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United Kingdom
AI Cameras Artificial Intelligence Technology Threat Intelligence United Kingdom

New AI Speed Cameras Record Drivers on Their Phones

 

New AI cameras have been deployed in vans to record drivers using their phones while driving or driving without a seatbelt. 

During a 12-hour evaluation in March, South Gloucestershire Council discovered 150 individuals not wearing seatbelts and seven drivers preoccupied by their cell phones. 

Pamela Williams, the council's road safety education manager, stated, "We believe that using technology like this will make people seriously consider their driving behaviour." 

According to figures, 425 people sustained injuries on South Gloucestershire roads in 2023, with 69 critically injured or killed. Throughout the survey, vans were equipped with mounted artificial intelligence (AI) technology. The devices monitored passing vehicles and determined whether drivers were infringing traffic laws. 

If a likely violation was spotted, the images were submitted to at least two specially experienced highways operators for inspection. There were no fixed penalty notices issued, and photographs that were not found to be in violation were automatically deleted. The authorities stated that it was just utilising the technology for surveys, not enforcement. 

Dave Adams, a road safety officer, helped conduct the area's first survey. He went on to say: "This is a survey so we can understand driver behaviour that will actually fit in with other bits of our road safety strategy to help make our roads safer.”

Ms Williams noted that "distracted drivers" and those who do not wear seatbelts are contributing contributors to road fatalities. "Working with our partners we want to reduce such dangerous driving and reduce the risks posed to both the drivers and other people." 

Fatalities remain high 

Dr Jamie Uff, Aecom's lead research specialist in charge of the technology's deployment, stated: Despite attempts by road safety agencies to modify behaviour via education, the number of individuals killed or badly wounded as a result of these risky driving practices remains high. 

"The use of technology like this, makes detection of these behaviours straightforward and is providing valuable insight to the police and policy makers.”
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Payments
Artificial Intelligence Cyber Security Cyberattacks CyberCrime CyberThreat Generative Artificial Intelligence Moody's Investors Payments

Cybersecurity Crisis: Small Firms Rank Attacks as the Greatest Business Risk

 


As a result of the rapid development of generative artificial intelligence, cyberattackers will likely have the upper hand in the short to medium term, compounding the long-term increase in cybersecurity risks for businesses, according to a report published by Moody's Investors Service. Based on University of Maryland data, the rating firm said cyberattacks rose by 26% per year between 2017 and 2023. 

According to Moody's, ransomware payments worldwide for the past year exceeded $1 billion, according to Chainanalysis, a cybersecurity firm. It has been reported that 23 per cent of small businesses are very prepared for cyberattacks, while half are considered somewhat prepared, according to a survey conducted by the U.S. Chamber and MetLife from Jan. 26 to Feb. 12, citing 750 small business owners. 

Even though small businesses in professional services are significantly more concerned about cyber security threats than those in manufacturing and services, the Chamber of Commerce and MetLife report that the industry is also better prepared to deal with these threats than those in manufacturing and services. 

As a result, the U.S. Chamber and MetLife survey found that small businesses in manufacturing and retail are most concerned about a supply chain breakdown, even though only about three out of five are prepared to handle one, according to the survey. A survey by the U.S. Chamber and MetLife stated that more than half of small businesses (52%), reported persistent price pressure to be their primary concern, noting inflation remains a stubborn concern.

A report by the National Federation of Independent Businesses indicates that 25% of small businesses view inflation as their largest operational problem, an increase of 2 percentage points since February according to the study and that inflation is one of the biggest operational problems that small businesses face. “Inflation has once again been cited by the NFIB Chief Economist Bill Dunkelberg as the top economic issue facing Main Street,” Dunkelberg stated. 

A third straight month of higher consumer prices was reported in March, prompting futures traders to predict that the Federal Reserve will not be cutting borrowing costs in 2024 as much as it should. According to the Bureau of Labor Statistics, the CPI was 0.4% higher in March and 3.5% higher over the past twelve months, well above the Fed's 2% target, thanks to the sharp rise in transportation and shelter prices.

Additionally, the core CPI, which excludes volatile food and energy prices, also surpassed expectations for the month, rising by 0.4% and up 3.8% over the same period last year in addition to the 0.4% increase for the month.
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Technology
Artificial Intelligence Business AI Financial Institution Generative AI Technology

AI Could Be As Impactful as Electricity, Predicts Jamie Dimon

 

Jamie Dimon might be concerned about the economy, but he's optimistic regarding artificial intelligence.

In his annual shareholder letter, JP Morgan Chase's (JPM) CEO stated that he believes the effects of AI on business, society, and the economy would be not just significant, but also life-changing. 

Dimon stated, we are fully convinced that the consequences of AI will be extraordinary and possibly as transformational as some of the major technological inventions of the past several hundred years: Think of the printing press, the steam engine, electricity, computing, and the Internet, among others. However, we do not know the full effect or the precise rate at which AI will change our business — or how it will affect society at large. 

Since the financial institution has been employing AI for over a decade, more than 2,000 data scientists and experts in AI and machine learning are employed there, according to Dimon. More than 400 use cases involving the technology are in the works, and they include fraud, risk, and marketing. 

“We're also exploring the potential that generative AI (GenAI) can unlock across a range of domains, most notably in software engineering, customer service and operations, as well as in general employee productivity,” Dimon added. “In the future, we envision GenAI helping us reimagine entire business workflows.”

JP Morgan is capitalising on its interest in artificial intelligence, advertising for almost 3,600 AI-related jobs last year, nearly twice as many as Citigroup, which had the second largest number of financial service industry ads (2,100). Deutsche Bank and BNP Paribas both advertised for little over 1,000 AI posts. 

JP Morgan is developing a ChatGPT-like service to assist consumers in making investing decisions. The company trademarked IndexGPT in May, stating that it would use "cloud computing software using artificial intelligence" for "analysing and selecting securities tailored to customer needs." 

Dimon has long advocated for artificial intelligence, stating earlier this year that the technology "can do things that the human mind simply cannot do." 

While Dimon is upbeat regarding the bank's future with AI, he also stated in his letter that the company is not disregarding the technology's potential risks.
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User Security
Artificial Intelligence Deep Fakes Technology Threat Intelligence User Security

What are Deepfakes and How to Spot Them

 

Artificial intelligence (AI)-generated fraudulent videos that can easily deceive average viewers have become commonplace as modern computers have enhanced their ability to simulate reality.

For example, modern cinema relies heavily on computer-generated sets, scenery, people, and even visual effects. These digital locations and props have replaced physical ones, and the scenes are almost indistinguishable from reality. Deepfakes, one of the most recent trends in computer imagery, are created by programming AI to make one person look like another in a recorded video. 

What is a deepfake? 

Deepfakes resemble digital magic tricks. They use computers to create fraudulent videos or audio that appear and sound authentic. It's like filming a movie, but with real people doing things they've never done before. 

Deepfake technology relies on a complicated interaction of two fundamental algorithms: a generator and a discriminator. These algorithms collaborate within a framework called a generative adversarial network (GAN), which uses deep learning concepts to create and refine fake content. 

Generator algorithm: The generator's principal function is to create initial fake digital content, such as audio, photos, or videos. The generator's goal is to replicate the target person's appearance, voice, or feelings as closely as possible. 

Discriminator algorithm: The discriminator then examines the generator's content to determine if it appears genuine or fake. The feedback loop between the generator and discriminator is repeated several times, resulting in a continual cycle of improvement. 

Why do deepfakes cause concerns? 

Misinformation and disinformation: Deepfakes can be used to make convincing films or audio recordings of people saying or doing things they did not do. This creates a significant risk of spreading misleading information, causing reputational damage and influencing public opinion.

Privacy invasion: Deepfake technology has the ability to violate innocent people's privacy by manipulating their images or voices for malicious intents, resulting in harassment, blackmail, or even exploitation. 

Crime and fraud: Criminals can employ deepfake technology to imitate others in fraudulent operations, making it challenging for authorities to detect and prosecute those responsible. 

Cybersecurity: As deepfake technology progresses, it may become more difficult to detect and prevent cyberattacks based on modified video or audio recordings. 

How to detect deepfakes 

Though recent advances in generative Artificial Intelligence (AI) have increased the quality of deepfakes, we can still identify telltale signals that differentiate a fake video from an original.

- Pay close attention to the video's commencement. For example, many viewers overlooked the fact that the individual's face was still Zara Patel at the start of the viral Mandana film; the deepfake software was not activated until the person boarded the lift.

- Pay close attention to the person's facial expression throughout the video. Throughout a discourse or an act, there will be irregular variations in expression. 

- Look for lip synchronisation issues. There will be some minor audio/visual sync issues in the deepfake video. Always try to watch viral videos several times before deciding whether they are a deepfake or not. 

In addition to tools, government agencies and tech companies should collaborate to develop cross-platform detection tools that will stop the creation of deepfake videos.
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University
Artificial Intelligence ChatGPT Procastination Software Student Technology University

Assessing ChatGPT Impact: Memory Loss, Student Procrastination

 


In a study published in the International Journal of Educational Technology in Higher Education, researchers concluded that students are more likely to use ChatGPT, an artificial intelligence tool based on generative artificial intelligence when overwhelmed with academic work. The study also revealed that ChatGPT is correlated with procrastination, memory loss, and a decrease in academic performance, as well as a concern about the future. 

 Using generative AI in education has been shown to have a profound impact in terms of its widespread use and potential drawbacks. The very fact that advanced AI programs have been available in public for only a short while has already raised a great deal of concern. AI has created a lot of dangers in the past few years, from people using the programs to produce work that was not their own, and taking credit for it, to AI impersonating celebrities with no consent of the celebrity. 

The legislature is finding it hard to keep up. AI software programs like ChatGPT, however, have been found to have negative psychological effects on students, including memory loss, which is an unfortunate new side effect that has yet to be discovered. A study has shown that students who use artificial intelligence software such as ChatGPT are more likely to perform poorly academically, suffer memory loss, and procrastinate more frequently, according to the study. 

It has been found that 32% of university students already use the AI chatbot ChatGPT every week, and it can generate convincing answers to simple text prompts. Several new studies have found that university students who use ChatGPT to complete assignments fall into a vicious circle where they don’t give themselves enough time to complete their assignments, they need to rely on ChatGPT to complete them, and their ability to remember facts gradually weakens over time. 

A study by the University of Oxford found that students who had heavy workloads and a lot of time pressure were more likely to use ChatGPT than those who had less sensitive rewards. They did, however, find a correlation between the degree to which a student reflects on their conscientiousness regarding work quality and the extent to which they use ChatGPT. This study found that students who frequently used ChatGPT procrastinated more than students who rarely used ChatGPT. 

This study was conducted in two phases, allowing the researchers to gain a better understanding of these dynamics. As part of the study, a scale was developed and validated to assess the use of ChatGPT as an academic tool by university students. Following expert evaluations of content validity, the original 12 items were reduced to 10 after the initial set of 12 items had been generated. 

Eventually, the final selection of eight items was made through exploratory factor analysis and reliability testing, which resulted in an effective measure of the extent to which ChatGPT has been used for academic purposes. Researchers conducted three surveys of students to determine who is most likely to use ChatGPT, and how easily users experience the consequences. 

To investigate whether ChatGPT is having any beneficial effects, the researchers asked a series of questions. A thesis was published that stated students who rely on AI because they feel overwhelmed by all of the work they have to do probably do so in a bid to save time as they feel overwhelmed by all of their work. Hence it might have been concluded from the results that ChatGPT may have been a tool that would be used mainly by students who had already been struggling academically. 

The advancement of artificial intelligence can be amazing, as exemplified by its recent use to recreate Marilyn Monroe's personality, but the dangers of a system allowing for super-intelligence cannot be ignored. There is no doubt that artificial intelligence is becoming more advanced every day. At the end of the research, the researchers found that high use of ChatGPT was linked to detrimental outcomes for the participants. 

ChatGPT has been reported to be a cause of memory loss in students and a lower overall GPA in these students. Researchers advise that educators should assign students activities, assignments, or projects that cannot be completed by ChatGPT so students are actively engaged in critical thinking and problem-solving activities, the study's authors recommend. To mitigate ChatGPT's adverse effects on a student's learning journey and mental capabilities, this can be said to be a beneficial factor.
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Technology
Advance Tools AI Gaming Artificial Intelligence LLM NPCs Technology

Here Are Three Ways AI Will Transform Gaming Forever

 

Technology has been impacted by artificial intelligence in practically every field. You would struggle to identify a tech-related field where artificial intelligence hasn't had some sort of impact, from data analysis to art programmes. AI hasn't advanced as quickly in video games as it has in other fields, but even in this field, there are still some fascinating advancements that have the potential to completely transform the gaming experience. 

Of course, developers are already utilising generic AI technologies to assist them create content for their games, such as generating art, writing scripts, and finding ideas for what to do next. But in certain instances, artificial intelligence (AI) has transformed gaming and accomplished tasks that would be extremely laborious or impossible for a human to complete. 

AI can design NPCs that respond to your words 

Making a game in which the main character speaks exactly what the player wants to say can be quite difficult. When continuing the tale, you can only provide the player a limited number of options, and even then, some gamers will want to divert the conversation or ask a question that the creator did not consider. And because everything is strictly scripted, the player has little freedom to interact with the non-player character (NPCs) as they see fit.

However, an AI LLM can help with this. A developer can connect an NPC to an AI and have it manage your responses, much like you do with a chatbot like ChatGPT. That way, you may ask the character whatever questions you want, and the AI will analyse the character it has been assigned to roleplay and reply appropriately. Best of all, once AI PCs take off, you won't need an internet connection to communicate with an external AI model; everything can be handled on your hardware.

AI can assist lip-sync character's lines

While AI-powered games are now on the market, other technologies are still being developed. One of these is Audio2Face, which Nvidia introduced as part of its efforts to integrate AI into game creation. Audio2Face employs artificial intelligence to automatically match a character's mouth movements to their dialogue, eliminating the need for an animator to perform the lip-syncing oneself. Nividia notes in its blog post how this technique will make localization much easier because developers will not have to adjust the lip sync for each language. Instead, they can have Audio2Face process the animation for them.

While Nvidia did not directly state it in their post, Audio2Face is likely to be used in conjunction with AI-generated chat. After all, if NPCs are generating language in real time, they'll require lip-syncing technology that can precisely animate the mouth on the fly. 

Turn 2D images into 3D objects 

Another recently introduced technique is Stability AI's 2D-to-3D converter. The premise behind this AI tool is that you may submit a 2D photo of an object, and it will do its best to create a 3D model of it. Most of the magic comes from the AI guessing what's on the other side of the object, which it does surprisingly well. 

Of course, this has the potential to allow developers to swiftly add 3D models to their games; simply take a photo of the thing they want to import and add it in. However, there is also the possibility of creating a game in which people can upload photographs of things around their house, which are then incorporated to the game.
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Technology
AI Artificial Intelligence ChatGPT Cyberattacks CyberCrime Cybersecurity CyberThreat Personal Computer Technology

From Personal Computer to Innovation Enabler: Unveiling the Future of Computing

 


The use of artificial intelligence (AI) has been largely invisible until now, automating processes and improving performance in the background. Despite the unprecedented adoption curve of generative AI, which is transforming the way humans interact with technology through natural language and conversation, it represents a reversible paradigm that will change the face of technology for a lifetime. 

According to a study of generative artificial intelligence's economic potential, if it is adopted to its full potential, artificial intelligence could increase the global economy by about 4 trillion dollars and the UK economy by about 31 billion pounds in GDP within the next decade. 

There is also a predicted $11 trillion increase in global GDP from non-generative AI as well as other forms of automation, which will also contribute to these figures. With great change comes great opportunity - so caution is justified but excitement is also justified - because great change comes great opportunity. 

In the past, most users have only encountered generative AI via web browsers and the cloud, a platform that carries inherent challenges related to reliability, speed, and privacy, since it is an online-only, open-access, corporate-owned platform. If users were to apply generative AI to their PC, they would benefit from the full advantages, without any of the disadvantages that come with it. 

The reason why artificial intelligence is redefining the role of a personal computer as dramatically and fundamentally as the internet did has to do with its ability to empower individuals to become creators of technology, rather than just consumers of it. The AI PC will give people the opportunity to become creative technologists rather than just consumers. 

By leveraging engineering strengths, people might be able to develop powerful new machines optimized for the use of local AI models—while still being able to utilize hybrid cloud computing and local inference to work offline while leveraging engineering strengths. By using local inference and data processing, data processing can also be performed in a faster and more efficient manner, resulting in lower latency and stronger data privacy and security, in addition to improved energy efficiency and access costs. 

By using this kind of technology, users' PCs can become intelligent personal companions who can keep their information secure while also performing tasks for them, as on-device artificial intelligence can access all of the same specific emails, reports, and spreadsheets the same way they do. While AI is being used to improve the performance and functionality of PCs, the research in using it will continue to accelerate. AI-powered cameras that can be optimized automatically for better video calls with AI-enhanced sound reduction, voice enhancement, and framing will be used to improve the hybrid work experience. 

As a result of enterprise-grade security and privacy, users' PCs will become a personal companion that offers personalized generative AI solutions. On-device AI allows users to trust that their information is safe while doing tasks for them because it has access to all the same, specific emails, presentations, reports, and spreadsheets that they do. 

By using ChatGPT-4, performance is significantly enhanced, which has been demonstrated to be over 25% faster, 40% faster in human ratings, and 12 per cent faster at completing tasks. If users can integrate their internal company information as well as their personalized working data into their companion, and yet still be able to quickly analyze vast amounts of public information, one can imagine the possible use cases with the two combined to produce the best and most relevant of both worlds.
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Technology
Algorithm Bias Artificial Intelligence Fairness Machine learning Technology

Fairness is a Critical And Challenging Feature of AI

 

 

Artificial intelligence's ability to process and analyse massive volumes of data has transformed decision-making processes, making operations in health care, banking, criminal justice, and other sectors of society more efficient and, in many cases, effective. 

This transformational power, however, carries a tremendous responsibility: ensuring that these technologies are created and implemented in an equitable and just manner. In short, AI must be fair.

The goal of fairness in AI is not only an ethical imperative, but also a requirement for building trust, inclusion, and responsible technological growth. However, ensuring that AI is fair presents a significant challenge. 

Importance of fairness

Fairness in AI has arisen as a major concern for researchers, developers, and regulators. It goes beyond technological achievement and addresses the ethical, social, and legal elements of technology. Fairness is a critical component of establishing trust and acceptance of AI systems.

People must trust that AI decisions that influence their life, such as employment algorithms, are done fairly. Socially, AI systems that reflect justice can assist address and alleviate past prejudices, such as those against women and minorities, thereby promoting inclusivity. Legally, including fairness into AI systems helps to match those systems with anti-discrimination laws and regulations around the world. 

Unfairness can come from two sources: the primary data and the algorithms. Research has revealed that input data can perpetuate bias in a variety of societal contexts. 

For example, in employment, algorithms that process data that mirror society preconceptions or lack diversity may perpetuate "like me" biases. These biases favour candidates who are similar to decision-makers or existing employees in an organisation. When biassed data is used to train a machine learning algorithm to assist a decision-maker, the programme could propagate and even increase these biases. 

Fairness challenges 

Fairness is essentially subjective, impacted by cultural, social and personal perceptions. In the context of AI, academics, developers, and policymakers frequently define fairness as the premise that machines should neither perpetuate or exacerbate existing prejudices or inequities.

However, measuring and incorporating fairness into AI systems is plagued with subjective decisions and technical challenges. Researchers and policymakers have advocated many definitions of fairness, such as demographic parity, equality of opportunity and individual fairness. 

In addition, fairness cannot be limited to a single statistic or guideline. It covers a wide range of issues, including, but not limited to, equality of opportunity, treatment, and impact.

The path forward 

Making AI fair is not easy, and there are no one-size-fits-all solutions. It necessitates a process of ongoing learning, adaptation, and collaboration. Given the prevalence of bias in society, I believe that those working in artificial intelligence should recognise that absolute fairness is impossible and instead strive for constant development. 

This task requires a dedication to serious research, thoughtful policymaking, and ethical behaviour. To make it work, researchers, developers, and AI users must guarantee that fairness is considered along the AI pipeline, from conception to data collecting to algorithm design to deployment and beyond.
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Technology
Artificial Intelligence Cyberattacks CyberCrime Music ChatGPT Soundtracks Suno Technology

ChatGPT Meets Music: Suno's Trailblazing Initiative Marks a New Era

 


In recent years, numerous text-to-music converters have been released onto the market, including those from Meta and Google. It should be noted that Suno AI music generators are becoming increasingly popular - most likely due to their ability to generate original lyrics and vocals and their leveraging of ChatGPT's capabilities. 

With the help of artificial intelligence (AI), Suno can generate original songs based on simple text prompts that can be entered into the computer. When the AI platform moved into open beta in July 2023, users were invited to join its Discord channel if they wished to test the model out and access the platform via its Discord channel. 

A web interface of this service enables users to create AI music with its interface, as well as play it back. There was a recent collaboration between Microsoft and the platform that allowed users of Copilot to create songs and also receive notifications when new songs are created. The extension was introduced in December 2023. A future that uses Suno's AI technology is one in which anyone would be able to create music and record it. 

Despite AI's progress in producing valid text, images, and videos in recent years, it has been slow to produce AI-generated music despite advancements in generative AI technology. The Suno project aspires to change that and to make music-making more accessible to everyone. There are concerns, however, about the potential impact that AI music may have on artists and the music industry. Suno's approach is to use large language models and speech recordings to create their AI music. 

The company is communicating with major label companies and has said it respects the intellectual property and artists of those labels. Similar to how camera phones and Instagram revolutionized photography, Suno's investors believe their technology will democratize music creation as well. 

A lot of Suno employees are musicians, and there are pianos and guitars available in the office as well as images of classical composers framed on the walls. Google's Dream Track, Suno's potential competitor, lets users create songs using famous voice recordings, but Suno believes that the future of music interaction with AI lies in creating original compositions that are unique and original. 

While AI music offers exciting prospects, some people have concerns about what it could mean for markets such as ad jingles and TV show soundtracks that are being disrupted. A key objective of Suno is to provide a platform for music creation that is accessible to everyone by navigating these challenges. 

It seems that many Midjourney users seem keen to create hyperrealistic sci-fi junk, heavy on form-fitting spacesuits, as well as hyperrealistic art so far, which is, in fact, kitsch. Suno is still a mere 2 years old. Founded in 2008 by two Harvard professors who are both experts in machine learning, Shulman and Freyberg, as well as Georg Kucsko and Martin Camacho, led another Cambridge company, Kensho Technologies, which used artificial intelligence as a solution to complex business problems until 2022. 

During their Kensho days, Shulman and Camacho were both musicians who used to jam together. In the course of their work at Kensho, the quartet devised a transcription technology for recording earnings calls for public companies, a difficult task since there was poor audio quality, excessive jargon, as well as an array of accents to contend with. 

Currently, Suno only has a few employees, but they intend to expand their team with a much larger permanent headquarters currently under construction on the top floor of the same building where they are currently located. There seems to be a great deal of competition for Suno that is coming from Google's Dream Track, which has acquired licenses that allow users to create their songs using famous voices such as Charlie Puth's through a similar prompt-based interface. 

However, Dream Track is still only being tested by a small group of people and so far, the samples released haven't been as impressive as Suno's samples, despite the famous voices attached. There is, however, one way that Suno gets around this tricky situation by not generating music sung in a manner that is similar to what a real artist would sing. 

It will refuse to generate music if a prompt such as that is entered. Furthermore, the AI startup is also in communication with major music labels, as per the report. It was announced on February 23 that Suno had released its Alpha model for Pros and Premiere users that “creates a more realistic, authentic sound." Free users are only allowed access to V1 and V2 models.
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Web AI
Artificial Intelligence Cyberattacks CyberCrime Cyberthreats Innovative Web Proxy Networks Skyvern Technology Web AI

Innovative Web Automation Solutions Unveiled by Skyvern AI

 


People can use Skyvern as more than just an automation tool; it's a comprehensive solution that utilizes cutting-edge technologies such as large language models, computer vision, and proxy networks to streamline their online activities by leveraging cutting-edge technologies. Skyvern reduces human error by automating web browser interactions, which allows users to concentrate more on the more crucial aspects of their business rather than on the most common errors. 

For Skyvern to function effectively, it must be able to interact with web pages similarly to the way a person would. A computer program that uses artificial intelligence Navigates websites, fills out forms, clicks buttons, and extracts data, all the while adapting to changes in the layout or content of the website. 

Feature and Benefit Highlights 


With Skyvern's Debugging and Transparency features, users are provided a visual step-by-step guide that helps them identify and address any issues that may occur during the automation process. Smart AI decision-making processes are transparent and reduce the chances of human error. 

It is possible to target specific geographical locations in Skyvern's architecture when using proxy networks. This makes it ideal when working with geo-based data or when tailoring user automation to certain markets, as Skyvern includes support for proxy networks. 

Skyvern can handle CAPTCHAs, two-factor authentication, and other complicated web interactions to guarantee that their automated workflows will run smoothly without interruption. In addition to efficient data extraction, Skyvern offers several user-friendly formats for retrieving information from the web such as CSV or JSON, allowing the data to be easily handled. 

Intuitive APIs make it easy for the tool to be integrated with your existing systems, allowing users to automate their workflows. Skyvern makes it possible for businesses to streamline procurement processes, navigate government websites, and collect insurance quotes, making it ideal for various applications such as streamlining procurement processes and navigating government websites. 

A Real-World Application 


One of the most effective ways for businesses to automate procurement processes is to use Skyvern, which allows businesses to navigate supplier websites, obtain relevant data, and populate internal systems, thus reducing the need to navigate supplier websites and saving businesses both time and manual effort. 

Getting around a government website can be a challenging process and can take a considerable amount of time. By automating the filling out of forms, obtaining the data, and retrieving the documents, Skyvern makes it easy for businesses and the government to interact with each other, to improve the quality of business and government interactions. 

Retrieval of insurance quotes: Skyvern can bring together insurance quotes from multiple providers and get them in multiple languages with ease, even if there are different languages spoken by the providers. In this way, businesses can inspect several options and make an informed decision without having to manually navigate between the various websites of the different providers. 

The Skyvern User Guide The setup process of Skyvern is quite easy due to the available quick-start tutorial that provides users with all the steps they need to take. For a fuller experience of Skyvern, watch out for the cloud version, currently in private beta. The digital landscape of today is fast-paced, and businesses need every advantage they can get so they can stay ahead of their competition.

Using artificial intelligence, Skyvern can automate web-based tasks in a smart, efficient, and reliable way. It's Skyvern's goal to simplify businesses' online workflows, reduce human error, and free up valuable time for more important tasks by leveraging advanced technologies and an intuitive interface. 

It's time to get rid of repetitive online tasks for good! With Skyvern, users will have access to the power of artificial intelligence-driven automation to revolutionize their web-based workflows. Skyvern's team will be right by users' side, helping them to focus on the things that are most important to them, such as growing their business and achieving their goals.
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Technology
Artificial Intelligence Blockchain Decentralised Identified Decentralization Technology

Decentralised Identity: The Next Revolution Enabled by Block Chain Technology

 

Identity is crucial in our daily digital life, from accessing websites and applications to establishing our credentials online. Traditional identity systems are no longer trusted as a result of numerous data breaches and unethical corporate usage of consumer data for advertising, market research, and algorithms.

Enter decentralised identity, a novel concept aimed at improving data privacy and user empowerment. 

In this article, we will delve into the world of decentralised identity, describing its principles, important components, and how decentralised identity systems backed by blockchain technology are being used to transform the way we use the Internet. 

What is decentralised identity? 

Decentralised identification, also known as self-sovereign identity, refers to digital identities that are owned and controlled by individuals rather than centralised third parties. 

Decentralised identity technology seeks to ensure that each individual has complete control and privacy over their identification information. At the same time, the technology aims to create a universal and trustworthy system in which digital IDs may be effortlessly utilised for personal verification both online and in person. 

Blockchain technology serves as the foundation for decentralised identity solutions. This is because public blockchains offer nearly immutable databases that may be used to store and retrieve data in a decentralised fashion. Blockchains, such as Bitcoin and Ethereum, use distributed databases with a broad and global network of participants to verify and process transactions. The decentralised nature of these public blockchains makes it extremely difficult for a centralised party to obtain control, modify, or alter the system. 

Modus operandi

A decentralised identification system relies largely on its underlying network, known as a trust system, which can be either a blockchain protocol or a non-blockchain protocol. In the case of blockchain, the various independent nodes that maintain and update the blockchain ledger in a decentralised manner contribute to a trustless system.

Decentralised identification systems can also be implemented in non-blockchain infrastructure. For example, Nostr is a non-blockchain, open protocol that enables developers to build decentralised social media networks. 

A decentralised identity system consists of two basic components: decentralised identifiers and verified credentials. 

Decentralised identifiers: Decentralised identifiers can be compared to the existing use of email addresses and social media handles when logging into a website. However, these Web 2.0 identifiers are not intended to protect user information or privacy.

In contrast, each decentralised identification is intended to be globally unique and verifiable on any platform. These decentralised IDs offer users (near-)immutability, censorship resistance, and increased security. Additionally, decentralised IDs will allow users to erase data related to their ID. 

Verifiable credentials: Authentication of the decentralised ID is critical. Here's where verifiable credentials come in. Consider it your driver's licence or passport, which you can use to verify your identity. Verifiable credentials enable users to prove their identities without disclosing too much personal information. 

A decentralised identity system allows users to own and control their verifiable credentials. One of the most promising verified credential developments in blockchain is known as zero-knowledge proof (ZK proof). 

Zero Knowledge Proofs: ZK proofs are arguably the most significant blockchain technology that provides decentralised digital identification solutions - at the time of publication. 

What is ZK proof? It is a cryptographic mechanism for proving a statement's validity without disclosing any information about it. ZK-proof decentralised identities enable personal verification and attestation without disclosing any personal information to third parties. 

For example, if you wish to open an account on a social media platform. Simply provide your ZK-proof decentralised ID to authenticate your identity. You will not be asked to provide personal information such as your email address, age, name, location, or date of birth, which is currently requested when "signing up" or "creating an account" on a website. 

All you need to do is complete a series of actions that require the underlying identity information but do not include any of the information itself. To determine whether the information is valid, the verifier can apply those operations to a certain cryptographic function. 

Is decentralised identity the future? 

Decentralised identification could be the future, and it is likely to be in the best interests of internet users. Unfortunately, personal data is so valuable to businesses that it will be a difficult battle for technology. 

If decentralised identities are successful, they will not only allow us to avoid the data privacy issues that plague the web2 environment, but will also set a higher bar for data protection, privacy, and user empowerment. Decentralised identification solutions, such as ZK-proof technology, have the potential to have a worldwide influence and disrupt industries spanning finance to retail.
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AI Collaboration Artificial Intelligence Backdoor Cyberattacks Cybersecureity Cybersecurity Hugging Face ML Model ML Models Technology

Hugging Face ML Models Compromised with Silent Backdoors Aimed at Data Scientists

 


As research from security firm JFrog revealed on Thursday in a report that is a likely harbinger of what's to come, code uploaded to AI developer platform Hugging Face concealed the installation of backdoors and other forms of malware on end-user machines. 

The JFrog researchers said that they found approximately 100 files that were downloaded and loaded onto an end-user device that was not intended and performed unwanted and hidden acts when they were installed. All of the machine learning models that were subsequently flagged, went undetected by Hugging Face, and all of them appeared to be benign proofs of concept uploaded by users or researchers who were unaware of any potential danger. 

A report published by JFrog researchers states that ten of them were actually "truly malicious" because they violated the users' security when they were installed, in that they implemented actions that compromised their security. This blog post aims to broaden the conversation surrounding AI Machine Language (ML) models for security, which has been a neglected subject for a long time and it is important to begin a discussion about it right now. 

The JFrog Security Research team is investigating ways in which machine learning models can be employed to compromise an individual's environment through executing code to compromise the environment of a Hugging Face user. The purpose of this post is to discuss the investigation into a malicious machine learning model that has been uncovered by us. 

People are regularly monitoring and scanning AI models uploaded by users on other open-source repositories, as they do with other open-source repositories, and it has been discovered that loading a pickle file can lead to code execution. A payload of this model allows the attacker to gain full control over a victim’s machine through what is commonly referred to as a “backdoor”, which allows them to gain complete control over their machines. 

The silent infiltration could result in the unauthorized accessing of critical internal systems, paving the way for massive data breaches or corporate espionage, affecting not just individuals, but potentially entire organizations across the globe, all while leaving victims utterly unaware of their compromised status, allowing for a wide range of possible repercussions. The attack mechanism is explained in detail, which sheds light on its complexities and potential implications. 

Taking a closer look at the intricate details of this nefarious scheme, it may be instructive to keep in mind the lessons that can be learned from it, the attacker's intentions, and the identity of whoever conducted this attack. In the same way as any technology, AI models can pose security risks if they are not handled correctly. 

A threat that is possible is code execution, where a malicious actor can run arbitrary code on the machine that loads or runs the model, thus posing a security risk. As a result of this, JFrog has created an external HoneyPot on an external server, completely isolated from any sensitive network to gain further insight into the actors' intentions. This HoneyPot can result in data breaches, system compromises, or malicious actions. HoneyPots are designed to attract different types of attacks by impersonating legitimate systems and services, so defenders can monitor and analyze the activities of attackers by monitoring and analyzing their behaviour. 

Several proactive measures can be taken by data scientists to prevent malicious models from being created and exploited to execute code. Examples include source verification, security scanning, safe loading methods, updating dependencies, reviewing model code, isolating environments, and educating users so that these risks can be mitigated. Several security measures were implemented by Hugging Face, a platform for AI collaboration, to prevent malware attacks, pickle attacks, and secret attacks. 

It is the purpose of these features to alert the users or moderators whenever a file in the repository contains malicious code, unsafe deserialization, or sensitive information. Although the platform has taken several precautions to protect itself from real threats, recent incidents serve to accentuate the fact that it is not immune from them.
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AI Apple Artificial Intelligence Cyber Hackers Cyberattacks CyberCrime Google Technology

Google's 'Woke' AI Troubles: Charting a Pragmatic Course

 


As Google CEO Sundar Pichai informed employees in a note on Tuesday, he is working to fix the AI tool Gemini that was implemented last year. The note stated that some of the text and image responses reported by the model were "biased" and "completely unacceptable". 

Following inaccuracies found in some historical depictions generated by its application, the company was forced to suspend its use of its tool for creating images of people last week. After being hammered for almost a week last week over supposedly coming out with a chatbot that could be used at work, Google finally apologised for missing the mark and apologized for getting it wrong. 

Despite the momentum of the criticism, the focus is shifting: This week, the barbs were aimed at Google for what appeared to be a reluctance to generate images of white people via its Gemini chatbot, when it came to images of white people. It appears that Gemini's text responses have been subjected to a similar criticism. 

In recent years, Google's artificial intelligence (AI) tool Gemini has been subjected to intense criticism and scrutiny, especially as a result of ongoing cultural clashes between those of left-leaning and right-leaning perspectives. In contrast to the viral chatbot ChatGPT, Gemini has faced significant backlash as a Google counterpart, demonstrating the difficulties associated with navigating AI biases. 

As a result of the controversy surrounding Gemini, images that depict historical figures inaccurately were generated, and responses to text prompts that were deemed overly politically correct or absurd by some users, escalated the controversy. It was quickly acknowledged by Google that the tool had been "missing the mark" and the tool was halted. 

However, the fallout from the incident continued as Gemini's decisions continued to fuel controversies. There has been a sense of disempowerment among Googlers on the ethical AI team during the past year, as the company increased the pace at which it rolled out AI products to keep up with its rivals, such as OpenAI, who have been rolling out AI products at a record pace. 

Gemini images included people of colour as a demonstration that the company was considering diversity, but it was also clear that the company failed to take into account all possible scenarios in which users might wish to create images. 

In her view, Margaret Mitchell, former co-head of Google's Ethical AI research group and chief ethics scientist for Hugging Face AI, has done a wonderful job of understanding the ethical challenges faced by users. As a company that had just been established four years ago, Google had been paying lip service to increasing its awareness of skin tone diversity, but it has made great strides since then.

As Mitchell put it, it is kind of like taking two steps forward and taking one step backwards." he said. There should be recognition given to them for taking the time to pay attention to this stuff. In a general opinion, Google employees should be concerned that the social media pile-on will make it even harder for internal teams who are responsible for mitigating the real-world harms that their artificial intelligence products are causing, such as whether the technology can hide systemic prejudices. 

The employees worry that Google employees should not be able to accomplish this task by themselves. A Google employee said that the outrage that was generated by the AI tool for unintentionally sidelining a group that is already overrepresented in the majority of training datasets could spur some at Google to argue for fewer protections or guardrails on the AI’s outputs — something that, if taken to an extreme, could hurt society in the end. 

The search engine giant is currently focused on damage control as a means to mitigate the damage. It was reported that Demis Hassabis, the director of Google DeepMind's research division, said on Feb. 26 that the company plans to bring the Gemini feature back online within the next few weeks. 

However, over the weekend, conservative personalities continued their attack against Google, specifically in light of the text responses Gemini provides to users. There is no doubt that Google is leading the AI race on paper, with a considerable lead. 

The company makes and supplies its artificial intelligence chips, has its cloud network, which is one of the requisites for AI computation, can access enormous amounts of data, and has an enormous base of customers. Google recruits top-tier AI talent, and its work in artificial intelligence enjoys widespread acclaim. A senior executive from a competing technology giant expressed to me the sentiment that witnessing the missteps of Gemini feels akin to observing a defeat taken from the brink of victory.
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Nvidia CEO Believes AI Would Kill Coding

 

When ChatGPT was first made public by OpenAI in November 2022, many were taken aback by its abilities. People discovered an array of opportunities for the AI chatbot, ranging from asking it to write poetry and music to debug and coding. Companies like Google and Microsoft also quickly released their own chatbots, Bard (now Gemini) and Bing. With ChatGPT, the popularity of generative AI reached new heights. 

AI has been heralded by many as the future. Notable figures in the IT industry, including Sam Altman, Satya Nadella, Bill Gates, and Sundar Pichai, have already spoken on the possible effects of AI on labour markets, highlighting its significance. While some IT professionals think AI will result in job losses in the IT industry, others think it will open up more opportunities. 

CEO of Nvidia Jensen Huang agrees that AI will have an impact on the labour market and argues that anyone can become a programmer with this new technology, so children don't need to learn how to code. 

The Nvidia CEO can be seen speaking at an event in a video that has gone viral. He claims that a decade or so ago, the consensus was that everyone should learn how to code. Now, however, things are entirely different because of artificial intelligence; everyone is a coder. He also said that children don't need to learn how to code and that it is our responsibility to create technology that would enable human language to be used in programming. Put another way, computers should be able to understand human language, minimising the necessity for coding languages like C++ or Java.

He explains, "Over the last 10-15 years, almost everybody who sits on a stage like this would tell you that it is vital that your children learn computer science, everybody should learn how to program. In fact, it is almost exactly the opposite. It is our job to create computing technology such that nobody has to program, and that the programming language is human. Everybody in the world is now a programmer. This is the miracle of AI."

"You now have a computer that will do what you tell it to do. It is vital that we upskill everyone and the upskilling process will be delightful and surprising,” Huang added. 

This is not the first time the Nvidia CEO has spoken about AI's ubiquitous effect across sectors. As one of the world's leading chipmakers, Nvidia was instrumental in the development of ChatGPT, which made use of hundreds of Nvidia GPUs. 

Huang announced the closure of the "digital divide" at a gathering held at the Computex convention in Taiwan last year. He emphasised how AI is bringing about a new era of computing, when previously unthinkable tasks are made possible. Huang highlighted how programming is now accessible to almost anyone, saying that all it takes to become a programmer is some computer involvement.
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AI Artificial Intelligence Cyberattacks Cyberchackers CyberCrime Ed Tech Education Technology

From Classrooms to Cyberspace: The AI Takeover in EdTech

 


Recently, the intersection between artificial intelligence (AI) and education technology (EdTech) has become one of the most significant areas of concern and growth within the educational industry. The rapid adoption of AI-based EdTech tools is creating a unique set of challenges and opportunities for educators, students, and parents who are faced with the rapid acceleration of online learning that is catalyzed by the COVID-19 pandemic. 

With the rise of these technologies in education, there has been a significant discussion about student data security and privacy and the effectiveness and ethical concerns associated with utilizing these technologies. 

With the advent of artificial intelligence in EdTech, we have seen innovative solutions to personalize learning and boost student engagement as well as substantial security risks associated with data privacy. It has become increasingly obvious that unbiased data and transparent technology use are crucial to evaluating student work and managing educational content, a situation underscored by the use of artificial intelligence algorithms in evaluating student work and managing educational content. 

EdTech companies have been forced to reevaluate their security measures and data handling practices after incidents of data breaches and unauthorized data use have highlighted vulnerabilities within the sector. It has been said that the ability of artificial intelligence to customize learning experiences and meet individual needs has made education technology a popular subject because it can optimize educational outcomes. 

The education platforms will be able to identify patterns by analyzing vast datasets and tailoring content accordingly if they use artificial intelligence algorithms to analyze large amounts of data. This will allow them to identify patterns and tailor content to meet the unique needs of students. There is no doubt that artificial intelligence is making a significant impact in the development of intelligent tutoring systems, which is one of the key areas where AI is making a significant impact on the educational environment in terms of engaging and effective education. 

A machine learning algorithm is used to identify a student's strengths and weaknesses and provide targeted feedback and individualized learning plans based on the assessment results. In this way, students receive tailored support that enables them to understand better and retain their academic content.

Moreover, AI is revolutionizing the assessment landscape, bringing automated grading systems to the classroom and streamlining the evaluation process for educators, thus transforming education’s landscape. By doing this, educators will be able to save valuable time as well as foster an interactive learning atmosphere as they will be able to focus on giving constructive feedback and providing constructive criticism. 

It is becoming more apparent that stringent security protocols and transparent data practices are essential to prevent significant security breaches, such as the lawsuit filed by the Federal Trade Commission against Edmodo for improper data use. As a result of these incidents, researchers have begun to reexamine how AI-based EdTech tools are used by educators in conjunction with how educators themselves safeguard information about their students.

AI has the prospect of bringing many benefits to education, but integrating it into the system requires a balanced approach that utilizes the advantages of technology while minimizing any potential risks associated with the process. 

There is an urgent need for educators and schools to establish strong data protection agreements with EdTech vendors, which will ensure privacy laws are adhered to, and clarity is provided on how personal data will be used, protected, and protected from unauthorized access. There is a need for transparency with stakeholders - parents, students, and teachers – about the use of AI tools, the data they collect, and the protective measures they are taking. 

To successfully navigate this complex terrain, it is essential to conduct regular reviews of privacy policies, monitor the effectiveness of EdTech tools, and engage with the evolving AI landscape daily. The use of artificial intelligence can enhance the learning experience and enhance student responses if educators adopt a proactive, informed approach to the use of AI to enhance student outcomes while maintaining a vigilant stance on the security and privacy of student data. 

As Artificial Intelligence (AI) is integrating into classrooms and classroom practices more and more, it is heralding an era that offers remarkable opportunities for innovation and personalized learning in teaching and learning. 

The ethical, privacy, and security implications of these technologies, however, call for a critical review of their potential use. There will be a crucial need to orchestrate a concerted effort by educators, policymakers, and technology providers to be able to realize the potential of AI in educational settings responsibly and effectively as the educational landscape continues to evolve.
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Workplace Security
Artificial Intelligence Cyber Security Data Leak Tech Giant Third Party Apps Workplace Security

Amazon Issues ‘Warning’ For Employees Using AI At Work

 

A leaked email to employees revealed Amazon's guidelines for using third-party GenAI tools at work. 

Business Insider claims that the email mandates employees to refrain from using third-party software due to data security concerns.

“While we may find ourselves using GenAl tools, especially when it seems to make life easier, we should be sure not to use it for confidential Amazon work,” the email reads. “Don’t share any confidential Amazon, customer, or employee data when you’re using 3rd party GenAl tools. Generally, confidential data would be data that is not publicly available.” 

This is not the first time that Amazon has had to remind employees. A company lawyer advised employees not to provide ChatGPT with "any Amazon confidential information (including Amazon code you are working on)" in a letter dated January 20, 2023.

The warning was issued due to concerns that these types of third-party resources may claim ownership over the information that workers exchange, leading to future output that might involve or resemble confidential data. "There have already been cases where the results closely align with pre-existing material," the lawyer stated at the time. 

Over half of employees are using GenAI without permission from their employer, according to Salesforce research, and seven out of ten employees are using AI without receiving training on its safe or ethical use. Merely 17% of American industries own vaguely defined AI policies. In sectors like healthcare, where 87% of worldwide workers report that their employer lacks a clear policy on AI use, the issue is particularly noticeable. 

Employers and HR departments need to have greater insight into how their staff members are utilising AI in order to ensure that they are using it carefully.
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Technology
AAP AI Artificial Intelligence cryptocurrency scams cyber literacy Cybersecurity Experts Fraudsters Law Enforcement online financial scams Pacific Islands Social Media Technology

Analysis: AI-Driven Online Financial Scams Surge

 

Cybersecurity experts are sounding the alarm about a surge in online financial scams, driven by artificial intelligence (AI), which they warn is becoming increasingly difficult to control. This warning coincides with an investigation by AAP FactCheck into cryptocurrency scams targeting the Pacific Islands.

AAP FactCheck's analysis of over 100 Facebook accounts purporting to be crypto traders reveals deceptive tactics such as fake profile images, altered bank notifications, and false affiliations with prestigious financial institutions.

The experts point out that Pacific Island nations, with their low levels of financial and media literacy and under-resourced law enforcement, are particularly vulnerable. However, they emphasize that this issue extends globally.

In 2022, Australians lost over $3 billion to scams, with a significant portion involving fraudulent investments. Ken Gamble, co-founder of IFW Global, notes that AI is amplifying the sophistication of scams, enabling faster dissemination across social media platforms and rendering them challenging to combat effectively.

Gamble highlights that scammers are leveraging AI to adapt to local languages, enabling them to target victims worldwide. While the Pacific Islands are a prime target due to their limited law enforcement capabilities, organized criminal groups from various countries, including Israel, China, and Nigeria, are behind many of these schemes.

Victims recount their experiences, such as a woman in PNG who fell prey to a scam after her relative's Facebook account was hacked, resulting in a loss of over 15,000 kina.

Dan Halpin from Cybertrace underscores the necessity of a coordinated global response involving law enforcement, international organizations like Interpol, public awareness campaigns, regulatory enhancements, and cross-border collaboration.

Halpin stresses the importance of improving cyber literacy levels in the region to mitigate these risks. However, Gamble warns that without prioritizing this issue, fueled by AI advancements, the situation will only deteriorate further.
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