Category Archives: Artificial Intelligence
Artificial Intelligence in Supply Chain Market Research With Amazon Web Services, Inc., project44.| Discusse Reach Good Valuation Queen Anne and…
With its unique ability to process millions of data points per second, AI can help supply chain managers solve tactical and strategic decision-making problems. This is particularly useful when dealing with large amounts of unstructured data. The ability to automate day-to-day tasks can help companies react more quickly to changes or problems in the supply chain. It also ensures that inventory levels are optimized for optimal availability at the lowest possible cost.
The Artificial Intelligence in Supply Chain Market research study provides a contextual analysis of the specialized limits, various challenges, and cost adequacy that influence the Artificial Intelligence in Supply Chain Market. It provides a comprehensive review of the total Market by offering in-depth knowledge, reliable data, and complete estimates about the growth of the Artificial Intelligence in Supply Chain industry. The report estimates were derived from proven research techniques and assumptions. Thus, the report serves as a repository of data and research for every market area, including but not limited to regional markets, applications, types and innovation.
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The research defines and explains the market by gathering relevant and unbiased data. It is growing at a 42.3% of CAGR during the forecast period.
This Artificial Intelligence in Supply Chain study provides an overview of the Market, a table of contents, and information on the multiple research methodologies and data sources used in the reports preparation. It summarizes current Artificial Intelligence in Supply Chain market trends that can assist businesses in understanding the Market and strategizing for future growth. It includes business sector size, industry share, development, major sections, CAGR, and driving factors. Finally, the research findings and conclusion are covered in depth.
Readers will learn about critical competitors and their strategies to acquire extraordinary advantages in the Artificial Intelligence in Supply Chain Market in this section. This fundamental analysis will help readers to determine which competitor contributes the most to the Artificial Intelligence in Supply Chain Market. The best-performing competitors are listed below:
Amazon Web Services, Inc., project44., Deutsche Post AG, FedEx, GENERAL ELECTRIC, Google LLC, IBM, Intel Corporation, Coupa Software Inc.., Micron Technology, Inc.
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Segmentation:
The segmentation study conducted in the Artificial Intelligence in Supply Chain report aids market players in boosting productivity by focusing on their organizations goals and assets in market segments that are most favorable to their objectives. The segments are done based on:
Artificial Intelligence in Supply Chain By type
Machine Learning, Supervised Learning, Unsupervised Learning, and others
Artificial Intelligence in Supply Chain By applications
Fleet Management, Supply Chain Planning, Warehouse Management, Others
The analysis report highlights the shifting facts in the Artificial Intelligence in Supply Chain Market that are used to influence Market, demand, and supply. In addition, it looks into the organizational developments that are expected to influence or disrupt the Markets growing trend. The report covers the worldwide Artificial Intelligence in Supply Chain market, focusing on the regions ;
Synopsis of the Artificial Intelligence in Supply Chain research report
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Artificial Intelligence in Supply Chain Market Research With Amazon Web Services, Inc., project44.| Discusse Reach Good Valuation Queen Anne and...
Artificial Intelligence in Diagnostics Market Recovery and Impact Analysis Report Aidoc, AliveCor, GE Healthcare Queen Anne and Mangolia News -…
Artificial Intelligence in Diagnostics Market research report is the new statistical data source added by Research Cognizance.
Artificial Intelligence in Diagnostics Market is growing at a High CAGR during the forecast period 2022-2029. The increasing interest of the individuals in this industry is that the major reason for the expansion of this market.
Artificial Intelligence in Diagnostics Market research is an intelligence report with meticulous efforts undertaken to study the right and valuable information. The data which has been looked upon is done considering both, the existing top players and the upcoming competitors. Business strategies of the key players and the new entering market industries are studied in detail. Well explained SWOT analysis, revenue share, and contact information are shared in this report analysis.
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Top Key Players Profiled in this report are:
Aidoc, AliveCor, GE Healthcare, Imagen Technologies, Vuno Inc., IDx Technologies Inc., Siemens Healthcare GmbH, Neural Analytics, Riverain Technologies,, Zebra Medical Vision
The key questions answered in this report:
Various factors are responsible for the markets growth trajectory, which are studied at length in the report. In addition, the report lists down the restraints that are posing threat to the global Artificial Intelligence in Diagnostics market. It also gauges the bargaining power of suppliers and buyers, threat from new entrants and product substitute, and the degree of competition prevailing in the market. The influence of the latest government guidelines is also analyzed in detail in the report. It studies the Artificial Intelligence in Diagnostics markets trajectory between forecast periods.
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Regions Covered in the Global Artificial Intelligence in Diagnostics Market Report 2022: The Middle East and Africa (GCC Countries and Egypt) North America (the United States, Mexico, and Canada) South America (Brazil etc.) Europe (Turkey, Germany, Russia UK, Italy, France, etc.) Asia-Pacific (Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)
The cost analysis of the Global Artificial Intelligence in Diagnostics Market has been performed while keeping in view manufacturing expenses, labor cost, and raw materials and their market concentration rate, suppliers, and price trend. Other factors such as Supply chain, downstream buyers, and sourcing strategy have been assessed to provide a complete and in-depth view of the market. Buyers of the report will also be exposed to a study on market positioning with factors such as target client, brand strategy, and price strategy taken into consideration.
The report provides insights on the following pointers:
Market Penetration: Comprehensive information on the product portfolios of the top players in the Artificial Intelligence in Diagnostics market.
Product Development/Innovation: Detailed insights on the upcoming technologies, R&D activities, and product launches in the market.
Competitive Assessment: In-depth assessment of the market strategies, geographic and business segments of the leading players in the market.
Market Development: Comprehensive information about emerging markets. This report analyzes the market for various segments across geographies.
Market Diversification: Exhaustive information about new products, untapped geographies, recent developments, and investments in the Artificial Intelligence in Diagnostics market.
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Research Cognizance is an India-based market research Company, registered in Pune. Research Cognizance aims to provide meticulously researched insights into the market. We offer high-quality consulting services to our clients and help them understand prevailing market opportunities. Our database presents ample statistics and thoroughly analyzed explanations at an affordable price.
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Artificial Intelligence in Diagnostics Market Recovery and Impact Analysis Report Aidoc, AliveCor, GE Healthcare Queen Anne and Mangolia News -...
Artificial Intelligence in Telecommunication Market Analysis, Research Study With IBM Corporation, Microsoft, Intel Corporation Queen Anne and…
Artificial Intelligence in Telecommunication Marketresearch is an intelligence report with meticulous efforts undertaken to study the right and valuable information. The data which has been looked upon is done considering both, the existing top players and the upcoming competitors. Business strategies of the key players and the new entering market industries are studied in detail. Well explained SWOT analysis, revenue share and contact information are shared in this report analysis. It also provides market information in terms of development and its capacities.
Artificial Intelligence in Telecommunication Market is growing at a High CAGR during the forecast period 2022-2029. The increasing interest of the individuals in this industry is that the major reason for the expansion of this market.
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Some of the Top companies Influencing in this Market includes:
IBM Corporation, Microsoft, Intel Corporation, Google, AT&T Intellectual Property, Cisco Systems, Nuance Communications, Inc., Evolv Technology Solutions, Inc., H2O.ai, Infosys Limited, Salesforce.com, Inc., and NVIDIA Corporation
Various factors are responsible for the markets growth trajectory, which are studied at length in the report. In addition, the report lists down the restraints that are posing threat to the global Artificial Intelligence in Telecommunication market. It also gauges the bargaining power of suppliers and buyers, threat from new entrants and product substitute, and the degree of competition prevailing in the market. The influence of the latest government guidelines is also analysed in detail in the report. It studies the Artificial Intelligence in Telecommunication markets trajectory between forecast periods.
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The cost analysis of the Global Artificial Intelligence in Telecommunication Market has been performed while keeping in view manufacturing expenses, labor cost, and raw materials and their market concentration rate, suppliers, and price trend. Other factors such as Supply chain, downstream buyers, and sourcing strategy have been assessed to provide a complete and in-depth view of the market. Buyers of the report will also be exposed to a study on market positioning with factors such as target client, brand strategy, and price strategy taken into consideration.
Key questions answered in the report include:
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Artificial Intelligence in Design and Art Market to Witness Growth Acceleration IBM, 99designs, Toptal Queen Anne and Mangolia News – Queen Anne and…
Artificial Intelligence in Design and Art Market research report is the new statistical data source added by Research Cognizance.
Artificial Intelligence in Design and Art Market is growing at a High CAGR during the forecast period 2022-2029. The increasing interest of the individuals in this industry is that the major reason for the expansion of this market.
Artificial Intelligence in Design and Art Market research is an intelligence report with meticulous efforts undertaken to study the right and valuable information. The data which has been looked upon is done considering both, the existing top players and the upcoming competitors. Business strategies of the key players and the new entering market industries are studied in detail. Well explained SWOT analysis, revenue share, and contact information are shared in this report analysis.
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Top Key Players Profiled in this report are:
IBM, 99designs, Toptal
The key questions answered in this report:
Various factors are responsible for the markets growth trajectory, which are studied at length in the report. In addition, the report lists down the restraints that are posing threat to the global Artificial Intelligence in Design and Art market. It also gauges the bargaining power of suppliers and buyers, threat from new entrants and product substitute, and the degree of competition prevailing in the market. The influence of the latest government guidelines is also analyzed in detail in the report. It studies the Artificial Intelligence in Design and Art markets trajectory between forecast periods.
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Regions Covered in the Global Artificial Intelligence in Design and Art Market Report 2022: The Middle East and Africa (GCC Countries and Egypt) North America (the United States, Mexico, and Canada) South America (Brazil etc.) Europe (Turkey, Germany, Russia UK, Italy, France, etc.) Asia-Pacific (Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)
The cost analysis of the Global Artificial Intelligence in Design and Art Market has been performed while keeping in view manufacturing expenses, labor cost, and raw materials and their market concentration rate, suppliers, and price trend. Other factors such as Supply chain, downstream buyers, and sourcing strategy have been assessed to provide a complete and in-depth view of the market. Buyers of the report will also be exposed to a study on market positioning with factors such as target client, brand strategy, and price strategy taken into consideration.
The report provides insights on the following pointers:
Market Penetration: Comprehensive information on the product portfolios of the top players in the Artificial Intelligence in Design and Art market.
Product Development/Innovation: Detailed insights on the upcoming technologies, R&D activities, and product launches in the market.
Competitive Assessment: In-depth assessment of the market strategies, geographic and business segments of the leading players in the market.
Market Development: Comprehensive information about emerging markets. This report analyzes the market for various segments across geographies.
Market Diversification: Exhaustive information about new products, untapped geographies, recent developments, and investments in the Artificial Intelligence in Design and Art market.
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Artificial Intelligence in Design and Art Market to Witness Growth Acceleration IBM, 99designs, Toptal Queen Anne and Mangolia News - Queen Anne and...
This new AI algorithm could help flying cars survive windy days – Popular Science
Dealing with wind is a part of flying through the air. Crosswinds can pose a challenge for pilots to overcome as they bring their airliners in for landings, or on a smaller level, a gust can push a drone around its small section of airspace.
To give drones better maneuverability when flying in the wind, a team of engineers from CalTech have developed a deep neural networkan artificial intelligence toolto allow a drone to be agile in the presence of blowing air. In a video, the researchers show off a quadcopter drone that, thanks to this software, can pull off figure-eight maneuvers and fly through a small gate, all in the presence of 27-mph-wind in a wind tunnel.
The scientists first had to gather data to be able to train a neural network in order to make the flying machine pull off the stunts. It didnt take much: just 12 minutes of flight time. Thats very little data, reflects Michael OConnell, graduate student in the aerospace department at CalTech and one of the authors of a new study describing the work published Wednesday in the journal Science Robotics. This AI-driven work is called Neural-Fly, and it follows other similar work called Neural Lander and Neural-Swarm.
During training for this latest Neural-Fly experiment, the drone flew in a wind tunnel in the presence of six different wind speeds, with 13.4 mph being the fastest. We basically teach the drone, This is what it looks like when youre hit by 5-mph wind, 10-mph wind, OConnell says. The drone is able to learn what wind looks like, and then when we go fly our figure-eight test trajectory, it uses that experience, and it says, Ive seen this before.
From that data, the team created the deep neural network that then allowed their flying machine to be skilled at carrying out maneuvers in the same wind tunnel, like zooming through a gate in a figure-eight pattern or cruising through two gates in ellipse shape. The speed the drone experienced in testing were faster than what it had encountered in training: about 27 miles per hour. Thats the maximum wind speed this wind tunnel could produce, notes Guanya Shi, another author on the paper and grad student at CalTech. In addition to needing just a small amount of data, the software runs on just a Raspberry Pi, an inexpensive piece of computing equipment.
Soon-Jo Chung, a professor of aerospace and control and dynamics systems at CalTech, and coauthor on the same paper, says that the rate of errors that they see with the new system is between 2.5 4 times better when comparing it to the existing state of the art tech for precise drone flying. The deep neural network flying the drone also has adaptive control, Chung notes, calling it a breakthrough method. This means that the AI can respond adaptively to what happens in real time with the wind.
Chung sees applications for this machine-learning system when it comes to a future in which our skies could be filled with more drones. Companies like FedEx are looking into using large drones to help move packages from one spot to another, and Alphabet-owned Wing is delivering consumer goods via small drones in Texas. Meanwhile, other firms are working on electric flying machines that can carry humansthese are air taxis that can take off and land vertically. The plans for those range from craft designed to fly themselves autonomously with a passenger on board, to those currently planned around human pilots.
Drones that need to have an ultimate safety guarantee could benefit from software like this, Chung says. The ultimate example is obviously, the flying cars, because they have to carry human passengers.
We are hopefully making that future where we can have safe unmanned vehicles that can survive potentially any wind conditionstornadoes, hurricanes, and heavy storms, Chung adds. I cannot say that we can achieve that immediately using our Neural-Fly, but we are making one great step forward toward that goal.
After all, whether the drone is carrying packages or people, it needs to land safely on its pad, even if the wind is blowing in an unpredictable way. Without the promise of a safe landing, the mission might have to be scrubbed before it gets off the ground, or the flying machine rerouted to a different location if its already buzzing through the air.
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This new AI algorithm could help flying cars survive windy days - Popular Science
Artificial Intelligence Technology Solutions (Stock Symbol: AITX) Is Driving The Future of AI and Robotics Innovation, Specializing in Security -…
With orders from Global Retailers, Colleges: Artificial Intelligence Technology Solutions, AITX is at the forefront of the AI and Robotics industry.
Key Highlights:
Artificial Intelligence and Robotic Solutions for Multiple Applications.
Expanding Sales Including Expectation of Large Orders from Global Small Box Retailer and other Operators.
Collaboration with Nightingale Security to Complete Autonomous Air and Ground Security Solution.
New Multi-Unit Order from Renowned East Coast Private College.
Security Robot Order Recently Received from New Dealer with Multiple Fortune 500 Business Relationships.
Artificial Intelligence Technology Solutions AITX is an innovator in delivering artificial intelligence-based solutions that empower organizations to gain new insight, solve complex challenges and fuel new business ideas. Through its next-generation robotic product offerings, the AITX RAD, RAD-M and RAD-G companies help organizations streamline operations, increase ROI, and strengthen the business.
AITX technology improves the simplicity and economics of patrolling and guard services and allows experienced personnel to focus on more strategic tasks. Customers augment the capabilities of existing staff and gain higher levels of situational awareness, all at drastically reduced cost. AITX solutions are well suited for use in multiple industries such as enterprises, government, transportation, critical infrastructure, education, and healthcare.
Video presentations of AITX advancements in AI and Robotics are available via YouTube: https://www.youtube.com/c/AITX-RAD/videos
AITX Subsidiary Robotic Assistance Devices Expects Large Orders from Global Small Box Retailers and other Operator:
On April 29th AITX announced it is awaiting final approval from a pair of significant pending orders. These 2 orders are expected after months of in-person meetings, trade show visits, site walks, and being fully vetted by the clients. The retailer is expected to initially deploy 8 ROSAs as a pilot program at 2 of their locations.
RAD Light My Way from AITX recently won 2 Secure Campus 2022 Awards from Campus Security & Life Safety Magazine. In October RAD Light My Way along with RADs ROSA won CBREs 2021 Best Workplace Experience Solution Award.
ROSA is a compact, self-contained, portable security and communication solution that can be deployed in about 15 minutes. Like other RAD solutions, it only requires power as it includes all necessary communications hardware. ROSAs AI-driven security analytics include human and vehicle detection, license plate recognition, responsive digital signage and audio messaging, and complete integration with RADs software suite notification and autonomous response library. Two-way communication is optimized for cellular, including live video from ROSAs dual high-resolution, full-color, always-on cameras.
AITX Subsidiary Robotic Assistance Devices and Nightingale Security Announce Complete Autonomous Air and Ground Security Solution :
On April 27th AITX announced it will offer special features to its ground-based security robots based on a collaboration with Nightingale Security. Nightingale Security develops fully autonomous, 24/7 physical security aerial drone systems equipped with real-time surveillance cameras & data-gathering sensors.
The result of this development will be the security and facility management industrys first integration of an aerial drone that is capable of being autonomously deployed by mobile or stationary security robot. Conversely, the integrated system will also allow for RADs mobile robot ROAMEO, and future RAD mobile solutions, to be dispatched by a Nightingale aerial drone. The companies confirmed that both organizations plan to offer the integrated solutions through their existing sales channels.
AITX Subsidiary Robotic Assistance Devices Receives Multiple ROSA Order from East Coast Private College:
On April 20th AITX announced an order for 5 ROSA security robots from a renowned private college on the East Coast. AITX confirmed that this order has been received through one of RADs largest authorized dealers. Details of the transaction have not been released due to non-disclosure agreements.
AITX also announced that the devices will be managed by RADs forthcoming incident management system. This cloud-based application advances RADs goal of replacing the security industrys disparate and obsolete user software and is offered by RAD at no additional cost. More than a dozen universities and colleges are actively considering AITX RAD Light My Way, along with multiple RAD devices per location.
Premier Protective Security Signed as New Dealer, Receives First Security Robot Order with Additional Units Expected:
On March 14th AITX announced Premier Protective Security, Inc. as a new authorized dealer, and has received an order for a ROSA security robot from this new dealer. Premier Protective Security is a minority-owned security personnel management company with nationwide engagement.
Premier Protective Security has existing relationships with multiple Fortune 500 companies. The initial ROSA order will be utilized for their demonstration purposes to clients and prospects.
RAD Light My Way an Integrated Facility and Campus Safety Application:
On March 10th AITX formally released RAD Light My Way, the first of its kind facility and campus safety solution where users can control the lighting and security conditions of their environment.
RAD Light My Way offers property management and campus security professionals a new and better way to address security. This breakthrough solution puts the power of security in the hands of employees, faculty, and students through the combination of affordable, smart, interactive technologies, a mobile app, and live remote monitoring and response services.
For more information on Artificial Intelligence Technology Solutions, Inc. (AITX) visit:
http://www.aitx.ai, stevereinharz.com, http://www.radsecurity.com and http://www.radlightmyway.com
DISCLAIMER: This article is purely for informational purposes and is not a recommendation in any way for buying or selling stocks
Media ContactCompany Name: Artificial Intelligence Technology Solutions Inc.Contact Person: Steve ReinharzEmail: Send EmailPhone: 702-990-3271Country: United StatesWebsite: http://www.radlightmyway.com
Press Release Distributed by ABNewswire.com
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How Does Artificial Intelligence Work in a Chatbot? – Robotics and Automation News
On any reputable website, one will find a chatbot to help the users. While interacting with the chatbot, the user engages themselves with a simulated human conversation instead of talking to a real human being.
A chatbot is a computer program or software that has the power to simulate human conversation both textual and voice conversation. The use of chatbots is extremely prevalent, especially in B2C and BCB websites.
Chatbot assistants on the website have many benefits like it reduces overhead costs of the company and providing support to the staff to handle the customer care service in a better way.
Chatbot uses Natural Language Processing NLP to function. NLP is a branch of artificial intelligence that powers the computer to understand both text and spoken words in a manner how human beings function.
Before understanding how chatbots work, it is important to know the three different types of chatbots. The different types of chatbots are rule-based chatbots, intellectual independent chatbots and AI-powered chatbots.
The rule-based chatbots are the simplest type of chatbots which give the users pre-defined options. Such chatbots are commonly visible in WhatsApp.
While engaging in such chatbots on WhatsApp, it is important to have a WhatsApp business account where the logo of the company serves as WhatsApp DP.
Also, WhatsApp Status can be used to keep the users updated about the products and services of the business. For such chatbots to function, the user needs to select one of the predefined options and on the basis of the option chosen by the user, the chatbot provides the solutions to the users.
These chatbots are particularly important to give frequently asked questions that many a time do not require actual human assistance. However, if the customer requires additional assistance, these chatbots are not quite helpful.
The second type of chatbot is an intellectually independent chatbot. These chatbots use machine learning to understand the inputs and requests of the users.
Machine learning gives the computer the ability to become powerful enough to teach itself from the data, recognize patterns and answer the queries of the customer without much human interference.
These chatbots are trained to identify specific keywords and phrases which then trigger the response of the chatbot. With more and more questions from the users, these chatbots train themselves to solve the queries of the customer.
For example, in such functioning chatbots, if the user types a problem such as, I want to know the ETA of the order. The bot will pick words such as, ETA and Order. By identifying these keywords, the chatbot gives predefined answers to the phrases.
The third type of chatbot is the AI-powered chatbot which is basically a combination of both the rule-based and intellectually independent chatbots.
These are the most powerful type of chatbot that simulates human intelligence. The artificial intelligence in such a chatbot is powerful enough to create an intelligent machine that has the ability to think like a woman.
The AI-powered chatbot is intelligent enough to understand free language. They do not need any predefined phrases to solve the queries of the users.
They are designed to understand both the preference of the user and understand the context of the conversation. On the basis of the requirement of the user, they can change the flow of the conversation.
To function in this way, they use machine learning, Natural Language Processing and AI to meet the requirements of the users.
These chatbots function by following different steps. In the very first step, the chatbot split the sentence written by the users in different parts which are also termed tokens.
Secondly, it divides the words used in the sentence in part of speech by identifying the words as adjectives, nouns and verbs, to name a few.
In the third step, the sentence is shortened only to contain the important words to produce a basic phrase. In the fourth step, the named entity is recognized by the chatbot.
In the final step, the chatbot engages in sentiment analysis to identify the mood of the user, which is extremely important to give better customer service to the user.
There are many benefits of using chatbots. For instance, it allows the business to handle multiple conversations in one. It saves both time and money for the company. The most important benefit of the chatbot is that it improves the customer engagement of the user.
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How Does Artificial Intelligence Work in a Chatbot? - Robotics and Automation News
How Artificial Intelligence Can Help Fight Fires in the West – Governing
(TNS) With wildfires becoming bigger and more destructive as the West dries out and heats up, agencies and officials tasked with preventing and battling the blazes could soon have a new tool to add to their arsenal of prescribed burns, pick axes, chain saws and aircraft.
The high-tech help could come way of an area not normally associated with fighting wildfires: artificial intelligence. And space.
Lockheed Martin Space, based in Jefferson County, Colo., is tapping decades of experience of managing satellites, exploring space and providing information for the U.S. military to offer more accurate data quicker to ground crews. They are talking to the U.S. Forest Service, university researchers and a Colorado state agency about how their their technology could help.
The scenario that wildland fire operators and commanders work in is very similar to that of the organizations and folks who defend our homeland and allies. Its a dynamic environment across multiple activities and responsibilities, said Dan Lordan, senior manager for AI integration at Lockheed Martins Artificial Intelligence Center.
Lockheed Martin aims to use its technology developed over years in other areas to reduce the time it takes to gather information and make decisions about wildfires, said Rich Carter, business development director for Lockheed Martin Spaces Mission Solutions.
The concept of a regular fire season has all but vanished as drought and warmer temperatures make Western lands ripe for ignition. At the end of December, the Marshall fire burned 991 homes and killed two people in Boulder County. The Denver area just experienced its third driest-ever April with only 0.06 of an inch of moisture, according to the National Weather Service.
Colorado had the highest number of fire-weather alerts in April than any other April in the past 15 years. Crews have quickly contained wind-driven fires that forced evacuations along the Front Range and on the Eastern Plains. But six families in Monte Vista lost their homes in April when a fire burned part of the southern Colorado town.
Since 2014, the Colorado Division of Fire Prevention and Control has flown planes equipped with infrared and color sensors to detect wildfires and provide the most up-to-date information possible to crews on the ground. The onboard equipment is integrated with the Colorado Wildfire Information System, a database that provides images and details to local fire managers.
Last year we found almost 200 new fires that nobody knew anything about, said Bruce Dikken, unit chief for the agencys multi-mission aircraft program. I dont know if any of those 200 fires would have become big fires. I know they didnt become big fires because we found them.
When the two Pilatus PC-12 airplanes began flying in 2014, Colorado was the only state with such a program conveying the information in near real time, Dikken said. Lockheed Martin representatives have spent time in the air on the planes recently to see if its AI can speed up the process.
We dont find every single fire that we fly over and it can certainly be faster if we could employ some kind of technology that might, for instance, automatically draw the fire perimeter, Dikken said. Right now, its very much a manual process.
Something like the 2020Cameron Peakfire, which at 208,663 acres is Colorados largest wildfire, could take hours to map, Dikken said.
And often the people on the planes are tracking several fires at the same time. Dikken said the faster they can collect and process the data on a fires perimeter, the faster they can move to the next fire. If it takes a couple of hours to map a fire, what I drew at the beginning may be a little bit different now, he said.
Lordan said Lockheed Martin engineers who have flown with the state crews, using the video and images gathered on the flights, have been able to produce fire maps in as little as 15 minutes.
The company has talked to the state about possibly carrying an additional computer that could help crunch all that information and transmit the map of the fire while still in flight to crews on the ground, Dikken said. The agency is waiting to hear the results of Lockheed Martins experiences aboard the aircraft and how the AI might help the state, he added.
They have a strong interest in applying their skills and capabilities to the wildland fire problem, and I think that would be welcome, Finney said.
The lab in Missoula has been involved in fire research since 1960 and developed most of the fire-management tools used for operations and planning, Finney said. Were pretty well situated to understand where new things and capabilities might be of use in the future and some of these things certainly might be.
However, Lockheed Martin is focused on technology and thats not really been where the most effective use of our efforts would be, Finney said.
Prevention and mitigation and preemptive kind of management activities are where the great opportunities are to change the trajectory were on, Finney said. Improving reactive management is unlikely to yield huge benefits because the underlying source of the problem is the fuel structure across large landscapes as well as climate change.
Logging and prescribed burns, or fires started under controlled conditions, are some of the management practices used to get rid of fuel sources or create a more diverse landscape. But those methods have sometimes met resistance, Finney said.
As bad as the Cameron Peak fire was, Finney said the prescribed burns the Arapaho and Roosevelt National Forests did through the years blunted the blazes intensity and changed the flames movement in spots.
Unfortunately, they hadnt had time to finish their planned work, Finney said.
Lordan said the value of artificial intelligence, whether in preventing fires or responding to a fire, is producing accurate and timely information for fire managers, what he called actionable intelligence.
One example, Lordan said, is information gathered and managed by federal agencies on the types and conditions of vegetation across the country. He said updates are done every two to three two years. Lockheed Martin uses data from satellites managed by the European Space Agency that updates the information about every five days.
Lockheed is working with Nvidia, a California software company, to produce a digital simulation of a wildfire based on an areas topography, condition of the vegetation, wind and weather to help forecast where and how it will burn. After the fact, the companies used the information about the Cameron Peak fire, plugging in the more timely satellite data on fuel conditions, and generated a video simulation that Lordan said was similar to the actual fires behavior and movement.
While appreciating the help technology provides, both Dikken with the state of Colorado and Finney with the Forest Service said there will always be a need for ground-truthing by people.
Applying AI to fighting wildfires isnt about taking people out of the loop, Lockheed Martin spokesman Chip Eschenfelder said. Somebody will always be in the loop, but people currently in the loop are besieged by so much data they cant sort through it fast enough. Thats where this is coming from.
2022 MediaNews Group, Inc. Distributed by Tribune Content Agency, LLC.
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How Artificial Intelligence Can Help Fight Fires in the West - Governing
The Rise Of Artificial Intelligence: Will Robots Actually Replace People? – Forbes
Will robots replace human workers?
Robots and artificial intelligence (AI) are expected to permeate our daily lives by 2025. This could have huge implications on several business sectors, most notably health care, customer service, and logistics. Already, AI is responsible for medical research breakthroughs and climate research, not to mention self-driving cars.
Will robots replace human workers?
The answer to that seems to be divided. According to PEW research, about half (48%) of experts surveyed felt that robots and digital agents will displace a significant number of blue- and white-collar jobs. Their concern is that this will increase income inequality and create a mass of virtually unemployable people. The other half (52%) expect robotics and AI to create more jobs than they take. This latter half believes that while AI will replace humans, these experts have faith in human ingenuity to create new jobs, industries, and new ways of making a living much like at the dawn of the Industrial Revolution.
Of interest in the PEW study, both groups are concerned that our educational institutions are not adequately preparing people for the job market of tomorrow.
What is artificial intelligence?
AI in its simplest form stands for artificial intelligence designed to mimic human intelligence to perform tasks. Advocates of AI see this as a positive step forward. It will make it easier for businesses to identify and rectify problems. AI will potentially improve recruitment, cybersecurity, marketing, and standard operating processes.
AI can process large amounts of data and execute complex algorithms quickly and accurately. Each year, AI is getting "smarter" and increasing business efficiency.
What will it be like to work with robots?
Leading expert Martina Mara, Professor of Robopsychology at Johannes Kepler University Linz, suggests we ask a different question: What do we want the future of work to look like? How do we want robots to change our lives? She reminds us that robots are developed by people. While robots can work 24/7, they cannot generalize or contextualize. They have no soft skills.
They're hard wired, literally, to perform highly specific and clearly structured tasks. This is great news for humans we get to pass off the mundane repetitive tasks and adopt those that require critical thinking and problem solving based on human intuition.
AI is evolving and technology is having an increasingly bigger role, but it will complement and augment most jobs, not replace them. In a study involving 1500 companies, researchers found that the most significant performance improvements occurred when humans and machines worked together. Humans perform three crucial roles: they train machines what to do, explain outcomes especially when those are counterintuitive or controversial, and they sustain responsible use of machines. Robots need us just as much as we need them.
Robots are used to do the heavy lifting, literally. In manufacturing, cobots, context-aware robots, perform repetitive actions dominated by heavy lifting, while their human coworker completes complementary tasks that require more dexterity and judgment.
Whether you are pro-bot or anti-bot, you may not have a choice. Rosie the Robot who worked for the Jetsons is probably still far away, but we already have robots that will vacuum our floors and AI has been used in the customer service industry for years.
We need to begin to look at how we can improve technology-related skills while at the same time promoting characteristically human skills. Creativity, intuition, initiative, and critical thinking are human skills that will not likely translate to robots at least not soon. We should already be thinking of how we as employers and employees can harness robots to augment the work we do.
If not already, it won't be long before your next coworker is a robot.
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The Rise Of Artificial Intelligence: Will Robots Actually Replace People? - Forbes
What You Need To Know Before You Start Working With Artificial Intelligence – Forbes
It seems like everyone is talking about artificial intelligence at the moment, and theres good reason for that. We are seeing its revolutionary impact across just about every industry:
In healthcare, where its used to track pandemics and develop vaccines.
In banking and finance, where it detects fraudulent transactions and enables more accurate assessments of lending risks.
In security, where it prevents cyberattacks and data breaches.
In biotechnology, where it augments advances made in fields such as gene editing, promising to help eradicate diseases and put an end to food shortages.
In retail, where it predicts what customers are likely to buy, and puts them in front of them at the time theyre ready to pull the trigger.
What You Need To Know Before You Start Working With Artificial Intelligence
I firmly believe that the true value of AI estimated to be worth $13 trillion to the global economy by 2030 will be realized due to it being accessible to businesses of all shapes and sizes, not just multinational corporations. A vast and eclectic ecosystem of cloud-based, as-a-service platforms reduces the need for expensive infrastructure investments and also means that niche solutions exist to help automate solutions in every industry.
But whether youre simply looking to use AI-augmented marketing tools or to implement machine learning and real-time data analytics from top to bottom of your organization, there are some important points to consider first. The cost of deploying AI may have fallen dramatically in the last decade, but it still requires an investment of time and money, and going into it half-cocked simply because it seems like everyone else is doing it, and you have a fear of missing out can be a recipe for an expensive disaster.
Strategy First
The first principle is to start with a strategy. Simply put, this means understanding what you are trying to achieve. AI technologies are tools that are deployed tactically to achieve strategic objectives. Your strategy should be in line with your business objectives are you aiming for growth? Improving customer retention or lifetime value? Or to reduce overheads involved with design, manufacturing, distribution, or after-sales service? Once you know what you want to achieve, then you can start looking for AI technologies such as machine learning, computer vision, or natural language processing - that can help you get the job done. I like to start by thinking of the key questions a business needs to answer to be able to hit its targets. Who wants to buy our products or services, or how can we improve the value customers get from dealing with us? Remember, always fit technology to a problem, rather than problems to the technology!
What data do I need?
Once you know what your problems are, start thinking about the information you need to answer questions and get them solved. Data might be internal, such as records of customer transactions and interactions, or external, such as information on demographic trends, behavioral data from social media, or publicly available government data. Data can also be structured neat, tidy data that fits into spreadsheets such as statistical data or website clickstream data, or unstructured messy but potentially highly valuable data such as images, videos, speech recordings, or written text. The most advanced AI projects often work with real-time streaming data. This gives us up-to-the minute insights that can be acted on immediately.
What infrastructure do I need?
Building AI infrastructure doesnt necessarily mean creating algorithms from scratch, big data storage solutions, and a complicated systems architecture process. Cloud providers give companies of any size access to pay-as-you-go storage and AI compute solutions, as well as consulting expertise to get them up and running. Nevertheless, its still important to understand the range of services and solutions available in your market. Will a public cloud provider give you everything you need? Particularly if youre interested in working with very sensitive personal data, you may need to consider on-premises or hybrid infrastructure at some level, which gives you more direct control over your information.
What governance issues will I face?
Working with data brings legal as well as moral and ethical obligations. Legislation is tightening around companies involved with collecting and processing personal information from their customers or the wider public, a good example of this is the European Union GDPR, introduced in 2018. The law (and others like it, such as the California Consumer Privacy Act) oblige businesses that collect personal data to operate within a robust legal framework or face harsh financial penalties. Governance also encompasses the ethical and moral questions that need to be addressed when applying technology in ways that might affect peoples lives. In the information age, trust is essential if customers dont trust you with their data, your plans are thwarted before you even start. This means you have to be able to demonstrate that everything youre doing is governed by a strong code of ethics.
What skills will I need?
There's no getting away from it; we are in the middle of an AI skills crisis. What that means is that industry is coming up with ideas for using AI quicker than colleges and universities can churn out graduates with the skills to bring these ideas to life. People with AI engineering talents are hot property on the jobs market, and their salaries reflect that. But AI doesnt build itself (quiet) yet, so you're going to need human skills. They can be acquired either by hiring them in (which, as mentioned, can be expensive) or by upskilling existing workforces. Another option is to partner with outside agencies, such as consultants. The approach you choose will depend to a large extent on the scale of your AI ambitions and the resources you have available.
Do you have a data-driven culture?
To some extent, this is all about attitude. What is the attitude, at all levels, towards technology, data, and AI-driven innovation in your organization? In a data-driven business culture, everyone from the boardroom to the shop floor understands the advantages that can be achieved by putting data at the heart of operations and decision-making. This certainly isnt true of all organizations. Some not-exactly-helpful attitudes that are still prevalent in business include "We aren't ready to be an AI company," "AI is too expensive or complicated," "We know our business better than a machine ever will, or Our customers arent interested in us becoming an AI company. There may be good reasons for all of these attitudes, but too often, they are grounded in a fear of the unknown or an unwillingness to move away from a methodology thats been successful in the past - even when its clearly becoming less successful as the world becomes increasingly digitized. The fact is, you can never know enough about your customers. You can never stop looking for ways to drive efficiency across your operations. And you can never stop making your products smarter and more useful. For almost any business, AI is the key to making these things happen.
Of course, this article only scratches the surface of what you need to know before you start working with AI. But all of these topics (and many more) are covered in-depth in the new edition of my book, Data Strategy: How to Profit From A World of Big Data, Analytics And Artificial Intelligence.
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What You Need To Know Before You Start Working With Artificial Intelligence - Forbes