leading EDA and photonics design tools vendors will demonstrate how close integration between schematic capture, electronic-photonic co-simulation, and layout tools, together with electronic/photonic PDKs delivers silicon-proven5Gdesigns. Attendees will learn about EPDA co-design and co-simulation, as well as photonic-specific compact model libraries (CMLs), in addition to getting hands-on experience with the latest EPDA design tools and foundry PDK.
Introduction to LIDARLIDAR (Light Detection and Ranging) is widely considered a necessity for fully automated self-drivingautomotiveapplications. In order to sample the far field with sufficient resolution, LIDAR systems must incorporate either a large number of optical emitters or a means of steering the optical emission from a small number of outputs across the far field. Due to the density of optical components required, LIDAR is ripe for optical integration in order to achieve miniaturization and scalable manufacturability. This talk will give an overview of LIDAR techniques, the components required for a chip-scale LIDAR solution, and the state of the art in silicon photonics with respect to this goal.
DesignCon 2020 is also supported byThe Institute of Electrical and Electronics Engineers (IEEE), offering its accreditation to conference attendees. Each conference hour is eligible for one professional development hour (PDH), and 10 PDHs result in one continuing education unit (CEU) and an official IEEE certificate. IEEE accreditation can be used to meet training requirements, stand out to future employers, and maintain an engineering license.
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Drones And Artificial Intelligence Help Combat The San Francisco Bays Trash Problem – Forbes
Ever since the industrial chemist Leo Baekeland began synthesizing phenol and formaldehyde in 1907, the world has developed a love-hate relationship with the resulting polymer: plastic.
While plastic is convenient, durable, and cheap, 50% of all plastics (about 150 million tons every year, worldwide) are used only once and then thrown away. Even for those who dutifully recycle our plastic water bottles and sandwich bags, were only tackling a small part of the problem. Thats because heavy winds and rain carry huge amounts of plastic waste along city streets and into the stormwater system, where it likely flows directly into creeks, rivers, bays, and eventually the ocean, with no treatment to filter out plastics.
Ora Loma Marsh in Hayward, California.
Considering the size of the problem, theres relatively limited infrastructure in place to capture and treat stormwater, says Tony Hale, program director for environmental informatics at the nonprofit San Francisco Estuary Institute (SFEI).
Thats where SFEI is looking to use research and dataand most recently, dronesto make a difference.
In addition to sending out crews of people on foot to count and collect trash in local waterways, SFEI began using camera-equipped drones to assess that waste on a much larger scale.
Most ground crews working for stormwater programs monitor trash once a year, twice if were lucky, Hale says. So what we can learn about trash and its impact on communities is limited by the number of people we can afford to send out.
With drone photography, we can track all of the trash in a creek, river, or stream, examine how its distributed, and then apply machine-learning algorithms to analyze those images as often as we want, Hale says.
The drone research is part of a new project by SFEI and its sister organization Southern California Coastal Water Research Project, through funding from the Ocean Protection Council, to validate trash-monitoring methods, and produce a trash-monitoring playbook that community cleanup groups, municipal programs, environmental agencies, and ecologists can learn from and put to use. The effort studies initiatives such as plastic bag bans to urban rain gardens.
Our mission is to help city planners find the best ways to filter their stormwater and stop contaminants such as trash and plastics from entering their protected wetlands and public waterways, Hale says.
Deep-Learning Cleanup Crew
By sending drones over the San Francisco Bay and neighboring tributaries, SFEI collected some 35,000 images in its initial foray.
Covering so much ground so quickly was amazing, Hale reflects. But his excitement soon faded, as the reality of crunching so much data in a reasonable amount of time set in: It took us almost a month to process these images.
Using 2,000 annotations to describe various trash particles, Hale and his team were training an open-source TensorFlow machine-learning algorithm to identify the type, quantity, and location of each particle of trash depicted in those 35,000 images.
To speed up the analysis, SFEI partnered with Kinetica, a data analytics startup that participates in the Oracle for Startups program. It put SFEIs trash-detection model into a Docker container and then brought it into Kineticas active analytics workbench, says Kinetica CMO Daniel Raskin. Using a Python API, Kinetica then streamed the images into a table, where they could be stored, categorized, and labeled.
Were not just ingesting these images and distributing them inside our platform Raskin says. Were also running SFEIs trash-detection model to classify all of the images as they hit our database.
This gives SFEI more than just a giant image catalog. The California water-quality watchdog can now visualize each of the 35,000 images based on its geographical location and trash profile.
Initially, Kinetica ran SFEIs deployment from a distributed CPU framework, on its own 4-core machine, using managed Kubernetes. It took us about 10 days to run the entire simulation, says Nick Alonso, a solution engineer at Kinetica who works on the SFEI project.Even after moving the application to a server using a single GPUprocessors that are well suited to machine learning workthe simulation still took the better part of a week.
Kinetica then decided to run SFEIs entire workload on Oracle Cloud Infrastructure, using eight V100 GPUs. Were no longer talking about days to run this simulation, Alonso says. Were doing it in hoursabout 18 hours and 26 minutes, to be exact.
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Drones And Artificial Intelligence Help Combat The San Francisco Bays Trash Problem - Forbes
Artificial Intelligence: A Need of Modern ‘Intelligent’ Education – Thrive Global
Artificial intelligence is influencing the future of virtuallyevery industry and every human being. It has acted as the main driver ofemerging technologies like big data, robotics, and IoT, and it will continue toact as a technological innovator for the near future.
According to tech experts, artificial intelligence(AI) has the potential to transform the world. However, those same experts donot agree on what kind of effect that transformation will have on the averageperson. Some believe that humans will be much better off in the hands ofadvanced AI systems, while others think it will lead to our inevitable downfall.
Artificial intelligence is software built to learnor problem solve processes typically performed in the human brain. Today,medical researchers are using AI to develop technology that will detect a rangeof diseases, improve radiology imaging, fine-tune radiation treatments,simplify DNA sequencing, and advance precision medicine for more individualizedhealth care.
In the coming years, progress in artificialintelligence (AI) will yield practical clinical tools. Mental health providerswill then use to plan tailored treatment of common psychiatric disorders suchas ADHD, PTSD, bipolar disorder, anxiety disorders, schizophrenia, Alzheimersdisease, and others.
These days, content is complicated. The role of AIto augment knowledge, skills, strategies, and tactics may be a powerful formulato transform yesterdays teacher into tomorrows informed mentor. One of thegreatest challenges concerning education is that people learn differently andat different rates. Students go through the education system with differinglevels of learning ability and aptitude. Some are more adept at left brainthinking with skills for analytical thought, while others are more skilled atright-brain thinking with creative, literary, and communicative ability.
Through the power of machine learning-basedhyper-personalization, AI systems are being used to develop a custom learningprofile of each student. It customizes the training materials for each studentbased on their ability, preferred mode of learning, and experience. Rather thanrequiring teachers to create a single curriculum for all students, educatorswill have augmented intelligence assistance that provides a wide range ofmaterials leveraging the same core curriculum, but cater to the specific needsof each student.
These autonomous conversational agents can answerquestions from students, provide assistance with learning or assignment tasks,and reinforce concepts with additional materials that can help reinforce thecurriculum. These intelligent assistants are also enhancing adaptive learningfeatures so that each of the students can learn at their own pace or timeframes. Something theMicrosoftEducation communityis striving to achieve globally.
Jean-Philippe Courtois leads global sales, marketing, and services for Microsoft International.
Learning is, therefore, getting paperless with time and soonthere will be less or no use of hard copy textbooks for learning. AI systemsalso have an online interactive interface that aids in feedback from thestudents to their professors for follow up purposes in areas where they mightbe struggling or have not yet fully grasped.
Voice assistants such as Amazon Alexa, Google Home,Apple Siri, andMicrosoftCortanaare givingstudents a chance to interact with educational material without the interactionof the teacher. These devices can be used at home or similar non-educationalenvironment to provide conversational interaction with teaching material andadditional educational assistance.
On the higher education side, college admissionsofficials are considering using AI systems to improve the fairness and qualityof the admissions process. AI systems that are trained in a way that eliminatesmuch of the human bias are starting to be used to provide a credible and fairadmission using given criteria when compared to humans.
In the final analysis, we are all students andteachers. This unique reciprocal combination can benefit from AI. From theclassroom to the boardroom to the operating room, our ability to learn, unlearnand relearn that will empower us all to drive real change and embrace thefuture.
Theilliterate of the 21st century will not be those who cannot read and write, butthose who cannot learn, unlearn, and relearn. Alvin Toffler
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Artificial Intelligence: A Need of Modern 'Intelligent' Education - Thrive Global
Artificial intelligence could be one of the most valuable tools mankind has built – here’s one small but meani – Business Insider India
Business Insider
Humans have enlisted nearly 100 AI-powered robots in North American to come to the rescue for something humans are terrible at: recycling.
Even when we try to do it right, we're often making things worse; About one out of every four of the things people throw into the recycling bin aren't recyclable at all.
Only a small fraction of the over 2.1 billion tons of the garbage the world produces each year gets recycled - about 16%.
And even that small sliver has gotten smaller over the past year.
For decades, the US sold more than half of its recyclables to China - mostly plastics to be melted into pellets, the raw material for making more plastic.
But in March of 2018, China said, "No More."
"They started shipping more and more stuff to China, often contaminated dirty plastics or mixed too many mixed goods," said Kate O'Neill, a UC Berkeley professor and author of "Waste."
So the Chinese government declared that bales could contain only up to half a percent of things that contaminated them, like food wrappers or a dirty jar of peanut butter. US consumers and recycling centers couldn't keep up.
"I think people in the wealthy countries had gotten complacent, never bothering to build more recycling facilities domestically," O'Neill added.
Today, a handful of start-ups are testing out new technology to make recycling sustainable.
AMP Robotics is an artificial intelligence and robotics company that aims to change the way we recycle.
Founder of AMP Robotics, Matanya Horowitz said "the situation with the Chinese export markets have actually been good for [the company]."
AMP Robotics is rolling out its latest model: a "Cortex Robot" that uses optical sensors to take in what rolls by, and a "brain" to figure out what his "hands" should do with something - even if it looks different to anything he's seen before.
At least four companies are rolling out similar models, in the hopes of turning a profit from the US' growing piles of hard-to-sort recyclables.
And investors are taking notice. In November 2019, AMP Robotics announced a $16 million Series A investment from Sequoia Capital.
But what about helping humans get better at choosing what to put in their recycling bins in the first place?
New policies in Shanghai are one of the first steps in China's push to solve its waste problems.
This past summer, citizens will face fines and what are called "social penalties" if they don't sort things properly.
One trash sorting volunteer said, Shanghai started the test run on June 24. "It was very hard for us at the beginning. Everyone was busy, people didn't know how to sort," the volunteer -who requested to be unidentified -said.
"At first we had some hard times," said Shanghai citizen Zhaoju Zhang. "The most difficult part was how to differentiate between dry and wet trash. It was so complicated that we all got confused."
Almost immediately, hundreds of AI-enabled apps sprouted up in order to assist everyday sorting.
But not everyone has access to AI to help parse the new rules, and many complain that complying is tough, and punishments are too harsh.
Kate O'Neill said the new laws are having a "massive cultural impact" and there are "some concerns about how draconian it is, but it's too early to really tell the results. But it certainly has seems to be a massive culture shift."
This kind of cultural shift in how we throw things away would be challenging in the US, where the average person produces twice as much trash as a Chinese citizen.
But experts warn that rethinking the way we deal with garbage is essential, and AI technology offers a promising way forward.
It's even possible for it to identify who created a piece of trash in the first place.
Horowitz explained that robots are able to learn the features of materials. They are able to sparse whether a material is cloudy or opaque. AI robots may even be able to identify symbols of specific brands. All of these abilities help the robots like Max narrow down the source of contamination and what to do with it.
Last year, over 250 companies signed a MacArthur Foundation agreement pledging that 100% of plastic packaging will be easily and safely reused, recycled, or composted by 2025.
Whether or not they make good on this pledge, AI will be quietly watching, and gathering data on the packaging these brands continue to use.
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Fujifilm Showcases Artificial Intelligence Initiative And Advances AI – AiThority
Fujifilm has a long and proven reputation as a trailblazer in medical imaging, and is committed to continuing to innovate and drive positive change in artificial intelligence, said Takuya Shimomura,Chief Technology Officer and Executive Director, FUJIFILM Medical Systems U.S.A., Inc. At RSNA 2019, we look forward to sharing the AI insights and advances weve made by working closely with clinical and research partners for several years. Ultimately, the long-term goal of our AI initiative is to help providers make better decisions that improve patient lives.
Underthe REiLI brand, Fujifilm is developing AI technologies that strongly support diagnostic imaging workflow, leveraging the combination of its deep learning innovations and distinct image processing heritage. Applications currently in development include, but are not limited to: Region Recognition, an AI technology that helps to accurately recognize and consistently extract organ regions, regardless of deviations in shape, presence or absence of disease, and imaging conditions; Computer Aided Detection, an AI technology to reduce the time of image interpretation and support radiologists clinical decision making; Workflow Support, using AI technology to realize optimal study prioritization, alert communications of AI findings, and report population automation.
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Our latest Synapse 7x brings diagnostic radiology, mammography and cardiology together on the server-side, enabling immediate interaction with these modality imaging data sets through a single AI-enabled platform, saidBill Lacy, Vice President, Medical Informatics, FUJIFILM Medical Systems U.S.A., Inc. Were excited to debut this solution for our US customers at RSNA 2019, showing our commitment to progressing AI technology to empower physicians to make more efficient and impactful care decisions.
At booth #4111, attendees can visit Fujifilms AI Lab. The lab will feature dedicated workstations demonstrating REiLI use cases within Synapse PACS. Attendees can witness first-hand the speedand depth of the integrated workflows achieved by unifying Fujifilms REiLI technology with the companys server-side PACS system. Featured in the AI lab will be Fujifilm developed algorithms, to include CT lung nodule, intracerebral hemorrhage, cerebral infarction MR & CT, spine label and bone temporal subtraction to name a few. In addition to the Fujifilm AI development, the AI lab will showcase its strengths by supporting a multitude of integration points in support of partner vendor and provider developed algorithms. This will include Riverains lung nodule, MaxQs stroke, Lunits Chest & 2D Mammography, LPixels MR Aneurysm, Koios US breast, Aidocs pulmonary embolism and Gleamers bone fracture.
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Hear from practicing radiologists, and those that support them, on how Artificial Intelligence (AI) is currently impacting their workflows, and what considerations they would recommend for future deployments. Led by Fujifilms Enterprise Imaging experts, this interactive panel will provide unprecedented insights around the real-world use cases of one of todays most anticipated technologies.
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Fujifilm Showcases Artificial Intelligence Initiative And Advances AI - AiThority