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Automakers Making Deals to Speed Incorporation of AI

Tech companies are helping auto manufacturers to accelerate the incorporation of AI into their software systems supporting self-driving vehicles. (GETTY IMAGES)

By AI Trends Staff

Automakers are making deals with technology companies to produce the next generation of cars that incorporate AI technology in new ways.

Nvidia last week reached an agreement with Mercedes-Benz to design a software-defined computing network for the car manufacturer’s entire fleet, with over-the-air updates and recurring revenue for applications, according to an account in Barron’s.

“This is the iPhone moment of the car industry,” stated Nvidia CEO Jensen Huang, who founded the company in 1993 to make a new chip to power three-dimensional video games. Gaming now represents $6.1 billion in revenue for Nvidia, which is now positioning for its next phase of growth, which will involve AI to a great extent. “People thought we were a videogame company,” stated Huang. “But we’re an accelerated computing company where videogames were our first killer app.”

The Data Center category, which exploits AI heavily, has been a winner for Nvidia, with revenue expected to more than double to $6.5 billion, making it the company’s biggest market.

Nvidia has established its CUDA parallel computing platform and application programming interface model used to develop applications to run on the company’s chips, as a market leader. Released in 2007, CUDA enables software developers and software engineers to use the graphics processing unit for general purpose processing, which is called GPGPU.

From its start producing hardware for videogames, to hardware and software to support AI, now to hardware, software and services for cars, Nvidia sees the opportunity as transformative.  “The first vertical market that we chose is autonomous vehicles because the scale is so great,” Huang stated. “And the life of the car is so long that if you offer new capabilities to each new owner, the economics could be quite wonderful.”

The software-centric computing architecture based on Nvidia’s Drive AGX Orin computer system-on-a-chip. The underlying architecture will be standard in Mercedes’ next generation of vehicles, starting sometime toward the end of 2024, stated Ola Källenius, chairman of the board of management of Daimler AG and head of Mercedes-Benz AG, during a live stream of the announcement, according to an account in TechCrunch.

Ola Källenius, chairman of Daimler AG and head of Mercedes-Benz AG

The two companies plan to jointly develop the AI and automated vehicle applications that include Level 2 and Level 3 driver assistance functions, as well as automated parking functions up to Level 4.

“Many people talk about the modern car, the new car as a kind of smartphone on wheels. If you want to take that approach you really have to look at source software architecture from a holistic point of view,” stated Källenius. “One of the most important domains here is the driving assistant domain. That needs to dovetail into what we call software-driven architecture, to be able to (with high computing power) add use cases for the customer, this case the driving assistant autonomous space.”

Waymo and Volvo Get Together on Self-Driving Electric Vehicles

In another automaker-tech partnership announced last week, Waymo and the Volvo Cars Group announced a new global partnership to develop a self-driving electric vehicle designed for ride-hailing use, according to a report in Reuters.

Waymo, a unit of Alphabet which also owns Google, will be the exclusive global partner for Volvo Cars for developing self-driving vehicles capable of operating safely without routine driver intervention. Waymo will focus on artificial intelligence for the software “driver.” Volvo will design and manufacture the vehicles.

Owned by China’s Zhejiang Geely Holding Group Co., Volvo has a separate agreement to deliver vehicles to ride hailing company Uber Technologies, that Uber will equip to operate as self-driving vehicles. Volvo Cars is continuing to deliver vehicles to Uber. The Uber effort to develop self-driving vehicle technology was disrupted after a self-driving Volvo SUV operated by Uber struck and killed a pedestrian in Arizona in 2018.

Waymo and Volvo did not say when they expect to launch their new ride-hailing vehicle. Waymo said it will continue working with Fiat Chrysler, Jaguar Land Rover, and the Renault Nissan Mitsubishi Alliance.

Startups Assisting Automakers with Self-Driving Car Tech

Meanwhile, a number of startups are assisting automakers with adding AI functions into new models of existing car lines.

AutoX of San Jose, Calif., has focused their self-driving car technology on a retail purpose such as delivering groceries, according to a recent account in builtin. Users can select grocery items from an app and have them delivered; users can also browse the vehicle-based mobile store upon delivery. AutoX has launched a pilot program in San Jose, testing the service within a geo-fenced zone.

AutoX was founded in 2016 by Dr. Jianxiong Xiao (aka. Professor X), a self-driving technologist from Princeton University. The company’s team of engineers and scientists have extensive industry experience in autonomous driving hardware and software. AutoX has eight offices and five R&D centers globally. Investors include Shanghai Auto (China’s largest car manufacturer), Dongfeng Motor (China’s second-largest car manufacturer), Alibaba AEF, MediaTek MTK, and financial institutions. The system has been deployed on 15 vehicle platforms, including one from Ford Motor.

Optimus Ride of Boston offers self-driving vehicles that can operate autonomously within geofenced environments, such as airports, academic campuses, residential communities, office/industrial parts and city zones.

In collaboration with Microsoft, Optimus Ride is working on Virtual Ride Assistant (VRA), to provide dynamic interactions between riders, the vehicle and a remote assistance team. The VRA provides audio-visual tools for riders to be informed about the system, to request changes in destination or routing and to contact a remote assistance system.

The company has deployments at the Brooklyn Navy Yard and Paradise Valley Estates in Paradise Valley, Calif., and a strategic development relationship with Brookfield Properties, developers of Halley Rise, a mixed-use district in Reston, Va.

A spinoff of MIT, Optimus Rid received approval from the Massachusetts Department of Transportation in 2017 to test highly automated vehicles on public streets.

The company incorporated a software system from Nvidia, the Nvidia Drive PX 2, to accelerate its development.

Sertac Karaman, co-founder, president and chief scientist, Optimus Ride

“We believe the computational power needed to make self-driving vehicles a reality is finally coming to market’” with the Nvidia software, stated Sertac Karaman, co-founder, president and chief scientist at Optimus Ride.

Rethink Robotics of Boston and Rheinböllen, Germany, builds smart, collaborative robots to help in industrial automation, and auto manufacturing in particular.

The company was founded in 2008 and acquired in 2018 by the HAHN Group of Germany, which runs a global network of specialized technology companies offering industrial automation and robotic solutions.  A year after the acquisition, HAHN announced a new generation of the Sawyer collaborative robot.

Read the source articles in Barron’s, TechCrunch, Reuters and  builtin.

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Synergy Between AI, 5G and IoT Yields Intelligent Connectivity

The synergy between AI and 5G is likely to lead to dramatic breakthroughs that will have a profound impact on a wide range of industries. (GETTY IMAGES)

By Berge Ayvazian, Senior Analyst and Consultant at Wireless 20/20

The major US mobile operators are all deploying their 5G networks in 2020, and each one claims that AI and machine learning will help them proactively manage the costs of deploying and maintaining new 5G networks.  AT&T recently outlined the company’s blueprint for leveraging artificial intelligence and machine learning (ML) to maximize the return on its 5G network investment.  AT&T’s Mazin Gilbert sees a “perfect marriage” of AI, ML and software defined networking (SDN) to help enable the speeds and low latency of 5G.

AT&T is using AI and ML to map its existing cell towers, fiber lines, and other transmitters that today, to build its 5G infrastructure and to pinpoint the best location for 5G build outs in the future. AT&T has more than 75,000 macro cells in its network and is using AI to guide plans for deploying hundreds of thousands of additional small cells and picocells. If AI detects a cell site isn’t functioning properly, it will signal another tower to pick up the slack.

AT&T is using AI to load balance traffic such as video on its network, and the company is using machine learning to detect congestion on small cells on 5G networks before service degrades. If one area is experiencing a high volume of usage, AI will trigger lower-use cell sites to ensure that speed isn’t compromised.  AT&T is also leveraging AI and ML to improve efforts in forecasting and capacity planning with the dispatch field services that help customers every day. And AI is being used to optimize schedules for technicians, to get as many jobs done during the workday as possible by minimizing drive time between jobs while maximizing jobs completed per technician.

AT&T is building its AI platform to scale from the core to the edge network and is putting more intelligence into its mobile edge compute (MEC) at the customer edge and into its radio access network (RAN).  By putting intelligence closer to the edge, AT&T is starting to load balance traffic across these small cells and move traffic around when needed. AI will also help enable SLAs from networking slicing offerings to AT&T’s customers. AI is also the key ingredient for implementing numerous new projects and platforms for AT&T, which is using AI to manage its third-party cloud arrangements, such as with Microsoft, and in its internal cloud and hybrid clouds.  In addition, AT&T is using AI to define policies that are currently set by systems and employees. AI and the data analytics tell AT&T if any of the policies have conflicts prior to defining them.

AI-driven Automation Transforms 5G Network Reliability and Wireless Field Service

Verizon recently confirmed that its plans for its 5G rollout across the US are ahead of schedule.  Verizon EVP and CTO Kyle Malady has reported that despite the coronavirus pandemic, the largest US wireless operator is successfully moving the technology forward with its 5G and intelligent edge network. Verizon is also using its AI-enabled Verizon Connect intelligent fleet and field service management platform to closely monitor 5G wireless network usage in the areas most impacting customers and communities during the COVID-19 pandemic. Verizon Wireless uses this platform to prioritize network demand, track assets and vehicles, dispatch employees and monitor work being performed for mission-critical customers including hospitals, first responders and government agencies. Reveal Field from Verizon Connect integrates proactive maintenance, intelligent scheduling and dispatching to improve first-time fix rates and reduce mean time to resolution.

AT&T and Verizon are not the only wireless operators focusing on the synergy between 5G and AI.  Orange recently appointed former Orange Belgium CEO, Michaël Trabbia, as chief technology and innovation officer with a mandate to leverage 5G, AI, cloud edge technologies and NFV (network function virtualization) under the French carrier’s Engage2025 strategic plan.  Orange recognizes the need to detect, accelerate and shorten reaction and decision times to confront with confidence the profound changes brought about by the global coronavirus epidemic. There are many uncertainties but also real opportunities for the Orange Post-Covid Strategy; the new CTO will drive AI and 5G innovation to seize these possible opportunities and accelerate digital transformation.

Michaël Trabbia, CEO, Orange Belgium

T-Mobile, AI and Enriching the Customer Experience

T-Mobile has long prided itself as a disruptor in the world of wireless communications, always thinking creatively about the relationship it wants to have with its consumers. That includes T-Mobile’s approach to using AI to enhance customer service. The Uncarrier believes the predictive capabilities of AI and machine learning creates an opportunity to serve customers better and faster, benefiting not just the company and its service agents but also enriching the customer service experience. T-Mobile could have used these advancements in AI-based proactive maintenance and intelligent network management to help address a recent emergency. The carrier had to resolve a 13-hour intermittent network outage that impacted customer ability to make calls and send text messages throughout the US.

After discounting rumors of widespread DDoS attack, Neville Ray, T-Mobile’s president of technology acknowledged the network outage has been linked to increased IP traffic that created significant capacity issues in the network. The trigger event was determined to be the failure of a leased fiber circuit from a third-party provider in the Southeast. The resulting overload resulted in an IP traffic storm that spread from the Southeast to create significant capacity issues across the IMS (IP multimedia Subsystem) core network that supports VoLTE calls. Ray reported that hundreds of engineers worked tirelessly alongside vendors and partners throughout the day to understand the root causes and resolve the issue. FCC Chairman Ajit Pai has called the T-Mobile outage “unacceptable” and added that the Commission would launch an investigation and demand answers regarding the network configuration and traffic related problems that created significant capacity issues in the mobile core network throughout the day.  Now that the nationwide network outage is over, perhaps T-Mobile could leverage AI and machine learning as it works with vendors to “add permanent additional safeguards” that would prevent such an issue from happening again.

Neville Ray, President of Technology, T-Mobile

AI and machine learning are helping 5G wireless carriers and IoT service providers to drive efficiency across their organizations, from the back office to the field. Zinier recently raised $90 million in venture capital to accelerate its effort to integrate AI technology to help automate field service management. The company is integrating AI and automation to create the next generation of intelligent field service automation. “Touchless service delivery” aims to drive predictive maintenance, increase network uptime and reduce costs.  Zinier believes that AI-driven automation can help mobile operators streamline field service processes ahead of 5G deployments. By analyzing real-time data against historical trends, leading wireless operators can leverage AI to create predictive insights and optimize intelligent field service operations. Zinier’s AI-driven automation platform can help wireless field service organizations install and maintain a rapidly increasing number of job sites for new 5G wireless networks.

AI, 5G and Digital Transformation

AI has transformational power for any company, and mobile operators know it will digitally disrupt every industry. Mobile operators are integrating AI-enabled deep automation with their 5G networks, unleashing new business opportunities by accelerating digital transformation. The synergy between AI and 5G is likely to lead to dramatic breakthroughs that will have a profound impact on a wide range of industries.  The convergence of 5G and AI holds tremendous promise to revolutionize healthcare, education, business, agriculture, IoT applications and waves of innovation that have not even been imagined. Verizon currently has seven 5G labs and recently created a new virtual lab to speed development of 5G solutions and applications for consumers, businesses, and government agencies.  Verizon recently launched the first laptop for its 5G Ultra Wideband Connected Device Plan. The new Lenovo Flex 5G laptop will also connect to WiFi, Verizon’s 4G LTE and the new low-band 5G network scheduled to go live later this year.

Having completed its merger with Sprint, T-Mobile recently announced the rebranding of the Sprint Accelerator program.  The T-Mobile Accelerator will continue the founding principles and mission of the original program to drive development in AI, drones, robotics, autonomous vehicles and more on the Un-carrier’s nationwide 5G network.  T-Mobile also unveiled six exciting companies handpicked to participate in this year’s T-Mobile Accelerator and work directly with T-Mobile leaders, other industry experts and mentors to develop and commercialize the next disruptive emerging products, applications and solutions made possible by T-Mobile’s nationwide 5G network.

Wireless Broadband Connectivity and the New Online World

We are all living in a new online world, as social distancing forces many of us to work, communicate and connect in new ways. In the US alone, 316 million Americans have been urged to stay indoors and, when possible, work from home.  As communities around the world adapt to a world with COVID-19, broadband connectivity and access have become more critical to our lives and livelihoods than ever before. Broadband already powers much of our modern lives, but COVID-19 has acted as an accelerant that has driven many essential activities online. All learning, many healthcare services, retail commerce, most workplaces and daily interactions online require a high-speed broadband connection to the internet. The FCC’s 2020 Broadband Deployment Report estimated that more than 21 million Americans lacked high-speed broadband access at year end 2019. A new study from BroadbandNow estimates the actual number of people lacking access to broadband in the US could be twice as high – closer to 42 million. The primary reason for the disparity between these estimates is a flaw in FCC Form 477 self-reporting, where if an ISP reports offering broadband service to at least one household in a census block, that entire block counts as being covered by that provider. Manually checking internet availability for each address has resulted in a more accurate estimation of broadband connections.

Americans living in remote and sparsely populated rural areas risk falling farther behind without broadband access to this online world. But ISP self-reporting and manual cross-checking do not seem to be the most effective ways to collect this data, to identify gaps in broadband performance and to ultimately expand broadband availability. The FCC’s Measuring Broadband America (MBA) program offers rigorous broadband performance testing for the largest wireline broadband providers that serve well over 80% of the U.S. consumer market. The MBA program also uses a Speed Test app, a smartphone-based technology to collect anonymized broadband performance data from volunteers participating in the collaborative, crowdsourcing initiative. This ongoing nationwide performance study of broadband service is designed to improve the availability of information for consumers about their broadband service.

Wireless 20/20 believes that AI and big data analytics should be used to extract more accurate, precise and actionable information from the FCC’s Form 477 reporting and Measuring Broadband America (MBA) data. These new metrics should be used to drive the FCC’s newly adopted Rural Digital Opportunity Fund (RDOF) rules for $20.4 billion Auction 904 rural broadband funding and upcoming spectrum auctions to bridge the digital divide.

The next major disruptive opportunity will come from 5G and AI in changing the way we connect and power our communities.  Given the challenges we are all facing with the COVID-19 pandemic, 5G wireless broadband and AI could be used to enable Tele-health networks, distance learning and advanced IoT networks to power the Fourth Industrial Revolution where working from home becomes the new normal.

Berge Ayvazian leads an integrated research and consulting practice at Wireless 20/20 on 4G/5G Networks and Mobile Internet Evolution. This report is based on a recent presentation he was invited to make for the FCC’s Artificial Intelligence Working Group (AIWG) focusing on the Synergy Between AI, 5G and IoT.  He was asked for his expert opinion on what is real, what is hype, and his opinion of the maturity of AI technology.  Learn more at Wireless 20/20.

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Staid Insurance Industry Exploring AI With Some Caution

Insurance industry taking careful steps in exploring AI for usage-based insurance, deep personalization, faster claims settlements. (Craig Whitehead on Unsplash)

By AI Trends Staff 

The insurance industry is dominated by massive national brands and legacy product lines that have remained largely unchanged for decades. It is a staid industry. This makes the industry ripe for disruption by new technologies and approaches, especially those enabled by AI. 

Venture capitalists see an opportunity and are investing. New York-based Lemonade, started in 2015, has attracted $480 million in funding so far, according to Crunchbase. Lemonade, which started in homeowner and renter’s insurance, recently filed to go public. Released financial information shows the company has a way to go to become profitable. 

Auto insurance, which makes up more than 40 percent of the overall business, is likely to shrink as self-driving cars come onto the roads and fulfill their promise of making driving safer, suggested a KPMG report in 2015. The consultants predicted the auto insurance market will shrink 60 percent over the next 25 years.   

Three trends are likely to drive savings for auto insurers, brokers and policyholders, suggests a recent account in emerj 

Behavioral policy pricing, also known as usage-based insurance (UBI), exploits Internet of Things (IoT) sensors to provide personalized data to pricing platforms, so that safer drivers pay less for auto insurance and people with healthier lifestyles pay less for health insurance. 

Customer Experience and Coverage Personalization, by for example employing chatbots to pull in customers’ geographic and social data to personalize interactions. Insurers are likely to allow users to customize coverage for specific items and events, in what is known as on-demand insurance.  

Faster, Customized Claims Settlement, with virtual claims adjusters making it more efficient to settle and play claims, while decreasing the opportunity for fraud.  

For behavioral policy pricing to work, consumers face a tradeoff: the need to give up a degree of personal privacy in exchange for lower premiums. For example, Neos Ventures offers smart home monitoring and emergency assistance IoT along with a home insurance policy. If the customer installs Neos cameras and sensors in their home, to make gas leaks, water damage and home intrusions less likely, they should save on premiums, is the idea. 

Octo Telematics supports this trend in auto insurance by supplying its Next Generation Platform, with telematics data compiled since the company’s founding in 2002. The platform currently has six million connected users and more than 267 billion miles of driving data, collected over 473,000 crashes and insurance events.   

Octo recently reached an agreement with the Insurance Corporation of British Columbia to launch a one-year project, Techpilot, for newly licensed drivers. The goal is to validate that telematics can modify driving behavior for the better. The system will detect and score driving behaviors such as speeding, braking and cellphone use. 

Joe Schneider, director of corporate finance, KPMG

If the idea that consumers can trade IoT data for lower premiums catches on, the market could move quickly. “Once the massive market disruption begins and traditional insurance business models are flipped upside down, we expect significant turmoil,” stated Joe Schneider, director of corporate finance for KPMG, in a recent report. 

Established Insurance Players Cautious 

The more established insurance industry of profitable companies is moving cautiously into AI. “The insurance industry has only begun its venture into AI, with many traditional insurers’ experimenting with new ways to incorporate it into their day-to-day operations in anticipation of further technological development,” stated a recent report on the impact of AI from the National Association of Insurance Commissioners (NAIC) 

Shaped by their experience in other industries, customers are coming to expect on-demand services, the report noted.  

Many insurance carriers are investing in chatbots, which are available 24/7 to answer questions, give basic advice, check billing information and address common queries and transactions. Insurance companies currently using chatbots include Lemonade, Geico, Allstate and Lincoln Financial.   

The report acknowledges the opportunities and challenges of implementing AI in the insurance business. “Traditional insurers could face challenges integrating AI into their existing technology due to issues such as data quality, privacy and infrastructure compatibility,” the report states. 

To move things along, the insurance group formed the Innovation and Technology Task Force.  A related working group on AI was then established to study the impact of AI on the insurance business, including issues around consumer protection, privacy, and the state-based insurance regulatory framework. The working group was scheduled to make recommendations to the task force at the NAIC’s 2020 summer meeting. 

RPA, Drones In the Mix 

The IoT, machine learning, robotic process automation and drones have opened new avenues to collect real time data, to better predict future events and to speed response times, which will enhance customer experience, suggests Abhijit Patil, Director of Analytics for Wipro, writing recently in BusinessWorld. 

He suggested insurers need to get moving. “Companies need to take a deep dive and embrace digital and AI technologies to survive in today’s digital era,” he stated. The insurer willing to embrace the latest technologies and willing to go the extra mile will stand out in the competitive market place and be the winner.” 

Read the source articles in emerj, at the National Association of Insurance Commissioners and in BusinessWorld. 

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Google Rules AI, with TensorFlow at Foundation, Leadership in Core Products

Google is a dominant player in AI on top of its leading core products shown here and a foundation in TensorFlow for software development. (GETTY IMAGES)

By John P. Desmond, AI Trends Editor

The way Google came from nowhere with the launch of Android in 2007 to today dominating the smartphone operating system market, is what the company is doing now with AI, some market observers suggest.

Google now has an 80 percent share of the worldwide smartphone OS market, and it has seeded the AI market by making its TensorFlow software library open source, putting it at the foundation of many AI applications, suggests a recent account in Analytics Insight.

Some 50 Google products use TensorFlow to build deep learning applications to help differentiate companions in Photos to refinements in the core search engine. Google has become a machine learning organization.

The authors state, “Google has gone through the most recent three years constructing a gigantic platform for artificial intelligence and now they’re unleashing it on the world.”

Differential Privacy Library Aims to Enhance Personal Security

Among recent releases is a “differential privacy library” – used to protect personal data while scanning massive volumes of data. Google wants to engage the development community in this new discussion about privacy protection. The “differential” works to cryptographically mask private information while drawing information from datasets.

By publicly releasing the library on GitHub, development companies with startup assets can explore a rigorous approach to privacy. Healthcare could be an interested segment.

“Differential security is a high-affirmation, analytic means of ensuring that use cases are addressed in a privacy-preserving manner,” stated Miguel Guevara, a Google product manager in the privacy and protection office, in a blog post. Health care researchers may for example want to look at the average amount of time patients spend at different clinics, to see if there are differences in care.

Miguel Guevara, leading product development for differential privacy, Google

AI Can Be Expensive

This work costs some money. A joint project of Carnegie Mellon University and Google to build XLNet, a new language model, generated a discussion about how much the services cost. Eliot Turner, entrepreneur, AI expert and now co-founder of Hologram AI, estimated that it cost the university $245,000 for 2.5 days to train the XLNet model. That was based on a resource breakdown that he outlined, according to an account in Medium.

That number was challenged by Google researchers who specified different resources and arrived at an estimate of $61,440 for 2.5 days. Also likely is the Google team did not charge full price, since it was leading the project.

XLNet was said to outperform the previous state-of-the-art (SoTA) for language tasks, called BERT (Bidirectional Encoder Representations from Transformers). XLNet achieved SoTA results on 18 of 20 language tasks. The model is big, thus expensive to run.

In another project, the University of Washington and the Allen Institute for AI in May 2019 developed Grover, a 1.5-billion-parameter neural net, tailored to detect fake news. Recently outsourced to Github, training for the Grover model cost a reported $25,000.

The GPT-2 language model recently developed by OpenAI, demonstrates impressive performance across a range of language tasks, such as machine translation, question answering, reading comprehension and summarization. The computer power required to run the model for training costs $256/hour.

Many machine learning models are running on smaller footprints. Computer scientist Yoshua Bengio, Turing Award winner and scientific director of MILA (Montreal Institute of Learning Algorithm), was quoted as saying, “Some models are so big that even in MILA (Montreal Institute of Learning Algorithm) we can’t run them because we don’t have the infrastructure for that. Only a few companies can run these very big models they’re talking about.”

In a recent financial report on Google’s business from its parent, Alphabet, notes that Google’s core products such as Search, Android, Maps, Chrome, YouTube, Google Play and Gmail each have over one billion monthly active users. “We believe we are just beginning to scratch the surface,” the report stated, in an account from Strategic Management Insight.

Google is a leader in acquisitions as well, making 118 acquisitions between 2012 and 2015, far outpacing Microsoft, Facebook and Apple.

Google’s revenue is generated by performance and brand advertising, and machine learning and AI are driving the company’s latest innovations, the report notes.

Google sees challenges to its business coming from general purpose search engines (Baidu, Bing, Yahoo), vertical search engines and e-commerce websites (Amazon, eBay, LinkedIn), social networks (Facebook, Twitter); providers of digital video services, enterprise cloud services and digital assistant providers.

One of the best sources of information about what is happening with AI at Google is of course Google itself. The Google AIBlog for example offers accounts of research written by participating engineers.

In one example, A Scalable Approach to Reducing Gender Bias in Google Translate, describes a project to provide gender-specific translations, male and female. The approach was tried with Turkish-to-English, and has recently been expanded to English-to-Spanish.

“We’ve made significant progress since our initial launch by increasing the quality of gender-specific translations,” the researchers stated on the blog, adding, “We are committed to further addressing gender bias in Google Translate and plan to extend this work to document-level translation, as well.”

Read the source articles in Analytics InsightMedium, Strategic Management Insight the Google AIBlog.

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Barclays Innovating in use of AI in Banking

Andy Challis, Managing Director of Principal Investments, Barclays

By AI Trends Staff

Barclays Bank is emerging as an innovator in the use of AI in financial services. The UK bank, ranked 20th on the S&P Global’s list of the top 100 banks, works with suppliers of AI products and services more than it develops AI applications in house, according to a recent account from  emerj.

Here are three AI initiatives underway at Barclays and the industry partners working on each one:

  • Risk Modeling with Simudyne, employs predictive analytics to assess loan risk
  • Voice Recognition for Authentication, with Nuance, aims to apply verification and authentication using voice recognition;
  • Business Process Automation with IBM, a project to automate debit card deactivation, and analyze customer feedback.

London-based Simudyne, founded in 2007, offers simulation software that models complex transactions with large data sets. The company uses “agent-based modeling” to execute banking tasks using simulated transactions and customers, resulting in detailed predictions that aim to improve on past practice. Banking customers try to better understand the upside and downside risks associated with making a certain loan or investment.

Barclays plans to use Simudyne to analyze mortgages, conduct stress tests, study investment opportunities and analyze low liquidity scenarios.

Jes Staley, CEO of Barclays, is quoted on the Simudyne website stating, “Simudyne is ground-breaking technology currently being leveraged across Barclays and enables us to model multiple scenarios on huge datasets, so we can understand our risk, exposure and options.”

Jes Staley, CEO of Barclays

Barclays plans to run the Simudyne simulations in the cloud, which positions  the bank to tap wider sets of data from any of the bank’s data science labs in the hopes of getting an early warning on shifts in banking trends.

Nuance, providing speech recognition and AI, has helped Barclays build a system to authenticate customers using voice over the phone. Nuance offers “voice biometrics” based on natural language processing technology. After the system was implemented, the bank saw a 90 percent reduction in complaints about the security questions the bank had to ask to authenticate customers. The bank also saw a 15 percent reduction in average call times.

Anne Grim, head of Global Client Experience for Barclays Wealth and Investment Management unit, states in a case study on Barclays on the Nuance website, “The use of Nuance’s voice biometric technology has been integral in our mission to deliver an excellent customer experience.”

IBM is providing its Business Process Manager and Blueworks Live products to help Barclays raise customer satisfaction through techniques such as offering fraud alerts via SMS messages, monitor possible identity theft and streamline processing of lost or stolen credit cards.

The system is said to have allowed the bank to replace missing or compromised cards 67% ages, and roll out new business processes 88% faster.

Barclays Eagle Labs unit works with startups and small businesses to help grow the UK economy. An AI at Barclays section on the Eagle Labs website to promote collaboration on AI projects throughout the organization and with its customers. The bank started its “AI Frenzy” events in 2018, inviting industry specialists and the bank’s own experts. The events have also been hosted by universities as a way to help students get introduced to AI and machine learning.

Investment in Simudyne

Barclays entered a closer relationship with Simudyne in 2019, investing $6 million to fund expansion, according to an account in Citya.m. “Partnering with high-growth fintech companies like Simudyne is core to our technology strategy,” stated Andy Challis, managing director of principal investments at Barclays, on the announcement of the investment. “As its adoption becomes more widespread, Simudyne’s platform will ultimately help cultivate a stronger, more efficient tech-enabled financial services sector.”

Writing about the relationship on the Barclays site, C.S. Venkatakrishnan, Barclays Group Chief Risk Officer, emphasized that the agent-based modeling approach has matured and been enabled by a more powerful generation of hardware. This is allowing the bank to create more realistic simulations to account for feedback loops, relationships between agents and complex scenarios that include external factors such as climate impact.

“Simudyne’s platform simplifies the design and operation of models by leveraging the power of distributed computing in the Cloud,” Venkatakrishnan stated. “This allows them to be deployed and scaled on-demand, radically reducing operational costs.”

Justin Lyon, CEO and Founder of Simudyne, stated in the Barclays case study, “Agent-based modelling has opened up a number of opportunities for banks to test any decision before committing resources or taking any action in the physical world. Barclays’ decision to use simulation as a competitive advantage is just one expression of their focus on innovation.”

Read the source article and reports at emerj, Eagle Labs, Citya.m and at Simudyne.

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Maritime Shipping Industry Ripe for AI Disruption

The maritime shipping industry is ripe for disruption by AI, with startups positioning to help established shippers exploit the potential. (GETTY IMAGES)

By AI Trends Staff

The maritime shipping industry is ripe for disruption by AI, with startups positioning to help established shippers exploit the potential.

The industry naturally produces huge amounts of data, and opportunities exist at every step of the supply chain for stakeholders to use AI to augment their operation with positive effects. The convergence of AI and the Internet of Things (IoT) also offers the potential of a more connected intelligence.

At every step in the supply chain, there are opportunities for stakeholders to use AI to positively augment their operation.

This will include predictive analytics – what will happen – prescriptive analytics – what should we do – and adaptive analytics – how should the system adapt to the latest changes, according to an account from Pacific Green Technologies Group. Major cargo shipping companies including Kongsberg, Rolls Royce, Maersk and Wartsila all know that change and developments brought on by AI in the field are poised to leap exponentially.

Startup Sea Machines of Boston is currently testing its perception and situational awareness technology aboard one of Maersk’s newest Winter Palace ice-class container ships. Several other installations are scheduled.

While it would not make the ship autonomous, it is a step towards self-steering vessels, employing technology similar to that of self-driving car features, collecting streams of data from a vessel’s environmental surroundings, identifying and tracking potential conflicts, and displaying the knowledge in the wheelhouse.

Sea Machine’s team includes experienced managers from marine construction, salvage, offshore oil and gas, world-class automation engineers, and autonomy scientists.The company has raised $12.3 million in funding so far, according to Crunchbase.

Orca AI of Tel Aviv offers a collision avoidance system used in marine navigation. The system applies AI to data provided by vision and other sensors. The company is committed to reducing human errors in maritime shipping through use of intelligent, automated vessels. The system helps the captain and navigation crew get an accurate view of the environment in real time, thus assisting in making decisions.

Major shipping companies are also involved in developing their own AI systems for navigation. Wartsila Guidance Marine, a unit of the shipping company Wartsila, in 2018 launched SceneScan, a system that uses laser position reference sensors to guide navigation in harbors. Tracking information is provided relative to structures within the sensor field of view. The system matches its current observation of the scene against a map generated from previous observations of the scene.

Wartsila Guidance Marine successfully completed sea trials of the SceneScan system in April 2019 aboard the Topaz Citadel, a vessel owned by Topaz Energy and Marine, a leading international offshore support vessel company.

Disruption Likely to Include Job Loss in Marine Industry

Longer term, autonomous shipping in the maritime shipping industry is leading to disruption including significant job loss, suggests a recent report in Sea News.

“Autonomous shipping is the future of the maritime industry. As disruptive as the smartphone, the smart ship will revolutionize the landscape of ship design and operations,” stated Mikael Mäkinen, President, Marine at Rolls-Royce Plc.

Mikael Mäkinen, President, Marine at Rolls-Royce Plc.

The timeline for delivery on the promise of autonomous ships is stretched out. Estimates are that the first remote-controlled, unmanned coastal vessels will not be launched until 2025. Fully-autonomous unmanned coastal vessels are not expected until 2035, according to a report by Nautix of Copenhagen, a company offering marine fleet management software.

The three founders of Nautix started their careers at the Singapore Maritime Academy in 2003. In ensuring years, they gained experience in the maritime industry working as deck officers, engineers, superintendents and software innovation managers.

“We’ve felt the pain of our colleagues being let down by the sub-standard tools they’ve been provided. We want to change the status quo. We have the software expertise and the technical knowledge to make a difference,” states Tarang Valecha, co-founder and CEO of Nautix on the company’s website.

Tarang Valecha, co-founder and CEO of Nautix

Serious challenges remain, not just technical in nature. International guidelines and regulations regarding autonomous ships are not likely to be agreed upon within the next decade. The International Transport Workers Federation (ITF) has suggested remote control vessels will lack the skills, knowledge and experience of professional seafarers, so that in the event of an accident or incident requiring immediate attention, the autonomous vessel could be at risk.

The ITF and the International Federal of Shipmasters’ Associations (IFSMA) are very concerned about job loss. Today the industry employs an estimated 1.6 million people on ships and land, who carry out 90 percent of world trade. More than 80 percent of seafarers surveyed by these two organizations have anxiety about possible job losses with the advent of AI and automation.

A study from Oxford University estimated that 47% of US jobs in the maritime industry could be lost over the next 20 years, low-skilled and high-skilled jobs.

Read the source articles and studies from  Pacific Green Technologies Group and in Sea News.

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UPS Committed to Electric Vehicles on an AI Platform

UPS has made a major commitment to electric delivery vehicles incorporating AI, including these bikes in Paris. (UPS PRESS SERVICE)

By AI Trends Staff

UPS, the logistics and delivery company, is spearheading a project in England to explore how AI systems can optimize the charging of electric fleet vehicles, and help integrate onsite renewable energy resources at vehicle depots.

The EV Fleet-Centered Local Energy Systems (EFLES) project is scheduled to start in May at the UPS depot in the Camden borough of London, according to a recent account in electrive. The UK Power Networks Services will provide oversight, while the smart battery and EV-charging software provider Moixa will contribute its GridShare smart AI platform to manage solar, storage and charging assets.

“We have the global expertise, smart-charging infrastructure and resources to host this first-of-a-kind test bed at our Camden facility,” stated UPS sustainable development coordinator Claire Thompson-Sage. “This project will build on our EV infrastructure technology to help develop a holistic local energy system.”

Claire Thompson-Sage, UPS Sustainable Development Coordinator

The GridShare software helps track hundreds of data sources for energy prices, power demand, weather conditions and more, to help determine which charging times are less expensive and which mix of renewable energy makes the most sense at any given point in time.

The ERLES project is the next stage in the UPS partnership with Arrival, the UK-based “generation 2” electric vehicle manufacturer, which developed its newest vehicle with UPS.

UPS recently placed an order for 10,000 electric vehicles from Arrival, to be delivered from 2020 to 2024, according to a recent press release issued by Arrival.

UPS co-developed the Generation 2 vehicles with Arrival, which employed a new method of assembly using low capital, low-footprint micro-factories located to serve local communities and be profitable making thousands of units. The UPS partnership with Arrival was first announced in 2016.

“UPS has been a strong strategic partner of Arrival, providing valuable insight to how electric delivery vans are used on the road and how they can be optimized for drivers, stated Denis Sverdlov, founder and CEO of Arrival. “Together our teams have been creating bespoke [custom] electric vehicles, based on our flexible skateboard platforms, that meet the end-to-end needs of UPS from driving, loading/unloading, depot and back office operations.”

Denis Sverdlov, founder and CEO of Arrival

Carlton Rose, President of UPS Global Fleet Maintenance & Engineering, stated, “Our investment and partnership with Arrival is directly aligned with UPS’s transformation strategy, led by the deployment of cutting-edge technologies.These vehicles will be among the world’s most advanced package delivery vehicles, redefining industry standards for electric, connected and intelligent vehicle solutions.”

UPS Has Had Long Commitment to Electric Vehicles

UPS had 1,000 electric vehicles in its fleet of 112,000 vehicles two years ago. The cost of the vehicle new was found to be no more than regular diesel vehicles, because the cost of electric batteries plummeted 80 percent in six years, according to a UPS press release from April 2018.The electric transporters are expected to create additional value of UPS in operational savings and routing efficiency.

In the U.S., UPS has been working with Workhorse to develop an electric transport vehicle. The target at the outset was a range of 100 miles, with similar procurement costs as an internal combustion motor. The founder and CEO of Workhorse, Steve Burns, late last year bought the Lordstown, Ohio electric vehicle plant from General Motors, through a company he set up to execute the transaction, Lordstown Motors. He has said he wants to build electric pickup trucks for “business and government customers” and has decided the name of the first model will be: Endurance.

Financially, Workhorse has faced some challenges, losing $38 million in 2019 and having little sales in late 2019, according to a recent account in The Verge. Workhorse will own 10 percent of Lordstown Motors, and license to it the intellectual property related to the planned W-15 electric pickup truck. Burns will transfer 6,000 pre-orders for the truck to Lordstown. He is searching for financing, saying he needs $300 million to start product in a year. He plans to run a union shop and produce 500,000 vehicles per year, double the number of Cruze sedans GM made at the plant.

In the case of these new trucks, UPS worked closely with a supplier, Workhorse, to redesign the trucks “from the ground up,” stated Scott Phillippi, UPS’s senior director of maintenance and engineering. Phillippi expects the new design will reduce the truck’s weight by some 1,000 pounds, compared with a diesel or gas-powered vehicle. That plus better batteries will give the truck an electric range of around 100 miles, enough for most routes in and around cities.

Read the source articles and releases at electrive, a UPS press release on the 10,000 vehicle order from Arrival,  and in The Verge., and a UPS press release from April 2018.

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AI Helping Customer Analytics Dive Deeper into Customer Experience

Sephora is credited with making good use of AI in customer analytics with its Visual Artist product, that lets visitors try on cosmetic products. The company has “considered the entire customer journey,” suggests one observer. (GETTY IMAGES)
By AI Trends Staff
Corporate marketers are using AI to more deeply analyze …

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Retailers Pursuing AI to Help Negotiate Prices, Enhance Operations

Retailers are expanding their use of AI beyond online shopping to contract negotiations with suppliers and achieving more efficient operations. (GETTY IMAGES)
By AI Trends Staff
Retailers are not only using AI to enhance the online shopping experience. Walmart has an agreement to pilot AI technology from Pactum to help …

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Executive Interview: Beena Ammanath Boosts Women and Diversity in Tech as AI Expands

Humans for AI was founded by Beena Ammanath to increase opportunities for women and to diversify the tech workforce as AI continues its march through business. (HUMANS FOR AI)
Putting Guardrails in Place for Women and Diversity in Tech as AI Is Infused Into Everything in the Organization
Beena Ammanath …

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