Category Archives: Artificial Intelligence
A pioneering artificial intelligence method to fight urban air pollution – Phys.org
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99% of the world's population breathes air that exceeds the limits recommended by the World Health Organization (WHO). This scenario is exacerbated in urban areas where more than 50% of the world's population is concentrated.
To mitigate the problem of air pollution, considered by the WHO to be the main environmental risk factor for health worldwide, it is crucial to have more reliable and accurate data on the concentration of air pollutants in our cities, especially nitrogen dioxide (NO2) because of its harmful effects on people's quality of life and the associated economic consequences.
To advance in this line of research, a team of scientists from the Earth System Services group of the Earth Sciences Department at the Barcelona Supercomputing CenterCentro Nacional de Supercomputacin (BSC-CNS) has carried out a study that shows that artificial intelligence can be of great use in obtaining reliable information on the probability of exceeding legal limits for air pollution throughout the city.
The aim of the research, published in the journal Geoscientific Model Development, is to help improve air quality management in urban areas by obtaining hourly maps of NO2 concentrations at the street level, as well as quantifying the associated uncertainty.
The new method combines for the first time the results of CALIOPE-Urban, a unique model in Spain that allows air pollution forecasting at very high resolutions of up to ten meters, at different heights and at any point in the city, with an extensive urban database that includes observations from official air quality stations, low-cost sensor campaigns, information on building density, meteorological variables, and a long list of other geospatial information.
In this way, areas of the city where the current monitoring system needs to be improved can be identified, helping to optimize strategies to reduce air pollution.
"The combination of CALIOPE-Urban predictions with all these urban data using artificial intelligence allows us to improve the model because where simulation cannot explain the spatial distribution of pollution, we can use machine learning to correct and improve this prediction," says Jan Mateu, leader of the BSC Air Quality Services team and one of the main authors of the study.
The use of machine learning techniques with observational data obtained during previous campaigns using passive dosimeters represents an important advance, as it reduces the inherent uncertainties associated with air quality models due to the low density of monitoring stations. This provides a better spatial characterization of excess air pollution in different parts of the city.
One of the main conclusions of the study, which in this pilot phase focused on the city of Barcelona, is that the district with the worst air quality in the Catalan capital is the Eixample, where 95% of its area has more than a 50% probability of exceeding the annual average NO2 limit of 40 g/m3 set by the European Commission (European Air Quality Directive 2008/50/EC).
"The Eixample district, the most populated district in Barcelona, is the most affected area in the city, as the vast majority of its surface area has a greater than 50% probability of exceeding the annual NO2 limit set by the European Commission. Thanks to our methodology, the public administration will be able to design and manage policies to improve air quality in urban areas, which is particularly important since air pollution is the main environmental risk factor for human health," adds lvaro Criado, a researcher in BSC's Air Quality Services team and one of the main authors of the study.
Developed at the BSC, CALIOPE-Urban is a modeling tool that estimates the concentration of nitrogen dioxide (NO2) at street level in the city of Barcelona, although it could also be applied to other cities or metropolitan areas. NO2 and its precursors are mainly emitted from combustion sources, such as vehicle engines, so monitoring is crucial to combat air pollution in large cities where traffic is often congested.
The system, which is unique in Spain, provides citizens and air quality managers with useful information on how traffic affects air pollution in each neighborhood. This information is essential for designing and implementing effective planning and mitigation strategies to protect citizens from the health threats posed by air pollution. CALIOPE-Urban is currently focused on the city of Barcelona, but work is already underway to extend it to other municipalities in collaboration with various municipal and regional administrations.
CALIOPE-Urban combines the technology of the CALIOPE regional model, the BSC air quality prediction system, with an urban model that considers air pollution at street level, using information on traffic emissions and meteorological data. CALIOPE, the only air quality system that provides operational forecasts for Barcelona, Catalonia, the Iberian Peninsula and Europe, is the sole Spanish contributor to the European Union's Copernicus Atmosphere Monitoring Service (CAMS).
More information: Alvaro Criado et al, Data fusion uncertainty-enabled methods to map street-scale hourly NO2 in Barcelona: a case study with CALIOPE-Urban v1.0, Geoscientific Model Development (2023). DOI: 10.5194/gmd-16-2193-2023
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A pioneering artificial intelligence method to fight urban air pollution - Phys.org
Artificial intelligence assists in dental care and jaw surgery – Medical Xpress
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Credit: Nature.com (CC BY 4.0)
A dentist inserting a tooth implant must know the exact location of the nerve canal in the patient's lower jaw to plan the size and position of the implant, along with the overall procedure. This requires X-ray images in which the dentist or radiologist manually specifies the location of the canal point by point. Studying and analyzing these images can be arduous and time-consuming.
Dental equipment manufacturer Planmeca, the Finnish Center for Artificial Intelligence (FCAI) and Tampere University Hospital (Tays) have joined forces to tackle the problem. The result is an AI-based model that locates the lower jaw nerve canal in 3D X-rays faster than a human and with better precision than other automated methods.
"The collaboration arose from the needs of experts practicing clinical work and from seeking ways to help their everyday work. A lot of time can be saved by using artificial intelligence in patient treatment planning," says Vesa Varjonen, Vice President of Research and Technology at Planmeca.
The method is based on training deep neural networks with a mass of clinical data, comprised of three-dimensional images rendered with cone beam computed tomography (CBCT).
"Tampere University Hospital provided us with extensive and versatile clinical materials produced with several 3D-imaging devices. The data was divided at random and part of it used for training the neural networks and part of it isolated for testing and validating the designed method," says Aalto University doctoral researcher Jaakko Sahlsten.
Nerves that control the motor functions of the jaw and facial senses run in the nerve canal of the lower jaw, the mandibular canal. In addition to implant placement, its location is crucial in wisdom teeth removal and jaw surgery. The location and route of the canal running inside the jawbone is unique to each person.
"One of the challenges in training the AI model was that the size of the mandibular canal in a 3D X-ray of the skull is very small compared to the data in the overall image. As a dataset, this type of training material is highly unbalanced," Sahlsten notes.
Working together with Tays radiologists was key for harnessing the data into use when training artificial intelligence.
"When a huge amount of data is fed to the neural network and the location of the mandibular canal is marked in it, it learns to optimize its own internal parameters. The neural network resulting from this learning quickly finds the mandibular canal from the individual 3D data input," Varjonen says.
Testing the neural network model with patient data isolated from the research materials demonstrated that the model managed to locate the mandibular canals with high precision: only 14% of the cases may be inaccurate.
"In clinical assessments, experts went through the results produced by the model and discovered that in 96% of the cases they were fully usable in clinical terms. We are highly confident that the model works well," Sahlsten says.
Compared to humans, one of the advantages of artificial intelligence is that it always works with equal efficiency and speed. The AI model speeds up the discovery of the mandibular canal and supports radiologists' and physicians' decision-making. Final treatment decisions are always made by a health professional.
Planmeca is a Finnish family business and one of the world's leading equipment manufacturers in health technology. Its products are exported to over 120 countries around the world. The company's business is founded on 3D imaging devices for dental care and software that supports them. For Planmeca, collaboration with FCAI and Tays means significant new business potential.
"Digitality and AI used in imaging equipment are important for us. We will integrate the neural network model developed in this research into our imaging software. This will improve the usability and performance of our equipment," Varjonen says.
The scientific publications produced in the collaboration are important for all project partners. Some of the results were published in Scientific Reports.
"Peer-reviewed publications are solid evidence of the functionality of the model. Deep learning has not previously been used in tasks of this type, which adds to the value of the publications. They also promote doctoral candidates' thesis work," Sahlsten says.
"The publications will be important for us when applying for a medical device approval for our software. They demonstrate that the software has been designed according to software development processes and scrutinized through all required phases," Varjonen notes.
In addition to locating the lower jaw nerve canal, the collaborative project between Planmeca, FCAI and Tays also covered the development of a neural network model for orthognathic surgery, in which anomalies in the lower face area are corrected through surgical measures.
"The model helps to identify landmarks in the skull area for correcting malocclusion and planning jaw alignment surgery. The same patient data was also used for another AI application," Varjonen says.
Going forward, artificial intelligence will have a lot to offer in health applications.
"I see artificial intelligence as a very powerful tool that physicians and other experts can use when making their first assessments or to get alternative opinions. The challenge with deep learning models is that we cannot give definite grounds as to why the model reaches a specific outcome. Further research is needed to increase the explainability and transparency of the models," Sahlsten concludes.
More information: Jorma Jrnstedt et al, Comparison of deep learning segmentation and multigrader-annotated mandibular canals of multicenter CBCT scans, Scientific Reports (2022). DOI: 10.1038/s41598-022-20605-w
Journal information: Scientific Reports
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Artificial intelligence assists in dental care and jaw surgery - Medical Xpress
How is artificial intelligence used in fraud detection? – Cointelegraph
How can artificial intelligence help detect fraud?
Artificial Intelligence can play a crucial role in fraud management by detecting and preventing fraudulent activities.
The global average rate of losses caused by fraud for the last two decades represents 6.05% of the gross domestic product. Additionally, companies have reported that cyber breaches have caused financial damages equaling 3% to 10% of their revenue. Moreover, global digital fraud losses are projected to exceed $343 billion between 2023 and 2027.
Given the estimated amounts, it is a crucial question for any organization to build up an efficient fraud management system. Fraud management is identifying, preventing, detecting and responding to fraudulent activities within an organization.
Artificial intelligence (AI) has a significant role in fraud management. AI technologies, such as machine learning (ML) algorithms, can analyze large amounts of data and detect patterns and anomalies that may indicate fraudulent activities. AI-powered fraud management systems can identify and prevent various types of fraud, such as payment fraud, identity theft or phishing attacks. They can also adapt and learn from new fraud patterns and trends, improving their detection over time.
AI-based solutions can also integrate with other security systems, such as identity verification and biometric authentication, to provide a more comprehensive approach to fraud prevention.
Machine learning algorithms are designed to recognize patterns based on a large amount of data, which can be leveraged to identify fraudulent activities.
AI refers to technologies that can perform tasks requiring human intelligence, such as analyzing data or understanding and responding to human language. They are designed to recognize patterns and make predictions in real time. AI algorithms are often a combination of different ML models.
ML is a subset of AI; it uses algorithms to analyze large amounts of data to enable systems to learn autonomously. The more data ML algorithms are exposed to, the better they perform over time. The two main approaches of ML are supervised machine learning (SML) and unsupervised machine learning (UML). SML algorithms use labeled data to help predict outcomes, while UML algorithms discover hidden patterns in the data.
As an example, SML algorithms use historical transaction data labeled as fraudulent or non-fraudulent that will be used to train the supervised machine learning model. UML would use anomaly detection algorithms to identify transactions significantly different from the norm based on given features. While UML models require less human intervention, they tend to be less accurate than SML.
AI technologies have a vital role in fighting cybercrime by enhancing the most commonly used cybersecurity systems.
AI and ML have a crucial role in online fraud detection, where algorithms detect fraudulent activities in online transactions, such as credit cards, online banking or e-commerce transactions. These algorithms can be applied in real-time to identify and flag suspicious activities.
A cybersecurity threat is any activity, event or situation that has the potential to cause harm to computer systems, networks or data. According to the Global Economic Crime and Fraud Survey 2022, after customer fraud, the second most common type of threat that financial services face is cybercrime.
Cybercrime refers to criminal activities involving technology, such as computers, networks or the internet. These activities can result in various harms, including financial loss, data theft or destruction and reputation damage. The most common cyber threats include hacking, phishing, identity theft and malware.
A Cyberattack is a specific type of cybercrime that involves an intentional attempt by a third party to disrupt or gain unauthorized access to a system or network.
Cybersecurity is defending different systems, networks and devices from malicious attacks. A crucial element of cybersecurity systems is the real-time monitoring of all electronic resources. The biggest software companies, like IBM, already use AI-powered technologies to enhance their cybersecurity solutions.
Using AI in fraud detection can lead to a faster, more accurate and more efficient process without compromising the customer experience.
The key benefits are discussed below:
Using AI-powered technologies also holds certain risk factors, which can be partly handled by explainable AI solutions.
The potential risks of AI in fraud detection are discussed below:
Explainable AI can help to partly overcome the incorporated risk factors. The term refers to the development of AI systems that can explain their decision-making processes in a way humans can understand. In the context of fraud detection, explainable AI can provide clear and interpretable explanations for why a particular transaction or activity was identified as potentially fraudulent.
For instance, The Montreal Declaration for Responsible Development of Artificial Intelligence outlines ethical principles for AI development, including transparency and explainability.
The same features that make AI valuable for legitimate purposes can also make it a powerful tool for cybercriminals.
Here are a few examples of attacks that can happen if criminals exploit AI:
There are several existing solutions for crime prevention with the help of AI-based technologies; however, a few of them raise ethical concerns.
AI can be used in crime prevention by analyzing data that may indicate criminal activity. One example of an existing solution is the PredPol system, which uses machine learning algorithms to analyze historical crime data and identify patterns in the time and location of crimes. Based on these patterns, the system generates predictive hotspots that indicate where crimes are most likely to occur in the future.
A well-known example of fraud prevention in blockchain transactions is Chainalysis. The company applies machine learning algorithms to monitor and analyze the flow of cryptocurrency transactions across various blockchain networks. By analyzing the patterns of these transactions, experts can identify suspicious activities and track the flow of funds across different addresses and accounts.
The crime prevention system of China is a controversial example of AI-based solutions. The system relies on three pillars: Facial recognition tools help authorities to identify suspected criminals, big data tools allow police to analyze behavioral data to detect criminal activities, and a machine learning tool supports the creation of a database involving every citizen. The result is an extensive data-powered rating system that identifies suspicious individuals based on background and behavior signals.
Its important to mention that AI in crime prevention has several limitations and raises serious ethical and privacy concerns. There are many debates about the accuracy and bias of some of these systems. Its crucial to ensure they are designed and used responsibly, with proper safeguards to protect individual rights and prevent abuse.
The features of efficient data processing and pattern recognition can also be valuable features of AI in the case of forensic investigation.
Forensic investigation is the scientific method of researching criminal cases. It involves gathering and analyzing all sorts of case-related data and evidence. The nature of data is often complex, taking the form of texts, images or videos. AI can help handle data effectively and perform meta-analysis during the investigation.
AI algorithms can be trained to recognize patterns in data, such as handwriting, fingerprints or faces. They can be used to analyze written or spoken language, such as emails and text messages, as well as images and videos, to identify objects, people and events.
In addition, AI can aid in investigating and prosecuting the perpetrators. For instance, predictive modeling a type of AI technology can use historical crime data to create predictive models to help law enforcement anticipate and prevent future crimes.
To evaluate crime data and pinpoint regions that are more likely to experience criminal activity, police departments in some cities can use predictive policing algorithms. This enables them to allocate resources more skillfully and stop crime in its tracks. Predictive modeling can also be used to identify individuals at risk of committing crimes, allowing law enforcement to intervene before any criminal activity occurs.
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How is artificial intelligence used in fraud detection? - Cointelegraph
Some teachers are embracing artificial intelligence as more platforms roll out – WOAI
Rodrigo Trevino looks over the coding for his app (Blake McCarty/SBG San Antonio)
SAN ANTONIO - Artificial intelligence platforms are rolling out left and right. You can put in a prompt or question and immediately get a detailed response.
Like most teachers, Joe Golembiewski at Northside ISD's NSITE Campus was worried students would use the technology to cheat.
"It turns out that I haven't had a big problem with that,"Golembiewski said. "I should knock on wood."
His students are learning coding and programming, but platforms like Chat GPT can help with almost every subject.
It was launched last November and uses a language-based model to scour for answers before presenting them to you in neat paragraphs.
Chat GPT site (Screengrab from OpenAI)
Students tell us they immediately knew it could present problems.
"There's definitely going to be a surge of students using it to not only aid them in their work, but completely do it for them," said Rodrigo Trevino, one of Golembiewski's students.
But Trevino went a different route with the technology.
"I tested it out as soon as as soon as I could," he said.
Trevino had already coded an app that helps determine your grade point average. He wondered what would happen if he asked Chat GPT to do the same. After inputting his prompt, he compared the two.
"It didn't go as far as you would expect it to, it just did the bare minimum that it needed," Trevino said. "I think mine was better, personally, because mine contained more features."
Golembiewski says that's how he'd prefer his students use Chat GPT and other AI, with schools integrating it into the learning rather than banning it.
"Tools can be used for good, tools can be used for bad... we've got to figure out, flesh out, the best ways to use the tool,"Golembiewski explained.
Author and education advocate Thomas Fellows agrees.
"We're gonna be able to use Chat GPT in the workforce, so we might as well prepare our students for the workforce, rather than just preparing them for tests and so forth," Fellows said.
Golembiewski says teachers are actually using AI to determine if students are using it too.
"And it'll not 100% always detect it, but it gives a pretty good estimation of whether or not the student did the work,"Golembiewski said.
Some districts tell us the language in their student handbooks is already inclusive enough to cover artificial intelligence when it comes to cheating.
Its use in the classroom is still largely up for debate.
LONDON, ENGLAND - AUGUST 03: A finger is posed next to the Snapchat app logo on an iPad on August 3, 2016 in London, England. (Photo by Carl Court/Getty Images)
Snapchat recently launched their own AI feature, calling it an "experimental, friendly, chatbot."
"My AI can answer a burning trivia question, offer advice on the perfect gift for your BFFs birthday, help plan a hiking trip for a long weekend, or suggest what to make for dinner. My AI is there to help and to connect you more deeply to the people and things you care about most," says the Snapchat support page.
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Some teachers are embracing artificial intelligence as more platforms roll out - WOAI
Artificial intelligence and pop music is getting weird, fast – Stuff
It didn't take long for AI to hit its hyperspeed moment, which was ushered in when a new song by The Weeknd and Drake took the internet by storm.
It wasn't because of the pairing of the two superstar artists, who have linked up together in the past.
It was the fact that neither of them had a single thing to do with the song, it was entirely AI-generated, and now artists, listeners and the recording industry have been thrown into an existential crisis that up until a few months ago seemed like the plot of a potential Black Mirror episode. And things are about to get really crazy, if they haven't already.
Heart on My Sleeve is the name of the song, and it sounds exactly like a collaboration between the two megastars. But it's just the tip of the iceberg of what is possible and what is already here, and what could reshape the music business as we know it.
READ MORE:* The controversial AI-generated track of Drake and The Weeknd making waves* Revolutionary AI is coming for a job near you, could it do yours?* The New Plymouth band who used Artificial Intelligence to make its latest music video
In just the last few months alone, artificial intelligence, or AI, has gone from a thing you may have used to tweak your Instagram avatar to something that is ready to take over the world.
ChatGPT was launched in November and can now do the work of a term paper in a few keystrokes, suddenly rendering the entire concept of homework futile. (A long overdue advancement, honestly.)
Buzzfeed folded its news operation this week, and will instead enlist quizzes created by ChatGPT for users rather than, you know, pay humans to do actual work. And after a story on AI that aired on last Sunday's program, 60 Minutes, Scott Pelley signed off with the following: We'll end with a note that has never appeared on 60 Minutes, but one in the AI revolution you may be hearing often: the preceding was created with 100% human content.
Yes, human content. That's humans with all their faults, misgivings, personality flaws, grudges, biases and, you know, humanity over here, and AI, spit-shined to perfection, over here. The choice seems simple. Which side are you on?
Humans, of course. C'mon. But have you listened to Heart on Your Sleeve, and were you also struck by the fact that it may be Drake's complete non-participation in the song aside Drake's best song in two years?
Drake is one of the artists, along with Frank Ocean and Chance the Rapper, to sign exclusive deals for new music with Apple Inc.
Not so easy now, is it? But it begs the question and we'll limit the wide-reaching AI debate here strictly to pop-music terms what do we want from artists?
Is it their artistry, their expression, the baring of their soul, which also includes making do with their flaws and imperfections, and the fact that sometimes, because they're human, they botch Coachella headlining performances?
Gonzales/Samy Khabthani/Avalon/Zuma Press/TNS
If you have listened to Heart on Your Sleeve, you may have been struck by the fact that it may be Drake's best song in two years, despite his lack of involvement.
Or do we want to control them, which is what AI allows us to do, in essence: cherry pick their best qualities, use them how we want to use them, and create what we want them to create.
It's the ultimate idea of fan-service, of wish fulfilment, rendered whole. And it's not just Drake and The Weeknd to whom it's happening.
Scroll through TikTok and you'll hear dozens of examples of fan-generated AI songs, pairing your favorite artists' likenesses over your other favourite artists' songs.
A young Paul McCartney singing John Lennon's Imagine? It's out there. Kanye West singing Creed's With Arms Wide Open? Not sure why anyone would want that, but it's out there. Ariana Grande singing pretty much anything you can think of? Just type it in the search bar, it's out there.
That's not all. Earlier this year, superstar DJ David Guetta called on AI to create an Eminem-sounding track, which he went on to sample in his live show. There's something that I made as a joke, he explained in a YouTube clip about the deepfake Eminem sample, and it worked so good!
And an entire album of songs in the style of Oasis, dubbed Aisis (see what they did there?), was released this week, a reimagining of what the band might have sounded like had its classic lineup stayed together and kept banging out tracks.
And listening to it, that's precisely what it sounds like, and if you didn't know any better, you might think the boys buried the hatchet and got the band back together. (Even Liam Gallagher himself weighed in on the experiment, giving his approval and opining of his not-quite vocals, I sound mega.)
Now if Oasis really does get back together, maybe Liam won't sound mega, and maybe the songs will be sluggish, the songwriting uninspired. Maybe it will be a letdown. But it will be real, it will be human, it will actually be them. So, what's better?
There's also the question of legality, and likeness, and appropriation of likeness, and a whole bunch of other technical stuff that is absolutely not going to stop someone from making Mariah Carey-soundalike Black Sabbath covers, or whatever else strikes their mood. (That doesn't exist yet, and probably shouldn't.)
The cat is out of the bag, and as the record companies learned the hard way from the great Napster debacle, it's not going back in.
That didn't stop Universal Music Group from pulling Heart on My Sleeve down from YouTube and streaming sites, where it had already garnered millions of listens. Making it go away isn't going to make it go away, or stop the next one from popping up, or the next one after that.
But what if the artists themselves got on board with Heart on My Sleeve? What if they re-recorded the song, using their own voices? Could the AI and the human user behind it, in this case the anonymous Ghostwriter977 inspire the real artists?
It's not going to be as simple as demonising AI. Maybe this year's song of the summer will be an AI creation. Would that automatically be bad?
This particular Black Mirror episode we're living inside is unfolding in real time, and is only beginning. While there are many questions yet to be asked and answered, of this much we're confident: the preceding was created with 100% human content.
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Artificial intelligence and pop music is getting weird, fast - Stuff
Hay River testing artificial intelligence for communications – Cabin Radio
The Town of Hay River says it is trialling artificial intelligence to help prepare material for some of its communications with residents.
Assistant senior administrative officer Patrick Bergen told town councillors on Monday that the municipality is testing the use of artificial intelligence in some circumstances.
Various AI applications have made headlines in recent months, from tools like Midjourney which can create realistic images based on text prompts to ChatGPT, which provides answers to users questions in a form of online conversation.
AI is also being introduced to search engines. Some Bing users can now search the web using an AI interface, while Google is carrying out limited testing of an equivalent tool named Bard.
On a broad level, concerns remain that AI tools to search the web or generate answers arent always accurate. They sometimes reproduce false or misleading information found online, an error known as hallucination.
But having been trained on a vast online resource of written material, AI apps are increasingly used to handle tasks like editing text or writing summaries of dense information.
The system is good at crunching large of pieces of information into something readable, Bergen said.
Its also good at grouping large amounts of data and summarizing it. That will speed up some of the releases that go out.
Its not clear if any of the towns communications to date have been published with the assistance of artificial intelligence.
Bergen told councillors that recent requests from journalists had been fairly routine in that they focused on breakup season, which has proceeded quietly to date, and were handled by senior administrator Glenn Smith.
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Hay River testing artificial intelligence for communications - Cabin Radio
Deloitte teams with NVIDIA on artificial intelligence platform for … – DC Velocity
Consulting firm Deloitte today launched a suite of artificial intelligence (AI) tools for logistics and retail businesses, saying they can help users to enhancecustomer experiences, optimize operations, and launch businesses in new markets.
Deloittes new Quartz AI package includes two new, cross-industry AI service offerings, both built on the NVIDIA AI and NVIDIA Omniverse platforms from California chip-maker NVIDIA. The two companies collaborate by applying NVIDIAs powerful video gaming chips, known as graphics processing units (GPUs) to Deloittes business goal to transform the world of data processing, analytics, and AI.
Quartz AI includes Deloitte Compass AI for routeoptimization in logistics and Deloitte Frontline AI for customer service at retail, quick-service restaurants.
According to the partners, Compass AI enables dynamic fleet routing and dispatchoptimization, enabling faster delivery, cost reduction andcustomer satisfaction. Through rapid dataprocessing and simulating scenarios economically, clientscan see tangible fleet and routing optimization notovernight, but in a matter of seconds, Deloitte says.
And Frontline AI provides a virtual customer care representative, able tointelligently converse in any language and provide aneffortless, humanized experience that increasescustomer loyalty. Deloitte calls the product a human engagement mechanism that uses visual conversational capabilities to streamline, measure, and address customer feedback.
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Deloitte teams with NVIDIA on artificial intelligence platform for ... - DC Velocity
Mizzou hosts Artificial Intelligence Hackathon for Show Me Research Week – krcgtv.com
The University of Missouri hosted an Artificial Intelligence Hackathon for Show Me Research Week. The hackathon took place in Mumford Hall, and students pitched and presented their AI ideas to judges from around the country. The theme of the hackathon is "AI for social good," so pitches included solving health care issues, food poverty problems, job search bias and the legality of Chat GPT.{}(Regan Mertz/KRCG 13){br}
The University of Missouri hosted an Artificial Intelligence Hackathon for Show Me Research Week.
The hackathon took place in Mumford Hall, a 100-year-old building off University Avenue on Mizzou's campus. Students pitched and presented their AI ideas to judges from around the country, Seattle, St. Louis and Dallas, who work in AI at companies like IBM.
The University of Missouri hosted an Artificial Intelligence Hackathon for Show Me Research Week. The hackathon took place in Mumford Hall, and students pitched and presented their AI ideas to judges from around the country. The theme of the hackathon is "AI for social good," so pitches included solving health care issues, food poverty problems, job search bias and the legality of Chat GPT.{{ }}(Regan Mertz/KRCG 13){br}
The history of Mumford Hall, which has a white brick exterior, huge trees, just now growing leaves that cast shade and a perpetual breeze on the lush front lawn of the building, contrasts the modern, futuristic ideas swirling inside the lecture hall.
The interior of the building is a creamy white with wood crown molding and staircase banisters. Huge windows cast rays of sunlight and blue skies onto the rows of chairs holding students, judges, advisors and guests.
Pizza was ordered and acoustic Taylor Swift songs were playing on a speaker to set the tone for an afternoon of pitches.
The University of Missouri hosted an Artificial Intelligence Hackathon for Show Me Research Week. The hackathon took place in Mumford Hall, and students pitched and presented their AI ideas to judges from around the country. The theme of the hackathon is "AI for social good," so pitches included solving health care issues, food poverty problems, job search bias and the legality of Chat GPT.{{ }}(Regan Mertz/KRCG 13){br}
The theme of the hackathon is "AI for social good," so pitches included solving health care issues, food poverty problems, job search bias and the legality of Chat GPT.
Each team had to be made up of 2-3 members, as well as a faculty advisor. The students had to choose a domain-specific problem and suggest an AI solution.
And each team only had five minutes and one slide presentation to sell their idea.
The University of Missouri hosted an Artificial Intelligence Hackathon for Show Me Research Week. The hackathon took place in Mumford Hall, and students pitched and presented their AI ideas to judges from around the country. The theme of the hackathon is "AI for social good," so pitches included solving health care issues, food poverty problems, job search bias and the legality of Chat GPT.{{ }}(Regan Mertz/KRCG 13){br}
The idea and the plan for it was presented on April 17.
Once the judges gave feedback, asked questions and stressed concerns, the teams had two days to bring their ideas to life.
The final tool was presented on April 20. The teams could source their data from outside data or use their own data they have compiled.
The first three teams were announced at the SMRW Award Ceremony on April 21.
The University of Missouri hosted an Artificial Intelligence Hackathon for Show Me Research Week. The hackathon took place in Mumford Hall, and students pitched and presented their AI ideas to judges from around the country. The theme of the hackathon is "AI for social good," so pitches included solving health care issues, food poverty problems, job search bias and the legality of Chat GPT.{{ }}(Regan Mertz/KRCG 13){br}
The hackathon is meant to give a platform to MU students to show their skills in developing AI applications to solve real-world problems. It was organized by the Graduate Student Organization of the Institute for Data Science and Informatics.
Two other organizations on campus, the Bond Life Sciences Center and the Office of Undergraduate Research, collaborated with Mizzou to ensure the week was a success.
The Research Week lasted from Monday, April 17, to Friday, April 21, and it is meant to be a time to celebrate student and postdoctoral research and creativity.
The University of Missouri hosted an Artificial Intelligence Hackathon for Show Me Research Week. The hackathon took place in Mumford Hall, and students pitched and presented their AI ideas to judges from around the country. The theme of the hackathon is "AI for social good," so pitches included solving health care issues, food poverty problems, job search bias and the legality of Chat GPT.{{ }}(Regan Mertz/KRCG 13){br}
Over 450 students showcased their work from around several schools and colleges at Mizzou.
Before the COVID 19 pandemic, both organizations had their own well established research weeks in order to celebrate the accomplishments. Eventually, it was decided that a campus-wide showcase was necessary for the entire research community.
Mizzou calls this research week, "a celebration of discovery," as well as a representation of the university's values, which are respect, responsibility, discovery and excellence.
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Mizzou hosts Artificial Intelligence Hackathon for Show Me Research Week - krcgtv.com
Artificial intelligence coming to a government near you soon? – The Guardian
Artificial intelligence (AI)
AI is already employed in various administrations in the US and its use is only set to grow but what dangers does it bring?
Sat 22 Apr 2023 06.00 EDT
The recent blizzard of warnings about artificial intelligence and how it is transforming learning, upending legal, financial and organizational functions, and reshaping social and cultural interaction, have mostly left out the role it is already playing in governance.
Governments in the US at every level are attempting the transition from a programmatic model of service delivery to a citizen-focused model.
Los Angeles, the USs second largest city, is a pioneer in the field, unveiling technologies to help streamline bureaucratic functions from police recruitment to paying parking tickets to filling potholes or locating resources at the library.
For now, AI advances are limited to automation. When ChatGPT was asked recently about how it might change how people deal with government, it responded that the next generation of AI, which includes ChatGPT, has the potential to revolutionize the way governments interact with their citizens.
But information flow and automated operations are only one aspect of governance that can be updated. AI, defined as technology that can think humanly, act humanly, think rationally, or act rationally, is also close to being used to simplify the political and bureaucratic business of policymaking.
The foundations of policymaking specifically, the ability to sense patterns of need, develop evidence-based programs, forecast outcomes and analyze effectiveness fall squarely in AIs sweet spot, the management consulting firm BCG said in a paper published in 2021. The use of it to help shape policy is just beginning.
That was an advance on a study published four years earlier that warned governments were continuing to operate the way they have for centuries, with structures that are hierarchical, siloed, and bureaucratic and the accelerating speed of social change was too great for most governments to handle in their current form.
According to Darrell West, senior fellow at the Center for Technology Innovation at the Brookings Institution and co-author of Turning Point: Policymaking in the Era of Artificial Intelligence government-focused AI could be substantial and transformational.
There are many ways AI can make government more efficient, West says. Were seeing advances on a monthly basis and need to make sure they conform to basic human values. Right now theres no regulation and hasnt been for 30 years.
But that immediately carries questions about bias. A recent Brookings study, Comparing Google Bard with OpenAIs ChatGPT on political bias, facts, and morality, found that Googles AI stated Russia should not have invaded Ukraine in 2022 while ChatGPT stated: As an AI language model, it is not appropriate for me to express opinions or take sides on political issues.
Earlier this month, the Biden administration called for stronger measures to test the safety of artificial intelligence tools such as ChatGPT, said to have reached 100 million users faster than any previous consumer app, before they are publicly released. There is a heightened level of concern now, given the pace of innovation, that it needs to happen responsibly, said the assistant commerce secretary Alan Davidson. President Biden was asked recently if the technology is dangerous. It remains to be seen. It could be, he said.
That came after the Tesla CEO, Elon Musk, and Apple co-founder Steve Wozniak joined hundreds calling for a six-month pause on AI experiments. But the OpenAI CEO, Sam Altman, said that while he agreed with parts of the open letter, it was missing most technical nuance about where we need the pause.
I think moving with caution and an increasing rigor for safety issues is really important, Altman added.
How that effects systems of governance has yet to be fully explored, but there are cautions. Algorithms are only as good as the data on which they are based, and the problem with current AI is that it was trained on data that was incomplete or unrepresentative and the risk of bias or unfairness is quite substantial, says West.
The fairness and equity of algorithms are only as good as the data-programming that underlie them. For the last few decades weve allowed the tech companies to decide, so we need better guardrails and to make sure the algorithms respect human values, West says. We need more oversight.
Michael Ahn, a professor in the department of public policy and public affairs at University of Massachusetts, says AI has the potential to customize government services to citizens based on their data. But while governments could work with companies like OpenAIs ChatGPT, Googles Bard or Metas LLaMa the systems would have to be closed off in a silo.
If they can keep a barrier so the information is not leaked, then it could be a big step forward. The downside is, can you really keep the data secure from the outside? If it leaks once, its leaked, so there are pretty huge potential risks there.
By any reading, underlying fears over the use of technology in the elections process underscored Dominion Voting Systems defamation lawsuit against false claims of vote rigging broadcast by Fox News. AI can weaponize information, West says. Its happening in the political sphere because its making it easier to spread false information, and its going to be a problem in the presidential election.
Introduce AI into any part of the political process, and the divisiveness attributed to misinformation will only amplify. People are only going to ask the questions they want to ask, and hear the answers they like, so the fracturing is only going to continue, says Ahn.
Government will have to show that decisions are made based on data and focused on the problems at hand, not the politics ... But people may not be happy about it.
And much of what is imagined around AI straddles the realms of science fiction and politics. Professor West said he doesnt need to read sci-fi he feels as if hes already living it. Arthur C Clarkes HAL 9000 from 1968 remains our template for a malevolent AI computer. But AIs impact on government, as a recent Center for Public Impact paper put it, is Destination Unknown.
Asked if artificial intelligence could ever become US president, ChatGPT answered: As an artificial intelligence language model, I do not have the physical capabilities to hold a presidential office. And it laid out other hold-backs, including constitutional requirements for being a natural-born citizen, being at least 35 years old and resident in the US for 14 years.
In 2016, the digital artist Aaron Siegel imagined IBMs Watson AI supercomputer running for president a response to his disillusionment with the candidates saying that the computer could advise the best options for any given decision based on its impact on the global economy, the environment, education, health care, foreign policy, and civil liberties.
Last year, tech worker Keir Newton published a novel, 2032: The Year A.I. Runs For President, that imagines a supercomputer named Algo, programmed by a Musk-like tech baron under the utilitarian ethos the most good for the most people and running for the White House under the campaign slogan, Not of one. Not for one. But of all and for all.
Newton says while his novel could be read as dystopian hes more optimistic than negative about AI as it moves from automation to cognition. He says that when he wrote the novel in the fractious lead-up the 2020 election it was reasonable to wish for rational leadership.
I dont think anyone expect AI to be at this point this quickly, but most of AI policymaking is around data analytics. The difference comes when we think AI is making decisions based on its own thinking instead of being prescribed a formula or set of rules.
Were in an interesting place. Even if we do believe that AI can be completely rational and unbiased people will still freak out. The most interesting part of this is not that the government calls for regulation, but the AI industry itself. Its clamoring for answers about what it should even be doing.
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Artificial intelligence coming to a government near you soon? - The Guardian
‘Artificial Intelligence’ May Be the New Buzzword, but Is It Really … – The Motley Fool
Buzzwords have been making their way into our general lexicon for decades. Whether it's famous movie quotes or certain words or phrases, these things have a way of spreading.
Remember when everyone was talking about blockchain? How about the metaverse?
For the last few months, investors have almost undoubtedly seen the term "artificial intelligence" (AI) dominating the headlines. The primary reason for the rise in AI's popularity is the commercial release of a tool called ChatGPT, which was developed by a company called OpenAI.
Let's dig in and see what all of the hoopla is about.
Alphabet (GOOG 0.01%) (GOOGL 0.11%) invested material time and capital in its own machine learning and AI capabilities. For example, the company has a conversational tool called Language Model for Dialogue Applications, or "LaMDA."
Furthermore, investors have been told about an internal AI product called Bard for quite some time. However,after years of dropping breadcrumbs, Alphabet finally gave the public a little preview of its own AI ambitions following the release of ChatGPT. The results weren't great.
Back in February, shares in Alphabet dropped nearly 14% across two trading days. During this period, Alphabet formally demonstrated Bard to the public, only to realize the AI still contains some bugs. This outcome was a bit ironic because just a few days before the public debut of Bard, Alphabet made a $300 million investment in a company called Anthropic, which is a competitor to ChatGPT.
Image source: Getty Images.
One of Alphabet's top competitors, Microsoft(MSFT -0.12%), has a completely different approach to commercial AI. Unlike Alphabet, which waited for years to debut Bard, Microsoft committed to a multibillion-dollar investment over the course of the next several years in OpenAI almost immediately following broad release of ChatGPT.
Since its investment, Microsoft has already been marketing new products. A fellow Fool contributor recently covered Microsoft's new AI art platform called DALL-E (it's a pun!) in this video. I have been a power user of DALL-E for a little while. My take is that it's entertaining and far more affordable than other artistic software available on the market. And while creating art is fun and satisfying, Microsoft has greater plans for OpenAI.
Despite the near-term cyclical headwinds the company will likely continue facing in its consumer hardware business, as well as its cloud business, Azure, Microsoft's management has a robust product roadmap and long-term vision. Most notably, Microsoft plans to integrate the technology from OpenAI into its search tools and cloud applications. This could have significant repercussions for Alphabet's search enginer, Google, while simultaneously help propel its cloud business forward and catch up to Amazon's cloud infrastructure, AWS.
Corporations of all sizes are relying more heavily on data to make strategic decisions. AI technology is undoubtedly one of the core pillars of this digital transformation. But with that said, there are a few things going on here that investors should acknowledge.
First and foremost, in investing (and in life) it is rarely a good idea to follow the pack. What this means is that even though AI is a new, trending topic, it does not mean it's necessarily a sound investment at the moment.
Microsoft and Alphabet are two of the largest corporations in the world by market capitalization. As of the time of this article, the combined market caps of these two behemoths is $3.5 trillion. I point this out in an effort to illustrate that while both firm's respective investments in AI appear significant, a few hundred million dollars for Alphabet, or even billions in the case of Microsoft, is not a huge commitment.
Perhaps most important is that both companies are several years away from monetizing these investments to their full potential. For Alphabet, management needs to step up and figure out when its AI products, which have been mostly secret up until recently, will work properly and be commercially released.
By contrast, Microsoft now needs to execute on its vision. Layering AI capabilities into cloud applications is an enormously complex project. While Microsoft has the talent and capital to do this, the company is likely years away from full monetization.
Investors looking to acquire shares in Alphabet or Microsoft should do so. However, the underlying thesis should not be AI. Both companies have plenty of other products and growth engines for investors to analyze. While the prospects of AI are exciting, the most prudent action for long-term investors should be to listen to earnings calls and assess if management is executing on its vision, or if it sounds like AI is becoming a costly burden.
John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Adam Spatacco has positions in Alphabet, Amazon.com, and Microsoft. The Motley Fool has positions in and recommends Alphabet, Amazon.com, and Microsoft. The Motley Fool has a disclosure policy.
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'Artificial Intelligence' May Be the New Buzzword, but Is It Really ... - The Motley Fool