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Vulnerabilities and Exploits
Artificial Intelligence Cyber flaws Cyberattacks CyberCrime Cyberhackers Cybersecurity Cyberthreats Data Breach LangChain Vulnerabilities and Exploits

LangChain Gen AI Under Scrutiny Experts Discover Significant Flaws

 


Two vulnerabilities have been identified by Palo Alto Networks researchers (CVE-2023-46229 and CVE-2023-44467) that exist in LangChain, an open-source computing framework for generative artificial intelligence that is available on GitHub. The vulnerabilities that affect various products are CVE-2023-46229. It is known as the CVE-2023-46229 or Server Side Request Forgery (SSRF) bug and is an online security vulnerability that affects a wide range of products due to a vulnerability triggered in one of these products.

It should be noted that LangChain versions before 0.0.317 are particularly susceptible to this issue, with the recursive_url_loader.py module being used in the affected products. SSRF attacks can be carried out using this vulnerability, which will allow an external server to crawl and access an internal server, giving rise to SSRF attacks. It is quite clear that this possibility poses a significant risk to a company as it can open up the possibility of unauthorized access to sensitive information, compromise the integrity of internal systems, and lead to the possible disclosure of sensitive information. 

As a precautionary measure, organizations are advised to apply the latest updates and patches provided by LangChain to address and strengthen their security posture to solve the SSRF vulnerability. CVE-2023-44467 (or langchain_experimental) refers to a hypervulnerability that affects LangChain versions 0.0.306 and older. It is also known as a cyberattack vulnerability. By using import in Python code, attackers can bypass the CVE-2023-36258 fix and execute arbitrary code even though it was tested with CVE-2023. 

It should be noted that pal_chain/base.py does not prohibit exploiting this vulnerability. In terms of exploitability, the score is 3.9 out of 10, with a base severity of CRITICAL, and a base score of 9.8 out of 10. The attack has no privilege requirements, and no user interaction is required, and it can be launched from the network. It is important to note that the impact has a high level of integrity and confidentiality as well as a high level of availability. 

Organizers should start taking action as soon as possible to make sure their systems and data are protected from damage or unauthorized access by exploiting this vulnerability. LangChain versions before 0.0.317 are vulnerable to these vulnerabilities. It is recommended that users and administrators of affected versions of the affected products update their products immediately to the latest version. 

The first vulnerability, about which we have been alerted, is a critical prompt injection flaw in PALChain, a Python library that LangChain uses to generate code. The flaw has been tracked as CVE-2023-44467. Essentially, the researchers exploited this flaw by altering the functionality of two security functions within the from_math_prompt method, in which the user's query is translated into Python code capable of being run. 

The researchers used the two security functions to alter LangChain's validation checks, and it also decreased its ability to detect dangerous functions by setting the two values to false; as a result, they were able to execute the malicious code as a user-specified action on LangChain. In the time of OpenSSL, LangChain is an open-source library that is designed to make complex large language models (LLMs) easier to use. 

LangChain provides a multitude of composable building blocks, including connectors to models, integrations with third-party services, and tool interfaces usable by large language models (LLMs). Users can build chains using these components to augment LLMs with capabilities such as retrieval-augmented generation (RAG). This technique supplies additional knowledge to large language models, incorporating data from sources such as private internal documents, the latest news, or blogs. 

Application developers can leverage these components to integrate advanced LLM capabilities into their applications. Initially, during its training phase, the model relied solely on the data available at that time. However, by connecting the basic large language model to LangChain and integrating RAG, the model can now access the latest data, allowing it to provide answers based on the most current information available. 

LangChain has garnered significant popularity within the community. As of May 2024, it boasts over 81,900 stars and more than 2,550 contributors to its core repository. The platform offers numerous pre-built chains within its repository, many of which are community-contributed. Developers can directly use these chains in their applications, thus minimizing the need to construct and test their own LLM prompts. Researchers from Palo Alto Networks have identified vulnerabilities within LangChain and LangChain Experimental. 

A comprehensive analysis of these vulnerabilities is provided. LangChain’s website claims that over one million developers utilize its frameworks for LLM application development. Partner packages for LangChain include major names in the cloud, AI, databases, and other technological development sectors. Two specific vulnerabilities were identified that could have allowed attackers to execute arbitrary code and access sensitive data. 

LangChain has issued patches to address these issues. The article offers a thorough technical examination of these security flaws and guides mitigating similar threats in the future. Palo Alto Networks encourages LangChain users to download the latest version of the product to ensure that these vulnerabilities are patched. Palo Alto Networks' customers benefit from enhanced protection against attacks utilizing CVE-2023-46229 and CVE-2023-44467. 

The Next-Generation Firewall with Cloud-Delivered Security Services, including Advanced Threat Prevention, can identify and block command injection traffic. Prisma Cloud aids in protecting cloud platforms from these attacks, while Cortex XDR and XSIAM protect against post-exploitation activities through a multi-layered protection approach. Precision AI-powered products help to identify and block AI-generated attacks, preventing the acceleration of polymorphic threats. 

One vulnerability, tracked as CVE-2023-46229, affects a LangChain feature called SitemapLoader, which scrapes information from various URLs to compile it into a PDF. The vulnerability arises from SitemapLoader's capability to retrieve information from every URL it receives. A supporting utility called scrape_all gathers data from each URL without filtering or sanitizing it. This flaw could allow a malicious actor to include URLs pointing to intranet resources within the provided sitemap, potentially resulting in server-side request forgery and the unintentional leakage of sensitive data when the content from these URLs is fetched and returned. 

Researchers indicated that threat actors could exploit this flaw to extract sensitive information from limited-access application programming interfaces (APIs) of an organization or other back-end environments that the LLM interacts with. To mitigate this vulnerability, LangChain introduced a new function called extract_scheme_and_domain and an allowlist to enable users to control domains. 

Both Palo Alto Networks and LangChain urged immediate patching, particularly as companies hasten to deploy AI solutions. It remains unclear whether threat actors have exploited these flaws. LangChain did not immediately respond to requests for comment.
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Technology
Artificial Intelligence biotechnology emerging technologies NATO security threats Quantum computing technological edge Technology

NATO Collaborates with Start-Ups to Address Growing Security Threats

 

Marking its 75th anniversary at a summit in Washington DC this week, the North Atlantic Treaty Organization (NATO) focused on Ukraine while emphasizing the importance of new technologies and start-ups to adapt to modern security threats.

In its Washington Summit Declaration, NATO highlighted its accelerated transformation to address current and future threats while maintaining a technological edge. This includes experimenting with and rapidly adopting emerging technologies like artificial intelligence (AI), biotechnology, and quantum computing.

Phil Lockwood, Head of NATO’s Innovation Unit, told Euronews Next, "We've long recognized that our ability to deter and defend relies on our technological edge. Although we're experiencing unprecedented technological innovation, our edge is potentially eroding. We must work hard to maintain this edge as adversaries and competitors pursue their own technological advancements."

One technology NATO is exploring is seabed mapping, with the Dutch start-up Lobster Robotics as a key partner. "If they had survey equipment, they could have detected the Nord Stream pipeline explosions. While they may not have intervened, at least the threat would have been known," said Stephan Rutten, co-founder and CEO of Lobster Robotics. Lobster Robotics is one of 44 companies selected from 1,300 applicants for NATO's Defence Innovation Accelerator for the North Atlantic (DIANA) program, which provides resources and networks to address critical defense and security challenges.

DIANA focuses on dual-use innovations, applicable both commercially and for defense. NATO also supports start-ups through the NATO Innovation Fund. Lobster Robotics' optical seabed mapping technology can significantly reduce costs and increase safety compared to using teams of divers. It is particularly useful for mapping critical underwater infrastructure like wind farms and oil rigs.

Access to government or defense contracts can be lucrative yet challenging for start-ups. "It comes down to networking. You need to know the people and how the organization works," Rutten said, noting that NATO’s approval helped them collaborate with governments. "I urge governments to think in the time scale of start-ups. They say they're moving fast, but procurement takes 18 months. I could start five new companies by then."

The Greece-based company Sortiria Technology, another underwater intelligence firm selected by NATO, also finds the procurement process lengthy. "There are long contraction cycles and varied buying processes in each country," said Angelos Tsereklas, Managing Director of Sortiria Technology. "But initiatives like DIANA and the NATO Innovation Fund, as well as support from the European Union and European Investment Bank, are disrupting that model."

This month, NATO launched a second round of the DIANA project, focusing on energy, human health, information security, logistics, and critical infrastructure. Information security is a top concern, with lessons to be learned from Ukraine's experience with sophisticated cyber attacks from Russia.

In its Washington Summit Declaration, NATO warned of cyber threats from Russia and China, announcing a new cyber alliance called the Integrated Cyber Defence Centre. This center will bring together civilian and military personnel from NATO member countries and industry experts.

One notable start-up is Hushmesh, which aims to create a safer, more efficient internet. While its vision may take decades to realize, CEO Manu Fontaine said, "The natural glide path is to develop services on an inherently secure, verified infrastructure." Hushmesh is currently developing a messaging service for a NATO pilot program in 2025.

The Washington Summit Declaration also stated NATO’s intent to monitor technological advancements on the battlefield in Ukraine through experimentation and rapid adoption of emerging technologies. Rutten noted that while government procurement remains challenging, change is underway. "Many countries are becoming more agile and open to innovation faster, inspired by the successes seen in Ukraine. However, it may take a few more years to fully implement these changes."
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Technology
Artificial Intelligence Indian Weddings NVIDIA Chips RTX40 Technology

Here's How Nvidia's Chips Can Disrupt Large-Scale Indian Weddings

 

The big large Indian wedding is all about making memories that will last a lifetime. Weddings of a significant size can budget anywhere between Rs 15 lakh and Rs 50 lakh specifically for photographs and videos that capture every moment.

But that might soon be changing thanks to Nvidia's RTX chips. These memories will be created at much lower prices and with higher quality at the same time. And there will be a significant improvement in the speed at which these pictures and videos can be managed. Big fat Indian weddings are becoming much less expensive thanks to graphics processing units (GPUs) made by Nvidia, the $3 trillion company whose semiconductor chips helped usher in the age of artificial intelligence (AI).

Six Indian custom computer makers are employing a variety of Nvidia chips known as RTX 40 to build systems capable of speeding up video editing using artificial intelligence. One of their primary target groups is studios that edit videos and photos from large weddings. 

“Imagine a wedding videographer covering three weddings in a day. They have thousands of images, videos from different kinds of angles and you have to combine all those things... We are talking about 1.8x performance improvement depending on what kind of GPUs (in the RTX range) you are using,” stated an Nvidia executive while demonstrating the editing chops of the chips in Delhi.

While the GPU giant's stock has risen in recent years, owing primarily to enterprise-grade AI chips such as the A100 and H100, which behemoths such as Microsoft-backed OpenAI and Meta have used to build their applications, the RTX 40 series was released in October 2022 and is being marketed as a chip that can assist gamers and content creators in leveraging AI in their studios and homes. 

What distinguishes RTX processors is their ability to do complicated calculations extremely quickly, particularly for giving realistic lighting, shadows, and reflections in videos. This makes the video more immersive since everything appears more lifelike and responds realistically to how you interact with it. Imagine having a powerful engine in a sports car that can manage high speeds and sharp curves with ease. Similarly, RTX chips can process large amounts of visual data and calculations without slowing down. 

According to a recent Jefferies analysis, India's wedding market is expected to have risen to $130 billion (approximately Rs 11 lakh crore), ranking second only to food and grocery in terms of consumption. The report underscores that the average Indian spends Rs 12 lakh, or around $15,000, on a wedding, which can often exceed the amount spent on 18 years of a child's education. 

This means that the average video editing cost for an Indian wedding is between Rs 30,000 and Rs 72,000, with some luxurious weddings costing up to Rs 20 lakh. By the same estimate, the entire wedding video editing industry might be worth up to Rs 66,000 crore.

“Now, a wedding videographer can say even though I was busy in three marriages, I will give you the videos on so and so date, and the guests who came can enjoy the memories at a time when it is fresh in their mind. And, it is infused with higher quality so that people can look better,” noted Vishal Dhupar, Nvidia South Asia.

“This technology isn't just for gamers; it also caters to creators and developers. Content creators, who once relied on costly workstations, now benefit from RTX studio workstations… This dynamic ecosystem features a thriving community of over 120 million creators. Together, we’re driving groundbreaking innovations that will redefine user experiences and elevate the industry to new heights,” Dhupar added.
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Technology
AI in education AI potential Artificial Intelligence boost productivity job loss Online Scams Technology

The Impact of AI on Society and Science

 

Nowadays, everyone is talking about artificial intelligence (AI). Governments view AI as both an opportunity and a challenge. Industries are excited about AI's potential to boost productivity, while academia is actively incorporating AI into teaching and research. However, the public is concerned about the negative aspects of AI. Job loss is a significant worry, as is the rise in online scams facilitated by AI. Many have fallen victim to cybercrime, and social media is increasingly plagued by AI-generated deepfakes.

The education sector is anxious about AI leading to more plagiarism and cheating in exams. Despite these concerns, one thing is certain: AI is here to stay. The world must manage it by mitigating the risks and harnessing the opportunities.

In a world where science and innovation create new possibilities, AI's impact on business is widely acknowledged. AI can enhance scientific systems in various ways, improving research and development, analysis, and collaboration. Key areas where AI can significantly impact have been identified.

Big data presents a new challenge for the world. Effective management and utilization of big data require reliable analytics. AI can process and analyze massive datasets much faster than humans, uncovering patterns and correlations that might otherwise be missed. This capability is essential in fields like genomics, climate science, and epidemiology. Machine learning models can predict outcomes and identify trends in scientific data, aiding scientists in making informed decisions and developing new hypotheses.

AI-driven robots and systems can perform repetitive experimental tasks, increasing efficiency and allowing scientists to focus on more complex aspects of their research. AI can automate data entry, curation, and management, reducing human error and freeing up researchers' time, thus enhancing research capabilities. AI can also scan and summarize vast amounts of scientific literature, helping researchers stay current with the latest developments and quickly find relevant information. Furthermore, AI can suggest new research directions and hypotheses based on existing data, potentially leading to innovative discoveries.

Many of the world's problems require interdisciplinary solutions. AI can facilitate collaboration between scientists from different disciplines and locations through advanced communication tools and platforms. Language algorithms can assist in writing and translating research papers, making scientific knowledge more accessible globally and supporting the open science agenda. AI can run complex simulations in fields like physics, chemistry, and biology, aiding in predicting experimental outcomes and better understanding complex systems. In medicine, AI models can simulate drug interactions with biological systems, accelerating the discovery of new medications.

With AI, precision medicine and personalized treatment are becoming a reality. AI can analyze genetic data to develop personalized treatment plans for patients, enhancing the effectiveness of medical treatments. AI-driven diagnostic tools can aid in the early detection and diagnosis of diseases, improving patient outcomes. By integrating AI into scientific systems, researchers can leverage these technologies to achieve faster, more accurate, and more innovative scientific discoveries.

A significant issue in scientific systems is the poor commercialization of R&D. Selecting research topics that efficiently link outputs with current and emerging market needs is crucial. AI can optimize the evaluation of R&D proposals to align with industry needs, overcoming the challenges of manual evaluation, such as poor market knowledge by academia and a lack of understanding of academic rigor by the industry.

Clearly, AI has much to offer in enhancing the productivity of scientific systems. The methods for achieving this should be the subject of more discourse and study among stakeholders. As science assumes a greater role in the global future, nations must enhance their scientific systems. Science is a significant investment, and AI can help realize better returns.
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Technology
Artificial Intelligence Cyberattacks CyberCrime Cyberhackers Cyberthreats Robotics South Korea Technology

Robot 'Suicide' in South Korea Raises Questions About AI Workload

 


At the bottom of a two-meter staircase in Gumi City Council, South Korea, a robot that worked for the city council was discovered unresponsive. There are those in the country who label the first robot to be built in the country as a suicide. According to the newspaper, a Daily Mail report claims that the incident occurred on the afternoon of June 20 around 4 pm. When the shattered robot was collected for analysis and sent to the company for examination, city council officials immediately contacted Bear Robotics, a California-based company, that made the robot. 

However, the reason behind the robot's erratic behaviour remains unknown. This robot, nicknamed "Robot Supervisor", was found piled up in a heap at the bottom of a stairwell between the first and second floors of the council building, where it was hidden from view. There were descriptions from witnesses that the robot behaved strangely, "circling in a certain area as if there was something there" before it fell to Earth untimely. It was one of the first robots in the city to be assigned this role in August 2023, with the robot being one of the first to accomplish this task. 

According to Bear Robotics, a startup company based out of California that develops robot waiters, the robot works from 9 am to 6 pm daily. Its civil service card validates its employment status. A difference between other robots and the Gumi City Council robot, which can call an elevator and move independently between different floors, is that the former can access multiple floors at the same time, whereas the latter cannot. 

Following the International Federation of Robotics (IFR), South Korea's industry boasts the highest robot density of any country in the world, with one industrial robot for every ten workers, making it one of the most robotic industries in the world. It has however been announced by the Gumi City Council that as a result of the recent incident, the city will not be adopting a second robot officer at present due to a lack of information. 

During the aftermath of the incident, there has been a debate in South Korea about how much work robots must do to function. Users are seeing a flurry of discussion on social media about what has been reported as a suicidal act by a robot, which has sparked debate about the pressures that humans experience at work. After the incident occurred, a major debate erupted as to how much burden the robot was supposed to handle. 

It has been employed since August 2023, a resident assistant called "Robot Supervisor" has been a very useful employee who can handle a wide range of tasks, from document delivery to assisting residents with their tasks. Following this unexpected event, there have been numerous discussions and focuses regarding the intense workload of this organization and the demands that are placed on it by these demands. South Korea has been taking an aggressive approach to automating society with its ambitious robot - a product developed by Bear Robotics, a California-based startup. 

Despite the large number of robots present in industrial settings in the county, this incident has sparked concern over the possibility that they will expand beyond factories and restaurants to serve a wider range of social functions as well. In the past few years, a growing number of companies have been investing in robots to take on roles beyond that of traditional workplaces, which has sparked public interest in this area. Various media outlets have been speculating about the outcome of the 2018 election, with a wide range of opinions and predictions. In a groundbreaking development, a robot's apparent act of self-destruction in South Korea has triggered profound contemplation and contentious discourse regarding the ethical and operational ramifications of employing robots for tasks traditionally undertaken by humans. 

The incident, believed by some to be a manifestation of excessive workload imposed on the machine, has prompted deliberations on the boundaries and responsibilities associated with integrating advanced technologies into daily life. Following careful consideration, the Gumi City Council has opted to suspend its initiatives aimed at expanding the use of robots. This decision, originating from a municipality renowned for its robust embrace of technological innovation, symbolizes a moment of introspection and critical reevaluation. 

It signifies a pivotal juncture in the ongoing dialogue about the role of automation and the deployment of artificial intelligence (AI) in contemporary societal frameworks. Undoubtedly tragic, the incident has nevertheless catalyzed substantive discussions and pivotal considerations about the future dynamics between robots and humanity. Stakeholders are now compelled to confront the broader implications of technological integration, emphasizing the imperative to navigate these advancements with conscientious regard for ethical, societal, and practical dimensions. The aftermath of this event serves as a poignant reminder of the imperative for vigilance and discernment in harnessing the potential of AI and robotics for the betterment of society.
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Healthcare
Artificial Intelligence Cyber Security Cyberattacks CyberCrime Digital Data Digital Transformation Healthcare

AI Accelerates Healthcare's Digital Transformation

 


Throughout the healthcare industry, CIOs are implementing technologies that allow precision diagnostics, reduce clinician workload, and automate back-office functions, from ambient documentation to machine learning-based scheduling. A lot of data is available in Penn Medicine BioBank, an institution run by the University of Pennsylvania Health System. A team led by Michael Restuccia's SVP and Chief Information Officer saw the opportunity to use this data for the benefit of patients at the research hospital. 

As a physician, professor, and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine, Charles Kahn says that understanding the characteristics of a population and how a particular individual differs from the rest allows the person to intervene earlier in the condition in question. This is a group of innovative healthcare companies that are pushing the envelope in the digitization of healthcare that has earned the CIO100 award over the past few years. Penn is just one example. The Stanford Medicine Children’s Health, the University of Miami Health System, as well as Atlantic Health have all begun working on precision medicine, machine learning, ambient documentation and other projects. 

From a clinical point of view, Bill Fera, MD, the principal who leads Deloitte Consulting’s AI practice, says that we’re witnessing a growing number of advances in radiology, diagnostic services, and pathology. It is very noteworthy that the AI-powered CT scan analysis system is one of the first systems to be implemented in clinical practice, partly because academic medical practices that conduct research can build and operate their own tools without the burden of obtaining FDA approval, which is what healthcare product manufacturers have to deal with. 

Although the system did not appear overnight, it took some time for it to come together. According to Donovan Reid, associate director of information services applications at Penn Medicine, it took at least two years for the algorithm to be ready for real-time deployment, and four years before the system finally became operational last year. "It took us hopefully two years to get it ready for actual deployment," he says. Due to the large amount of processing resources required, the team decided to host the algorithm in the cloud. 

As a result, the data was encrypted before it was sent to the cloud for processing, and the results were returned to the radiology report after the processing was completed. This was coordinated by the IT team, who developed an AI orchestrator that will be made available to other healthcare providers as a free software package. According to Penn professor Walter Witschey, the availability of this will be a great help for community service hospitals. 

A couple of challenges were faced by the team before the system was up and running. There was concern among IT regarding the impact of imaging data flows on infrastructure, and the amount of computing resources needed at any given time had to be matched to the amount of imaging studies being required. Additionally, the system would have to be able to provide results as soon as possible. It has been incredibly surprising to find out that the direct cost, outside of labor, is only about $700 per month. “Doctors want interpretation right away, not at 4 a.m.,” she says. 

Over 6,000 scans have already been processed through the system, and the team now plans to expand the application to accommodate more of the 1.5 million imaging scans that the hospital system performs on an annual basis.
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Virtual Reality
Artificial Intelligence Education Machine learning Technology Virtual Reality

Here's How Technology is Enhancing the Immersive Learning Experience

 

In the ever-changing environment of education, a seismic shift is taking place, with technology emerging as a change agent and disrupting conventional approaches to learning. Technology bridges the gap between theoretical knowledge and practical application, especially in the transformative realm of immersive technologies such as virtual reality (VR) and augmented reality (AR). These technologies give educators unparalleled possibilities for expanding learning experiences beyond the constraints of traditional textbooks and lectures. 

VR: A pathway to boundless exploration

Virtual reality (VR), previously considered a futuristic concept, is now a powerful force in education. It immerses students in computer-generated settings, promoting deep engagement and comprehension. VR integration in education is more than just a change; it is a revolution. From simulated field trips to historical recreations, the many applications of virtual reality in education allow students to delve into subjects like never before, discovering the world without leaving their seats. VR and AR can accommodate different learning styles. 

According to Deloitte, students who use immersive technologies are 30 times more likely to complete their schoolwork than their traditional counterparts. The rise of augmented reality (AR), virtual reality (VR), and other cutting-edge technology has considerably improved problem-solving abilities across multiple sectors. These immersive technologies promote inventive problem-solving approaches, allowing students to visualise complex situations and devise effective solutions in sectors such as engineering and design. 

A research published in the International Journal of Human-Computer Interaction states that incorporating immersive technologies into education improves critical thinking and problem-solving skills by giving students hands-on experience in simulated environments. 

The convergence of immersive technology goes beyond VR and AR. The introduction of these technologies aligns with a larger trend in industry recognition. According to Forbes, companies that use AR/VR see improved decision-making processes as a result of greater data visualisation and collaborative issue solving. In summary, the emergence of AR/VR, along with other sophisticated technologies, demonstrates its critical role in catalysing novel problem-solving approaches across varied sectors, hence increasing efficiency and understanding. 

Multiple sectors have begun to recognise the importance of AR and VR skills. The demand for employees with experience in these technologies is expanding. According to research by Burning Glass Technologies, job postings requiring VR skills surged by over 800% between 2014 and 2019. As we embrace the present, we must also consider the future. Predicting trends helps us plan for what comes next, keeping education at the forefront of technology breakthroughs.
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Technology
Artificial Intelligence Cyberattacks CyberCrime Cybersecuriyt CyberThreat New Updates Technology

AI vs. Developers: A Modern-Day Conundrum

 


According to many experts, large language models and artificial intelligence are dramatically simplifying the process of creating quality software, and this is a perspective that is being touted a lot. It has even been predicted that this trend could lead to software engineers becoming redundant in the future and simplified abstractions, including no-code solutions, handling all of our business problems. There is an overwhelming belief that artificial intelligence will destroy developers' jobs, but this is a fundamental misconception about the profession. 

It is generally thought that software developers are the ones who take specifications and turn them into code. That is true in a way, but the true purpose of a software developer lies far deeper than that. Many businesses are keen on integrating new applications for artificial intelligence into their products and services, regardless of their size. An employment survey conducted by Hired in March 2024 found that 56% of employers plan to incorporate or launch products using AI tools by the end of 2024. It is not surprising that AI provokes excitement, confusion, and fear in the same way that every technological advancement does. 

Software engineers is in a unique position as a result of the fact that they can create AI rather than just use it—they can build it. As the future of software engineering is set to begin, artificial intelligence is poised to change the way software engineers perform their duties, the skills required to excel as engineers will change, and what success in the technology industry will mean. The Hired CTO Dave Walters stated that Artificial Intelligence will be one of the biggest disruptors of software engineering in the future. 

By using AI to handle routine tasks and accelerate development, engineers will be able to focus on innovation while AI takes care of routine tasks. Even among those who warn about AI’s drawbacks, there is a consensus among the engineering community that AI is an invaluable tool that engineers can utilize. It is important to realize that artificial intelligence (AI) has the potential to boost productivity and efficiency in teams by streamlining workflows, speeding up prototyping, automating repetitive tasks, and even writing code. 

According to Walters, early adopters are using AI to generate standard code blocks that they optimize for their companies and organizations. Additionally, AI is an effective tool for creating documentation with less effort and interpreting data. A tool such as GitHub CoPilot, for instance, can offer developers suggestions in real time when they are working with boilerplate code blocks, which can be particularly helpful for those who work with them. 

Besides debugging AI tools, many tools can be used to assist with testing and debugging such as spotting common or recurrent issues in a code base, allowing software engineers to focus on the trickier areas of the codebase rather than on the mundane ones.  In addition to the practical uses of AI, the technology can also generate documents and sum up meetings in a simple and manageable way. In Peter Bell's view, and as he explains in the following video, AI has many applications that can be applied to a variety of industries and situations.

“It is not just about code generation (which is still of variable quality), but also helps you with thinking through your business challenges, creating requirements documentation, working with your team more efficiently, and creating documentation.” To clear the way for developers to perform more meaningful work, artificial intelligence can be used to remove key blocks to deeper and deeper understanding. The company TrueNorthCTO, founded by Bohdan Zabawskyj, has developed a tool that will allow the company's founder to take care of routine tasks more efficiently using AI tools such as Copilot, which has been developed by TrueNorthCTO. 

By doing this, they will be able to devote more time to solving larger problems and problems that are more complicated. There has been a trend in recent years for companies to develop more AI-based tools that will help their developers make their work even more effective, so they can make a bigger impact with their work." Naturally, every new technology comes with its risks, and AI is no different.” There has been a lot of talk about biases in artificial intelligence models trained on skewed data sets, and security and privacy concerns have been raised based on the processing and storage of information. 

The risks of artificial intelligence are acutely aware among even those who are optimistic about the technology. Taking special care to address and mitigate issues related to privacy and data security is essential for software engineers when approaching AI models and tools," indicates Zabawskyj, "and they must approach these issues with an understanding of their limitations.".  The Role of AI in Transforming Software Engineering: Opportunities and Challenges As AI technologies advance, their ability to process personal and sensitive data necessitates robust measures to safeguard this information and ensure adherence to relevant data protection laws and ethical guidelines. 

AI also raises important questions regarding ownership and accountability: if the code is written by AI, who owns it? Additionally, there are concerns about the potential for AI to generate false information. Zabawskyj explains, “AI systems, while sophisticated, can sometimes generate misleading or entirely fabricated information — a phenomenon known as ‘hallucinations.’ These inaccuracies can arise from biases in the training data or the model’s inability to understand context deeply.” For individual software engineers, the imperative for proactive, continuous learning is as crucial as ever. Even those not currently utilizing AI in their organizations can benefit from seeking opportunities to familiarize themselves with AI technologies. Creating internal channels for knowledge-sharing, where developers can exchange insights and learnings, is also valuable. 

There is no substitute for personal, hands-on experience. Bell encourages engineers to “try different models, learn about the strengths and weaknesses of generated code, and use large language models (LLMs) to become proficient in new languages and open-source software code bases.” Experimenting with AI in personal activities, such as cooking, exercising, playing guitar, or dating, can also help individuals learn how to prompt better and maximize the utility of AI models. To thrive in the AI-driven landscape, software engineers should not only focus on technical skills but also enhance their soft skills. Communication, problem-solving, and emotional intelligence will become increasingly critical. AI serves as a valuable tool for engineering teams, streamlining workflows, automating tasks, and assisting with debugging, ultimately enhancing efficiency and productivity. 

However, there are risks associated with biased models, privacy concerns, and the generation of false information, emphasizing the need for understanding AI's limitations and implementing robust safeguards. AI will reshape the role of software engineers, allowing more time for complex projects and shifting the focus towards model development and data analysis, with an increased emphasis on architectural knowledge and soft skills. Junior engineers will have opportunities to accelerate their learning and productivity, while senior engineers will focus on guiding AI integration and making complex decisions, leading to a transformation in job responsibilities. 

The impact of AI varies depending on business size, with smaller companies benefiting from increased efficiency and larger enterprises facing challenges integrating AI into existing systems and processes. As AI becomes more prevalent, software engineering specializations and skills are evolving, with a growing demand for roles like Machine Learning Engineers and an emphasis on soft skills such as critical thinking and communication. To build teams prepared for the AI age, tech leaders should seek candidates with emerging coding and soft skills, encourage experimentation with AI tools, and foster a culture of continuous learning and improvement. Employers should embed AI into company culture, provide AI tools and education access, and promote knowledge-sharing and experimentation among team members to facilitate upskilling. 

Individual software engineers should engage in continuous learning, gain hands-on experience with AI, and develop soft skills like communication and problem-solving to succeed in the age of AI. To thrive in this new era, both software engineers and engineering organizations must embrace continuous learning, adaptability, and evolution, focusing on problem-solving, design, and soft skills alongside technical expertise.
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Technology
Artificial Intelligence Data Storage IT Sector Security Framework Technology

Here's How to Solve Top Challenges in Data Storage

 

Data volumes are not only expanding, but also accelerating and diversifying. According to recent IDG research, data professionals state that data volumes are rising by 63 percent every month on average in their organisations. The majority of these organisations also collect data from 400 or more sources; 20% of respondents report having over 1,000 data sources. 

The result is an increasing demand for dependable, scalable storage. Companies want systems that can do more than just store data in an IT ecosystem informed by evolving compliance, agility, and sustainability requirements. Here are three of the most common data storage challenges, along with how suitable remedies can help. 

Top three challenges in data storage 

While more data opens up greater options for analytics and insight, the sheer volume of data collected and stored by companies creates issues. Three of the most major problems are security, complexity, and efficiency. 

Companies require storage security frameworks that prioritise cyber resilience, as cyberattacks are inevitable. According to Ben Jastrab, director of storage product marketing at Dell Technologies, “this is such a big topic, and such an important one. Every company in every industry is worried.”A zero-trust framework built on least privilege principles and advanced detecting technologies can assist businesses in identifying storage attacks and minimise the damage done. 

Storage faces additional challenges as complexity increases. IT teams can easily become complacent when it comes to purchasing, maintaining, and replacing physical hardware, as well as adopting, monitoring, and upgrading storage software. "Companies have more things to manage than ever," explains Jastrab. "To make the most of storage, they need to automate operations.” 

More data, less time. Higher expenses and lower costs. Higher demands and a smaller pool of skilled staff. These common challenges share a unifying thread: efficiency. Companies that can increase the efficiency of their storage solutions will be better prepared to manage the ever-changing storage landscape. 

Consider the recent data from the United States Energy Information Administration, which estimates that wholesale power rates would be 20% to 60% higher this winter than in 2022. As storage volumes grow, companies require a solution to cut physical footprints and energy costs.
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Threat Intelligence
AI Firms Artificial Intelligence Open AI Technology Threat Intelligence

Employees Claim OpenAI and Google DeepMind Are Hiding Dangers From the Public

 

A number of current and former OpenAI and Google DeepMind employees have claimed that AI businesses "possess substantial non-public data regarding the capabilities and limitations of their systems" that they cannot be expected to share voluntarily.

The claim was made in a widely publicised open letter in which the group emphasised what they called "serious risks" posed by AI. These risks include the entrenchment of existing inequities, manipulation and misinformation, and the loss of control over autonomous AI systems, which could lead to "human extinction." They bemoaned the absence of effective oversight and advocated for stronger whistleblower protections. 

The letter’s authors said they believe AI can bring unprecedented benefits to society and that the risks they highlighted can be reduced with the involvement of scientists, policymakers, and the general public. However, they said that AI companies have financial incentives to avoid effective oversight. 

Claiming that AI firms are aware of the risk levels of different kinds of harm and the adequacy of their protective measures, the group of employees stated that the companies have only weak requirements to communicate this information with governments "and none with civil society." They further stated that strict confidentiality agreements prevented them from publicly voicing their concerns. 

“Ordinary whistleblower protections are insufficient because they focus on illegal activity, whereas many of the risks we are concerned about are not yet regulated,” they wrote.

Vox revealed in May that former OpenAI employees are barred from criticising their former employer for the rest of their life. If they refuse to sign the agreement, they risk losing all of their vested stock gained while working for the company. OpenAI CEO Sam Altman later said on X that the standard exit paperwork would be altered.

In reaction to the open letter, an OpenAI representative told The New York Times that the company is proud of its track record of developing the most powerful and safe AI systems, as well as its scientific approach to risk management.

Such open letters are not uncommon in the field of artificial intelligence. Most famously, the Future of Life Institute published an open letter signed by Elon Musk and Steve Wozniak calling for a 6-month moratorium in AI development, which was disregarded.
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XDR Tools
Artificial Intelligence Cyber Security SOC Threat Intelligence XDR Tools

Invest in Future-Proofing Your Cybersecurity AI Plan

 

With the ongoing barrage of new attacks and emerging dangers, one might argue that every day is an exciting day in the security operations centre (SOC). However, today's SOC teams are experiencing one of the most compelling and transformative changes in how we detect and respond to cybersecurity threats. Innovative security organisations are attempting to modernise SOCs with extended detection and response (XDR) platforms that incorporate the most recent developments in artificial intelligence (AI) into the defensive effort. 

XDR systems combine security telemetry from several domains, such as identities, endpoints, software-as-a-service apps, email, and cloud workloads, to provide detection and response features in a single platform. As a result, security teams employing XDR have greater visibility across the company than ever before. But that's only half the tale. The combination of this unprecedented insight and an AI-powered SOC aid can allow security teams to operate at the pace required to turn the tables on potential attackers. 

Innovative security organisations need to have a strategic implementation plan that considers the future in order to effectively leverage today's AI capabilities and provide the foundation for tomorrow's breakthroughs. This is because the industry is evolving rapidly. 

XDR breadth matters 

Unlike traditional automated detection and blocking solutions, which frequently rely on a single indicator of compromise, XDR platforms employ AI to correlate cross-domain security signals that analyse a full attack and identify threats with high confidence. AI's greater fidelity improves the signal-to-noise ratio, resulting in fewer false positives for manual investigation and triage. Notably, the larger the dataset on which the AI is operating, the more effective it will be; therefore, XDR's inherent breadth is critical. 

An effective XDR strategy should identify and account for high-risk regions, cybersecurity maturity, modern architecture and technologies, and budgetary limits, among other things. While adoption should be gradual to minimise operational impact, organisations must also examine how to acquire the broadest XDR coverage possible in order to make the most of AI's capabilities. 

Create AI-Confident teams

The purpose of AI is not to replace humans in your SOC, but to enable them. If your team lacks faith in the tools they use they will be unable to fully realise the platform's potential. As previously noted, minimising false positives will help increase user trust over time, but it is also critical to provide operational transparency so that everyone understands where data is coming from and what actions have been taken. 

XDR platforms must provide SOC teams with complete control over investigating, remediating, and bringing assets back online when they are required. Tightly integrating threat detection and automatic attack disruption capabilities into existing workflows will speed up triage and provide a clear view of threats and remedial operations across the infrastructure. 

Stay vigilant 

The indicators of attack and compromise are continually evolving. An effective, long-term XDR plan will meet the ongoing requirement for rapid analysis and continuous vetting of the most recent threat intelligence. Implementation roadmaps should address how to facilitate the incorporation of timely threat intelligence and include flexibility to grow or augment teams when complex incidents demand additional expertise or support. 

As more organisations look to engage in XDR and AI to improve their security operations, taking a careful, future-focused approach to deployment will allow them to better use today's AI capabilities while also being prepared for tomorrow's breakthroughs. After all, successful organisations will not rely solely on artificial intelligence to stay ahead of attackers. They will plan AI investments to keep them relevant.
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Vulnerability management
Artificial Intelligence Cyber Security Deepfake Technology Threat Landscape Vulnerability management

Deepfakes and AI’s New Threat to Cyber Security

 

With its potential to manipulate reality, violate privacy, and facilitate crimes like fraud and character assassination, deepfake technology presents significant risks to celebrities, prominent individuals, and the general public. This article analyses recent incidents which bring such risks to light, stressing the importance of vigilance and preventative steps.

In an age where technology has advanced at an unprecedented rate, the introduction of deepfake technologies, such as stable diffusion software, presents a serious and concerning threat. This software, which was previously only available to trained experts, is now shockingly accessible to the general public, creating severe issues about privacy, security, and the integrity of digital content.

The alarming ease with which steady diffusion software can be downloaded and used has opened a Pandora's box of possible abuse. With a few clicks, anyone with basic technological knowledge can access these tools, which can generate hyper-realistic deepfakes. This programme, which employs sophisticated artificial intelligence algorithms, can modify photographs and videos to the point that the generated content appears astonishingly real, blurring the line between truth and deception. 

This ease of access significantly reduces the barrier to entry for developing deepfakes, democratising a technology that was previously only available to individuals with significant computational resources and technical experience. Anyone with a simple computer and internet access can now enjoy the benefits of dependable diffusion software. This development has significant ramifications for personal privacy and security. It raises serious concerns about the potential for abuse, particularly against prominent figures, celebrities, and high-net-worth individuals, who are frequently the target of such malicious activity. Rise in incidents 

Targeting different sectors 

Deepfakes: According to the World Economic Forum, the number of deepfake videos online has increased by an astonishing 900% every year. The surge in cases of harassment, revenge, and crypto frauds highlights an increasing threat to everyone, especially those in the public eye or with significant assets. 

Elon Musk impersonation: In one noteworthy case, scammers used a deepfake video of Elon Musk to promote a fraudulent cryptocurrency scheme, causing large financial losses for people misled by the hoax. This instance highlights the potential for deepfakes to be utilised in sophisticated financial crimes against naïve investors.

Targeting organisations: Deepfakes offer a significant threat to organisations, with reports of extortion, blackmail, and industrial espionage. A prominent case involves fraudsters tricking a bank manager in the UAE with a voice deepfake, resulting in a $35 million robbery. In another case, scammers used a deepfake to deceive Binance, a large cryptocurrency platform, during an online encounter.

Conclusion 

The incidents mentioned above highlight the critical need for safeguards against deepfake technology. This is where services like Loti come in, providing tools to detect and counteract unauthorised usage of a person's image or voice. Celebrities, high-net-worth individuals, and corporations use such safeguards to protect not only their privacy and reputation, but also against potential financial and emotional harm.

Finally, as deepfake technology evolves and presents new issues, proactive measures and increased knowledge can help reduce its risks. Companies like Loti provide a significant resource in this continuous battle, helping to maintain personal and professional integrity in the digital age.
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Technology
Artificial Intelligence CISO Hybrid Cloud Private Cloud Technology

AI Enables the Return of Private Cloud

 

Private cloud providers may be among the primary winners of today's generative AI gold rush, as CIOs are reconsidering private clouds, whether on-premises or hosted by a partner, after previously dismissing them in favour of public clouds. 

At the heart of this trend is a growing recognition that in order to handle AI workloads while keeping costs under control, organisations will eventually rely on a hybrid mix of public and private cloud. 

"With how fast things are changing in the data and cloud space, we believe in a hybrid model of cloud and data centre strategy," claims Jim Stathopoulos, SVP and CIO of Sun Country Airlines, who joined the regional airline from United Airlines in early 2023 and acquired a Microsoft Azure cloud infrastructure and Databricks AI platform, but is open to future IT decisions.

Controlling escalating cloud and AI expenses and minimising data leakage are the primary reasons why organisations are considering hybrid infrastructure as their AI solution. Most experts agree that most IT leaders will need to choose a hybrid approach that includes on-premises or co-located private clouds to provide cost control and data integrity in the face of AI's resource requirements and critical business concerns about its deployment. 

According to IDC's top cloud analyst, Dave McCarthy, private cloud platforms such as Dell APEX and HPE GreenLake, which provide generative AI capabilities, as well as co-locating with partners such as Equinix to host workloads in private clouds, could provide a solution to enterprise customers. 

“The excitement and related fears surrounding AI only reinforces the need for private clouds. Enterprises need to ensure that private corporate data does not find itself inside a public AI model,” McCarthy notes. “CIOs are working through how to leverage the most of what LLMs can provide in the public cloud while retaining sensitive data in private clouds that they control.” 

Generative AI changes the cloud calculus 

Somerset Capital Group is one company that has chosen to go private to run its ERP software and pave the path for generative AI. The Milford, Conn.-based financial services corporation moved data to the public cloud over a decade ago and will continue to add workloads, particularly for customer-centric apps. Somerset's EVP and CIO, Andrew Cotter, believes that the company's important data, as well as any future generative AI data, will most likely run on its new hosted private cloud. 

"As we are testing and dipping our toes in the water with AI, we are choosing to keep that as private as possible," he says, noting that while the public cloud provides the horsepower needed for many LLMs today, his firm has the option of adding GPUs if needed via its privately owned Dell equipment. "You don't want to make a mistake and have it ingested or used in another model. We're maintaining tight control and storing it in the private cloud." 

Todd Scott, senior vice president of Kyndryl US, recognises that AI and cost are important drivers driving organisations to private clouds. 

Buying into the private cloud

Analysts believe that private cloud spending is on rise. According to Forrester's Infrastructure Cloud Survey in 2023, 79% of the almost 1,300 enterprise cloud decision-makers polled claimed their companies are developing internal private clouds that will include virtualization and private cloud management. Over a third (31%) of respondents are creating internal private clouds employing hybrid cloud management technologies such as software-defined storage and API-consistent hardware to make the private cloud more similar to the public cloud, Forrester added.

IDC predicts that global spending on private, dedicated cloud services, which comprise hosted private cloud and dedicated cloud infrastructure as a service, would reach $20.4 billion in 2024 and more than double by 2027. According to IDC, global spending on enterprise private cloud infrastructure, which includes hardware, software, and support services, will reach $51.8 billion in 2024 and $66.4 billion in 2027. 

While those figures pale in comparison to the public cloud's projected $815.7 billion in 2024, IDC's McCarthy views hybrid cloud architecture as the future for most organisations in this space. According to McCarthy, the introduction of turnkey private cloud products from HPE and Dell provides customers with a private cloud that can be run on-premises or in a co-location facility that offers managed services. Private clouds may also help organisations better control their overall cloud costs, but he emphasises that both have benefits as well as drawbacks. 

“Enterprises are in a bit of a pickle with this,” McCarthy added. “Security concerns are what is driving them to private cloud, but the specialised hardware required to do large-scale AI is expensive and requires extensive power and cooling. This is a problem that companies like Equinix believe they can help solve, by allowing enterprises to build a private cloud in Equinix datacenters that are already equipped to handle this type of infrastructure.”
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Technology
AI Image Generator Artificial Intelligence data security Multi Layer Security Technology

Invoke AI Introduces Refined Control Features for Image Generation

 

Invoke AI has added two novel features to its AI-based image generation platform. According to the company, two new features—the Model Trainer and Control Layers—provide some of the most refined controls in image generation. Both apps provide users granular control over how AI develops and changes their photographs. Invoke also stated that it has achieved SOC 2 certification, which means that the company has completed multiple tests that demonstrate a high level of data security. 

Invoke CEO Kent Keirsey spoke with GamesBeat, a local media outlet, regarding the platform's new features, which provide greater control and customisation over an image. The customised Model Trainer enables a company to train custom image generating models using as few as twelve pieces of its own content. According to Keirsey, this results in more consistent graphics that are congruent with a developer's IP, allowing the AI to create art with the same style and design features more frequently. 

“We’re helping the models understand what we mean when we use a certain language,” stated Keirsey. “When we get specific and say we want this specific interpretation, what that means is we need anywhere from 10-20 images of this idea, this style we want to train… We’re saying, ‘Here’s our studio’s style with different subjects.’ You might do that for a general art style. You might do it for a certain intellectual property.” 

According to Invoke, one of its goals is to provide increased security, which explains the SOC 2 compliance. Enhanced safety minimises the possibility that a developer's images will be exploited to help create another studio's intellectual property. 

How to Train Your AI 

Keirsey presented the second feature, Control Layers, which allows users to segment an image and assign prompts to certain sections. For example, a user can use the layer tool to paint the upper corner of an image and then instruct the AI to place a celestial body in that exact location. It enables creators to change the composition of their image and alter individual elements without impacting the whole image. 

Each layer's cues can be refined and generated as any other AI image. However, the effects are limited to a specific part of the image. Control Layers also allows users to submit images to specific layers, and the creator can specify what elements of the image the AI should maintain - style, composition, colour, and so on. Regarding how Invoke's new tools can be integrated into the game development workflow, Keirsey stated that most developers are cautious about the usage of AI, owing to copyright concerns. 

“The human concept has to be there — a human sketch, a human initial idea. That will go to the point where you draw the line saying, ‘None of this is gonna go in the game yet. Until we can prove that we can get copyright, we’re not willing to risk it.’ The moment that you can get copyright, you’ll start to see that make its way into games… That’s why Invoke is trying to answer that for organizations, demonstrating human expression, giving them more ways to exhibit that, so that we can demonstrate copyright and accelerate that process,” Keirsey stated.
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Video Games
Artificial Intelligence BBC CyberCrime Cybersecurity Microsoft Technology Video Games

AI Takes the Controller: Revolutionizing Computer Games

 


The computer games industry has been a part of Andrew Maximov's life for 12 years and despite all of this experience, he still marvels at how much money it costs to build some of the biggest games of all time. According to him, artificial intelligence (AI) will be crucial to reducing the soaring cost of video game production and saving video game designers precious time by automating repetitive tasks. 

In addition to providing developers with a set of tools to construct their virtual worlds, Promethean AI offers developers an array of tools. To disrupt the way games are produced today, Mr Maximov hopes to make a tremendous impact. Likely, humans will still play a crucial role in the production process. In the future, artificial intelligence will allow humans to be more creative. 

Californian software company Inworld is also using artificial intelligence to create computer games. This company has developed a game engine that is designed to enhance the realism and emotional depth of game worlds and characters by using the engine. Additionally, the firm is developing a narrative graph that it has partnered with Microsoft, which will make it easier for storytellers to build their characters, which will utilize artificial intelligence. 

In an interview with the BBC, chief executive Kylan Gibbs stated his belief that artificial intelligence would allow developers to dream bigger than they ever had in the past. "In this engine, developers can use artificial intelligence agents that are capable of seeing, sensing, and understanding the world around them, as well as interacting with players and taking actions within the game. It opens up a whole new paradigm for storytelling and gameplay when users can infuse virtual characters with advanced cognitive abilities," he explains. 

 The chief executive of Latitude.io is Nick Walton, who believes artificial intelligence has the potential to personalize the gaming experience in several ways. During his time as CEO of his firm, he said that he was surprised by the huge success of AI Dungeon, a game that allowed players to create their own stories in a variety of worlds. He was pleasantly surprised by how successful the first version of Dungeon was.
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User Security
Artificial Intelligence ChatGPT Technology Threat Intelligence User Security

Is ChatGPT Secure? Risks, Data Safety, and Chatbot Privacy Explained

 

You've employed ChatGPT to make your life easier when drafting an essay or doing research. Indeed, the chatbot's ability to accept massive volumes of data, break down it in seconds, and answer in natural language is incredibly valuable. But does convenience come at a cost, and can you rely on ChatGPT to safeguard your secrets? It's a significant topic to ask because many of us lose our guard around chatbots and computers in general. So, in this article, we will ask and answer a simple question: Is ChatGPT safe?

Is ChatGPT safe to use?

Yes, ChatGPT is safe because it will not bring any direct harm to you or your laptop. Sandboxing is a safety system used by both online browsers and smartphone operating systems, such as iOS. This means ChatGPT can't access the rest of your device. You don't have to worry about your system being hacked or infected with malware when you use the official ChatGPT app or website. 

Having said that, ChatGPT has the potential to be harmful in other ways, such as privacy and secrecy. We'll go into more detail about this in the next section, but for now, remember that your conversations with the chatbot aren't private, even if they only surface when you log into your account. 

The final aspect of safety worth analysing is the overall existence of ChatGPT. Several IT giants have criticised modern chatbots and their developers for aggressively advancing without contemplating the potential risks of AI. Computers can now replicate human speech and creativity so perfectly that it's nearly impossible to tell the difference. For example, AI image generators may already generate deceptive visuals that have the potential to instigate violence and political unrest. Does this imply that you shouldn't use ChatGPT? Not necessarily, but it's an unsettling insight into what the future may hold. 

How to safely use ChatGPT

Even though OpenAI claims to store user data on American soil, we can't presume their systems are secure. We've seen higher-profile organisations suffer security breaches, regardless of their location or affiliations. So, how can you use ChatGPT safely? We've compiled a short list of tips: 

Don't share any private information that you don't want the world to know about. This includes trade secrets, proprietary code from the company for which you work, credit card data, and addresses. Some organisations, like Samsung, have prohibited their staff from using the chatbot for this reason. 

Avoid using third-party apps and instead download the official ChatGPT app from the App Store or Play Store. Alternatively, you can access the chatbot through a web browser. 

If you do not want OpenAI to utilise your talks for training, you may turn off data collection by toggling a toggle in Settings > Data controls > Improve the model for everyone. 

Set a strong password for your OpenAI account so that others cannot see your ChatGPT chat history. Periodically delete your conversation history. In this manner, even if someone tries to break into your account, they will be unable to view any of your previous chats.

Assuming you follow these guidelines, you should not be concerned about utilising ChatGPT to assist with everyday, tedious tasks. After all, the chatbot enjoys the backing of major industry companies such as Microsoft, and its core language model supports competing chatbots such as Microsoft Copilot.
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