There’s no other way to describe it: Artificial Intelligence (AI) is revolutionizing the world of logistics. That may seem like a cliché, or hype, or buzz, but it is true.
The tech is fundamentally changing the way packages move around the world, from predictive analytics to autonomous vehicles and robotics. Here are the top five ways in which Artificial Intelligence is transforming the logistics industry as we know it:
Since our founding in 2014, ARK Invest has had one focus: Disruptive Innovation. We define disruptive innovation as the introduction of a technologically enabled new product or service that is going to change the way the world works and make it a better place. Seeking to educate investors and innovation enthusiasts, ARK decided to publish “Big Ideas” in 2017. This annual presentation showcases a selection of innovations that we believe will accelerate the pace of change. The research presented aims to illustrate how these ideas are transforming the way the world works and delivering outsized growth opportunities across different industries.
Big Ideas 2018 highlights our research on Mobility-as-a-Service (MaaS), Robotics, Deep Learning, CRISPR Genome-Editing, Cryptoassets, Frictionless Value Transfers, and 3D Printing.
We invite you to download Big Ideas 2018 and share your thoughts with us!
Innomantra - Patent Portfolio of Electric Cars - 2015 ver 1.0F2Innomantra
The purpose of this study is to analyze the importance given by selected major automobile companies in the electric car segment to innovation, based on their Patent Portfolios. Apart from providing an account of innovation and technological development taking place in the automobile, specifically to electric car segment, the analysis of the patenting activity provides an insight into the current trends in the intellectual property generation activity. The study summarizes results of the research that was conducted on Toyota Motor Corporation, Tesla Motor Inc., The Ford Motor Company, Nissan Motor Company Ltd and General Motors Company.
This report covers filing trends of the above mentioned companies along with status of Patents, International Patent Classification and Priority Date. The study also provides the filing trends and status in the field of engineering to which they belong, along with details of all Patents filed by these companies since 2008.
The electric car industry is still in the nascent stage of growth. The electric car market is majorly concentrated in US and Japanese market. There is an increasing trend in the formation of Joint Ventures in research of electric battery technology by the automobile companies. Electronic and electronic components manufacturing companies like Samsung are filing patents in the electric car segment. This shows that electronic companies are planning to enter the electric automobile market. Developing low cost batteries, providing long range and government support are essential for success of mass-market electric vehicle industry.
The major automobile companies have filed patents in electrical machinery and transport segments. This shows that the investment is majorly done in battery and power train technologies. Though Tesla motors started recently in 2003, it is competing with top automobile companies like Toyota, Nissan, Ford and General Motors which were established nearly 100 years ago. Tesla patents are referred by all the major automobile companies and automobile component manufacturing companies. Tesla motors are followed by General motors which show that GM considers Tesla a direct competitor for the company in the electric car segment. Tesla motors did not cite any other patents filed by other automobile companies. This shows that Tesla motors is leading other automobile companies in technology research. Toyota motors have cited patents of all the other major automobile companies which shows that Toyota is following technological research of all the other major automobile companies.
Innomantra - Patent Portfolio of Electric Cars - Report July 2015Innomantra
Executive Summary'
The purpose of this study is to analyze the importance given by selected major automobile companies in the
electric car segment to innovation, based on their Patent Portfolios. Apart from providing an account of innovation
and technological development taking place in the automobile, specifically to electric car segment, the analysisof the patenting activity provides an insight into the current trends in the intellectual property generation activity.
The study summarizes results of the research that was conducted on Toyota Motor Corporation, Tesla Motor Inc.,
The Ford Motor Company, Nissan Motor Company Ltd and General Motors Company.
This report covers filing trends of the above mentioned companies along with status of Patents, International Patent
Classification and Priority Date. The study also provides the filing trends and status in the field of engineering to
which they belong, along with details of all Patents filed by these companies since 2008.
The electric car industry is still in the nascent stage of growth. The electric car market is majorly concentrated
in US and Japanese market. There is an increasing trend in the formation of Joint Ventures in research of
electric battery technology by the automobile companies. Electronic and electronic components manufacturing
companies like Samsung are filing patents in the electric car segment. This shows that electronic companies
are planning to enter the electric automobile market. Developing low cost batteries, providing long range and
government support are essential for success of mass-market electric vehicle industry.
The major automobile companies have filed patents in electrical machinery and transport segments. This shows
that the investment is majorly done in battery and power train technologies. Though Tesla motors started recently
in 2003, it is competing with top automobile companies like Toyota, Nissan, Ford and General Motors which
were established nearly 100 years ago. Tesla patents are referred by all the major automobile companies and
automobile component manufacturing companies. Tesla motors are followed by General motors which show
that GM considers Tesla a direct competitor for the company in the electric car segment. Tesla motors did not cite
any other patents filed by other automobile companies. This shows that Tesla motors is leading other automobile
companies in technology research. Toyota motors have cited patents of all the other major automobile companies
which shows that Toyota is following technological research of all the other major automobile companies
Artificial Intelligence In Automotive Industry: Surprisingly Slow Uptake And ...Bernard Marr
Artificial intelligence has been a hot topic in the automotive industry for years, and we have seen rapid advances in things like autonomous driving. It, therefore, comes as a bit of a surprise that new research shows a slower than expected AI adoption rate. Let’s look at why.
Since our founding in 2014, ARK Invest has had one focus: Disruptive Innovation. We define disruptive innovation as the introduction of a technologically enabled new product or service that is going to change the way the world works and make it a better place. Seeking to educate investors and innovation enthusiasts, ARK decided to publish “Big Ideas” in 2017. This annual presentation showcases a selection of innovations that we believe will accelerate the pace of change. The research presented aims to illustrate how these ideas are transforming the way the world works and delivering outsized growth opportunities across different industries.
Big Ideas 2018 highlights our research on Mobility-as-a-Service (MaaS), Robotics, Deep Learning, CRISPR Genome-Editing, Cryptoassets, Frictionless Value Transfers, and 3D Printing.
We invite you to download Big Ideas 2018 and share your thoughts with us!
Innomantra - Patent Portfolio of Electric Cars - 2015 ver 1.0F2Innomantra
The purpose of this study is to analyze the importance given by selected major automobile companies in the electric car segment to innovation, based on their Patent Portfolios. Apart from providing an account of innovation and technological development taking place in the automobile, specifically to electric car segment, the analysis of the patenting activity provides an insight into the current trends in the intellectual property generation activity. The study summarizes results of the research that was conducted on Toyota Motor Corporation, Tesla Motor Inc., The Ford Motor Company, Nissan Motor Company Ltd and General Motors Company.
This report covers filing trends of the above mentioned companies along with status of Patents, International Patent Classification and Priority Date. The study also provides the filing trends and status in the field of engineering to which they belong, along with details of all Patents filed by these companies since 2008.
The electric car industry is still in the nascent stage of growth. The electric car market is majorly concentrated in US and Japanese market. There is an increasing trend in the formation of Joint Ventures in research of electric battery technology by the automobile companies. Electronic and electronic components manufacturing companies like Samsung are filing patents in the electric car segment. This shows that electronic companies are planning to enter the electric automobile market. Developing low cost batteries, providing long range and government support are essential for success of mass-market electric vehicle industry.
The major automobile companies have filed patents in electrical machinery and transport segments. This shows that the investment is majorly done in battery and power train technologies. Though Tesla motors started recently in 2003, it is competing with top automobile companies like Toyota, Nissan, Ford and General Motors which were established nearly 100 years ago. Tesla patents are referred by all the major automobile companies and automobile component manufacturing companies. Tesla motors are followed by General motors which show that GM considers Tesla a direct competitor for the company in the electric car segment. Tesla motors did not cite any other patents filed by other automobile companies. This shows that Tesla motors is leading other automobile companies in technology research. Toyota motors have cited patents of all the other major automobile companies which shows that Toyota is following technological research of all the other major automobile companies.
Innomantra - Patent Portfolio of Electric Cars - Report July 2015Innomantra
Executive Summary'
The purpose of this study is to analyze the importance given by selected major automobile companies in the
electric car segment to innovation, based on their Patent Portfolios. Apart from providing an account of innovation
and technological development taking place in the automobile, specifically to electric car segment, the analysisof the patenting activity provides an insight into the current trends in the intellectual property generation activity.
The study summarizes results of the research that was conducted on Toyota Motor Corporation, Tesla Motor Inc.,
The Ford Motor Company, Nissan Motor Company Ltd and General Motors Company.
This report covers filing trends of the above mentioned companies along with status of Patents, International Patent
Classification and Priority Date. The study also provides the filing trends and status in the field of engineering to
which they belong, along with details of all Patents filed by these companies since 2008.
The electric car industry is still in the nascent stage of growth. The electric car market is majorly concentrated
in US and Japanese market. There is an increasing trend in the formation of Joint Ventures in research of
electric battery technology by the automobile companies. Electronic and electronic components manufacturing
companies like Samsung are filing patents in the electric car segment. This shows that electronic companies
are planning to enter the electric automobile market. Developing low cost batteries, providing long range and
government support are essential for success of mass-market electric vehicle industry.
The major automobile companies have filed patents in electrical machinery and transport segments. This shows
that the investment is majorly done in battery and power train technologies. Though Tesla motors started recently
in 2003, it is competing with top automobile companies like Toyota, Nissan, Ford and General Motors which
were established nearly 100 years ago. Tesla patents are referred by all the major automobile companies and
automobile component manufacturing companies. Tesla motors are followed by General motors which show
that GM considers Tesla a direct competitor for the company in the electric car segment. Tesla motors did not cite
any other patents filed by other automobile companies. This shows that Tesla motors is leading other automobile
companies in technology research. Toyota motors have cited patents of all the other major automobile companies
which shows that Toyota is following technological research of all the other major automobile companies
Artificial Intelligence In Automotive Industry: Surprisingly Slow Uptake And ...Bernard Marr
Artificial intelligence has been a hot topic in the automotive industry for years, and we have seen rapid advances in things like autonomous driving. It, therefore, comes as a bit of a surprise that new research shows a slower than expected AI adoption rate. Let’s look at why.
Artificial Intelligence (AI) will create $13 trillion in value by 2030, according to McKinsey. That's a pretty good reason to take a closer look at the AI market and see what's under the hood. And that's exactly what I did in the Enterprise VC: 2019 AI Market Review deck.
Rooted in almost 40 years of experience, ARK Invest aims to
identify large-scale investment opportunities resulting from
technological change. We believe innovation is key to growth.
From a broad spectrum of disruptive innovations, “Big Ideas”
represents our annual breakout of technologies that we believe
will accelerate significantly in the months ahead.
Each section provides you with a brief introduction before
illustrating the opportunity. At the end of each section we list
sources for additional research and insights.
To enlighten investors on the impact of these breakthroughs and the opportunities they will create, we began publishing Big Ideas in 2017. This annual research report highlights the latest developments in innovation and offers some of our most provocative research conclusions for the coming year. We hope you enjoy our “Big Ideas” for 2020.
Innovation is Key to Growth - Big ideas - 2019 - ARK InvestPaulo Ratinecas
Why Invest in Disruptive Innovation?
ARK believes that disruptive innovation is key to growth.
We aim to identify large-scale investment opportunities
by focusing on public companies that are the leaders,
enablers, and beneficiaries of disruptive innovation.
Opportunities resulting from disruptive innovation are
often undiscovered or misunderstood by traditional
investment managers who are focused on sectors,
indexes, short-term earnings and price movements.
ARK’s research spans across sectors, industries, and
markets to gain a deeper understanding of the
convergence, market potential, and long-term impact
of disruptive innovation.
DISRUPTIVEINNOVATION
ARK defines ‘‘disruptive innovation’’ as the introduction
of a technologically enabled new product or service
that should transform economic activity by creating
simplicity and accessibility while driving down costs.
Gain insight from the CA World ’14 keynote addresses of Michael Gregoire, CEO, and Amit Chatterjee, EVP, Enterprise Solutions and Technology of CA Technologies.
For more information on the latest DevOps, Management Cloud and Security solutions from CA Technologies, visit: http://bit.ly/1x4fVyO
ARTIFICIAL INTELLIGENCE (AI) ENABLED TRANSPORTATION - DISRUPTING AND OPTIMIZI...OliviaThomas57
Transport in developing or emerging markets often faces severe challenges due to growing populations, urbanization, poor infrastructure, and rising prosperity in some regions, increasing cargo volumes, vehicle traffic, and pollution
Artificial Intelligence and Robotics in 2017Mike Quindazzi
Artificial Intelligence refers to the ability of a computer or a computer-enabled robotic system to process information and produce outcomes in a manner similar to the thought process of humans in learning, decision making and solving problems.
In all actuality, a considerable lot of the organizations that linger behind this advanced pattern don't have enough comprehension about AI to boost its maximum capacity or see the ROI they're passing up a major opportunity for.
Big Data Analytics for Commercial aviation and AerospaceSeda Eskiler
globalaviationaerospace.com
An opportunity for insight in the changing commercial aerospace business
Vision for New Applications of Analytic Insight in Commercial Aerospace
Benefit of Big Data Analytics for the Airline Operator
Modern, Mobile Experience
Big Data Analytics In Action
Predictive Analytics To Prevent Engine Events
Predictive Analytics Improves Safety and Quality
Predictive Analytics Keeps More Planes in the Air
How The Iot Affects The Automotive IndustryJeff Lupient
It is said that by 2020, more than 250 million cars will be connected to the internet. This presents an opportunity for carmakers to open up new areas where they could rake in more revenue. For example, car owners are used to purchasing automotive devices, such as in-car entertainment, dash cams, or diagnostic tools, separately. But car manufacturers instead add such features to new models.
Connected and Self-Driving Vehicles Spark Industry ConvergenceRay Pun
We live in a connected world where industries and organizations are partnering to serve the consumer. Organizations are responding to major trends including the Internet of Things, urban mobility and the automotive revolution that will lead to:
• More than 190 million connected vehicles by 2021.
• Massive growth in big data.
• Ready or not, self-driving vehicles are coming.
As part of a J.D. Power and Acxiom research study, consumers were asked to share their opinions about self-driving and connected vehicles.
ROBOTS AND HUMANS: COMBINED CAPABILITY WILL ENABLE BUSINESSES DELIVER UNEXPEC...VARUN KESAVAN
The last few years have seen a significant infusion of robots in various industries. This trend is expected to continue in the next 3-5 years. Almost 1 million robots are expected to be sold for enterprise use in 2020. There are primarily 3 types of robots - industrial, professional services and software robots.
Professional service robots (e.g., those used in healthcare, retail industries) and software robots (e.g., those used in functions such as Finance, HR, Procurement) will comprise a significant portion of these new robot sales. The market for professional services and software robots is growing much faster than that for industrial robots.
As the use of robots, increase in non-manufacturing industries, the companies which are able to combine the uniquely native human capabilities (e.g., inspiration, aspiration, emotion, empathy, imagination) with powerful robot capabilities (e.g., accurate transaction processing) will be able to re-imagine their business processes and deliver better and newer business outcomes for their stakeholders.
Newshores international college - New shores Bangalorenew shores
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Internet of Things Investment Report - February 2017Harbor Research
Harbor Research releases IoT investment and corporate development report. The IoT landscape has been busy over the past month with over $3.4 billion in investments. We saw an uptake in IoT mentions in quarterly earnings, consolidation in the fiber market, partnerships for the future of secure networks, continued exodus of leadership at a major incumbent chipmaker and large deals funded in AR/MR and autonomous vehicles.
How AI and ML Can Optimize the Supply Chain.pdfGlobal Sources
Artificial intelligence (AI) and machine learning (ML) were already buzzwords in the technology and manufacturing spheres before the pandemic upended the global supply chain. Ironically, with the disruption from the health crisis the push toward translating them into reality has become stronger.
Although there is still a huge gap between “ambition and execution,” as industry analysts put it, the AI and ML promises of higher productivity and better resilience cannot be ignored. A few have started adopting the technologies and many more are expected to follow and reap the benefits of a highly integrated system in the coming years.
Global Sources‘ latest e-book, How Artificial Intelligence & Machine Learning Can Optimize the Supply Chain, explores the potential benefit of technology on key areas, such as data collection and analysis, supply chain optimization, cost reduction, forecasting and planning. It offers a roadmap to augmentation and automation, and how this will help speed up operations, boost efficiency and build resilience. The book also covers challenges posed by the adoption of artificial intelligence and machine learning in current setups, and how they can be overcome.
Read more about the advantages of adopting a highly integrated system using artificial intelligence and machine learning.
Download here to get a free copy of How Artificial Intelligence & Machine Learning Can Optimize the Supply Chain.
Top 9 Trends and Technologies Reshaping Supply Chain Management | The Enterpr...TEWMAGAZINE
Here are 9 major trends and technological developments for the future of supply chain management: 1. Supply Chain Agility 2. Artificial and Augmented Intelligence 3. Real-Time Supply Chain Visibility 4. Digital Twins 5. Blockchain 6. Data Standards and Advanced Analytics
Artificial Intelligence (AI) will create $13 trillion in value by 2030, according to McKinsey. That's a pretty good reason to take a closer look at the AI market and see what's under the hood. And that's exactly what I did in the Enterprise VC: 2019 AI Market Review deck.
Rooted in almost 40 years of experience, ARK Invest aims to
identify large-scale investment opportunities resulting from
technological change. We believe innovation is key to growth.
From a broad spectrum of disruptive innovations, “Big Ideas”
represents our annual breakout of technologies that we believe
will accelerate significantly in the months ahead.
Each section provides you with a brief introduction before
illustrating the opportunity. At the end of each section we list
sources for additional research and insights.
To enlighten investors on the impact of these breakthroughs and the opportunities they will create, we began publishing Big Ideas in 2017. This annual research report highlights the latest developments in innovation and offers some of our most provocative research conclusions for the coming year. We hope you enjoy our “Big Ideas” for 2020.
Innovation is Key to Growth - Big ideas - 2019 - ARK InvestPaulo Ratinecas
Why Invest in Disruptive Innovation?
ARK believes that disruptive innovation is key to growth.
We aim to identify large-scale investment opportunities
by focusing on public companies that are the leaders,
enablers, and beneficiaries of disruptive innovation.
Opportunities resulting from disruptive innovation are
often undiscovered or misunderstood by traditional
investment managers who are focused on sectors,
indexes, short-term earnings and price movements.
ARK’s research spans across sectors, industries, and
markets to gain a deeper understanding of the
convergence, market potential, and long-term impact
of disruptive innovation.
DISRUPTIVEINNOVATION
ARK defines ‘‘disruptive innovation’’ as the introduction
of a technologically enabled new product or service
that should transform economic activity by creating
simplicity and accessibility while driving down costs.
Gain insight from the CA World ’14 keynote addresses of Michael Gregoire, CEO, and Amit Chatterjee, EVP, Enterprise Solutions and Technology of CA Technologies.
For more information on the latest DevOps, Management Cloud and Security solutions from CA Technologies, visit: http://bit.ly/1x4fVyO
ARTIFICIAL INTELLIGENCE (AI) ENABLED TRANSPORTATION - DISRUPTING AND OPTIMIZI...OliviaThomas57
Transport in developing or emerging markets often faces severe challenges due to growing populations, urbanization, poor infrastructure, and rising prosperity in some regions, increasing cargo volumes, vehicle traffic, and pollution
Artificial Intelligence and Robotics in 2017Mike Quindazzi
Artificial Intelligence refers to the ability of a computer or a computer-enabled robotic system to process information and produce outcomes in a manner similar to the thought process of humans in learning, decision making and solving problems.
In all actuality, a considerable lot of the organizations that linger behind this advanced pattern don't have enough comprehension about AI to boost its maximum capacity or see the ROI they're passing up a major opportunity for.
Big Data Analytics for Commercial aviation and AerospaceSeda Eskiler
globalaviationaerospace.com
An opportunity for insight in the changing commercial aerospace business
Vision for New Applications of Analytic Insight in Commercial Aerospace
Benefit of Big Data Analytics for the Airline Operator
Modern, Mobile Experience
Big Data Analytics In Action
Predictive Analytics To Prevent Engine Events
Predictive Analytics Improves Safety and Quality
Predictive Analytics Keeps More Planes in the Air
How The Iot Affects The Automotive IndustryJeff Lupient
It is said that by 2020, more than 250 million cars will be connected to the internet. This presents an opportunity for carmakers to open up new areas where they could rake in more revenue. For example, car owners are used to purchasing automotive devices, such as in-car entertainment, dash cams, or diagnostic tools, separately. But car manufacturers instead add such features to new models.
Connected and Self-Driving Vehicles Spark Industry ConvergenceRay Pun
We live in a connected world where industries and organizations are partnering to serve the consumer. Organizations are responding to major trends including the Internet of Things, urban mobility and the automotive revolution that will lead to:
• More than 190 million connected vehicles by 2021.
• Massive growth in big data.
• Ready or not, self-driving vehicles are coming.
As part of a J.D. Power and Acxiom research study, consumers were asked to share their opinions about self-driving and connected vehicles.
ROBOTS AND HUMANS: COMBINED CAPABILITY WILL ENABLE BUSINESSES DELIVER UNEXPEC...VARUN KESAVAN
The last few years have seen a significant infusion of robots in various industries. This trend is expected to continue in the next 3-5 years. Almost 1 million robots are expected to be sold for enterprise use in 2020. There are primarily 3 types of robots - industrial, professional services and software robots.
Professional service robots (e.g., those used in healthcare, retail industries) and software robots (e.g., those used in functions such as Finance, HR, Procurement) will comprise a significant portion of these new robot sales. The market for professional services and software robots is growing much faster than that for industrial robots.
As the use of robots, increase in non-manufacturing industries, the companies which are able to combine the uniquely native human capabilities (e.g., inspiration, aspiration, emotion, empathy, imagination) with powerful robot capabilities (e.g., accurate transaction processing) will be able to re-imagine their business processes and deliver better and newer business outcomes for their stakeholders.
Newshores international college - New shores Bangalorenew shores
Newshores international college - New shores Bangalore. Newshores international college - New shores Bangalore. Newshores international college - New shores Bangalore. Newshores international college - New shores Bangalore. Newshores international college - New shores Bangalore. Newshores international college - New shores Bangalore. Newshores international college - New shores Bangalore. Newshores international college - New shores Bangalore. Newshores international college - New shores Bangalore. Newshores international college - New shores Bangalore
Internet of Things Investment Report - February 2017Harbor Research
Harbor Research releases IoT investment and corporate development report. The IoT landscape has been busy over the past month with over $3.4 billion in investments. We saw an uptake in IoT mentions in quarterly earnings, consolidation in the fiber market, partnerships for the future of secure networks, continued exodus of leadership at a major incumbent chipmaker and large deals funded in AR/MR and autonomous vehicles.
How AI and ML Can Optimize the Supply Chain.pdfGlobal Sources
Artificial intelligence (AI) and machine learning (ML) were already buzzwords in the technology and manufacturing spheres before the pandemic upended the global supply chain. Ironically, with the disruption from the health crisis the push toward translating them into reality has become stronger.
Although there is still a huge gap between “ambition and execution,” as industry analysts put it, the AI and ML promises of higher productivity and better resilience cannot be ignored. A few have started adopting the technologies and many more are expected to follow and reap the benefits of a highly integrated system in the coming years.
Global Sources‘ latest e-book, How Artificial Intelligence & Machine Learning Can Optimize the Supply Chain, explores the potential benefit of technology on key areas, such as data collection and analysis, supply chain optimization, cost reduction, forecasting and planning. It offers a roadmap to augmentation and automation, and how this will help speed up operations, boost efficiency and build resilience. The book also covers challenges posed by the adoption of artificial intelligence and machine learning in current setups, and how they can be overcome.
Read more about the advantages of adopting a highly integrated system using artificial intelligence and machine learning.
Download here to get a free copy of How Artificial Intelligence & Machine Learning Can Optimize the Supply Chain.
Top 9 Trends and Technologies Reshaping Supply Chain Management | The Enterpr...TEWMAGAZINE
Here are 9 major trends and technological developments for the future of supply chain management: 1. Supply Chain Agility 2. Artificial and Augmented Intelligence 3. Real-Time Supply Chain Visibility 4. Digital Twins 5. Blockchain 6. Data Standards and Advanced Analytics
Evolution of AI ML Solutions - A Review of Past and Future Impact.pdfChristine Shepherd
Need to incorporate technologies that drive unparalleled advancements? If yes, leveraging AI and Machine Learning services helps enterprises to streamline operations and also usher in a new era of possibilities and societal benefits. Whether it's designing novel solutions, creating intelligent products, or optimizing workflows, AI and ML serve as catalysts for innovation, propelling enterprises into the forefront of their respective industries.
The overall impact of artificial intelligencekoteshwarreddy7
Artificial intelligence (AI) can have a transformative impact on international trade. Specific applications in areas such as data analytics and translation services are already lowering barriers to trade. At the same time, there are challenges in Artificial Intelligence App Development that international trade rules could address, such as improving global access to data to train AI systems.
IoT in Logistics and Supply Chain- Role, Benefits and Use Cases.Techugo
Discover how the Internet of Things (IoT) is revolutionizing logistics and supply chain management. IoT devices enable real-time monitoring of inventory, transportation, and delivery, increasing efficiency, reducing costs, and improving customer satisfaction. Explore the role, benefits, and use cases of IoT in logistics and supply chain management, and learn how it can help you streamline your operations and stay ahead of the competition.
Venture Investors Bet AI Can Improve Supply-Chain ManagementLogist.pdfsales223546
Venture Investors Bet AI Can Improve Supply-Chain Management
Logistics could serve as an early test case for how AI can reshape a sector
By
Marc Vartabedian
Follow
Sept. 8, 2023 6:00 am ET
Eclipse, a venture firm focused on industrial technology, has backed startups developing logistics
tech with AI applications including Reliable Robotics, which focuses on autonomous cargo
aviation. Artificial intelligence isnt new to the logistics world. For years, companies have used
the technology to reshape operations. Now, venture-capital investors are betting the overhaul
has just begun.
Venture investors are writing checks to start-upsleveraging AI for a host of emerging supply-
chain applications such as predictive analytics and industrial safety. The data-heavy nature of
logistics makes it ripe for an AI remake, investors and entrepreneurs say, and the sector might
serve as an early test case for how AI can reshape an industry.
I think AI can be such a great place to take all of these varying data sources, structure it and then
drive predictable and accurate analytics that really get to the end goal of when is my cargo going
to get to me, what time and what items are going to arrive, said Kaitlyn Glancy, a partner at
Eclipse, a venture firm focused on industrial technology.
Kaitlyn Glancy is a partner at Eclipse and focuses on supply-chain tech. PHOTO: JOSEPH SEIF
Eclipse has backed startups developing logistics tech with AI applications including Reliable
Robotics, which focuses on autonomous cargo aviation; Cheetah, which is developing demand
forecasting and inventory prediction for restaurants; and Voxel, which leverages computer vision
AI to monitor and score industrial safety in logistics and manufacturing environments.
AI could provide a host of benefits such as helping logistics companies cut costs by reducing
timing inefficiencies, enabling retailers to avoid supply crunches, and allowing consumers to
have better visibility of when goods will arrive.
Recent advancements in AI, such as conversational AI tools like OpenAIs ChatGPT, could
benefit companies. Third-party logistics providers and freight forwarders could boost
productivity by using ChatGPT-like tools to optimize scheduling, planning and pricing, Jonathan
Geurkink, senior analyst for mobility tech and supply-chain tech at analytics firm PitchBook
Data, said in a recent note.
Supply-chain startups saw a huge infusion of capital during the Covid-19 pandemic as venture
investing boomed and the global supply-chain crisis gave these startups the chance to offer
potential solutions. Funding for global logistics startups jumped 75% to $62 billion from 2020 to
2021, according to PitchBook. While it has slowed significantly since, the 2021 capital has
provided a healthy runway for many of these companies.
One deal announced in May highlights the role that AI could play in the sector. Pando offers an
AI software platform to help companies automate their logistics processes. The software allow.
leewayhertz.com-AI in logistics and supply chain Use cases applications solut...alexjohnson7307
In the fast-paced world of logistics and supply chain management, efficiency is key. With the advent of Artificial Intelligence (AI), the industry is experiencing a transformative shift. AI in logistics and supply chain is streamlining operations, optimizing routes, and enhancing decision-making processes like never before. Let's delve into how AI is reshaping this critical sector.
Simply put, it translates into the ability of a computer or computer-controlled robot to perform tasks that are usually associated with intelligent creatures, usually humans. As a result, it exhibits the ability to reason, find meaning, generalize, or learn from experience..
Simply put, it translates into the ability of a computer or computer-controlled robot to perform tasks that are usually associated with intelligent creatures, usually humans. As a result, it exhibits the ability to reason, find meaning, generalize, or learn from experience..
Using the Open Source VS Code Editor with the HPCC Systems PlatformHPCC Systems
As part of the 2018 HPCC Systems Summit Community Day event:
Up first, Matt Butler, Kennesaw State University, briefly discusses his poster, The Future of Automotive Telemetry: Assessing Inherent Risk Implications and Cyber Security Vulnerabilities.
Following, Arjuna Chala presents his breakout session in the User Interfaces track.
Are you a fan of the VS Code Editor for building and debugging your code? Join me as I demonstrate how this can be used as a modern, extensible alternative to the ECL IDE and why most developers choose the VS Code editor due to its benefits of being cross-platform, multi-language support, and open source.
Arjuna Chala is Sr. Director of Special Projects for the HPCC Systems® platform at LexisNexis Risk Solutions®. With almost 20 years of experience in software design, Arjuna leads the development of next generation big data capabilities including creating tools around exploratory data analysis, data streaming and business intelligence. Arjuna strives to understanding new technologies and bring innovative applications and design to the HPCC System platform. Dedicated to development excellence, Arjuna served as a key member of the team to bring the HPCC Systems platform to the open source community. In his work with HPCC Systems community leaders and system integrator partners, Arjuna’s efforts have contributed to the spread of HPCC Systems technology into the enterprise domestically as well as the international markets of China, Brazil, Europe and India. Arjuna has a BS in Computer Science from RVCE, Bangalore University.
Ai in retail sales and crm venkat vajradhar - mediumvenkatvajradhar1
Artificial intelligence in the retail sector is being applied in new ways, from the whole product and service cycle to assembly-to-post customer service interactions, but the key questions for retail players.
IoT in logistics and supply chain management by providing real-time visibility and transparency. It allows the tracking of goods, equipment, and vehicles using sensors, RFID, and other technologies. IoT helps optimize operations by automating inventory management, predicting demand, reducing waste, and enhancing efficiency.
Rapid technological advancements are opening up new possibilities for innovation, intelligence and automation. Intelligent Automation is being used across multiple industries to create new value for businesses and society alike.
This paper is an analysis on the impact machine learning, Artificial Intelligence, and robotics has on the supply chain management. The analysis covers the basis of AI in the SCM mechanisms while defining it from the ground up. Later on, to shed a true light on supply first the paper zooms in on the effects of machines in marketing. From what particular methodologies are deployed in today’s environment extending all the way to its anticipated outcomes. As the reader progresses he/she will find valuable studies on the main segments of machine learning within the supply chain itself. Certain novelties and innovations are scrutinized regarding SCM alongside these studies. These innovations are exemplified by certain cases presented in Part 3. The penultimate section briefly examines the possible drawbacks of the surge in machine application in SCM. The final section compiles the ideas presented in the paper as a whole and gives a glimpse of an estimate for the near future.
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Top 3 improvements that made by ai in logistics venkat k - medium
1. 6/4/2020 Top 3 improvements that made by AI in Logistics - venkat k - Medium
https://medium.com/@venkat34.k/top-3-improvements-that-made-by-ai-in-logistics-413798d43851 1/4
Top 3 improvements that made by AI in Logistics
venkat k
Jun 4 · 4 min read
There’s no other way to describe it: Artificial Intelligence (AI) is revolutionizing the
world of logistics. That may seem like a cliché, or hype, or buzz, but it is true.
The tech is fundamentally changing the way packages move around the world, from
predictive analytics to autonomous vehicles and robotics. Here are the top five ways in
which Artificial Intelligence is transforming the logistics industry as we know it:
1. Predictive Capabilities Skyrocket When AI in Logistics is Implemented
The capabilities of AI are seriously ramping up company efficiencies in the areas of
predictive demand and network planning. Having a tool for accurate demand
forecasting and capacity planning allows companies to be more proactive.
2. 6/4/2020 Top 3 improvements that made by AI in Logistics - venkat k - Medium
https://medium.com/@venkat34.k/top-3-improvements-that-made-by-ai-in-logistics-413798d43851 2/4
By knowing what to expect, they can decrease the number of total vehicles needed for
transport and direct them to the locations where the demand is expected, which leads to
significantly lower operational costs. The tech is using data to its full potential to better
anticipate events, avoid risks, and create solutions.
This allows organizations to then modify how resources are used for maximum benefit
— and Artificial Intelligence can do these equations much faster and more accurately
than ever before.
In general, the predictive analytics solutions in the logistics and supply chains are on the
rise. However, while the technology is available, there is still a scarcity of people who
can make sense out of the incomplete and low-quality data, the case commonly
presented in the logistics industry.
Only a few largest companies can afford to hire a whole team of data science
professionals to develop such a tool in-house, as in the case of UPS. Meanwhile, other
players can also benefit from AI predictive capabilities by implementing already
available solutions. The most well-known examples are Transmetrics and ClearMetal,
which were both mentioned in the latest DHL’s Logistics Trend Radar.
AI analysis can also be used to safeguard against risk. Another good example from DHL
is its platform which monitors more than 8 million online and social media posts to
identify potential supply chain problems. Through advanced machine learning and
natural language processing the system can understand the sentiment of online
conversations and identify potential material shortages, access issues, and supplier
status.
Also Read: Uses Cases of AI in Supply Chain Management
2. Big, clean data
The Artificial Intelligence answer is not only about robots, however. The power of Big
Data is allowing logistics companies to forecast highly accurate outlooks and optimize
future performance better than ever before.
The insights of Big Data, especially when generated by AI, can improve many facets of
the supply chain like route optimization and supply chain transparency.
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Generating clean data has become an important step for AI in logistics companies as
many simply do not have usable figures to implement. Efficiency gains are difficult to
measure as some companies generate their data from multiple points and multiple
people.
Such figures cannot be easily improved at the source, so algorithms are being used to
analyze historical data, identify issues, and improve data quality to the level where
significant transparency on the business is gained.
A good example of data cleansing in action is when companies have incomplete
shipment data, AI can systematically go through past shipments to create precise
deductions on the unknown quantity.
As written previously, these AI algorithms only require 5 to 10 percent of correct data in
order to create a training dataset that can be used as a basis for data cleansing and
enrichment. From there the data offers an accurate estimate of the whole shipments’
properties in how full or empty the vehicle is.
3. Computer vision
Another set of eyes is always a bonus when moving cargo around the world — and this is
especially true when those eyes are connected to state-of-the-art technology.
Computer vision-based AI is allowing us to see things in new ways: including the supply
chain. According to logistics giant DHL, visual inspection powered by AI is identifying
“damage, classifying the damage type, and determining the appropriate corrective
action” faster than ever before.”
IBM Watson is a prime example of what can be possible with AI vision. The machine had
been programmed to identify what damaged train wagons looked like.
Then when cameras were installed along train tracks to gather images of the wagons,
IBM Watson quickly gathered and processed their status. Within a short period of time,
the robot’s visual recognition capabilities improved to an accuracy rate of more than 90
percent.
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Another good example is from retail giant Amazon, who utilizes computer vision
systems which can help to unload a trailer of inventory in only 30 minutes compared to
hours without using such systems.
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