Category Archives: Artificial Intelligence
Artificial intelligence could be used to diagnose dementia – The Guardian
Its been used to detect eye diseases, make medical diagnoses, and spot early signs of oesophageal cancer. Now it has been claimed artificial intelligence may be able to diagnose dementia from just one brain scan, with researchers starting a trial to test the approach.
The team behind the AI tool say the hope is that it will lead to earlier diagnoses, which could improve outcomes for patients, while it may also help to shed light on their prognoses.
Dr Timothy Rittman, a senior clinical research associate and consultant neurologist at the University of Cambridge, who is leading the study, told the BBC the AI system is a fantastic development.
These set of diseases are really devastating for people, he said. So when I am delivering this information to a patient, anything I can do to be more confident about the diagnosis, to give them more information about the likely progression of the disease to help them plan their lives is a great thing to be able to do.
It is expected that in the first year of the trial the AI system, which uses algorithms to detect patterns in brain scans, will be tested in a real-world clinical setting on about 500 patients at Addenbrookes hospital in Cambridge and other memory clinics across the country.
If we intervene early, the treatments can kick in early and slow down the progression of the disease and at the same time avoid more damage, Prof Zoe Kourtzi, of Cambridge University and a fellow of national centre for AI and data science the Alan Turing Institute, told the BBC. And its likely that symptoms occur much later in life or may never occur.
Dr Laura Phipps at Alzheimers Research UK said Kourtzi was also leading a research project, funded by the charity, that used data from wearable technology to predict diseases like Alzheimers 15-20 years earlier than it was currently possible. Phipps added that the application of AI to brain scans might bring benefits.
To diagnose dementia today, doctors need to rely on the interpretation of brain scans and cognitive tests, often over a period of time, she said. Machine learning models such as those being developed by Prof Kourtzi could give doctors greater confidence in interpreting scans, leading to a more accurate diagnosis for patients.
Phipps added that it is hoped such approaches may eventually help to detect the diseases that cause dementia much earlier.This would have a huge impact on people with dementia and their families, she said.
However Prof Tara Spires-Jones, deputy director of the Centre for Discovery Brain Sciences at the University of Edinburgh, who was not involved in the study, said excitement might be premature.
Finding ways to diagnose dementias very early in the disease process is a very important goal that will help both research and eventually treatment, but it looks like this is still in fairly early stages, she said.
Prof Clive Ballard, a dementia expert at the University of Exeter, agreed. AI has been shown to improve the diagnostic potential of brain scans compared to clinical reading of the scans, but there is so much heterogeneity between individuals that it is completely infeasible for a single scan, biomarker or clinical test to be that certain in a single assessment, he said.
This approach is definitely a positive direction of travel that will lead to improvements in diagnosis, but we need to be really careful not to create false expectations.
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Artificial intelligence could be used to diagnose dementia - The Guardian
Artificial Intelligence could identify dementia years before it first appears – India Today
As supercomputers take on the mighty challenge of accelerating research in the complexities of life sciences, Artificial Intelligence (AI) is not far behind. Researchers are testing a system based on AI to detect neurological disorders like dementia in just one brain scan.
As researchers begin the trial of the system, currently it takes several scans and tests to diagnose dementia. An earlier diagnosis of the disorder could be life-saving and enhance treatment strategies. The team of researchers from the University of Cambridge are hopeful that the AI system will be tested in a real-world clinical setting on about 500 patients, in its first year of trial.
The system uses algorithms to detect patterns in brain scans that are at times even missed by neurological experts. According to a report in BBC, the AI has been able to diagnose dementia in pre-clinical tests and that too years before symptoms develop at a time when there is no sign of damage to the brain.
Professor Kourtzi of Cambridge University, who is part of the study told BBC, "If we intervene early, the treatments can kick in early and slow down the progression of the disease and at the same time avoid more damage. And it's likely that symptoms occur much later in life or may never occur."
As part of the trial, researchers will test whether it works in a clinical setting, alongside conventional ways of diagnosing dementia. The researchers conducting the trial at Addenbrooke's Hospital in the UK will send the reports to participant's doctors for clinical advice.
The AI has been able to diagnose dementia in pre-clinical tests. (Photo: Getty)
"These sets of diseases are really devastating for people. So when I am delivering this information to a patient, anything I can do to be more confident about the diagnosis, to give them more information about the likely progression of the disease to help them plan their lives is a great thing to be able to do," BBC quoted neurologist Dr Tim Rittman, who is leading the study as saying.
So far doctors and neurologists have depended upon brain scans and MRIs to identify neurological disorders, however, the new system under development could significantly boost their abilities in identifying the issues and devise an early treatment strategy.
"AI has been shown to improve the diagnostic potential of brain scans compared to a clinical reading of the scans, but there is so much heterogeneity between individuals that it is completely infeasible for a single scan, biomarker or clinical test to be that certain in a single assessment," Professor Clive Ballard, a dementia expert at the University of Exeter told The Guardian.
The clinical trial underway by the Cambridge team is not the first to use the advances of AI, Cambridge-1, one of the worlds fastest AI supercomputers, has also begun operations in the UK as it looks for new medical breakthroughs with its unique ability to process digital biology, genomics, quantum computing and artificial intelligence.
In its first attempt, Cambridge-1 is working with AstraZeneca, GSK, Guys and St Thomas NHS foundation trust, Kings College London and Oxford Nanopore in developing a deeper understanding of diseases like dementia, look for new drugs, design and run simulations and enhance knowledge around variations in human genomes.
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Artificial Intelligence could identify dementia years before it first appears - India Today
A Peek at Top Artificial Intelligence Funding in July and Aug 2021 – Analytics Insight
The amount of money invested annually into startup companies working in the artificial intelligence (AI) market worldwide has continuously increased. The companies receive funding by showcasing their expertise and their clients reviews.
July 26: Olive deploys the Artificial Intelligence workforce built specifically for healthcare, delivering hospitals and health systems increased revenue, reduced costs, and increased capacity. The objective is to automate all those repetitive, high-volume tasks and workflows, and also to monitor their performance, identify their improvements, and find opportunities for new work as well. As far as the AI funding of this firm is concerned, it is funded by 18 investors. Olive, in over 9 rounds has raised a total funding of $856.3M. Their recent funding was raised on July 1, 2021, from a Series H round. This recent funding amounted to $400 million.
July 27: Covariant, a leading AI Robotics company, today announced it has raised $80 million in Series C funding, bringing its total capitalization to $147 million within two years of the companys public launch. The round was led by returning investors, Index Ventures, with the additional participation of Amplify Partners and Radical Ventures.
July 26: Artificial intelligence computing company Blaize Inc has raised $71 million from investors including Temasek and Franklin Templeton, according to people familiar with the matter. The El Dorado Hills, California-based company is also in early-stage talks with special purpose acquisition companies (SPACs) about a potential deal that would make it public, the sources added. Blaize previously raised $65 million in 2018, at a valuation of about $370 million from investors including Denso, Temasek, GGV Capital, and Daimler. The new series D round of funding will be primarily used to scale out the business and products development. Details on Blaizes latest valuation were not immediately available.
August 2: Nektar.ai, a business-to-business (B2B) sales productivity startup, has raised $6 million as part of the second tranche of its seed round, from investors led by B Capital Group, 3One4 Capital, and Nexus Venture Partners. This takes its total funding in the seed round to $8.1 million, making it one of the biggest such rounds for a Software as a Service (SaaS) startup in the region.
August 10: Amid the broad proliferation of devices and data in our homes and businesses, Neuron7.ai, a new cloud-software company focused on the new category of service intelligence, has emerged from stealth mode and announced a seed investment of $4.2 million from Nexus Venture Partners and Battery Ventures. The company, led by repeat entrepreneurs Niken Patel and Vinay Saini, is helping drive the transformation of customer service into a cloud-based AI-powered workflow, particularly for companies managing complex products in technology, manufacturing, and healthcare, where service organizations are required to support hundreds of product models, versions, errors, and issues.
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A Peek at Top Artificial Intelligence Funding in July and Aug 2021 - Analytics Insight
CompTIA Names Top 10 Applications for Artificial Intelligence and Internet of Things in 2021 Emerging Technology List – PRNewswire
Organizations will invest in technologies that power digital work, automation and human-machine collaboration.
The Emerging Technology Community utilized CompTIA data from a recent quantitative study that consisted of an online survey fielded to professionals during February 2021. A total of 400 businesses based in the United States participated in the survey and identified the most common use cases for IoT and AI. The Emerging Technology Community then narrowed that list to five use cases for each technology based on member input and experience.
"We challenged ourselves to be as relevant as possible, inclusive of our community members' input, and prescriptive with recommendations," said Greg Plum, senior vice president, strategic alliances forMarkee.io and chair of the council. "We made a conscious effort this year to move to a more practical model allowing our audience to understand not only the types of technologies that were emerging, but how they are being leveraged and monetized right now."
Top Artificial Intelligence Use Cases
Top Internet of Things Use Cases
Predictive sales/lead scoring CRM/service delivery optimization Chatbots/digital assistants Asset tracking Industrial monitoring
Cybersecurity Threat Detection Marketing Automation Smart Badges Fleet Management Smart Buildings
"The pandemic has accelerated digital transformation and changed how we work," said Khali Henderson, senior partner at BuzzTheory and vice chair of the Council. "We learned somewhat painfully that traditional tech infrastructure doesn't provide the agility, scalability and resilience we now require. Going forward, organizations will invest in technologies and services that power digital work, automation and human-machine collaboration. Emerging technologies like AI and IoT will be a big part of that investment, which IDC pegs at $656 billion globally this year."
To learn more about the Top 10 Emerging Technologies list and view the infographic visit https://connect.comptia.org/content/infographic/list-of-emerging-technologies.
The CompTIA Emerging Technology Community includes industry executives and thought leaders who have both a keen sense of new technologies, and insight into how to create business opportunities and transform business operations. To learn more about the community and get involved with the group visit https://connect.comptia.org/connect/communities/emerging-technology-community.
About CompTIAThe Computing Technology Industry Association (CompTIA) is a leading voice and advocate for the $5.2 trillion global information technology ecosystem; and the estimated 75 million industry and tech professionals who design, implement, manage, and safeguard the technology that powers the world's economy. Through education, training, certifications, advocacy, philanthropy, and market research, CompTIA is the hub for advancing the tech industry and its workforce. Visithttps://connect.comptia.org/ to learn more.
Media ContactRoger HughlettCompTIA[emailprotected]630-678-8644
SOURCE CompTIA
Indian Artificial Intelligence on the field to help the forces – Goa Chronicle – Goa Chronicle
The hi-tech cameras will now help the security forces to have an eagle eye on infiltrations of China and Pakistan through distinct borders as they are designed in such a way that they can detect a vehicle from a wide distance of 20 km.
A widely spread nation like India has been always on target by Pakistan and China over many years in the past. The Indian army as ever keeps an eagle eye on the infiltrators to protect the land and millions of countrymen. In the last few years, the use of technology has been constantly increasing in military operations for surveillance. However, for such advanced technology India until now has to depend on technology-oriented nations like the USA, Russia, and Israel. But now the domestic Artificial Intelligence agencies are witnessing new dawn in the field. For the development of the same, the defense sector and Indian Artificial Intelligence agencies are working hand in hand with sheer efficacy.
For efficient surveillance on the borders of China, India is to put up exceptional cameras on the field. Optimized Electrotech, a startup from Ahmedabad, Gujarat is to play a prominent role in the initiative. Putting it in simple words, the cameras by the new startup will now be keeping an eagle eye on the borders of China and Pakistan. The device holds multiple significant features among which the most prominent is that it can capture the loaded vehicle from a wide range of 20 km and can detect the resource being carried in it viz human or substantial.
Trial Camera on the Chinese border
As per the reports, Optimized Electrotech co-founder Mr. Sandeep Shah claimed to have been put up a camera for the trial base on the Indo-China border. The results came as the camera was successful in catching the details about infiltrations done and the minute movements of the army from neighboring countries.
Specifications of the Hi-tech device
Detection: the camera detects the minute movements of a vehicle from a wide-ranged distance of 30 km and manly movements from a wide-ranged distance of 18 km.
Identification: the vehicle moving in the area belongs to the army or a normally used vehicle will be detected from a distance of 20 km.
Technology: made with artificial intelligence the camera works with Machine learning techniques and informs the control room about the conspicuous movements in the alerting area with its high-resolution image. The camera rotates 360 degrees.
India to root its position in Border surveillance
Co-founder Sandeep Shah asserted it is near to impossible for only three army men to keep an eye on the borders of India widespread across thousand miles and the core reason why technology is needed on the battlefield. The camera will serve the purpose of catching the minutest details and movements in the civilian restricted area and even beyond help the forces safeguard the land.
He further said, India has been a constant customer of America, Russia, and Israel in terms of technology although it costs much higher. In the last few years, Indian policies have witnessed some dramatic changes which have contributed efficiently to the domestic market as the forces now use (mostly) the domestic surveillance systems and technology developed in the nation itself. However, the benchmark in these systems is recorded very high as Afterall the core concern is Indias security. The companies and start-ups related to the defense sectors have also been actively participating. This will enable the real growth of the nation as Atmanirbhar Bharat in the upcoming years and will be rooting its existence in the efficient border surveillance systems.
Defense policy contributed to better opportunities
The government of India passed a Defense Procurement Policy back in the year 2016 and the prominence was laid on domestic weapons and armaments. This widened the opportunities for the Indian start-ups who dreamt of creating such efficient technological weapons and devices which can contribute to the development process. Today, Optimize Electrotech is one of the top 10 defense start-ups inside the boundaries.
Internal Security to be at the core
The cameras fulfill the demand in various other fields as airports, railway stations, and bus stations as well. It can even be used to detect conspicuous movements in government or non-government buildings, public places, etc. The camera is adorned with the latest technology of face recognition, body temperature, thermal image, and many such.
Manufacturing of such is done in Bengaluru with the price ranging from INR 20 lakhs to 3 crores.
The initiative of Atmanirbhar Bharat has been making a great impact on the Indian economy as well as in the growing process of India at a global plinth. As the brains of India, are now working for the betterment of the land, the day isnt far away when India will make it to a platform that it used to be in its glorious history.
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Indian Artificial Intelligence on the field to help the forces - Goa Chronicle - Goa Chronicle
Global Radiotherapy Markets 2021-2026 – Artificial Intelligence In Radiotherapy, CyberKnife S7 System, Hypofractionation, PreciseART Adaptive…
Dublin, Aug. 13, 2021 (GLOBE NEWSWIRE) -- The "Global Radiotherapy Market - Analysis By Procedure (External Radiation, Internal Radiation), Product, Application, By Region, By Country (2021 Edition): Market Insights and Forecast with Impact of COVID-19 (2021-2026)" report has been added to ResearchAndMarkets.com's offering.
The global radiotherapy market is forecasted to reach USD 7987.01 Million in the year 2020
Increasing healthcare expenditure on the back of growing disposable income, rapid technological advancements along with high prevalence of cancer is expected to drive the radiotherapy market significantly across the globe.
Further, expanding healthcare infrastructure accompanied with rising R&D activities is expected to propel the radiotherapy market during the forecast period. Artificial Intelligence (AI) is a leading trend in the radiotherapy market and is gaining significant popularity in the market. Incorporation of AI innovation in disease care is expected to improve exactness and speed of analysis, help clinical dynamics, and lead to better results.
For instance, Varian Medical Systems, a US-based manufacturer of radiation oncology medical devices, launched Ethos artificial intelligence radiotherapy device. The traditional treatment arranging process takes days to make an improved radiation treatment conveyance plan; however, the new AI advancements are helping to speed up this procedure.
AI is also expected to include deep learning applications in treatment planning, clinical decision support, and automated image-guided adaptive radiation therapy and genomic/radio-biologic data mining, thus supporting the growth of the market. Virtual and remote care via video consultations, online patient portals, patient wellness apps and remote monitoring provide even more data and are being used to overcome shortages of oncologists and to meet patient demands for more access points. Several significant mergers have been taken place in the radiotherapy industry.
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For instance, Siemens Healthineers AG has successfully completed the acquisition of Varian Medical Systems, Inc. With Varian, Siemens Healthineers has the most comprehensive portfolio in the MedTech sector, which offers the company considerable potential for value creation.
With a highly integrated approach, Siemens Healthineers will take the global fight against cancer to a new level. The combined company is creating a unique, highly integrated portfolio of imaging, laboratory diagnostics, artificial intelligence and treatment for the global fight against cancer with significant potential for increased value creation.
The North America region dominates the radiotherapy market. Key factors responsible for ample regional demand of radiotherapy equipment include growing incidence of cancer especially, amongst pediatric patients, favorable reimbursement policies and presence of large multinational companies. In addition, high focus on international sales, mergers and acquisitions by key players in the region along with improving economic conditions is anticipated to drive the market in the forecast period.
Key Topics Covered:
1. Market Overview
2. Impact of COVID-19
3. Global Radiotherapy Market Analysis3.1 Global Radiotherapy Market Value, 2016-20263.2 Global Radiotherapy Market Segmentation By Procedure3.2.1 External-Beam Radiation Therapy- Market Size and Forecast (2016-2026)3.2.2 Internal Radiation Therapy- Market Size and Forecast (2016-2026)3.3 Global Radiotherapy Market Segmentation By Product3.3.1 Linear Accelerators- Market Size and Forecast (2016-2026)3.3.2 Proton Therapy- Market Size and Forecast (2016-2026)3.3.3 Compact Advanced Radiotherapy Systems- Market Size and Forecast (2016-2026)3.4 Global Radiotherapy Market Segmentation By Application3.4.1 Breast Cancer- Market Size and Forecast (2016-2026)3.4.2 Prostate Cancer- Market Size and Forecast (2016-2026)3.4.3 Lung Cancer- Market Size and Forecast (2016-2026)3.4.4 Colorectal Cancer- Market Size and Forecast (2016-2026)3.4.5 Others- Market Size and Forecast (2016-2026)3.5 Global Radiotherapy Market: Regional Analysis
4. Regional Radiotherapy Market Analysis4.1 North America4.1.1 North America Radiotherapy Market: Size and Forecast (2016-2026), By Value4.1.2 North America Radiotherapy Market - Prominent Companies4.1.3 Market Segmentation By Procedure (External-Beam Radiation Therapy and Internal Beam Radiation Therapy)4.1.4 Market Segmentation By Product (Linear Accelerators, Proton Therapy and Compact Advanced Radiotherapy Systems)4.1.5 Market Segmentation By Application (Breast Cancer, Lung Cancer, Colorectal Cancer, Prostate Cancer and Others)4.1.6 North America Radiotherapy Market: Country Analysis4.1.7 Market Opportunity Chart of North America Radiotherapy Market - By Country, By Value (Year-2026)4.1.8 Competitive Scenario of North America- By Country4.1.9 United States Radiotherapy Market: Size and Forecast (2016-2026), By Value4.1.10 Prominent Companies in Radiotherapy Market4.1.11 United States Radiotherapy Market Segmentation By Procedure, Product and Application4.1.12 Canada Radiotherapy Market: Size and Forecast (2016-2026), By Value4.1.13 Canada Radiotherapy Market Segmentation By Procedure, Product and Application4.2 Europe4.3 Asia Pacific
5. Market Dynamics5.1 Growth Drivers5.1.1 Increasing incidence & prevalence of cancer5.1.2 Range of Healthcare Applications5.1.3 Increasing Number of Conferences and Symposium to Boost Awareness about Radiation Therapy5.1.4 Favorable Government Initiatives5.1.5 Rising healthcare expenditure across developing countries5.1.6 Technological advancements5.2 Key Trends and Developments5.2.1 Artificial Intelligence In Radiotherapy5.2.2 CyberKnife S7 System5.2.3 Hypofractionation5.2.4 PreciseART Adaptive Radiation Therapy Option5.2.5 Tomotherapy Systems, including Radixact, the next generation Tomotherapy platform5.3 Challenges5.3.1 Lack of adequate healthcare infrastructure5.3.2 Risk of radiation exposure
6. Competitive Landscape6.1 Global Mosquito Repellent Market6.1.1 Key Players - Market Share Comparison6.1.2 Key Players - Revenues Comparison6.1.3 Key Players - Market Cap Comparison6.1.4 Key Players - R&D Expenditures Comparison
7. Company Profiles7.1 Business Overview7.2 Financial Overview7.3 Business Strategies
For more information about this report visit https://www.researchandmarkets.com/r/6shrnp
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Global Radiotherapy Markets 2021-2026 - Artificial Intelligence In Radiotherapy, CyberKnife S7 System, Hypofractionation, PreciseART Adaptive...
The Convergence: Artificial Intelligence and IoT – IoT For All
Artificial Intelligence of Things (AIoT) is the next key step for IoT transforming the process of analyzing data and turning it into action.
IoT will help with a new generation of AI enablement due to the aggregation nature of IoT. At its core, IoT is gathering massive amounts of data. And as that data is processed through the data-hungry algorithms of AI, the analytical and action parts of IoT will be greatly enhanced.
IoT is key for collecting relevant, intelligent data and communicating it to be processed, analyzed, and made actionable. The role of AI within IoT is to streamline making sense out of all the data collected. It will open new channels for IoT Applications, as it will be incredibly efficient to analyze data coming from thousands of endpoints.
The ability to analyze vast quantities of data will lead to many benefits, including:
Increase operational efficiency:The ability of artificial intelligence to predict circumstances based on trends through historical data can increase efficiency for many verticals, including fleet, assets, logistics, and manufacturing.
Boost safety:AIoT can increase safety in several ways. For example, using computer vision on a manufacturing floor to monitor employees or using virtual or augmented reality in hazardous situations. Artificial vision is leveraged in fleet management solutions to monitor driver behavior and use real-time alerts to prevent accidents, such as falling asleep behind the wheel.
Mitigate downtime: In manufacturing, unplanned downtime due to machine or equipment failure is one of the leading causes of revenue loss. With artificial intelligence analyzing data generated through IoT sensors on machine equipment, predictive maintenance can mitigate the risk of unplanned downtime and allow manufacturers to plan for machine maintenance.
Utility automation:In homes, smart buildings, and smart cities, utilities can be managed via AIoT based on trends. Not only does this create ease for consumers and citizens, but it can also increase safety, aid in traffic management, and bolster sustainability.
One of the most encouraging running themes in this new era of IoT is how emerging technologies work strongly together instead of competitively. 5G has incredible speed and low latency, but in mission-critical communications such as robotics and autonomous vehicles the need for lower latency is further supported through edge computing.
Artificial intelligence can run more efficiently when closer to the edge rather than being sent to the cloud for computation. Automation through AI in those mission-critical communications will be utilized to the full potential when leveraging edge computing.
Much like how 5G, the edge, and AIoT can work in support of each other, cloud computing will not be replaced by edge computing. The cloud still provides flexible, agile, and anywhere data access for organizations big and small.
The decision between cloud and edge depends on the individual Applications. Distributed computing allows organizations to pick and choose between the different options. Some Applications might pull together a hybrid cloud approach (public and private) and tie in some edge computing while also leveraging a local data center.
The pitfall to having so many different options in computing and analytics is that it can be difficult to decide which options are optimized for your business case. Thats why working with an expert strategic partner can not only help you make the best decisions but streamline the process to bring your solution to market faster.
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The Convergence: Artificial Intelligence and IoT - IoT For All
Digital transformation depends on diversity – TechCrunch
Across industries, businesses are now tech and data companies. The sooner they grasp and live that, the quicker they will meet their customer needs and expectations, create more business value and grow. It is increasingly important to reimagine business and use digital technologies to create new business processes, cultures, customer experiences and opportunities.
One of the myths about digital transformation is that its all about harnessing technology. Its not. To succeed, digital transformation inherently requires and relies on diversity. Artificial intelligence (AI) is the result of human intelligence, enabled by its vast talents and also susceptible to its limitations.
Therefore, it is imperative for organizations and teams to make diversity a priority and think about it beyond the traditional sense. For me, diversity centers around three key pillars.
People are the most important part of artificial intelligence; the fact is that humans create artificial intelligence. The diversity of people the team of decision-makers in the creation of AI algorithms must reflect the diversity of the general population.
This goes beyond ensuring opportunities for women in AI and technology roles. In addition, it includes the full dimensions of gender, race, ethnicity, skill set, experience, geography, education, perspectives, interests and more. Why? When you have diverse teams reviewing and analyzing data to make decisions, you mitigate the chances of their own individual and uniquely human experiences, privileges and limitations blinding them to the experiences of others.
Collectively, we have an opportunity to apply AI and machine learning to propel the future and do good. That begins with diverse teams of people who reflect the full diversity and rich perspectives of our world.
Diversity of skills, perspectives, experiences and geographies has played a key role in our digital transformation. At Levi Strauss & Co., our growing strategy and AI team doesnt include solely data and machine learning scientists and engineers. We recently tapped employees from across the organization around the world and deliberately set out to train people with no previous experience in coding or statistics. We took people in retail operations, distribution centers and warehouses, and design and planning and put them through our first-ever machine learning bootcamp, building on their expert retail skills and supercharging them with coding and statistics.
We did not limit the required backgrounds; we simply looked for people who were curious problem solvers, analytical by nature and persistent to look for various ways of approaching business issues. The combination of existing expert retail skills and added machine learning knowledge meant employees who graduated from the program now have meaningful new perspectives on top of their business value. This first-of-its-kind initiative in the retail industry helped us develop a talented and diverse bench of team members.
AI and machine learning capabilities are only as good as the data put into the system. We often limit ourselves to thinking of data in terms of structured tables numbers and figures but data is anything that can be digitized.
The digital images of the jeans and jackets our company has been producing for the past 168 years are data. The customer service conversations (recorded only with permissions) are data. The heatmaps from how people move in our stores are data. The reviews from our consumers are data. Today, everything that can be digitized becomes data. We need to broaden how we think of data and ensure we constantly feed all data into AI work.
Most predictive models use data from the past to predict the future. But because the apparel industry is still in the nascent stages of digital, data and AI adoption, having past data to reference is often a common problem. In fashion, were looking ahead to predict trends and demand for completely new products, which have no sales history. How do we do that?
We use more data than ever before, for example, both images of the new products and a database of our products from past seasons. We then apply computer vision algorithms to detect similarity between past and new fashion products, which helps us predict demand for those new products. These applications provide much more accurate estimates than experience or intuition do, supplementing previous practices with data- and AI-powered predictions.
At Levi Strauss & Co., we also use digital images and 3D assets to simulate how clothes feel and even create new fashion. For example, we train neural networks to understand the nuances around various jean styles like tapered legs, whisker patterns and distressed looks, and detect the physical properties of the components that affect the drapes, folds and creases. Were then able to combine this with market data, where we can tailor our product collections to meet changing consumer needs and desires and focus on the inclusiveness of our brand across demographics. Furthermore, we use AI to create new styles of apparel while always retaining the creativity and innovation of our world-class designers.
In addition to people and data, we need to ensure diversity in the tools and techniques we use in the creation and production of algorithms. Some AI systems and products use classification techniques, which can perpetuate gender or racial bias.
For example, classification techniques assume gender is binary and commonly assign people as male or female based on physical appearance and stereotypical assumptions, meaning all other forms of gender identity are erased. Thats a problem, and its upon all of us working in this space, in any company or industry, to prevent bias and advance techniques in order to capture all the nuances and ranges in peoples lives. For example, we can take race out of the data to try and render an algorithm race-blind while continuously safeguarding against bias.
We are committed to diversity in our AI products and systems and, in striving for that, we use open-source tools. Open-source tools and libraries by their nature are more diverse because they are available to everyone around the world and people from all backgrounds and fields work to enhance and advance them, enriching with their experiences and thus limiting bias.
An example of how we do this at Levi Strauss & Company is with our U.S. Red Tab loyalty program. As fans set up their profiles, we dont ask them to pick a gender or allow the AI system to make assumptions. Instead, we ask them to pick their style preferences (Women, Men, Both or Dont Know) in order to help our AI system build tailored shopping experiences and more personalized product recommendations.
Diversity of people, data, and techniques and tools is helping Levi Strauss & Co. revolutionize its business and our entire industry, transforming manual to automated, analog to digital, and intuitive to predictive. We are also building on the legacy of our companys social values, which has stood for equality, democracy and inclusiveness for 168 years. Diversity in AI is one of the latest opportunities to continue this legacy and shape the future of fashion.
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Digital transformation depends on diversity - TechCrunch
T-Street talk: The future dominance of artificial intelligence, we will focus on these 6 companies … – The Press Stories
After Govt, artificial intelligence becomes an important need for us. That is why large companies are increasing their productivity and developing new products through technology based on artificial intelligence (AI) and machine learning.
What is artificial intelligence?
Artificial intelligence is a branch of computer science that works to create intelligent machines. The important thing is that these machines think like humans. Speech recognition, problem solving, learning and planning. This information was provided by Kshitij Mahajan of Complete Circle Consultants Pvt. But we do not recommend the companies mentioned by them, we only give information about these companies and their shares for your information.
Bosch
By 2025, AI will be used in all PASS products. The Bosch Indigo S + is a good example. This is a robot lawn trio. You can enable this with voice control by Amazon Alexa. A similar Bosch Sound Sea is a sensor system that uses AI-based audio analysis.
Happy minds
Hobby Minds Tech Ltd. provides digital transformation for technology providers and all companies. The Digital Transformation of Happiest Minds uses technologies such as AI blockchain, cloud, digital process automation, Internet of Things, robotics / drones, security, virtual / augmented reality.
Scient
Scient is a company that serves digital map developers. This company facilitates the safe operation of automatic vehicles.
Affecting India
Affle is a global technology company. Affley makes extensive use of AI in your business.
Sensor technologies
The company is very confident in AI. AI is where digital technology was some time ago. Sensor technologies focus on AI. In the last 2 years, the company has registered 100 patents in its name.
SoxSoft
Soxoft offers its customers a wide range of services such as intelligent automation, legacy modernization, managed infrastructure support, advanced analysis, and quality assurance.
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T-Street talk: The future dominance of artificial intelligence, we will focus on these 6 companies ... - The Press Stories
Artificial Intelligence Solutions Spending to Reach Half Trillion Dollars By 2024 According to Market Forecasts – Digital Information World
Artificial intelligence is one of the hottest topics out there right now because of the fact that this is the sort of thing that could potentially end up taking us to a whole new level in terms of technological advancement and the like. The IDC, a company that specializes in making reports based on market intelligence, recently releases an annual report that forecasts an approximate $342 billion being spent on this sector in 2021 alone, something that indicates that most tech companies are really ramping up their investments into this sector.
AI also doesnt seem to be showing any sign of slowing down, with the IDC report revealing that an increase of about 18.8% is expected next year. At this rate, it can be reasonably expected that the total amount of money that corporations would be spending on their various AI related projects would cross half a trillion dollars by 2024, and the increase in investment is actually accelerating if market intelligence is anything to go by.
This survey involved around 700 organizations from over two dozen countries spread across the world, which means that this is not just a myopic report that is only taking American companies and interests into account. AI is definitely going to become a key aspect of how we interact with in the world, and it is being used quite frequently to provide solutions to businesses as well.
Hence, it is safe to say that this sector is a good one to invest in as well as acquire specialized skills for so that you can start to work in it. The sheer quantity of investment here means that it will only accelerate in the future and we could be seeing the rest of the 21st Century as the Age of AI which will make the world quite different from how it was previously.
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Artificial Intelligence Solutions Spending to Reach Half Trillion Dollars By 2024 According to Market Forecasts - Digital Information World