Category Archives: Artificial Intelligence
Column: The artificial intelligence field is infected with hype. Here’s how not to get duped – Yahoo Finance
The star of the show at Tesla's annual "AI Day" (for "artificial intelligence") on Sept. 30 was a humanoid robot introduced by Tesla Chief Executive Elon Musk as "Optimus."
The robot could walk, if gingerly, and perform a few repetitive mechanical tasks such as waving its arms and wielding a watering can over plant boxes. The demo was greeted enthusiastically by the several hundred engineers in the audience, many of whom hoped to land a job with Tesla.
"This means a future of abundance," Musk proclaimed from the stage. "A future where there is no poverty. ... It really is a fundamental transformation of civilization as we know it."
We still don't have a learning paradigm that allows machines to learn how the world works, like human and many non-human babies do.
AI researcher Yann LeCun
Robotics experts watching remotely were less impressed. "Not mind-blowing" was the sober judgment of Christian Hubicki of Florida State University.
Some AI experts were even less charitable. "The event was quite the dud," Ben Shneiderman of the University of Maryland told me. Among other shortcomings, Musk failed to articulate a coherent use case for the robot that is, what would it do?
To Shneiderman and others in the AI field, the Tesla demo embodied some of the worst qualities of AI hype; its reduction to humanoid characters, its exorbitant promises, its promotion by self-interested entrepreneurs and its suggestion that AI systems or devices can function autonomously, without human guidance, to achieve results that outmatch human capacities.
"When news articles uncritically repeat PR statements, overuse images of robots, attribute agency to AI tools, or downplay their limitations, they mislead and misinform readers about the potential and limitations of AI," Sayash Kapoor and Arvind Narayanan wrote in a checklist of AI reporting pitfalls posted online the very day of the Tesla demo.
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"When we talk about AI," Kapoor says, "we tend to say things like 'AI is doing X artificial intelligence is grading your homework,' for instance. We don't talk about any other technology this way we don't say, 'the truck is driving on the road' or 'a telescope is looking at a star.' It's illuminating to think about why we consider AI to be different from other tools. In reality, it's just another tool for doing a task."
That is not how AI is commonly portrayed in the media or, indeed, in announcements by researchers and firms engaged in the field. There, the systems are described as having learned to read, to grade papers or to diagnose diseases at least as well as, or even better than, humans.
Kapoor believes that the reason some researchers may try to hide the human ingenuity behind their AI systems is that it's easier to attract investors and publicity with claims of AI breakthroughs in the same way that "dot-com" was a marketing draw around the year 2000 or "crypto" is today.
What is typically left out of much AI reporting is that the machines' successes apply in only limited cases, or that the evidence of their accomplishments is dubious. Some years ago, the education world was rocked by a study purporting to show that machine- and human-generated grades of a selection of student essays were similar.
The claim was challenged by researchers who questioned its methodology and results, but not before headlines appeared in national newspapers such as: "Essay-Grading Software Offers Professors a Break." One of the study's leading critics, Les Perelman of MIT, subsequently built a system he dubbed the Basic Automatic B.S. Essay Language Generator, or Babel, with which he demonstrated that machine grading couldn't tell the difference between gibberish and cogent writing.
"The emperor has no clothes," Perelman told the Chronicle of Higher Education at the time. OK, maybe in 200 years the emperor will get clothes. ... But right now, the emperor doesnt.
A more recent claim was that AI systems "may be as effective as medical specialists at diagnosing disease," as a CNN article asserted in 2019. The diagnostic system in question, according to the article, employed "algorithms, big data, and computing power to emulate human intelligence."
Those are buzzwords that promoted the false impression that the system actually did "emulate human intelligence," Kapoor observed. Nor did the article make clear that the AI system's purported success was seen in only a very narrow range of diseases.
AI hype is not only a hazard to laypersons' understanding of the field but poses the danger of undermining the field itself. One key to human-machine interaction is trust, but if people begin to see a field having overpromised and underdelivered, the route to public acceptance will only grow longer.
Oversimplification of achievements in artificial intelligence evokes scenarios familiar from science fiction: futurescapes in which machines take over the world, reducing humans to enslaved drones or leaving them with nothing to do but laze around.
A persistent fear is that AI-powered automation, supposedly cheaper and more efficient than humans, will put millions of people out of work. This concern was triggered in part by a 2013 Oxford University paper estimating that "future computerization" placed 47% of U.S. employment at risk.
Shneiderman rejected this forecast in his book "Human Centered AI," published in January. "Automation eliminates certain jobs, as it has ... from at least the time when Gutenberg's printing presses put scribes out of work," he wrote. "However, automation usually lowers costs and increases quality.... The expanded production, broader distribution channels, and novel products lead to increased employment."
Technological innovations may render older occupations obsolete, according to a 2020 MIT report on the future of work, but also "bring new occupations to life, generate demands for new forms of expertise, and create opportunities for rewarding work."
A common feature of AI hype is the drawing of a straight line from an existing accomplishment to a limitless future in which all the problems in the way of further advancement are magically solved, and therefore success in reaching "human-level AI" is "just around the corner."
Yet "we still don't have a learning paradigm that allows machines to learn how the world works, like human and many non-human babies do," Yann LeCun, chief AI scientist at Meta Platforms (formerly Facebook) and a professor of computer science at NYU, observed recently on Facebook. "The solution is not just around the corner. We have a number of obstacles to clear, and we don't know how."
So how can readers and consumers avoid getting duped by AI hype?
Beware of the "sleight of hand that asks readers to believe that something that takes the form of a human artifact is equivalent to that artifact," counsels Emily Bender, a computational linguistics expert at the University of Washington. That includes claims that AI systems have written nonfiction, composed software or produced sophisticated legal documents.
The system may have replicated those forms, but it doesn't have access to the multitude of facts needed for nonfiction or the specifications that make a software program work or a document legally valid.
Among the 18 pitfalls in AI reporting cited by Kapoor and Narayanan are the anthropomorphizing of AI tools through images of humanoid robots (including, sadly, the illustration accompanying this article) and descriptions that utilize human-like intellectual qualities such as "learning" or "seeing" these tend to be simulations of human behavior, far from the real thing.
Readers should beware of phrases such as the magic of AI or references to "superhuman" qualities, which "implies that an AI tool is doing something remarkable," they write. "It hides how mundane the tasks are."
Shneiderman advises reporters and editors to take care to "clarify human initiative and control. ... Instead of suggesting that computers take actions on their own initiative, clarify that humans program the computers to take these actions."
It's also important to be aware of the source of any exaggerated claims for AI. "When an article only or primarily has quotes from company spokespeople or researchers who built an AI tool," Kapoor and Narayanan advise, "it is likely to be over-optimistic about the potential benefits of the tool."
The best defense is healthy skepticism. Artificial intelligence has progressed over recent decades, but it is still in its infancy, and claims for its applications in the modern world, much less into the future, are inescapably incomplete.
To put it another way, no one knows where AI is heading. It's theoretically possible that, as Musk claimed, humanoid robots may eventually bring about "a fundamental transformation of civilization as we know it." But no one really knows when or if that utopia will arrive. Until then, the road will be pockmarked by hype.
As Bender advised readers of an especially breathless article about a supposed AI advance: "Resist the urge to be impressed."
This story originally appeared in Los Angeles Times.
Tech companies tapping artificial intelligence to treat and predict mental health disorders – CNA
SINGAPORE: Could the future of managing mental health lie in strings of code and predictive models?
Behavioural health tech provider Holmusk is banking on that, partnering authorities in Singapore to develop a suite of digital tools for hospitals and clinics.
One solution the firm is looking to introduce is a smart pill to track when patients forget or skip their medication.
How that works, is through a small, grain-sized biosensor embedded within the pill, and a sticky patch on the patients body that can detect when the pill is ingested. The technology is approved in the United States.
Let's say schizophrenia, depression patients with some psychosis not taking the pill for a few days can be bad enough to drive them off the cliff. And if you knew that they have stopped taking the pill two days in a row, you can intervene. You can catch them early, chief analytics officer of Holmusk, Joydeep Sarkar, told CNA.
He described the sensor as a "fascinating solution", which will work with other parts of the puzzle - ensuring that the information is fed into the patients clinical records, flagging missed doses, and ensuring any necessary intervention is part of the workflow.
The firm has also developed an artificial intelligence (AI) model to analyse information from notes-driven mental health treatment or therapy.
This may allow researchers to generate insights into the efficacy of treatments and the progression of disorders at a larger scale in future.
Such data in areas like medication and treatment could also feed into predictive models to understand the risks surrounding each patient.
"A big part of where artificial intelligence plays a role is more complex patients - where the answers are not obvious, Mr Sarkar said.
Let's say somebody comes in and you stabilise them, and you keep them in the hospital. When is it okay to release them What support systems could you actually really have in place so that patients don't get worse?
One disease his firm is looking to zoom in on is bipolar disorder, which has a high genetic component.
The aim is to tap data to identify and track those at risk of developing the disorder to catch the signs early.
"I call them the low-hanging fruit because you don't really need much, (you) just (need) to connect the data, Mr Sarkar said.
Other industry players are also looking to tap into artificial intelligence to help people take care of their own mental health.
Among them is mental health platform Intellect, which has attracted 3 million users globally since its launch in 2020.Mental health has long been a very strong need across Asia, in the world. That has been unmet in support. We've seen quite a sharp rise in client service over two years, said Intellect chief executive Theodoric Chew.
Intellect's app uses information like user-reported moods and usage patterns to recommend programmes to users. It also uses algorithms to match individuals to therapists, based on their needs and specialisations.
The app counts 24-year-old Charis Liang among its users. The undergraduate, who previously worked as an intern at the company, takes to the app for sessions when she's overwhelmed and needs help quickly.
You can't call up your therapist at 3am, but you can do this", she said. Ms Liang said exercises on the app, based on cognitive behavioural therapy, are similar to what she went through at a traditional therapy session with the added ease of being on-demand.
Originally posted here:
Tech companies tapping artificial intelligence to treat and predict mental health disorders - CNA
Global Urban Security Screening Markets Report 2022: A $17.91 Billion Market by 2027 – Inclusion of Artificial Intelligence to Bring Digital…
DUBLIN--(BUSINESS WIRE)--The "Global Urban Security Screening Market (2022-2027) by Technology, Application, End-Use, Geography, Competitive Analysis, and the Impact of Covid-19 with Ansoff Analysis" report has been added to ResearchAndMarkets.com's offering.
The Global Urban Security Screening Market is estimated to be USD 11.06 Bn in 2022 and is projected to reach USD 17.91 Bn by 2027, growing at a CAGR of 10.12%.
These forces create pricing signals which result from the changes in the supply and demand curves for a given product or service. Forces of Market Dynamics may be related to macro-economic and micro-economic factors. There are dynamic market forces other than price, demand, and supply.
As the market dynamics impact the supply and demand curves, decision-makers aim to determine the best way to use various financial tools to stem various strategies for speeding the growth and reducing the risks.
The report provides a detailed analysis of the competitors in the market. It covers the financial performance analysis for the publicly listed companies in the market. The report also offers detailed information on the companies' recent development and competitive scenario.
Some of the companies covered in this report are 3DX-RAY, Adani systems, Analogic, Autoclear, Aware, Bruker, Cognitec Systems, Daon, Dermalog identification systems, Teledyne FLIR, Garett electronics, Leidos, Magal security systems, Metrasens, NEC, Nuctech Company, OSI Systems, Precise Biometrics, Smiths Detection, Stanley Black & Decker, Thales, Vidisco, Westminster Group, etc.
Report Highlights:
Company Profiles
Key Topics Covered:
1 Report Description
2 Research Methodology
3 Executive Summary
3.1 Introduction
3.2 Market Size, Segmentations and Outlook
4 Market Dynamics
4.1 Drivers
4.1.1 Global Increase in Terrorist Attacks
4.1.2 Public Gatherings Fuel Demand for Security Enhancement Solutions
4.1.3 Improvements in Security Screening at Airports
4.1.4 Surge In Demand for Biometrics Solutions in Private Sector
4.2 Restraints
4.2.1 High Installation and Maintenance Costs
4.3 Opportunities
4.3.1 Technological Advancements in Security Screening Systems
4.3.2 Inclusion Of Artificial Intelligence to Bring Digital Transformation in Security Applications
4.4 Challenges
4.4.1 Health Hazards of Full-Body Scanning
4.4.2 Privacy Concerns
5 Market Analysis
5.1 Regulatory Scenario
5.2 Porter's Five Forces Analysis
5.3 Impact of COVID-19
5.4 Ansoff Matrix Analysis
6 Global Urban Security Screening Market, By Technology
6.1 Introduction
6.2 X-Ray Screening
6.2.1 Body Scanners
6.2.2 Baggage Scanners
6.2.3 Handheld Scanners
6.2.4 Cabinet X-Ray Systems
6.3 Biometric
6.3.1 Facial Recognition Systems
6.3.2 Iris Recognition Systems
6.3.3 Fingerprint Recognition System
6.4 Electromagnetic Metal Detection
6.5 Spectrometry and Spectroscopy
6.6 Others
7 Global Urban Security Screening Market, By Application
7.1 Introduction
7.2 People Screening
7.3 Baggage and Cargo Screening
7.4 Vehicle Inspection
8 Global Urban Security Screening Market, By End-Use
8.1 Introduction
8.2 Transportation
8.3 Retail Stores and Malls
8.4 Hospitality
8.5 Government
8.6 Industrial
8.7 Commercial
8.8 Educational Institutes
8.9 Events and Sports
For more information about this report visit https://www.researchandmarkets.com/r/cljzn5
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Global Urban Security Screening Markets Report 2022: A $17.91 Billion Market by 2027 - Inclusion of Artificial Intelligence to Bring Digital...
Insights on the Artificial Intelligence in Supply Chain Global Market to 2027 – Rapidly Growing E-commerce Industry Presents Opportunities -…
DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence in Supply Chain Market Research Report by Offering (Hardware, Services, and Software), Technology, Application, Industry, Region (Americas, Asia-Pacific, and Europe, Middle East & Africa) - Global Forecast to 2027 - Cumulative Impact of COVID-19" report has been added to ResearchAndMarkets.com's offering.
The Global Artificial Intelligence in Supply Chain Market size was estimated at USD 2,661.57 million in 2021, USD 3,350.10 million in 2022, and is projected to grow at a CAGR 26.04% to reach USD 10,673.88 million by 2027.
Competitive Strategic Window:
The Competitive Strategic Window analyses the competitive landscape in terms of markets, applications, and geographies to help the vendor define an alignment or fit between their capabilities and opportunities for future growth prospects. It describes the optimal or favorable fit for the vendors to adopt successive merger and acquisition strategies, geography expansion, research & development, and new product introduction strategies to execute further business expansion and growth during a forecast period.
FPNV Positioning Matrix:
The FPNV Positioning Matrix evaluates and categorizes the vendors in the Artificial Intelligence in Supply Chain Market based on Business Strategy (Business Growth, Industry Coverage, Financial Viability, and Channel Support) and Product Satisfaction (Value for Money, Ease of Use, Product Features, and Customer Support) that aids businesses in better decision making and understanding the competitive landscape.
Market Share Analysis:
The Market Share Analysis offers the analysis of vendors considering their contribution to the overall market. It provides the idea of its revenue generation into the overall market compared to other vendors in the space. It provides insights into how vendors are performing in terms of revenue generation and customer base compared to others. Knowing market share offers an idea of the size and competitiveness of the vendors for the base year. It reveals the market characteristics in terms of accumulation, fragmentation, dominance, and amalgamation traits.
The report provides insights on the following pointers:
1. Market Penetration: Provides comprehensive information on the market offered by the key players
2. Market Development: Provides in-depth information about lucrative emerging markets and analyze penetration across mature segments of the markets
3. Market Diversification: Provides detailed information about new product launches, untapped geographies, recent developments, and investments
4. Competitive Assessment & Intelligence: Provides an exhaustive assessment of market shares, strategies, products, certification, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players
5. Product Development & Innovation: Provides intelligent insights on future technologies, R&D activities, and breakthrough product developments
The report answers questions such as:
1. What is the market size and forecast of the Global Artificial Intelligence in Supply Chain Market?
2. What are the inhibiting factors and impact of COVID-19 shaping the Global Artificial Intelligence in Supply Chain Market during the forecast period?
3. Which are the products/segments/applications/areas to invest in over the forecast period in the Global Artificial Intelligence in Supply Chain Market?
4. What is the competitive strategic window for opportunities in the Global Artificial Intelligence in Supply Chain Market?
5. What are the technology trends and regulatory frameworks in the Global Artificial Intelligence in Supply Chain Market?
6. What is the market share of the leading vendors in the Global Artificial Intelligence in Supply Chain Market?
7. What modes and strategic moves are considered suitable for entering the Global Artificial Intelligence in Supply Chain Market?
Market Dynamics
Drivers
Restraints
Opportunities
Challenges
Companies Mentioned
For more information about this report visit https://www.researchandmarkets.com/r/1rs55q
Pellenc ST aims to optimise sorting technology with combination of X-ray and artificial intelligence – Packaging Europe
Pellenc ST claims that its new instalment of Xpert technology combines a dual-energy transmission X-ray with machine learning, a form of artificial intelligence said to learn and remember data to improve the efficiency of metal and e-scrap waste sorting processes.
Functioning with a detector and a 100-Watt X-ray generator, the machine can run a conveyor from 2 m/s to 4.5 m/s depending on its application. Its new software can apparently target multiple materials and densities in a single sorting step, enabling high-capacity sorting without sacrificing performance.
This enhanced sorting process is said to recognise the shape, density, and thickness of the materials that pass through it. In doing so, it can improve recovery rates in metal sorting by removing plastics containing flame retardants and other charges, as well as recovering high-added-value materials such as PCBs.
According to Pellenc ST, the Xpert is utilised to process Zorba and for sorting different aluminium alloys in order to produce a Twitch product, which can then be sent to a furnace. It can also sort leaded glass, it is claimed.
PellencSTs turnkey service solution is available with wear parts and the Smart&Share application, which is said to analyse the operation of individual sorters and provide alerts and reports aimed at improving availability and sorting quality. The machinery is equipped with the Central Nervous System (CNS) software platform, allowing for future upgrades as new technologies and sensors arise.
The new technology is expected to improve safety, reduce the workload of operators, and lower maintenance costs.
Earlier this year, the Perfect Sorting Consortium was formed to develop and test an artificial intelligence decision model to improve the recycling of packaging over the next two years.
CEFLEX also ran a testing programme to test the sorting of multi-layer flexible packaging using NIR technology. It was anticipated that the results would be shared with stakeholders last month.
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Pellenc ST aims to optimise sorting technology with combination of X-ray and artificial intelligence - Packaging Europe
World’s most popular car brands through the eyes of artificial intelligence – Hippo Leasing
With the recent invention of artificial intelligence or AI being able to generate imagery, here at Hippo Leasing, we thought wed see how AI Image Generators would interpret, and consequently create, imagery based on what car manufacturers say about the design of their vehicle.
As a result, we have taken snippets of the descriptions used by car manufacturers about the design of their cars. These words were then inputted into AI Image Generators to see how the same car would look through the eyes of AI.
According to Car Industry Analysis, the most popular hatchback worldwide on the market today is the Toyota Corolla. When referring to the Toyota website, they describe the Corolla as having:
a distinctive and strikingly sleek exterior, which can be made even more eye-catching with a variety of bi-tone paint options. A low bonnet increases the drivers field of vision while an impressive wide grill and stand-out LED headlights add to the refined profile.
AI Input Criteria
We then input certain words and phrases from the description provided by Toyota into AI Imagery Generator DALL.E mini by Craiyon, which creates a collage of nine different images based on the entered information. These were:
Car / distinctive / strikingly sleek / eye-catching / bi-tone paint colours / impressive wide grille / refined profile.
Image Generated
The AI Image Generator then produced the following
As you can see from the image generated, the AI pictured a much sleeker and sportier car than anticipated. The Toyota Corolla is the manufacturers flagship hatchback and does have a sporty-look variant in its GR SPORT model, however, the AI seems to have gone a step further and developed a car with a more polished sports-coupe feel.
We then followed the same methodology for other popular cars to see if the AI could get any closer to the actual real-life vehicles.
Toyota describe the RAV4 as:
Powerful with a real road presence, the RAV4s strong body draws the eye from the elegant front LED headlights, along the bold silhouette and through to the unique LED rear lights producing a look that is individual and refined.
AI Input Criteria
SUV, powerful, strong body, elegant, unique, individual, refined.
Image Generated
The AI certainly captured the SUV element here, with all images generating large 44 type cars. It could be argued, however, that the elegant and refined elements of Toyotas RAV4 are missing though, with the AI producing a far bolder and boxier look to its cars that resemble something more like a Mercedes-Benz G-Class.
Fords F-150 might not be available in the UK, but it doesnt stop the American go-to truck from being the worlds most popular Pick-Up Truck. Fords website uses words and phrases to describe their F-150, such as:
Tough and productive, supreme comfort, off-roader, and big front grille.
AI Input Criteria
Pick-up truck, tough, productive, comfort, off-roader, big front grille.
Image Generated
As you can see, the AI has managed to produce a car that genuinely resembles an F-150 pretty closely, which is remarkable. The big grille and tough looks are definitely captured in these images, especially those on the top line.
Ford also has two of the most popular cars worldwide when figures are broken down into body types. In the sports car category, their Mustang tops the charts. Ford describes the Mustang as:
Streamlined, aeronautically inspired, an icon, fun, has new unique colour choices, and aerodynamic.
AI Input Criteria
Sports car, streamlined, aeronautical, iconic, fun, unique colours, aerodynamic.
Image Generated
Wow! Has there ever been a greater contrast in styles? Sports car, streamlined, aeronautical, iconic, fun, unique colours and aerodynamic are all certainly apparent, but the AI seems to have taken a 1950s concept car theme for the vehicles it has generated. The complete opposite end of the scale to how Fords ferocious-looking Mustang has been designed.
Tesla has taken the world by storm and has been a key trailblazer when it comes to electric cars. Their Model 3 is currently the most popular EV, and their site describes its design as:
Built for safety, brighter, more spacious and enhanced comfort.
As this wasnt too much to go off, we researched how others described the design of the Tesla Model 3, such as Business Insider, who said the Model 3 was:
Subtle, graceful, disciplined, and restrained.
AI Input Criteria
Electric car, subtle, graceful, disciplined, restrained, safe, bright, spacious, comfortable.
Image Generated
The AI interestingly sees the Tesla Model 3 in a much more futuristic way and has lent on a design very reminiscent of early EV concept art, where cars went from saloon-type shapes to smaller and almost bubble-like in design. We see a little bit of the BMW i meets the Seat Ami here.
The Corolla covered earlier is also a Hybrid, so next on the list is Hondas CR-V, which sold over 900,000 units and was the third best-selling car last year. Honda describes their hybrid as:
The spaciousness, combined with its distinctive, sporty design, provides real driving pleasure for you and your passengers The CR-V is so spacious. The open, airy feeling creates a relaxing and comfortable ambience combined with the practicality and convenience of a large boot.
AI Input Criteria
Hybrid car, spacious, distinctive, sporty, relaxing, comfortable, practical, convenient.
Image Generated
The AIs version of a Honda CR-V is quite accurate in comparison to other attempts at recreating the types of cars. The size and shape of the cars in particular are pretty close to the real CR-V, as well as the overall look and feel.
The Nissan Sentra is another car not available in the UK, but outside the UK its the best-selling saloon with nearly 700,000 units sold last year worldwide. Nissan describes the Sentra as:
Crisp and modern, the 2022 Sentra features advanced technology and a premium feel inside and out.
They also refer to the Sentra as:
Compact, stylish, sculpted, painstakingly crafted, serious attitude, sport-inspired, aggressive, powerful, exciting, crisp and modern, and sporty.
AI Input Criteria
Sedan, crisp, modern, premium, compact, stylish, aggressive, powerful, exciting sporty.
Image Generated
Similarly, to the Honda CR-V, the AIs attempt at recreating the Nissan Sentra is relatively accurate. Its created a saloon car with an executive feel and in the right colour scheme and style of the American-based saloon.
As you can see from the images generated by the AI, some get pretty close to how the actual cars look in real life and then some are a complete contrast.
The AI did a really good job at recreating the Ford F-150, with the first row, in particular, looking almost identical. It also did pretty well with the Honda CR-V and Nissan Sentra, getting the overall size and shape of the cars accurate as well as some of the styling features too.
At the other end of the scale, we have the images generated of the Ford Mustang, a tough, bold and fierce-looking muscle car.
After looking into how AI Imagery Generators perceive different cars using their features, we then wondered how theyd interpret manufacturers slogans and/or taglines.
Slogan/Tagline = Vorsprung durch Technik (Progress Through Technology)
Image Generated
The AI has interpreted Progress Through Technology by generating what appears, for the most part, to be holographic images of Earth, with some showing human hands interacting with the hologram. Could this be the AI telling us that well be able to interact, or control, our planet through technology in the future?
Slogan = Sheer Driving Pleasure
Image Generated
AI seems to picture Sheer Driving Pleasure as a nice drive in the countryside on a summers day. It does seem pleasurable.
Slogan = Best or Nothing
Image Generated
We have no idea what the AI has in mind when it comes to Best or Nothing. But what we do know is that it is very, very weird.
Slogan = The Power of Dreams
Image Generated
The visualisation the AI has come up with for The Power of Dreams seems logical, although somewhat trippy, and a little bit spiritual/Godly at the same time.
Slogan = The Art of Performance
Image Generated
The Art of Performance through the eyes of AI is quite interesting, as it appears to focus on the theatrical version of performance, instead of other things such as mechanical performance or athletic performance.
Slogan = Lets Go Places
Image Generated
The AI seems to want a trip to the beach, as all the imagery it has produced from the phrase Lets Go Places pretty much centres around a seaside setting.
Slogan = Movement that inspires
Image Generated
The AI has interpreted Movement that inspires as dance.
Slogan = Simply Clever
Image Generated
Were not entirely sure what the AIs goal was when visualising Simply Clever, but it seems to be Art of some kind or a new form of typography, maybe?
Slogan = The Future is Sustainable
Image Generated
Green is the theme that the AI has produced when visualising The Future is Sustainable. It pictures what seems to be a green version of Earth, sometimes cupped in human hands.
Slogan = Drive your Ambition
Image Generated
The AI has produced a varied assortment of visuals for Mitsubishis Drive your Ambition slogan. We get a curved road in most pictures, some with a human either on or to the side of them, and some show people looking out of the window while parked by the side of the road.
We then thought, what would happen if you input the same criteria into other AI Image Generators? Will we get the same outcome or something entirely different?
As you can see, theres a huge difference in how the various AI Image Generators interpret Audis Vorsprung durch Technik slogan. In comparison to how DALL.E mini visualised the slogan, Hypotenuse AI delivered two medieval, yet futuristic, sets of armour. Dream AI produced a rather odd timeline-looking visual, which goes up to 2080, and Night Cafe produced a landscape picture of what looks like another world close to Earth, in the future.
As for the comparison between Tesla Model 3s, the AIs definitely still interpreted things differently, however, its a lot closer than Audis slogan. Theyve all created a curvy car, and picture it in a futuristic, clean design. The only main differences are that all except Hypotenuse shape the car in a bubble-like, small hatchback style, and all except Dream have the majority of the car coloured white.
We hope you enjoyed seeing artificial intelligence interpretations of the worlds most popular cars. If you would like to lease one of the real most popular cars, you can with Hippo Leasing. If you need any help or have any questions, please feel free to get in touch and one of our team will be on hand to assist you with anything you need.
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World's most popular car brands through the eyes of artificial intelligence - Hippo Leasing
Trusted Customer Experiences and Payments Innovation Driven by Artificial Intelligence – Global Banking And Finance Review
Yuval Marco, General Manager, Enterprise Fraud Management, NICE Actimize
By Yuval Marco, General Manager, Enterprise Fraud Management, NICE Actimize
Innovation is inextricably linked to financial services and payments, with most financial institutions focusing on payments and streamlined customer experience as the primary focus of their strategic direction. However, innovation doesnt come without risk, and financial institutions require financial crime technologies utilizing artificial intelligence (AI) and machine learning (ML) to realize the optimal customer experience.
Supporting best-in-class customer experience (safely) and maintaining competitive advantages requires strategic investment and monumental change across your financial crime and compliance programs.
While payments innovation has increased access to banking and facilitated instant payments, which are highly beneficial to the customer, they have also drawn interest from fraudsters looking to exploit the instant movement of money. As a result, customers are being targeted for various scams, and financial institutions are in the middle of balancing risk and customer experience in an instant payment environment and undergoing a liability shift. This shift in liability for fraud loss associated with scams from the consumer to the bank are due to the prevalence and sophistication of such complex scams as social engineering, Authorized Push Payment fraud, and romance scams.
Digital Innovation Speeds Fraud Detection
Fraud loss associated with these scams continues to grow significantly in 2022, supported by fraudsters ability to access personally identifiable information on the deep and dark web and weaponize it against their victims. Technology will advance and focus on these themes, particularly on the influence of the compromised PII. The increased speed of fraud detection is at the nexus of supporting payments innovation and customer experience. Led by the digital acceleration and infrastructure changes over the past two years, the new ISO 20022 standardization will enable safer and faster payments with compliance being adopted by new real-time payment entrants such as FedNow, RTR, SWIFTNet Instant, P27 as well as current real-time payment rails.
In addition, AI and ML will be necessary for an intelligent fraud prevention strategy that utilizes automation and decreases friction across the payment lifecycle. The industry will also see fraud strategy and prevention teams shift from simple risk mitigation to forceful business enablers as a smoother frictionless Customer Experience (CX) becomes increasingly improved. CX is no longer a nice to have but a key focus for fraud teams at financial institutions and within contact centers the by-product of digital banking and faster payment.
These interactions must be seamless and secure. As a result, we now see fraud and risk mitigation teams placed more directly in the middle of CX conversations. In other key impact points, identity fraud continues to accelerate and expand to become a core component of payments fraud, money mules, and account takeover. Specific to the US, the Federal Reserve has created a new definition and classifier for Synthetic Identity Fraud (SIF) as they have acknowledged the significant risk these manipulated and fake identities pose as well as the need to fully track fraud losses associated with SIF and build strategies to deter them from being created.
Frictionless Customer Experience Key to Retention
Within the past few years, many financial institutions grappled with the impact of the pandemic. Concerning fraud, payments related to reimbursements afforded consumers and businesses
during this timeframe were the perfect target for fraudsters. Post pandemic, as financial services institutions pivot from storefronts to a dominant online, digital environment, customer
satisfaction and frictionless customer experiences has become even more critical to retaining customers and competing in a digital world.
Fraudsters will continue to refocus their efforts in 2022 by attacking a banks or other corporates assets by perpetrating fraud schemes and flooding traditional payment channels. Increasingly, the industry is seeing well-trained, funded, and equipped fraudsters able to commit fraud at scale using advanced tools and technology, creating a trend of Industrialized Fraud. This was manifested throughout 2021 in the form of business email compromise along with the uptick of ransomware that continues to become more pronounced throughout 2022.
Payments innovation, such as next-generation payment products that include QR, BNPL, Crypto, and Biometric, will also be focused on improving the customer experience led by advancements in digital acceleration and newly adopted infrastructure put in place over the past two years. As a result, faster payments will become more prevalent and even faster.
For example, the new ISO 20022 standardization will offer a universal messaging language that will allow machines to read messages with better automation and faster resolution. According to a 2022 Frost & Sullivan The North American Enterprise Fraud Management Industry Excellence in Best- Practices report, The need for machine learning and advanced analytics to counter sophisticated attacks is paramount; fraud solutions must maintain a friction right customer experience and manage immense volumes of data. FIs must support increased customer interactions across newer digital channels; they must implement appropriate fraud prevention without compromising on customer experience.
Regardless of the trend, artificial intelligence is at the core of advancements that will drive process improvements that ultimately lead to exceptional customer experiences and a more competitive position in the market for the financial institution that implements them in their technology and infrastructure strategy moving forward.
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Trusted Customer Experiences and Payments Innovation Driven by Artificial Intelligence - Global Banking And Finance Review
Artificial Intelligence to act as catalyst in India’s transformation into a developed nation by 2047: Piyush.. – ETCIO
Union Minister of Commerce and Industry, Consumer Affairs, Food and Public Distribution and Textiles Piyush Goyal on Friday said Artificial Intelligence will help the country become a developed nation by 2047. "AI will act as a catalyst in India's journey towards becoming a developed nation by 2047 and bring prosperity to every citizen of this country," the minister said while addressing the 3rd edition of Global Artificial Intelligence Summit & Awards in New Delhi.
Goyal said Artificial intelligence will truly be a catalyst in India's development journey, and added that The Make in India program when juxtaposed with AI technology, will enable India to become the factory of the world providing both equipment and technology to the world. He noted that the huge talent pool available in the country will definitely help in exploring newer ways to take AI in every sector of economic activity. The minister appreciated the Department of Science and Technology for its wonderful work in supporting the efforts of the scientific community of the country over the years, and particularly during the challenging times of Covid.
The government is using AI to redefine the way it works, he said citing the example of Unified Logistics Interface Platform (ULIP), which is leveraging AI to improve the entire logistics ecosystem of the country. Similarly initiatives like PM Gatishakti National Master Plan, which aims at developing our infrastructure smarter; ONDC, which aims at democratising E- commerce, GeM which has made a significant impact for government procurement - all these are leveraging Artificial Intellegence to bring efficiency and better delivery of services.
Stating that the AI revolution is here to stay, he added that with the meaningful contribution by industry, startups, incubators and academia, India is going to emerge as the hub of the artificial intelligence revolution across the world. He urged the young minds to inculcate the spirit of inquiry and start thinking of different ways the AI technologies can be harnessed to bring prosperity in our day to day life. He asked them to explore how AI can play a crucial role in empowering the lives of farmers, fishermen and the MSME sector.
The third AI Summit has been organised by AICRA and is focusing on the areas of defence, healthcare, agriculture, smartcities, mobility and education in partnership with the government. The aim is to develop a roadmap on how to use AI ecosystem and startups for the benefit of society. The 3rd annual conference has set up multidisciplinary groups to break down the silos in which different stakeholders have been working and to find technological solutions for the key sectors of our society, according to a press release.
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Artificial Intelligence to act as catalyst in India's transformation into a developed nation by 2047: Piyush.. - ETCIO
Faculty Position in Artificial Intelligence and Advanced Computing job with XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU) | 311882 – Times Higher…
Position Title: Faculty Position in Artificial Intelligence and Advanced Computing
Position Information: Open Rank
School: School of AI and Advanced Computing, XJTLU Entrepreneur College
Academic Discipline: Computer science, data science, artificial intelligence, networking and communication, systems engineering.
Location: Taicang, Greater Suzhou, China
ABOUT XJTLU
In 2006 Xian Jiaotong-Liverpool University (XJTLU) was created by the University of Liverpool and Xian Jiaotong University a top ten university in China. Offering a unique international education experience, XJTLU brings together excellent research practice and expertise from both institutions and gives students the skills and knowledge they need to secure careers in a global marketplace. XJTLU now has over 25,000 enrolled students in both Suzhou and Liverpool in the UK, with plans to grow to about 28,000 students by 2025. There are currently about 2,000 staff, among which about 1,000 academic staff, with an almost even split between citizens of the Peoples Republic of China and international passport holders. XJTLU offers our undergraduates and postgraduates over 100 programmes with a diverse spectrum of courses.
With a focus on innovative learning and teaching, and research, XJTLU draws on the strengths of its parent universities, and plays a pivotal role in facilitating access to China for UK and other institutional partners. At same time, XJTLU is exploring future education by blending the educational theory, best practice and culture from west and east.
For detailed information about the university, please visitwww.xjtlu.edu.cn.
ABOUT ENTREPRENEUR COLLEGE (TAICANG)
In 2019, XJTLU launched Entrepreneur College, which was build and developed in collaboration with the Taicang Municipal Government and industry partners. In September 2022, XJTLU Entrepreneur College just moved to a new campus in Taicang, part of Greater Suzhou, which also won the WAN Awards for the campus design. The XJTLU Entrepreneur College are a pioneers of, and an educational model for, the future college in developing talents and leaders to meet local, national, and global challenges from the 4th Industrial Revolution. As a result, there are opportunities at all levels for innovative academics in the fields represented by the following schools and education platforms:
ABOUT THE SCHOOL OF AI AND ADVANCED COMPUTING
The School of AI and Advanced Computing is one of the 7 industry-themed Schools in the XJTLU Entrepreneur College (Taicang). Each School consists of an Education, Research and Development Institute (ERDI) for teaching and university-business research collaboration, a professional services centre supporting daily activities of students, staff, and business partners, and a School Affiliated Company jointly established by XJTLU and the Schools industry partner for practical on-the-job learning and teaching.
Industry Partner Overview
The current major partner in collaboration with XJTLU to co-develop the School of AI and Advanced Computing is SUGON.
Sugon is a leading enterprise in the field of high-performance computing, server, storage, cloud computing and big data in China. It is a national high-tech enterprise formed on the foundations of the significant scientific and technological achievements made under the National 863 Programme and with the strong support of the Chinese Academy of Sciences. More information please see https://www.sugon.com/en.
Personal Attributes
The School of AI and Advanced Computing is adopting a new higher education model based upon the concept of Syntegrative Education (SE). SE is a new model developed by the University to address an increasingly networked and complex future of work in the 4th Industrial Revolution. The model is core to the Universitys strategy for its next ten-year development focusing on innovation and entrepreneurship. SE aims to train syntegrative leaders with Management skills, International perspective, Discipline-specific knowledge, and adaptability in Industry (MIDI).
The position will attract individuals embodying these SE values and are passionate in engaging in a future-focused co-learning ecosystem comprising students, academics, practitioners, university, industry, and community. The School seeks academic members who thrive by creating impact through authentic engagement, cross-boundary collaboration, collective learning and discovery, and action-oriented inquiries. These creative educators adopt a systems mindset and use their knowledge, skills, and experiences to co-design and deliver an enriching educational experience for students. They view education as an integrative and life-long transformative process.
RESPONSIBILITIES
We are looking for future colleagues from candidates in all the fields of computer science, data science, artificial intelligence, machine learning, networking and communication, and systems engineering who can:
ESSENTIAL QUALIFICATIONS/EXPERIENCES
DESIRABLE QUALIFICATIONS/EXPERIENCE
CITIZENSHIP AND VISA REGULATIONS
Employment at Xian Jiaotong-Liverpool University is regulated by Chinese Labour Laws, and must comply with the regulations of the provincial government. These regulations stipulate who is eligible for legal employment with regard to obtaining work permits and visas. Please be advised candidates over 65 may be not eligible for a work visa in the P.R. China.
CAREER DEVELOPMENT
COPENSATION & BENEFITS
SALARY: Competitive salary in the market
BENEFITS
HOW TO APPLY
Please submit your application on our university website:
https://career15.sapsf.cn/career?career_company=xjtlu
Applications must be submitted in a single pdf file that includes 3 parts in the order of:
For specific enquiries relating to the position, please email to Professor Angelos Stefanidis, Dean of School by email on Angelos.Stefanidis@xjtlu.edu.cn. or to HRBP on Mingyu.Yuan@xjtlu.edu.cn.
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Faculty Position in Artificial Intelligence and Advanced Computing job with XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU) | 311882 - Times Higher...
How Artificial Intelligence Testing is Changing the Cyberworld? – ReadWrite
In the cybersecurity sector, artificial intelligence testing is crucial. This is because AI has the potential to help cybersecurity overcome some of its major obstacles. And there are many obstacles, including the incapacity of many organizations to stay on top of the numerous new risks and attacks that emerge as the internet and technological usage increase.
AI-powered cybersecurity is expected to change how we respond to cyber attacks. Because of its capacity to study and learn from enormous volumes of data, artificial intelligence will be crucial in identifying sophisticated threats. Moreover, AI testing is an all-in-one answer to safeguard these gadgets from malicious actors, as new technology and gadgets are always available.
This blog will walk you through the difficulties that the cybersecurity sector is now facing, the significance of employing Artificial Intelligence testing to overcome those difficulties and some of the drawbacks of doing so. Finally, we shall examine some actual applications of AI in this area before we conclude.
Cybersecurity describes the processes followed by people or organizations to safeguard their online-connected computer hardware and software against cyberattacks.
The proliferation of emerging digital technologies like the Internet of Things (IoT). The rising frequency and intricacy of cyberattacks and rigorous data protection laws for data security. An uptick in attacks that target software supply chains is the key driver of the cybersecurity market.
In addition, the COVID-19 pandemic has increased the incidence of malicious attacks on databases in large enterprises. They are necessitating tighter database protection and fostering the expansion of the cybersecurity industry. In healthcare, banking, insurance, manufacturing, and financial services, growth in adopting organization security solutions is provident.
You may be surprised to learn that human mistake accounts for 95% of cybersecurity breaches, according to a Google survey. These mistakes might include everything from downloading a virus-filled email attachment to using a weak password to access an unsafe website. According to studies, phishing attacks are among the most common cyber events, CEO fraud, stolen computers, and ransomware assaults. The effects of these attacks are stunning, even though they may seem easy to handle. In small and medium businesses (SMBs), data breaches cost, on average, $3.9 million. The top four are the top four: large-scale data monitoring, a slower turnaround, a lack of threat understanding, and organizational compliance standards.
Cybercrime is always changing, with hackers constantly refining their tactics to cause the most harm, complicating the issues outlined in the previous section. Malware that could modify its source to evade detection made up 93.67% of the malware observed in 2019. Additionally, within the same year, 53% of consumer PCs and 50% of commercial computers both relapsed the infection. To eradicate this virus from its source, action and awareness are vital.
We should all be aware of the following examples of the typical cybersecurity threats that clever hackers have cleverly created.
When a hacker uses the social engineering technique of phishing, they send you an email that contains a dangerous link. By clicking the link, you could give them access to your computer so they can infect it with a bug and steal all of your personal data.
If your systems hardware and software are not updated to the most recent versions, missing critical security updates can be a risk. It can be introduced to back doors or trojans and obtain access to the system.
Data going to and from a network endpoint can be hindered by malicious actors and decrypted. If they arent caught in time, they might alter it, tamper with it, or use it illegally.
Since more people are using private and public clouds, unencrypted data stored there is an open invitation to malicious hackers. Data saved in the cloud can also be composed due to unreliable interfaces or APIs, insufficient access control, and inadequate security architecture.
Mobile devices internal operating systems may become unreliable due to this dangerous malware, which could reduce their functionality. This frequently occurs as a result of URLs being insecure online. In addition, downloaded applications with security flaws also contribute to mobile virus problems.
One of the most common types of cyberattacks is ransomware, in which the attackers send a virus into peoples personal laptops and smartphones to access and use the data on those devices. They then want a ransom to give you access to it again.
A notable benefit of AI testing is that it significantly reduces some labor-intensive jobs known to be time-consuming, such as security monitoring, which is unquestionably a significant time-sink for IT security experts. AI testing can do this repetitious labor instead of humans having to keep an eye on numerous gadgets. To enforce proper cybersecurity, decrease attack surfaces, and detect malicious behavior, AI and machine learning testing need to be in collar.
Lets look at some additional crucial areas where AI testing proves to be of the utmost significance:
Each day, data of over 2.5 quintillion bytes are produced. Artificial intelligence (AI) technologies can assist in automating data processing. It makes sense of vast amounts of data that would be impossible for humans to understand in a usable manner. Security experts cannot evaluate and classify every piece of information because firms face millions of risks. As a result, it is tough for security specialists to foresee dangers before they destroy IT systems. Artificial intelligence testing can identify numerous cyber-security threats and issues without human analysts.
By analyzing how users typically interact with their devices, ML algorithms are intelligent enough to learn and create a pattern of user behavior.
AI testing flag the user as suspicious and possibly block them if it notices unexpected behaviors that are out of the ordinary. These actions include altering the users typing speed or attempting to access the system at odd times.
AI testing analyzes millions of events and detects a wide range of threats. These threats include malware that exploits zero-day vulnerabilities, phishing attempts, and malicious code downloads. As a result, AI and ML have emerged as essential information security technologies. Companies may better understand dangers and respond to them faster thanks to these insights. It also helps them adhere to the best security procedures.
Spam detection, as well as other types of social engineering aided by natural language processing(NLP), is a subfield of deep learning.
In general, NLP employs a variety of statistical techniques and extensively learns typical verbal and nonverbal communication patterns to identify and prevent spam content.
These systems can detect harmful network activity, guard against intrusions, and warn users of potential dangers. Systems using ID and IP frequently prove useful in addressing data breaches and improving the security of user information.
Furthermore, it is feasible to guarantee a more effective operation of ID/IP systems by utilizing deep learning, recurrent, and convolutional neural networks. The methods above will make it easier for security teams to distinguish between safe and risky network activity. In addition, it improves traffic analysis accuracy and decreases false alarm frequency.
When it comes to hacking networks, cybercriminals are becoming more skilled and quick. The use of cutting-edge technology, such as machine learning, makes it easier to detect cyberattacks. However, it is hard for humans to keep track of every connected system for every possible hazard. These data are used to educate AI-powered devices, which can then learn from real and digital world data.
Given the rising interest in AI in cybersecurity, its realistic to assume that in the future, well see even more sophisticated solutions capable of resolving difficulties in the business that is even more difficult and complex. By automating threat detection, artificial intelligence testing will strive to save cybersecurity and contribute to internet safety.
IT security professionals now utilize AI to reinforce sound cybersecurity procedures. It reduces the attack surface and tracks malicious activity. In addition, it evaluates and deals with massive volumes of data and assesses human behavior.
This is by no means a comprehensive list of its functions. Its preferable to embrace technology today and keep up with the times if you want to be more prepared for the AI-testing cybersecurity future.
Featured Image Credit: Provided by the Author; Thank you!
I am Timothy Joseph, a testing expert with over 10 years of experience in QASource. In a nutshell, a techie who enjoys studying the pinnacles of current technology & creativity!
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How Artificial Intelligence Testing is Changing the Cyberworld? - ReadWrite