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VPN security
Safe Browsing Technology VPN VPN Hacking VPN security

Is Your VPN Safe? Or Can It be Hacked?


A virtual private network is one of the simplest ways for consumers to secure their internet activity. VPNs utilize tunneling technology to encrypt a user's online traffic and make it unreadable to prying eyes.

This additional layer of security has become a popular choice for both businesses and customers seeking to secure their privacy. According to Statista, more than 24% of all internet users in 2023 utilized a VPN to protect their internet connection.

With such widespread use, one might wonder if VPNs are impervious to hacking. Are they susceptible to hacking? Can VPNs be used to steal user data instead of securing it?

Can VPNs be hacked?

VPNs, like any other software, can be hacked. No software is perfect, and VPNs, like all internet-based technologies, are vulnerable to various threats. That being said, a good VPN will be extremely difficult to crack, especially if it has a secure server infrastructure and application.

VPNs function by creating a secret connection via which your internet activity is encrypted and rendered unreadable. Your internet traffic is routed via a VPN server, which masks your IP address and gives you an extra degree of privacy online.

This encryption protects critical user data including your IP address, device location, browsing history, and online searches from your internet service provider, government agencies, and cybercriminals.

VPNs provide simple safety for your online activity by encrypting user data and routing it over a secure channel. However, this does not render them invincible.

There are a few vulnerabilities in VPNs that hackers can exploit or target. Let's look at a few of them:

How VPNs Can Be Hacked

Breaking the VPN encryption

One approach to hack VPNs is to break through the encryption. Hackers can employ cryptographic attacks to break poorly constructed encryption ciphers. However, breaking encryption requires a significant amount of effort, time, and resources.

Most current VPNs use the Advanced Encryption Standard (AES-256) encryption method. This encryption standard encrypts and decrypts data with 256-bit keys and is commonly regarded as the gold standard in encryption.

This is because AES-256 is nearly impregnable, taking millions to billions of years to brute force and crack even with today's technology. That is why many governments and banks employ AES-256 encryption to protect their data.

In any event, most modern VPN companies use AES-256 encryption, so there isn't anything to worry about.

VPNs employing outdated tunneling protocols

Hackers can also attack older VPN tunneling standards. Tunneling protocols are simply a set of rules governing how your data is processed and transmitted via a certain network.

We wish to avoid utilizing old protocols like PPTP and L2TP/IPSec. These protocols are outdated and are regarded as medium to low security by modern standards.

PPTP, in example, is an older technology with documented weaknesses that unscrupulous actors can exploit. In contrast, L2TP/IPSec provides better security but slower performance than newer protocols.

Fortunately, more recent VPN protocols such as OpenVPN, WireGuard, and IKEv2 offer an excellent balance of high-level security and speed.

DNS, IP, and WebRTC leaks

Malicious actors can also steal user data via VPN leaks. VPN leaks occur when user data is "leaked" from the secure VPN tunnel as a result of a bug or vulnerability inside the software. The primary types of VPN leaks include the following:

DNS leaks occur when the VPN reveals your internet activity, such as DNS queries or browsing history, to the ISP DNS server despite being connected over an encrypted VPN connection.

IP leaks occur when your IP address is accidentally leaked or exposed to the internet, undermining the primary function of a VPN in disguising your true IP address and location.

WebRTC leaks are browser-based leaks in which websites gain unauthorized access to your actual IP address by bypassing the encrypted VPN connection.

VPNs inherently log user data

Finally, hacking is possible when VPN providers access customer data without their authorization.

While many VPN services promise to have no-logs policies, indicating that they are not keeping user data, VPNs have been shown to store user information notwithstanding these rules.

Why should you still invest in a VPN?

Even after understanding the various ways VPNs can be exploited, utilizing a VPN is significantly more secure than not using one. VPNs enable you and your organization to mask your IP address with the touch of a button.

Hiding your IP address is critical because criminal actors can exploit it to send you invasive adverts, learn your location, and collect information about your personal identity. VPNs are one of the simplest and most accessible ways to accomplish this.

VPNs are also an excellent solution for larger enterprises to maintain the security of company data, especially if your company has distant employees who access company resources via the Internet.

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Technology
AI overrated ChatGPT ban life sciences industry Pharmas survey findings Technology

Survey Finds Two-Thirds of Leading Pharmas Restrict ChatGPT Usage, While Many in Life Sciences Industry Deem AI 'Overrated'

 

In the ongoing debate over the integration of artificial intelligence (AI) into various industries, the biopharmaceutical sector is taking a cautious approach. According to a recent survey conducted by ZoomRx among over 200 professionals in life sciences, more than half reported that their companies have prohibited the use of OpenAI's ChatGPT tool. 

This ban was particularly prevalent among the top 20 pharmaceutical companies, with 65% implementing it. Concerns about potential leaks of sensitive internal data to competitors drove these policies.

Andrew Yukawa, a product manager at ZoomRx, emphasized the delicate balance between the speculative benefits and recognized security risks associated with AI implementation in life sciences. He highlighted a past incident where a bug in ChatGPT led to a temporary shutdown, allowing some users to access others' chat history. This raised concerns that proprietary information could inadvertently become part of OpenAI's training dataset.

Despite the prevalence of bans, the survey revealed a lack of proactive measures beyond restrictions. Less than 60% of companies provided training or guidelines on the safe use of ChatGPT, though some indicated plans to do so in the future.

Nevertheless, despite the reservations and bans, many professionals in the life sciences sector are actively using ChatGPT. Over half of the respondents reported using it at least a few times per month, with a significant portion using it weekly or even daily.

While the survey participants expressed skepticism about AI's overhyped reputation, many companies are already leveraging AI technologies. Drug discovery emerged as the most common application, followed by personalized medicine, copywriting, and trial optimization. Cost savings were cited as the primary motivation for AI implementation, outweighing its perceived impact on revenue.

Despite the widespread adoption, concerns about data security and privacy persist. The majority of respondents expressed belief in AI's potential to enhance efficiency and effectiveness but also acknowledged significant concerns about its impact on data security and privacy.
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Technology
Apple Internet Internet Complexity Tech Outage Technology

Tech Outages: Exposing the Web’s Fragile Threads

Tech Outages: Exposing the Web’s Fragile Threads

Today, technology outages have become more than mere inconveniences—they’re disruptions that ripple across industries, affecting businesses, individuals, and even our daily routines. Over 1.75 million user-reported issues flooded in from across the globe.  From WhatsApp to Greggs (the UK’s popular sausage roll maker), and even tech giants like Apple and Meta, all have recently faced service disruptions due to IT outages. Let’s explore the reasons behind this trend.

Downdetector

This platform monitors web outages and provides insights into the extent of problems faced by companies. On April 3, 2024, more than 1.75 million user-reported issues were flagged worldwide for WhatsApp, with tens of thousands also reported for the App Store and Apple TV. Neither firm responded to inquiries about the cause of their outages.

Internet Complexity

The internet, like software, comprises multiple layers. Regulatory changes, consumer demands for seamless data access, and the integration of new features (such as AI chatbots) add layers and complexity. Unfortunately, more layers mean a higher risk of things going wrong. Companies are pushing for innovation, but it comes with the potential of breaking existing systems.

Moving Parts and Cloud Services

Various factors can cause internet services to fail, including typos in code, hardware faults, power outages, and cyberattacks. Severe weather conditions can also impact data centers housing powerful servers. Additionally, many companies have shifted from managing their infrastructure in-house to using cloud services. While this enables faster development, a single outage at the cloud service provider can affect multiple platforms and technologies.

Tech Giants

Glitches in services provided by major cloud providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud have previously led to downtime for thousands of customers.

The internet's complexity, rapid innovation, and reliance on cloud services contribute to the increased occurrence of tech outages. As companies strive for progress, maintaining stability remains a challenge.

The Quest for Progress

We crave seamless experiences. We want our apps to load instantly, our streaming services to buffer flawlessly, and our online orders to arrive yesterday. But progress is a hungry beast. It devours stability, chews on reliability, and spits out error messages. The quest for innovation pushes boundaries, but it also tests the limits of our digital infrastructure.

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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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Technology
AI technology AI Tool ChatGPT ChatGPT-4 Medical Sector Patient Data Technology

Harnessing AI and ChatGPT for Eye Care Triage: Advancements in Patient Management

 

In a groundbreaking study conducted by Dr. Arun Thirunavukarasu, a former University of Cambridge researcher, artificial intelligence (AI) emerges as a promising tool for triaging patients with eye issues. Dr. Thirunavukarasu's research highlights the potential of AI to revolutionize patient management in ophthalmology, particularly in identifying urgent cases that require immediate specialist attention. 

The study, conducted in collaboration with Cambridge University academics, evaluated the performance of ChatGPT 4, an advanced language model, in comparison to expert ophthalmologists and medical trainees. Remarkably, ChatGPT 4 exhibited a scoring accuracy of 69% in a simulated exam setting, outperforming previous iterations of the program and rival language models such as ChatGPT 3.5, Llama, and Palm2. 

Utilizing a vast dataset comprising 374 ophthalmology questions, ChatGPT 4 demonstrated its capability to analyze complex eye symptoms and signs, providing accurate recommendations for patient triage. When compared to expert clinicians, trainees, and junior doctors, ChatGPT 4 proved to be on par with experienced ophthalmologists in processing clinical information and making informed decisions. 

Dr. Thirunavukarasu emphasizes the transformative potential of AI in streamlining patient care pathways. He envisions AI algorithms assisting healthcare professionals in prioritizing patient cases, distinguishing between emergencies requiring immediate specialist intervention and those suitable for primary care or non-urgent follow-up. 

By leveraging AI-driven triage systems, healthcare providers can optimize resource allocation and ensure timely access to specialist services for patients in need. Furthermore, the integration of AI technologies in primary care settings holds promise for enhancing diagnostic accuracy and expediting treatment referrals. ChatGPT 4 and similar language models could serve as invaluable decision support tools for general practitioners, offering timely guidance on eye-related concerns and facilitating prompt referrals to specialist ophthalmologists. 

Despite the remarkable advancements in AI-driven healthcare, Dr. Thirunavukarasu underscores the indispensable role of human clinicians in patient care. While AI technologies offer invaluable assistance and decision support, they complement rather than replace the expertise and empathy of healthcare professionals. Dr. Thirunavukarasu reaffirms the central role of doctors in overseeing patient management and emphasizes the collaborative potential of AI-human partnerships in delivering high-quality care. 

As the field of AI continues to evolve, propelled by innovative research and technological advancements, the integration of AI-driven triage systems in clinical practice holds immense promise for enhancing patient outcomes and optimizing healthcare delivery in ophthalmology and beyond. Dr. Thirunavukarasu's pioneering work exemplifies the transformative impact of AI in revolutionizing patient care pathways and underscores the imperative of embracing AI-enabled solutions to address the evolving needs of healthcare delivery.
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zero-trust solutions
AI governance Cybersecurity Threats GenAI SaaS security Technology zero-trust solutions

GenAI Presents a Fresh Challenge for SaaS Security Teams

The software industry witnessed a pivotal moment with the introduction of Open AI's ChatGPT in November 2022, sparking a race dubbed the GenAI race. This event spurred SaaS vendors into a frenzy to enhance their tools with generative AI-driven productivity features.

GenAI tools serve a multitude of purposes, simplifying software development for developers, aiding sales teams in crafting emails, assisting marketers in creating low-cost unique content, and facilitating brainstorming sessions for teams and creatives.

Notable recent launches in the GenAI space include Microsoft 365 Copilot, GitHub Copilot, and Salesforce Einstein GPT, all of which are paid enhancements, indicating the eagerness of SaaS providers to capitalize on the GenAI trend. Google is also gearing up to launch its SGE (Search Generative Experience) platform, offering premium AI-generated summaries instead of conventional website listings.

The rapid integration of AI capabilities into SaaS applications suggests that it won't be long before AI becomes a standard feature in such tools.

However, alongside these advancements come new risks and challenges for users. The widespread adoption of GenAI applications in workplaces is raising concerns about exposure to cybersecurity threats.

GenAI operates by training models to generate data similar to the original based on user-provided information. This exposes organizations to risks such as IP leakage, exposure of sensitive customer data, and the potential for cybercriminals to use deepfakes for phishing scams and identity theft.

These concerns, coupled with the need to comply with regulations, have led to a backlash against GenAI applications, especially in industries handling confidential data. Some organizations have even banned the use of GenAI tools altogether.

Despite these bans, organizations struggle to control the use of GenAI applications effectively, as they often enter the workplace without proper oversight or approval.

In response to these challenges, the US government is urging organizations to implement better governance around AI usage. This includes appointing Chief AI Officers to oversee AI technologies and ensure responsible usage.

With the rise of GenAI applications, organizations need to reassess their security measures. Traditional perimeter protection strategies are proving inadequate against modern threats, which target vulnerabilities within organizations.

To regain control and mitigate risks associated with GenAI apps, organizations can adopt advanced zero-trust solutions like SSPM (SaaS Security Posture Management). These solutions provide visibility into AI-enabled apps and assess their security posture to prevent, detect, and respond to threats effectively.

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Wireless
Cyber Scammers cyber threat Cyberattacks CyberCrime FBI FCC Financial Loss Reddit SIM SIM swap Swap Scam T-Mobile Technology Verizon Wireless

Inside Job Exposed: T-Mobile US, Verizon Staff Solicited for SIM Swap Scam

 


T-Mobile and Verizon employees are being texted by criminals who are attempting to entice them into swapping SIM cards with cash. In their screenshots, the targeted employees are offering $300 as an incentive for those willing to assist the senders in their criminal endeavours, and they have shared them with us. 

The report indicates that this was part of a campaign that targets current and former mobile carrier workers who could be able to access the systems that would be necessary for the swapping of SIM cards. The message was also received by Reddit users claiming to be Verizon employees, which indicates that the scam isn't limited to T-Mobile US alone. 

It is known that SIM swapping is essentially a social engineering scam in which the perpetrator convinces the carrier that their number will be transferred to a SIM card that they own, which is then used to transfer the number to a new SIM card owned by the perpetrator. 

The scammer can use this information to gain access to a victim's cell phone number, allowing them to receive multi-factor authentication text messages to break into other accounts. If the scammer has complete access to the private information of the victim, then it is extremely lucrative. 

SIM swapping is a method cybercriminals utilize to breach multi-factor authentication (MFA) protected accounts. It is also known as simjacking. Wireless carriers will be able to send messages intended for a victim if they port the victim’s SIM card information from their legitimate SIM card to one controlled by a threat actor, which allows the threat actor to take control of their account if a message is sent to the victim. 

Cyber gangs are often able to trick carrier support staff into performing swaps by presenting fake information to them, but it can be far more efficient if they hire an insider to take care of it. In the past, both T-Mobile and Verizon have been impacted by breaches of employee information, including T-Mobile in 2020 and Verizon last year, despite it being unclear how the hackers obtained the mobile numbers of the workers who received the texts. 

The company stated at the time that there was no evidence that some of the information had been misused or shared outside the organization as a result of unauthorized access to the file, as well as in 2010 a Verizon employee had accessed a file containing details for about half of Verizon s 117,00-strong workforce without the employee's authorization.

It appears that the hackers behind the SIM swap campaign were working with outdated information, as opposed to recent data stolen from T-Mobile, according to the number of former T-Mobile employees who commented on Reddit that they received the SIM swap message. As the company confirmed the fact that there had not been any system breaches at T-Mobile in a statement, this was reinforced by the company. 

Using SIM swap attacks, criminals attempt to reroute a victim's wireless service to a device controlled by the fraudster by tricking their wireless carrier into rerouting their service to it. A successful attack can result in unauthorized access to personal information, identity theft, financial losses, emotional distress for the victim, and financial loss. Criminals started hijacking victims' phone numbers in February 2022 to steal millions of dollars by performing SIM swap attacks. 

The FBI warned about this in February 2022. Additionally, the IC3 reported that Americans reported 1,075 SIM-swapping complaints during the year 2023, with an adjusted loss of $48,798,103 for each SIM-swapping complaint. In addition to 2,026 complaints about SIM-swapping attacks in the past year, the FBI also received $72,652,571 worth of complaints about SIM-swapping attacks from January 2018 to December 2020. 

Between January 2018 and December 2020, however, only 320 complaints were filed regarding SIM-swapping incidents resulting in losses of around $12 million. Following this huge wave of consumer complaints, the Federal Communications Commission (FCC) announced new regulations that will protect Americans from SIM-swapping attacks to protect Americans from this sort of attack in the future.

It is required by the new regulations that carriers have a secure authentication procedure in place before they transfer the customer's phone numbers to a different device or service provider. Additionally, they need to warn them if their accounts are changed or they receive a SIM port out request.
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Workforce
Data Management Employee Security Robots Technology Workforce

Second Largest Employer Amazon Opts For Robots, Substituting 100,000 Jobs

 

Amazon.com Inc. is swiftly increasing the use of robotics, with over 750,000 robots functioning alongside its employees. 

There are 1.5 million people at the second-largest private company in the world. Even if it's a large number, it represents a drop of more than 100,000 jobs from the 1.6 million it had in 2021. In the meanwhile, the company employed 200,000 robots in 2019 and 520,000 in 2022. Amazon is gradually cutting back on employees whilst it adds hundreds of thousands of robots annually. 

The robots, which include new models such as Sequoia and Digit, are designed to execute repetitive duties, boost productivity, safety, and delivery speed for Amazon customers. Sequoia, for example, speeds inventory management and order processing at delivery centres, whereas Digit, a bipedal robot developed in collaboration with Agility Robotics, handles positions such as transporting empty tote boxes. 

Amazon's significant investment in robots illustrates the company's commitment to supply chain innovation as well as its belief in the synergistic potential of human-robot collaboration. Despite the vast amount of automation, Amazon stresses that deploying robots has led to the creation of new skilled job categories at the company, mirroring a larger industry trend of integrating innovative technologies with human workforces. 

Amazon's deployment of more than 750,000 robots marks a huge step towards automation at the world's second-largest employer. The move has the potential to drastically alter job dynamics within the organisation and outside. While Amazon claims that robots are designed to collaborate with human employees, assisting them with repetitive chores to increase productivity and workplace safety, concerns about job displacement and the consequences for the workforce are unavoidable. 

The tech giant's integration of robots like Sequoia and Digit into its fulfilment centres is part of a larger drive to enhance supply chain operations using innovative technologies. The robots are intended to streamline processes and provide quicker delivery times to customers. The company emphasises that robotic solutions promote workplace safety and enable it to provide a wider range of products for same-day or next-day delivery. 

The introduction of so many robots into the workplace raises concerns about the future role of human labour in Amazon's operational paradigm. Many people are concerned about the impact on occupations, particularly highly repetitive tasks that could be easily mechanised. Research from universities such as the Massachusetts Institute of Technology (MIT) has found that industrial robots have a major detrimental impact on workers, hurting jobs and salaries in the areas where they are deployed. The broader discussion of automation's economic and political ramifications emphasises common concerns about job displacement and the possibility of higher income inequality. 

Despite these worries, Amazon has noted the emergence of 700 categories of skilled job kinds that did not previously exist at the company, implying that automation can also result in the creation of new forms of employment prospects. This change in Amazon's workforce may indicate a shift in the nature of labour, with human employees moving towards more complicated, non-repetitive jobs that demand higher levels of ability and creativity.
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Technology
Biometric Security Data Privacy Facial Recognition KYC Technology

Is Facial Biometrics the Future of Digital Security?

 



Within the dynamic sphere of digital technology, businesses are continually seeking innovative solutions to streamline operations and step up their security measures. One such innovation that has garnered widespread attention is facial biometrics, a cutting-edge technology encompassing face recognition and liveness detection. This technology, now available through platforms like Auth0 marketplace, is revolutionising digital processes and significantly enhancing security protocols.

What's Facial Biometrics?

Facial biometrics operates by analysing unique facial features to verify an individual's identity. Through face recognition, it compares facial characteristics from a provided image with stored templates for authentication purposes. Similarly, face liveness detection distinguishes live human faces from static images or videos, ensuring the authenticity of user interactions. This highlights the technology's versatility, applicable across various domains ranging from smartphone security to border control measures.

Streamlining Digital Processes

One of the key benefits of facial biometrics is its ability to streamline digital processes, starting with digital onboarding procedures. For instance, banks can expedite the verification process for new customers by comparing a selfie with their provided identification documents, ensuring compliance with regulatory requirements such as Know Your Customer (KYC) norms. Moreover, facial biometrics eliminates the need for complex passwords, offering users a secure and user-friendly authentication method. This streamlined approach not only strengthens security but also improves the overall user experience.

A Step-Up In The Security Measures

Beyond simplifying processes, facial biometrics adds an additional layer of security to business operations. By verifying user identities at critical junctures, such as transaction confirmations, businesses can thwart unauthorised access attempts by fraudsters. This proactive stance against potential threats not only safeguards sensitive information but also mitigates financial risks associated with fraudulent activities.

Embracing the Future

As facial biometrics continues to gain momentum, businesses are presented with an array of opportunities to bolster security measures and upgrade user experiences. Organisations can not only mitigate risks but also explore new possibilities for growth in the digital age. With a focus on simplicity, security, and user-centric design, facial biometrics promises to redefine the future of digital authentication and identity verification.

All in all, facial biometrics represents an impactful milestone in the realm of digital security and user convenience. By embracing this technology, businesses can achieve a delicate balance between efficiency and security, staying ahead of unprecedented threats posed by AI bots and malicious actors. However, it is imperative to implement facial biometrics in a manner that prioritises user privacy and data protection. As businesses work out the digital transformation journey, platforms like Auth0 marketplace offer comprehensive solutions tailored to diverse needs, ensuring a seamless integration of facial biometrics into existing frameworks.


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Technology
AI electricity Energy Security future grid resilience prevent power cuts Tech Technology

AI's Role in Averting Future Power Outages

 

Amidst an ever-growing demand for electricity, artificial intelligence (AI) is stepping in to mitigate power disruptions.

Aseef Raihan vividly recalls a chilling night in February 2021 in San Antonio, Texas, during winter storm Uri. As temperatures plunged to -19°C, Texas faced an unprecedented surge in electricity demand to combat the cold. 

However, the state's electricity grid faltered, with frozen wind turbines, snow-covered solar panels, and precautionary shutdowns of nuclear reactors leading to widespread power outages affecting over 4.5 million homes and businesses. Raihan's experience of enduring cold nights without power underscored the vulnerability of our electricity systems.

The incident in Texas highlights a global challenge as countries witness escalating electricity demands due to factors like the rise in electric vehicle usage and increased adoption of home appliances like air conditioners. Simultaneously, many nations are transitioning to renewable energy sources, which pose challenges due to their variable nature. For instance, electricity production from wind and solar sources fluctuates based on weather conditions.

To bolster energy resilience, countries like the UK are considering the construction of additional gas-powered plants. Moreover, integrating large-scale battery storage systems into the grid has emerged as a solution. In Texas, significant strides have been made in this regard, with over five gigawatts of battery storage capacity added within three years following the storm.

However, the effectiveness of these batteries hinges on their ability to predict optimal charging and discharging times. This is where AI steps in. Tech companies like WattTime and Electricity Maps are leveraging AI algorithms to forecast electricity supply and demand patterns, enabling batteries to charge during periods of surplus energy and discharge when demand peaks. 

Additionally, AI is enhancing the monitoring of electricity infrastructure, with companies like Buzz Solutions employing AI-powered solutions to detect damage and potential hazards such as overgrown vegetation and wildlife intrusion, thus mitigating the risk of power outages and associated hazards like wildfires.
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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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Technology
Data Technology Encryption Tools Quantum Quantum computing Technology

The Future of Quantum Computers: Challenging Space Encryption with Light

 

In the realm of technology and communications, the race for supremacy between quantum computers and space encryption is intensifying. 

While quantum computers hold the promise of unprecedented processing power, space encryption, leveraging light to beam data around, presents a formidable challenge. 

The advent of the first satellite slated for launch in 2025 heralds a new era in secure communication. Quantum computers, with their ability to perform complex calculations at speeds far surpassing traditional computers, have long been hailed as the future of computing. 

However, their potential to unravel existing encryption methods poses a significant threat to data security. With the ability to quickly factor large numbers, quantum computers could potentially break conventional encryption algorithms, jeopardizing sensitive information across various sectors. 

On the other hand, space-based encryption offers a robust solution to this dilemma. By harnessing the properties of light to encode and transmit data, space encryption provides an inherently secure method of communication. Unlike conventional methods that rely on mathematical algorithms, which could be compromised by quantum computing, light-based encryption offers a level of security that is theoretically unbreakable. 

The upcoming launch of the first satellite dedicated to space encryption marks a pivotal moment in the evolution of secure communication. Equipped with advanced photonics technology, this satellite will demonstrate the feasibility of transmitting data securely over long distances using quantum principles. 

By beaming encrypted data through space via light particles, it will lay the groundwork for a future where secure communication is not only possible but also practical on a global scale. One of the key advantages of space encryption lies in its resistance to interception and tampering. Unlike terrestrial communication networks, which are susceptible to eavesdropping and hacking, data transmitted via space-based encryption is inherently secure. 

The vast distances involved make it extremely difficult for unauthorized parties to intercept or manipulate the data without detection, providing a level of security unmatched by conventional methods. Furthermore, space encryption offers unparalleled reliability and speed. With data transmitted at the speed of light, communication delays are virtually nonexistent, making it ideal for applications where real-time transmission is critical. 

From financial transactions to government communications, the ability to transmit data quickly and securely is paramount, and space encryption delivers on both fronts. As quantum computers continue to advance, the need for secure communication methods becomes increasingly urgent. While quantum-resistant encryption algorithms are being developed, they may not be sufficient to withstand the full potential of quantum computing. 

In contrast, space encryption offers a solution that is not only resistant to quantum attacks but also provides a level of security that is unmatched by any other method. In conclusion, the future of quantum computers and space encryption is intertwined in a battle for supremacy in the realm of secure communication. While quantum computers hold the promise of unparalleled processing power, space encryption offers a robust solution to the threat of quantum attacks. 

With the launch of the first satellite dedicated to space encryption on the horizon, we stand at the cusp of a new era in secure communication—one where light reigns supreme. Search Description: Explore the future of quantum computers challenging space encryption with light-based data transmission, as the first satellite launch in 2025 heralds a new era in secure communication.
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Technology
AI technology AI tools Generative AI generative AI tools innovative features Technology

What AI Can Do Today? The latest generative AI tool to find the perfect AI solution for your tasks

 

Generative AI tools have proliferated in recent times, offering a myriad of capabilities to users across various domains. From ChatGPT to Microsoft's Copilot, Google's Gemini, and Anthrophic's Claude, these tools can assist with tasks ranging from text generation to image editing and music composition.
 
The advent of platforms like ChatGPT Plus has revolutionized user experiences, eliminating the need for logins and providing seamless interactions. With the integration of advanced features like Dall-E image editing support, these AI models have become indispensable resources for users seeking innovative solutions. 

However, the sheer abundance of generative AI tools can be overwhelming, making it challenging to find the right fit for specific tasks. Fortunately, websites like What AI Can Do Today serve as invaluable resources, offering comprehensive analyses of over 5,800 AI tools and cataloguing over 30,000 tasks that AI can perform. 

Navigating What AI Can Do Today is akin to using a sophisticated search engine tailored specifically for AI capabilities. Users can input queries and receive curated lists of AI tools suited to their requirements, along with links for immediate access. 

Additionally, the platform facilitates filtering by category, further streamlining the selection process. While major AI models like ChatGPT and Copilot are adept at addressing a wide array of queries, What AI Can Do Today offers a complementary approach, presenting users with a diverse range of options and allowing for experimentation and discovery. 

By leveraging both avenues, users can maximize their chances of finding the most suitable solution for their needs. Moreover, the evolution of custom GPTs, supported by platforms like ChatGPT Plus and Copilot, introduces another dimension to the selection process. These specialized models cater to specific tasks, providing tailored solutions and enhancing efficiency. 

It's essential to acknowledge the inherent limitations of generative AI tools, including the potential for misinformation and inaccuracies. As such, users must exercise discernment and critically evaluate the outputs generated by these models. 

Ultimately, the journey to finding the right generative AI tool is characterized by experimentation and refinement. While seasoned users may navigate this landscape with ease, novices can rely on resources like What AI Can Do Today to guide their exploration and facilitate informed decision-making. 

The ecosystem of generative AI tools offers boundless opportunities for innovation and problem-solving. By leveraging platforms like ChatGPT, Copilot, Gemini, Claude, and What AI Can Do Today, users can unlock the full potential of AI and harness its transformative capabilities.
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VespAI
Artifical Inteligence Cornwall Technology UK University of Exeter VespAI

AI Developed to Detect Invasive Asian Hornets

 



Researchers at the University of Exeter have made an exceptional breakthrough in combating the threat of unsettling Asian hornets by developing an artificial intelligence (AI) system. Named VespAI, this automated system boasts the capability to identify Asian hornets with exceptional accuracy, per the findings of the university’s recent study.

Dr. Thomas O'Shea-Wheller, from the Environment and Sustainability Institute from Exter's Penryn Campus in Cornwall, highlighted the system's user-friendly nature, emphasising its potential for widespread adoption, from governmental agencies to individual beekeepers. He described the aim as creating an affordable and adaptable solution to address the pressing issue of invasive species detection.

How VespAI Works

VespAI operates using a compact processor and remains inactive until its sensors detect an insect within the size range of an Asian hornet. Once triggered, the AI algorithm aanalyses aptured images to determine whether the insect is an Asian hornet (Vespa velutina) or a native European hornet (Vespa crabro). If an Asian hornet is identified, the system sends an image alert to the user for confirmation.

Record Numbers of Sightings

The development of VespAI is a response to a surge in Asian hornet sightings not only across the UK but also in mainland Europe. In 2023, record numbers of these invasive hornets were observed, posing a significant threat to honeybee populations and biodiversity. With just one hornet capable of consuming up to 50 bees per day, the urgency for effective surveillance and response strategies is paramount.

Addressing Misidentification

Dr. Peter Kennedy, the mastermind behind VespAI, emphasised the system's ability to mitigate misidentifications, which have been prevalent in previous reports. By providing accurate and automated surveillance, VespAI aims to improve the efficiency of response efforts while minimising environmental impact.

What The Testing Indicate?

The effectiveness of VespAI was demonstrated through testing in Jersey, an area prone to Asian hornet incursions due to its proximity to mainland Europe. The system's high accuracy ensures that no Asian hornets are overlooked, while also preventing misidentification of other species.

Interdisciplinary Collaboration

The development of VespAI involved collaboration between biologists and data scientists from various departments within the University of Exeter. This interdisciplinary approach enabled the integration of biological expertise with cutting-edge AI technology, resulting in a versatile and robust solution.

The breakthrough AI system, dubbed VespAI, as detailed in their recent paper titled “VespAI: a deep learning-based system for the detection of invasive hornets,” published in the journal Communications Biology. This publication highlights the notable discovery made by the researchers in confronting the growing danger of invasive species. As we see it, this innovative AI system offers hope for protecting ecosystems and biodiversity from the threats posed by Asian hornets.


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Technology
AI technology Compliance Data Privacy Data Usage Microsoft privacy protection Privacy Regulations Privacy Tools Technology

Microsoft's Priva Platform: Revolutionizing Enterprise Data Privacy and Compliance

 

Microsoft has taken a significant step forward in the realm of enterprise data privacy and compliance with the expansive expansion of its Priva platform. With the introduction of five new automated products, Microsoft aims to assist organizations worldwide in navigating the ever-evolving landscape of privacy regulations. 

In today's world, the importance of prioritizing data privacy for businesses cannot be overstated. There is a growing demand from individuals for transparency and control over their personal data, while governments are implementing stricter laws to regulate data usage, such as the AI Accountability Act. Paul Brightmore, principal group program manager for Microsoft’s Governance and Privacy Platform, highlighted the challenges faced by organizations, noting a common reactive approach to privacy management. 

The new Priva products are designed to shift organizations from reactive to proactive data privacy operations through automation and comprehensive risk assessment. Leveraging AI technology, these offerings aim to provide complete visibility into an organization’s entire data estate, regardless of its location. 

Brightmore emphasized the capabilities of Priva in handling data requests from individuals and ensuring compliance across various data sources. The expanded Priva family includes Privacy Assessments, Privacy Risk Management, Tracker Scanning, Consent Management, and Subject Rights Requests. These products automate compliance audits, detect privacy violations, monitor web tracking technologies, manage user consent, and handle data access requests at scale, respectively. 

Brightmore highlighted the importance of Privacy by Design principles and emphasized the continuous updating of Priva's automated risk management features to address emerging data privacy risks. Microsoft's move into the enterprise AI governance space with Priva follows its recent disagreement with AI ethics leaders over responsibility assignment practices in its AI copilot product. 

However, Priva's AI capabilities for sensitive data identification could raise concerns among privacy advocates. Brightmore referenced Microsoft's commitment to protecting customer privacy in the AI era through technologies like privacy sandboxing and federated analytics. With fines for privacy violations increasing annually, solutions like Priva are becoming essential for data-driven organizations. 

Microsoft strategically positions Priva as a comprehensive privacy governance solution for the enterprise, aiming to make privacy a fundamental aspect of its product stack. By tightly integrating these capabilities into the Microsoft cloud, the company seeks to establish privacy as a key driver of revenue across its offerings. 

However, integrating disparate privacy tools under one umbrella poses significant challenges, and Microsoft's track record in this area is mixed. Privacy-native startups may prove more agile in this regard. Nonetheless, Priva's seamless integration with workplace applications like Teams, Outlook, and Word could be its key differentiator, ensuring widespread adoption and usage among employees. 

Microsoft's Priva platform represents a significant advancement in enterprise data privacy and compliance. With its suite of automated solutions, Microsoft aims to empower organizations to navigate complex privacy regulations effectively while maintaining transparency and accountability in data usage.
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Technology
AI technology Algorithm Applications Machine learning Neural Networks Technology

Deciphering the Impact of Neural Networks on Artificial Intelligence Evolution

 

Artificial intelligence (AI) has long been a frontier of innovation, pushing the boundaries of what machines can achieve. At the heart of AI's evolution lies the fascinating realm of neural networks, sophisticated systems inspired by the complex workings of the human brain. 

In this comprehensive exploration, we delve into the multifaceted landscape of neural networks, uncovering their pivotal role in shaping the future of artificial intelligence. Neural networks have emerged as the cornerstone of AI advancement, revolutionizing the way machines learn, adapt, and make decisions. 

Unlike traditional AI models constrained by rigid programming, neural networks possess the remarkable ability to glean insights from vast datasets through adaptive learning mechanisms. This paradigm shift has ushered in a new era of AI characterized by flexibility, intelligence, and innovation. 

At their core, neural networks mimic the interconnected neurons of the human brain, with layers of artificial nodes orchestrating information processing and decision-making. These networks come in various forms, from Feedforward Neural Networks (FNN) for basic tasks to complex architectures like Convolutional Neural Networks (CNN) for image recognition and Generative Adversarial Networks (GAN) for creative tasks. 

Each type offers unique capabilities, allowing AI systems to excel in diverse applications. One of the defining features of neural networks is their ability to adapt and learn from data patterns. Through techniques such as machine learning and deep learning, these systems can analyze complex datasets, identify intricate patterns, and make intelligent judgments without explicit programming. This adaptive learning capability empowers AI systems to continuously evolve and improve their performance over time, paving the way for unprecedented levels of sophistication. 

Despite their transformative potential, neural networks are not without challenges and ethical dilemmas. Issues such as algorithmic bias, opacity in decision-making processes, and data privacy concerns loom large, underscoring the need for responsible development and governance frameworks. By addressing these challenges head-on, we can ensure that AI advances in a manner that aligns with ethical principles and societal values. 

As we embark on this journey of exploration and innovation, it is essential to recognize the immense potential of neural networks to shape the future of artificial intelligence. By fostering a culture of responsible development, collaboration, and ethical stewardship, we can harness the full power of neural networks to tackle complex challenges, drive innovation, and enrich the human experience. 

The evolution of artificial intelligence is intricately intertwined with the transformative capabilities of neural networks. As these systems continue to evolve and mature, they hold the promise of unlocking new frontiers of innovation and discovery. By embracing responsible development practices and ethical guidelines, we can ensure that neural networks serve as catalysts for positive change, empowering AI to fulfill its potential as a force for good in the world.
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Technology
AI CISO cyber threat Data protection LLM Machine learning Ransomware Technology

Enterprise AI Adoption Raises Cybersecurity Concerns

 




Enterprises are rapidly embracing Artificial Intelligence (AI) and Machine Learning (ML) tools, with transactions skyrocketing by almost 600% in less than a year, according to a recent report by Zscaler. The surge, from 521 million transactions in April 2023 to 3.1 billion monthly by January 2024, underscores a growing reliance on these technologies. However, heightened security concerns have led to a 577% increase in blocked AI/ML transactions, as organisations grapple with emerging cyber threats.

The report highlights the developing tactics of cyber attackers, who now exploit AI tools like Language Model-based Machine Learning (LLMs) to infiltrate organisations covertly. Adversarial AI, a form of AI designed to bypass traditional security measures, poses a particularly stealthy threat.

Concerns about data protection and privacy loom large as enterprises integrate AI/ML tools into their operations. Industries such as healthcare, finance, insurance, services, technology, and manufacturing are at risk, with manufacturing leading in AI traffic generation.

To mitigate risks, many Chief Information Security Officers (CISOs) opt to block a record number of AI/ML transactions, although this approach is seen as a short-term solution. The most commonly blocked AI tools include ChatGPT and OpenAI, while domains like Bing.com and Drift.com are among the most frequently blocked.

However, blocking transactions alone may not suffice in the face of evolving cyber threats. Leading cybersecurity vendors are exploring novel approaches to threat detection, leveraging telemetry data and AI capabilities to identify and respond to potential risks more effectively.

CISOs and security teams face a daunting task in defending against AI-driven attacks, necessitating a comprehensive cybersecurity strategy. Balancing productivity and security is crucial, as evidenced by recent incidents like vishing and smishing attacks targeting high-profile executives.

Attackers increasingly leverage AI in ransomware attacks, automating various stages of the attack chain for faster and more targeted strikes. Generative AI, in particular, enables attackers to identify vulnerabilities and exploit them with greater efficiency, posing significant challenges to enterprise security.

Taking into account these advancements, enterprises must prioritise risk management and enhance their cybersecurity posture to combat the dynamic AI threat landscape. Educating board members and implementing robust security measures are essential in safeguarding against AI-driven cyberattacks.

As institutions deal with the complexities of AI adoption, ensuring data privacy, protecting intellectual property, and mitigating the risks associated with AI tools become paramount. By staying vigilant and adopting proactive security measures, enterprises can better defend against the growing threat posed by these cyberattacks.

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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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Technology
Data Brokerage Data Brokers Data collection data security Privacy Invasion Technology

Data Broker Tracked Visitors to Jeffrey Epstein’s Island, New Report Reveals

 

The saga surrounding Jeffrey Epstein, a convicted sex offender with ties to numerous wealthy and influential figures, continues to unfold with alarming revelations surfacing about the extent of privacy intrusion. Among the latest reports is the shocking revelation that a data broker actively tracked visitors to Epstein’s private island, Little Saint James, leveraging their mobile data to monitor their movements. This discovery has ignited a firestorm of controversy and renewed concerns about privacy rights and the unchecked power of data brokers. 

For years, Epstein's island remained shrouded in secrecy, known only to a select few within his inner circle. However, recent investigations have shed light on the island's dark activities and the prominent individuals who frequented its shores. Now, the emergence of evidence suggesting that a data broker exploited mobile data to monitor visits to the island has cast a disturbing spotlight on the invasive tactics employed by third-party entities. 

The implications of this revelation are profound and far-reaching. It raises serious questions about the ethical boundaries of data collection and surveillance in the digital age. While the practice of tracking mobile data is not new, its use in monitoring individuals' visits to sensitive and controversial locations like Epstein’s island underscores the need for greater transparency and accountability in the data brokerage industry. 

At its core, the issue revolves around the fundamental right to privacy and the protection of personal data. In an era where our every move is tracked and recorded, often without our knowledge or consent, the need for robust data protection regulations has never been more pressing. Without adequate safeguards in place, individuals are vulnerable to exploitation and manipulation by unscrupulous actors seeking to profit from their private information. 

Moreover, the revelation highlights the broader societal implications of unchecked data surveillance. It serves as a stark reminder of the power wielded by data brokers and the potential consequences of their actions on individuals' lives. From wealthy elites to everyday citizens, no one is immune to the pervasive reach of data tracking and monitoring. 

In response to these revelations, there is a growing call for increased transparency and accountability in the data brokerage industry. Individuals must be empowered with greater control over their personal data, including the ability to opt-out of invasive tracking practices. Additionally, regulators must step up enforcement efforts to hold data brokers accountable for any violations of privacy rights. 

As the investigation into the tracking of visitors to Epstein’s island continues, it serves as a sobering reminder of the urgent need to address the growing threats posed by unchecked data surveillance. Only through concerted action and meaningful reforms can we safeguard individuals' privacy rights and ensure a more ethical and responsible approach to data collection and usage in the digital age.
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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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