Category Archives: Artificial Intelligence
OPINION: As a proponent of Artificial Intelligence, a middle ground must be found for use at a university level – Louisville Cardinal Online
By Marc Ramsingh
Artificial Intelligence (AI) has become an integral part of our lives, and its use in college work is a topic that has been gaining attention. AI can be used to enhance the learning experience, improve student outcomes, and streamline administrative tasks. One of the most significant benefits of using AI in college work is that it can help students learn more effectively. With AI-powered tools like chatbots and virtual assistants, students can get instant feedback on their work and access personalized learning resources. This can help them stay engaged in their studies and improve their academic performance.
It is time for colleges to embrace this technology and incorporate it into their curriculum.
While this certainly sounds convincing, the above paragraph was written by an AI I prompted on The use of AI in college works.
The use of AI writers in higher education has been in debate since the birth of commercially available AI, however, the argument has surged alongside the massive advancements from AI such as ChatGPT. These advancements worry professors, who argue that the use of AI will diminish student learning; it excites students, who believe that with changing times the way we approach homework and essays should change too.
Its clear AI isnt going anywhere so its important to find a middle ground, especially regarding collegiate work.
There are a couple of stances spread across students and professors.
According to a survey done by BestColleges, 32% of students have used AI tools for a class. This number is expected to grow; as a widely available competent, AI is extremely new and young. The remaining 57% of students said that they havent used AI tools for classwork this isnt surprising as it takes time for tools of such to gain traction with a majority of the student population as well as university regulations to take place on AI tools first. The remaining 11% had no response to the question.
Professors are spilt in their approach to AI tools in their classes.
In my personal experience, I am in a business class in the spring semester; our professor told us that the use of AI tools like ChatGPT is prohibited and will detect if AI is used. This brings us to the first group of professors who believe that the use of AI tools is cheating and academic dishonesty.
51% of professors have prohibited the use of AI tools in their syllabus and 60% of professors have addressed how they use AI tools in their syllabus. With the newness of these tools, we can expect these numbers to go up and for university regulation to step in at some point in the midterm future. The rest of surveyed professors, 49% of them, believe in AIs use in classwork. Its not clear how much this figure would increase, but I would expect it to generally increase when university regulation makes its stance on the matter first.
The future of tools like AI is questionable. The unlikely event is that AI tools would be banned outright via university regulation. Another more likely scenario is that universities recognize you cant get rid of growing AI tools and the best way to handle it is to regulate it by allowing its use, not abuse, by students.
File Photo // The Louisville Cardinal //
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OPINION: As a proponent of Artificial Intelligence, a middle ground must be found for use at a university level - Louisville Cardinal Online
IDVV Closes Acquisition of Company in (AI) Artificial Intelligence … – AccessWire
LOS ANGELES, CA / ACCESSWIRE / March 29, 2023 / International Endeavors Corporation "IEC" (OTC PINK:IDVV) announced the following corporate updates related to its previously announced acquisitions and AI.
IDVV has issued an update that the company has completed it's acquisition of SF Corp earlier than its estimated date of April 30th 2023.
Advisory Board member John Peterson and Vice President Bill Martin issued the following joint statement regarding the acquisition "By modifying the initial agreement we were able to close the deal and bring SF Corp operations into IDVV faster than expected. We believe that due to the AI sectors rapid growth it is necessary to expedite acquisitions to the betterment of the company. We saw that the process of adding board members was going to delay the closing, and also delay IDVV from participating in the revenue. By adopting these changes we were able to close at what we feel is little to no risk to IDVV. This also enables us to pursue other needed acquisitions in the sector at the required pace."
The following terms of the agreement were modified:
Jeremy Smith, Founder of SF Corp issued the following statement "On behalf of SF Corp we're very excited to officially be a part of IDVV. The technology that we have developed along with what WITech had in place and other targeted acquisitions can take us to another level."
The Company will be posting information on OTCMarkets as well as updating its website regarding the acquisition upon completion of its annual report being published soon.
Relevant information on how AI is changing several industries that IDVV plans to be involved with
Artificial Intelligence (AI) has already made significant inroads in various industries, transforming the way we work, communicate, and live. One area where AI is creating a massive impact is in content creation. From marketing to legal, lending, and medical industries, AI-powered content creation tools are becoming increasingly popular, allowing businesses to produce high-quality content faster and more efficiently than ever before.
Marketing Industry:
Marketing is an industry that relies heavily on high-quality content to attract and engage customers. With the rise of AI, marketers can now leverage advanced tools to create personalized, targeted content that resonates with their audience. AI-powered content creation tools can analyze vast amounts of data, such as search queries, social media interactions, and customer behavior, to generate content that is tailored to the interests and preferences of individual customers.
AI can also be used to automate the content creation process, saving time and reducing costs. For instance, AI-powered chatbots can handle customer queries and support, allowing marketers to focus on creating high-quality content that drives traffic and conversions. Additionally, AI can be used to optimize content for search engines, ensuring that it ranks higher in search engine results pages (SERPs).
Legal Industry:
The legal industry is also being transformed by AI-powered content creation tools. Lawyers and legal professionals often deal with vast amounts of data, documents, and other legal materials, making it challenging to find and analyze the relevant information. With AI, legal professionals can now automate the process of document review, contract analysis, and legal research, allowing them to work faster and more efficiently.
AI can also be used to generate legal content, such as contracts, agreements, and other legal documents. AI-powered contract review tools can analyze contracts and identify potential risks and legal issues, allowing lawyers to review and revise them quickly. This not only saves time but also reduces the likelihood of errors and inconsistencies.
Lending Industry:
In the lending industry, AI-powered content creation tools are being used to automate the loan underwriting process. AI algorithms can analyze vast amounts of data, such as credit history, income, employment status, and other relevant factors, to assess creditworthiness and determine the likelihood of loan repayment. This not only speeds up the underwriting process but also reduces the risk of defaults and loan losses.
AI can also be used to generate marketing content for lenders. AI-powered tools can analyze borrower data and create personalized marketing messages that resonate with their interests and preferences. This can help lenders to attract more customers and improve their conversion rates.
Medical Industry:
The medical industry is also benefiting from AI-powered content creation tools. Medical professionals can use AI to analyze patient data, such as medical records, test results, and other health-related information, to make more accurate diagnoses and treatment recommendations. AI algorithms can also be used to generate medical content, such as patient education materials, treatment plans, and other health-related documents.
Additionally, AI-powered chatbots and virtual assistants can provide patients with personalized support and guidance, allowing healthcare providers to focus on delivering high-quality care.
In conclusion, AI is changing the world of content creation in various industries, from marketing to legal, lending, and medical. AI-powered content creation tools are allowing businesses to create high-quality content faster and more efficiently than ever before, while also personalizing it to meet the needs and preferences of individual customers.
As AI continues to evolve, we can expect to see even more innovative and impactful applications in content creation across a wide range of industries.
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About Us
International Endeavors Corporation ("IEC") is a technology holdings company focused on Clean Energy, Crypto and A.I.
Specializing in solar technology, battery storage, as well as clean energy crypto mining options for both on & off grid.
We're currently implementing EV2G / Bi-directional charging options, thus allowing you to use your electric vehicle as a means of a backup battery, or to sell power back to the grid.
In 2022 IDVV started to offer its clients a Clean Energy Crypto mining solution. Our Plug-n-Play mining rigs can be installed in existing or current systems and allows the option to sell power back to the grid or mine crypto currency with any power surplus.
In 2023 We acquired WITech and SF Corp as part of an expansion into the AI Sector. We are incorporating AI technology into our crypto offerings, and developing a platform for AI Content Marketing.
The Company currently is reporting its financial information on OTCMarkets.
Our filings can be seen at https://www.otcmarkets.com
About SF Corp
SF Corp, formed by Jeremy Smith in 2020 is currently operating in Nevada. It has developed automated and artificial intelligence technologies for several industries including Auto, Medical, Robotics and Financial.
Disclaimer
Forward-Looking Statements are included within the meaning of Section 27A of the Securities Act of 1933, and Section 21E of the Securities Exchange Act of 1934, as amended. All statements regarding our expected future financial position, results of operations, cash flows, financing plans, business strategy, products and services, competitive positions, growth opportunities, plans and objectives of management for future operations, including words such as "anticipate," "if," "believe," "plan," "estimate," "expect," "intend," "may," "could," "should," "will," and other similar expressions are forward-looking statements and involve risks, uncertainties and contingencies, many of which are beyond our control, which may cause actual results, performance, or achievements to differ materially from anticipated results, performance, or achievements. International Endeavors Corporation (IDVV) is under no obligation to (and expressly disclaim any such obligation to) update or alter our forward-looking statements, whether as a result of new information, future events, or otherwise.
Contact:
Bill Martin, Vice PresidentPhone: 1-619-343-3199Email: [emailprotected]
SOURCE: International Endeavors Corporation, Inc.
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IDVV Closes Acquisition of Company in (AI) Artificial Intelligence ... - AccessWire
Kathleen Featheringham Selected as VP of Artificial Intelligence … – Executive Gov
Kathleen Featheringham has joinedMaximus as its new vice president of artificial intelligence and machine learning, bringing over two decades of experience in the public sector technology market to the company.
In this position, Featheringham will drive the development and growth of MaximusAI and advanced analytics portfolio under its Federal Technology Consulting Services business, the Tysons, Virginia-headquartered organization announced on Tuesday.
Federal agency leaders understand the value and potential that emerging technologies such as AI, machine learning and advanced analytics can deliver and how an experienced partner like Maximus can make that reality, saidScott Barr, who leads Maximus TCS unit.
He commented on Featheringhams more than 20-year history in the industry, which he said is unmatched in the field and will help the Maximus team advance its approach to public sector technology transformation.
Featheringham emphasized the extraordinary period for federal technology that is currently informing the efforts of government agencies to better meet their mission, customer experience and service delivery goals.
Her career, she added, was built around the intersection of U.S. government missions and has placed a special emphasis on the human element of adoption.
I joined Maximus to become part of a team that has shown federal agencies how the full potential of new technologies can be realized with a trusted partner, said Featheringham.
Throughout her career, she has primarily focused on AI, data science, strategy and change management.
Prior to joining Maximus, Featheringham was a director at Booz Allen Hamilton, a role in which she created and scaled the firms AI strategy. She also oversaw the development of its AI governance and risk management procedures and drove initiatives to boost federal agencies analytics capabilities for data-driven decision-making.
Featheringhams appointment follows anearlier leadership change made by Maximus last month, when the company appointedElisabeth Schmidt as one of its senior vice presidents for technology and consulting services.
Maximus is sponsoring the Potomac Officers Clubs 4th Annual CIO Summit, which will bring together notable GovCon CIOs to consider current information technology challenges and solutions on May 16. To learn more and register to attend, please visit the Potomac Officers Club events page.
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Kathleen Featheringham Selected as VP of Artificial Intelligence ... - Executive Gov
Artificial Intelligence in Fashion: The Future of Innovation – Fibre2fashion.com
The realm of fashion is rapidly changing as demands for eco-friendliness, individualisation, and novelty surge with unprecedented intensity. Among the essential weaponry in their arsenal lies Artificial Intelligence (AI), which plays a crucial role enabling clothing companies to craft one-of-a-kind designs that are customer-focused and sustainable at once. This article delves into todays state of AI technology within the industry and foresees forthcoming trends anticipated to reshape it over the ensuing years.
The fashion realm is experiencing a notable shift and Artificial Intelligence (AI) holds a pivotal post in spurring creativity, streamlining operations, and promoting eco-friendliness. Fashion firms are grappling with the effects of modern technology, therefore, seeking novel approaches to improve customer satisfaction while minimising excesses and developing sustainable apparel designs that meet present-day demands. It has become imperative for industries to embrace technological advancements as it is currently essential to do so if they intend on keeping pace with evolving markets.
Current State of AI in the Fashion Industry
AI technology is already making its mark on the fashion industry, it is enabling companies to analyse data, enhance creativity, and streamline operations. AI algorithms are being used to analyse customer data and create personalised product recommendations, increasing sales and customer satisfaction.
In design, AI is enabling fashion companies to create unique and innovative designs. For example, AI-powered generative design is being used to create designs that are impossible to create manually and at the same time ensure time management.Generative design algorithmsuse machine learning techniques to analyse historical data and create new designs based on specific design parameters.
In manufacturing, AI is enabling companies to optimise production, reduce waste, and improve sustainability. AI-powered inventory management systems help reduce the risk of overstocking or understocking, thus improving operational efficiency. Furthermore, AI-powered predictive maintenance can detect equipment failures before they occur, reducing downtime and increasing productivity.
Future Trends in AI in the Fashion Industry
The fashion industry has a bright future for AI with numerous thrilling advancements projected to revolutionise the sector over time. The following are examples of some exceptional technologies that will influence forthcoming developments in AI within the fashion world:
Computer Vision: Computer vision is a high-end technology that enables machines to understand images and videos. In the fashion industry, computer vision is being used to improve the customer experience by enabling virtual try-ons, visual search, and personalised styling recommendations. By using computer vision algorithms, fashion companies can analyse customer data, create personalised recommendations, and improve the overall customer experience.
One example of computer vision in the fashion industry is virtual try-on. Using computer vision algorithms, fashion companies can create a virtual mirror that allows customers to try on clothes virtually, without physically trying them on. This technology can help reduce the risk of product returns and enhance the customer experience. For example, Gucci launched an AR-based try-on feature in its app that uses computer vision to enable customers to virtually try on sneakers.
An advanced technology called Natural Language Processing (NLP) allows machines to comprehend and construe human language. This cutting-edge innovation is being leveraged in the fashion industry, where it enables chatbots and virtual assistants to interpret customer inquiries intelligently. By doing so, these tools can cater with personalised recommendations enhancing the overall customer service experience.
Using NLP algorithms, fashion companies can create chatbots and virtual assistants that can understand and interpret customer queries and provide personalised recommendations. For example, H&M launched an AI-powered chatbot that uses NLP to answer customer queries and provide styling recommendations.
Improving Decision-Making: Utilising cutting-edge technology, machines are now able to learn from their past experiences and enhance their decision-making abilities. Fashion companies have begun adopting a specific type of this technique called reinforcement learning in order to improve supply chain management by minimising waste production. This approach deploys algorithms that allow fashion firms the opportunity for process optimisation while simultaneously reducing overstock/understock risks; ultimately contributing significantly towards overall sustainability levels within these industries workflow processes.
Among others, fashion companies can optimise production processes, reduce the risk of overstocking or understocking, and improve overall sustainability with the help of reinforcement learning. Particularly, Adidas is using reinforcement learning algorithms to optimise production processes and reduce waste by analysing data on demand patterns, production lead times, and material availability.
Augmented Reality (AR) and Virtual Reality (VR): AR and VR are high-end technologies that enable customers to visualise products in a virtual environment. In the fashion industry, AR and VR are being used to enhance the customer experience by enabling virtual try-ons and creating immersive virtual showrooms. By leveraging AR and VR technologies, fashion companies can improve customer engagement, reduce the risk of product returns, and enhance the overall customer experience.
For example, virtual showrooms are one such application of AR and VR in the fashion industry. Using AR and VR technologies, fashion companies can create immersive virtual showrooms that allow customers to visualise products in a virtual environment. For example, Dior launched a VR experience that allows customers to virtually tour its fashion show venue and view the latest collections in a virtual showroom.
Blockchain Technology: Blockchain technology is a high-end technology that enables secure and transparent transactions to provide a case study or proposed example of each technology and how it can be used in the fashion industry.
For instance, let us take supply chain transparency. Using blockchain technology, fashion companies can create a secure and transparent supply chain, enabling customers to trace the origin of their products and ensure that they are ethically sourced. For example, Bext360 is using blockchain technology to create a traceability system that allows customers to track the origin of their coffee, cotton, and cocoa products.
Generative Adversarial Networks (GANs): Another high-end technology that is expected to transform the fashion industry is Generative Adversarial Networks (GANs). GANs are a class of machine learning algorithms that can generate new, unique, and realistic images based on a given input. In the fashion industry, GANs can be used to generate new and unique designs, enabling fashion companies to create custom designs tailored to specific customer needs.
For instance, H&M is experimenting with GANs to generate new designs for its Conscious Exclusive collection. The company is using GANs to analyse customer data, identify popular design patterns, and generate new designs that meet customer preferences. This approach can help H&M create more sustainable and customer-centric designs, reduce production waste, and enhance customer loyalty.
Predictive Analytics: Predictive analytics is another high-end technology that is transforming the fashion industry. Fashion companies can use predictive analytics algorithms to analyse customer data, identify trends and patterns, and forecast customer preferences and behaviours. This information can help fashion companies create more targeted and personalised marketing campaigns, improve product recommendations, and optimise inventory management.
Zara is using predictive analytics to optimise its inventory management processes. The company is using machine learning algorithms to analyse sales data, identify popular products, and forecast demand patterns. Based on this information, the company can optimise its production processes, reduce overstocking and understocking, and improve overall efficiency.
In Summary
The fashion industry holds a bright future ahead. It is expected that within the next decade, there will be various advanced technologies paving their way into this field. Fashion companies can leverage such tools to bring out more exceptional and exclusive designs personalised according to individual preferences while also being environmentally sustainable at large-scale production levels. This would empower them to improve customer satisfaction by providing an enhanced shopping experience with optimised manufacturing processes giving them an edge over competitors.
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Artificial Intelligence in Fashion: The Future of Innovation - Fibre2fashion.com
HUMBL Launches Artificial Intelligence and Automated Machine … – GlobeNewswire
San Diego, California, March 28, 2023 (GLOBE NEWSWIRE) -- HUMBL, Inc. (OTCQB: HMBL) HUMBL announced today the launch of its Artificial Intelligence (AI) and Automated Machine Learning initiatives across its consumer, commercial and Latin America business units.
On the commercial side, HUMBL kicked off its AI / Automated Machine Learning initiatives with the announcement of its first commercial sales contract in its HUMBL Latin America subsidiary, with the sale of AI / Automated Machine Learning services for a leading IT / Telecommunications provider in the Latin America region in the form of a $60,000 (USD) contract for initial deliverables and a total contract value of $195,000 (USD) over three years, pending the achievement of milestones by HUMBL Latin America.
Artificial Intelligence is an accelerant to the principles of web3, said Brian Foote, CEO of HUMBL. The use of public data sets to create more autonomous, intelligent outcomes for consumers, as well as the corporations and governments that serve them, is an excellent use of automated machine learning technologies, continued Foote. The use of AI can help our clients model for more predictive outcomes around things like credit scoring, default rates, churn rates, healthcare patterns and more; driving more tailored experiences for consumers, while driving revenues and improved efficiencies for corporations and governments.
HUMBL has also moved into internal testing on its consumer AI initiatives and its planned Hey BLUE virtual assistant, which builds on the companys signature mascot, a Bored Ape Yacht Club NFT of the same name (BLUE). The company intends to scale up its consumer AI product lines across the HUMBL Platform - in particular around its planned HUMBL Pro subscription services - which will be available across key touch points throughout the HUMBL ecosystem.
About HUMBL
HUMBL is a Web 3 platform with product lines including the HUMBL Wallet, HUMBL Search Engine, HUMBL Social, HUMBL Tickets, HUMBL Marketplace and HUMBL Authentics. The company also has a commercial blockchain services unit called HUMBL Blockchain Services (HBS) for private and public sector clients.
Safe Harbor Statement
This release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. You can identify these statements by the use of the words "may," "will," "should," "plans," "expects," "anticipates," "continue," "estimates," "projects," "intends," and similar expressions. Forward-looking statements involve risks and uncertainties that could cause results to differ materially from those projected or anticipated. These risks and uncertainties include, but are not limited to, the Company's ability to successfully execute its expanded business strategy, including by entering into definitive agreements with suppliers, commercial partners and customers; general economic and business conditions, effects of continued geopolitical unrest and regional conflicts, competition, changes in technology and methods of marketing, delays in completing various engineering and manufacturing programs, changes in customer order patterns, changes in product mix, continued success in technical advances and delivering technological innovations, shortages in components, production delays due to performance quality issues with outsourced components, regulatory requirements and the ability to meet them, government agency rules and changes, and various other factors beyond the Company's control. Except as may be required by law, HUMBL undertakes no obligation, and does not intend, to update these forward-looking statements after the date of this release.
Contact
HUMBL, Inc.PR@HUMBL.com
Source: HUMBL, Inc.
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Artificial Intelligence and Robotics Helping Physicians Better Predict and Diagnose Lung Cancer – Newswise
Newswise WINSTON-SALEM, N.C. March 29, 2023 A new artificial intelligence (AI) tool is helping physicians at Atrium Health Wake Forest Baptist better predict and diagnose lung cancer in patients.
Wake Forest Baptist was the first academic medical center in the U.S. to begin using this technology, which is still not widely available across North Carolina and much of the country.
Through training on more than 70,000 computerized tomography (CT) scans, the AI tool can predict the likelihood of lung cancer based on imaging nodule characteristics and classify patients into high-risk, intermediate-risk, or low-risk categories.
This technology helps pulmonologists and radiologists better detect and track suspicious lung nodules that are cancerous in order to identify patients who should receive timely biopsies and treatment, while reducing unnecessary biopsies for patients who are classified as low risk.
According to the National Cancer Institute, lung cancer kills more Americans than any other cancer. Early detection can reduce deaths, but false-positive results often lead to increased anxiety and follow-up imaging.
We are proud to be an early adopter of proven and innovative technologies that enable our clinicians to identify and treat lung cancer at their early stages when its possible to cure the cancer, said Dr. Christina Bellinger, director of Wake Forest Baptists interventional pulmonary program and associate professor of pulmonary, critical care, allergy and immunologic diseases at Wake Forest University School of Medicine. The exciting part of this artificial intelligence lung cancer prediction tool is that it enhances our decision making, helping doctors intervene sooner and treat more lung cancers at an earlier stage.
Bellinger and her Wake Forest University School of Medicine colleagues were involved in a study, led by the University of Pennsylvania, and published in Radiology, that found computer-aided diagnosis improves risk assessments for pulmonary nodules that are unclear and helps clinicians better recommend earlier treatment options for patients.
In addition to the AI tool, Wake Forest Baptist uses robotic bronchoscopy to help Bellinger and other specially trained physicians on her team reach and diagnose small lung nodules that are difficult to access through traditional bronchoscopy.
This technology is already changing lives, Bellinger said. We are getting better samples, diagnosing cancer earlier and improving patient outcomes.
Wake Forest Baptists lung cancer screening program is a Screening Center of Excellence, designated by the Lung Cancer Alliance, and the health systems Comprehensive Cancer Center is one of only 53 to carry the National Cancer Institute designation.
The AI tool is developed by Optellum and the robotic bronchoscopy platform is developed by Intuitive.
Can artificial intelligence be used to diagnose influenza? – Medical Xpress
This article has been reviewed according to ScienceX's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility:
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Visual abstract. Credit: Journal of Medical Internet Research (2022). DOI: 10.2196/38751
The recently published article "Examining the Use of an Artificial Intelligence Model to Diagnose Influenza: Development and Validation Study" in the Journal of Medical Internet Research, reported that it may be possible to diagnose influenza infection by applying deep learning to pharyngeal images given that influenza primarily infects the upper respiratory system.
These authors aimed to develop a deep learning model to diagnose influenza infection using pharyngeal images and clinical information. They recruited patients who visited clinics and hospitals because of influenza-like symptoms.
In the training stage, the authors developed a diagnostic prediction artificial intelligence (AI) model based on deep learning to predict polymerase chain reaction (PCR)confirmed influenza from pharyngeal images and clinical information. In the validation stage, they assessed the diagnostic performance of the AI model. In an additional analysis, the authors compared the diagnostic performance of the AI model with that of 3 physicians and interpreted the AI model using importance heat maps.
This process led to the development of the first AI model that can accurately diagnose influenza.
Dr. Sho Okiyama, MD, from Aillis, Inc said, "According to the Global Burden of Disease Study 2016, the global burden of influenza is substantial."
Timely and accurate diagnosis of influenza has the potential to prevent widespread transmission of the virus within the population and during subsequent epidemics and pandemics, as well as to prevent the unnecessary prescription of antibiotics in primary care, which is a cause of emerging antibiotic-resistant bacteria.
The COVID-19 pandemic and surge in the use of telemedicine highlighted the importance of accurately diagnosing influenza infection without increasing the risk of spreading the virus through physical interaction. The gold-standard method for diagnosing influenza infection is the reverse transcriptionPCR (RT-PCR) of nasopharyngeal aspirates or swabs; however, RT-PCR is not easily performed in primary care, and the result's turnaround time could delay prompt diagnosis and preventive or treatment interventions.
Neither of these tests can be performed through telemedicine, and the sensitivity and specificity of diagnosing influenza using clinical information only are suboptimal. Given the recent increase in the number of patients being diagnosed through telemedicine, an alternative influenza test that can be conducted through telemedicine is warranted.
Dr. Okiyama and the research team concluded, "we developed the first AI-assisted diagnostic camera for influenza and prospectively validated its high performance. We found that the AI model often focused on follicles, which confirmed previous case reports and series suggesting that visual inspection of the pharynx would help in the diagnosis of influenza infection."
More information: Sho Okiyama et al, Examining the Use of an Artificial Intelligence Model to Diagnose Influenza: Development and Validation Study, Journal of Medical Internet Research (2022). DOI: 10.2196/38751
Journal information: Journal of Medical Internet Research
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Can artificial intelligence be used to diagnose influenza? - Medical Xpress
Digital Dr. Dolittle: decoding animal conversations with artificial … – KUOW News and Information
We could be talking to animals in the next year using AI. But are we ready?
Whenever I'm out doing field work or on a hike, Ive not only got my eyes wide open, but my ears too. Theres a lot going on in a forest or under the sea - the sounds of nature. So many of those sounds are about communication. And some species seem more chatty than others. Birds and whales seem to have a lot more to say than bears or mountain lions.
Personally, I love to chat with ravens. I like to think that we have lovely conversations. I know Im fooling myself but theres something happening that might change that.
Theres a tech company out of Silicon Valley that is hoping to make that dream of communicating with animals a reality. Earth Species Project is a non-profit working to develop machine learning that can decode animal language. Basically, artificial intelligence that can speak whale or monkey...or perhaps even raven?
We are awash in meanings and signals. And what we're gonna have to do is use these brand new big telescopes of AI to discover what's been there all along, said Aza Raskin, co-founder of Earth Species Project.
So we are doing something a bit different on The Wild today - fun to mix things up now and then. For this episode Im not outdoors among the wild creatures, but in my home studio, talking with two fascinating people about the latest developments in technology that are being created to talk to wild animals. Well also explore the ethics of this technology... something Karen Bakker, a professor at the University of British Columbia, knows a lot about.
We could lure every animal on the planet to their deaths with this technology, if it develops as Aza suggests it might, said Bakker.
What are the downsides to playing the role of Digital Dr. Dolittle?
Guests:
Aza Raskin, co-founder of Earth Species Project and co-founder of the Center for Humane Technology.
Karen Bakker, professor at the University of British Columbia where she researches digital innovation and environmental governance. She also leads the Smart Earth Project.
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Digital Dr. Dolittle: decoding animal conversations with artificial ... - KUOW News and Information
The Perception of Artificial Intelligence in the News Industry A Study … – Al Jazeera Center for Studies
ABSTRACT
This study aims to examine the perceptions of the news industry on artificial intelligence utilizing Aljazeera as a case study. Literature reported that studies on A.I. in the context of the news industry are scarce; therefore, exploratory and qualitative research approaches were used to study this phenomenon in greater detail. The data were collected through four in-depth interviews coupled with a survey. The interview participants were carefully selected to understand the research topic comprehensively. Different perspectives were sought: a professor and a decision-maker with a broad vision and plan for the future of artificial intelligence, an expert in A.I. models providing a technical perspective, a journalist and an academic at the same time, and an Aljazeera producer working with A.I. models. A structured five-point Likert Scale questionnaire was completed by 33 respondents working at Aljazeera media network. This study used descriptive statistics to extract information from the collected data. Descriptive statistics reported that 91% of respondents believe that A.I is less biased compared to humans. The results further revealed that the majority (62.5%) of respondents showed disagreement that A.I might replace humans in the newsroom for writing articles. Moreover, 66% of respondents believe A.I will increase the unemployment rate in the news industry because of replacing humans. Most respondents showed disagreement that A.I will comply with the journalism ethics, with only 21% agreeing.
Click here to view the full study.
Who are the leading innovators in AI-assisted CAD for the … – just-auto.com
The automotive industry continues to be a hotbed of innovation, with activity driven by factors such as passenger safety and enhanced in-car experiences, and growing importance of technologies such as artificial intelligence, the Internet of Things, sensors, and machine learning. In the last three years alone, there have been over 1.2 million patents filed and granted in the automotive industry, according to GlobalDatas report on Artificial intelligence in Automotive: AI-assisted CAD.
However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilising and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
290+ innovations will shape the automotive industry
According to GlobalDatas Technology Foresights, which plots the S-curve for the automotive industry using innovation intensity models built on over 619,000 patents, there are 290+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, manufacturability analysis, autonomous parking, and lidar for vehicle anti-collision are disruptive technologies that are in the early stages of application and should be tracked closely. Speed profile estimation, smart light dimmers, and driver drowsiness detection are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are road slope estimation and adaptive cruise control, which are now well established in the industry.
Innovation S-curve for artificial intelligence in the automotive industry
AI-assisted CAD is a key innovation area in artificial intelligence
AI is frequently integrated with CAD for automated decision-making (ADM), which involves the use of AI algorithms to collect, process, model, and use data in support of automated decisions. Finally, decision-making feedback is reviewed and evaluated in order to improve the decision-making process.
GlobalDatas analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 80+ companies, spanning technology vendors, established automotive companies, and up-and-coming start-ups engaged in the development and application of AI-assisted CAD.
Key players in AI-assisted CAD a disruptive innovation in the automotive industry
Application diversity measures the number of different applications identified for each relevant patent and broadly splits companies into either niche or diversified innovators.
Geographic reach refers to the number of different countries each relevant patent is registered in and reflects the breadth of geographic application intended, ranging from global to local.
Source: GlobalData Patent Analytics
Taiwan Semiconductor Manufacturing is one of the leading innovators in AI-assisted CAD. The company has developed ground-breaking microelectronic technologies, with 3D integrated circuit packaging. A huge amount was invested in this chip development project by Taiwan Semiconductor Manufacturing and the Japanese governments to enhance the scope of the CAD industry. Other companies innovating in this technology domain are Halliburton, General Motors, Bosch, Toyota Motors, Hitachi, etc.
To further understand how artificial intelligence is disrupting the automotive industry, access GlobalDatas latest thematic research report on Artificial Intelligence (AI) in Automotive.
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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalDatas Patent Analytics tracks patent filings and grants from official offices around the world. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the worlds largest industries.
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Who are the leading innovators in AI-assisted CAD for the ... - just-auto.com