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By Kyle Anthony, Benzinga
The proliferation of AI tools in recent years has been remarkable, with individuals' willingness to use them seemingly being the only thing keeping pace with their rapid development. But with millions of individuals using AI chatbots that can record a single user’s notes on any topic and then summarize that information or search for more details, the natural question that comes to mind is, how secure is the information being stored and used?
Rising Cybersecurity Concerns With AI
The success of ChatGPT and its adoption by the masses has been noteworthy, with the platform receiving 152 million visitors in its first month of being launched. At its peak in April 2024, the site received nearly 2 billion monthly visits. However, the platform’s growth has also welcomed threat actors who have identified vulnerabilities. Last year, a notable one was identified in ChatGPT’s Redis open-source library, allowing users to see other active users' chat history. OpenAI uses Redis to cache user information for faster recall and access. Because thousands of contributors develop and access open-source code, it’s easy for vulnerabilities to open up and go unnoticed. Threat actors know this, hence why attacks on open-source libraries have materially increased in recent years, with a reported overall increase of 742% since 2019.
A cornerstone of ChatGPT’s development is cloud computing, as it accelerates research & development innovation. However, a person acting with malicious intent can gather information from ChatGPT that they can later use for harm. Since the chatbot has been trained on copious amounts of data, it possesses a lot of information that could potentially be weaponized by threat actors. Recognizing the potential risks of ChatGPT, the Cloud Security Alliance (CSA), the world’s leading organization dedicated to defining and raising awareness of best practices to help ensure a secure cloud computing environment, released a whitepaper entitled Security Implications of ChatGPT that provides guidance across four dimensions of concern around this extremely popular large language model (LLM). The CSA has also called for public collaboration in developing an artificial intelligence roadmap for this next frontier in cybersecurity and cloud computing.
For companies developing their own LLMs using their proprietary dataset, on-premises data storage is preferable for many use cases. Though cloud storage has grown in popularity lately, some companies still believe that on-premises solutions or private clouds are best suited for their mission-critical business needs. For example, many value the greater security and control that on-premises solutions and storage give their data.
Taking A Differentiated Approach With iLearningEngines
iLearningEngines (NASDAQ: AILE) (iLE) has built this security approach and options for data security and control into its approach, and believes that this is one of the key drivers for their success in the market.
iLE is an applied AI platform that empowers its enterprise and education customers to “productize” their institutional knowledge, improve efficiency and drive better mission-critical business outcomes. The company operates at the intersection of three large and growing markets: global artificial intelligence, global e-learning and hyper-automation.
iLE's differentiation in the market is rooted in its proprietary AI technology and specialized data sets, thus avoiding the pitfall of open-source libraries. First, the company builds a secure Knowledge Cloud – an enterprise “brain” made up of specialized datasets – within a customer’s data environment. Then, it employs its no-code AI canvas, enabling rapid integration without custom programming. This enables iLE’s cognitive AI engine to generate insights, events and recommendations across many use cases. Employees use these valuable insights to close knowledge gaps, automate workflows and improve business outcomes.
From a security perspective, iLE recognizes the imperative of integrating transparency, human oversight, fairness and other ethical considerations into AI development and deployment. It believes that taking such an approach allows businesses to foster trust, navigate risks effectively and unlock the full potential of AI. The company also deploys private cloud storage, which is ideal for industries like banking, finance and healthcare, where data security and compliance are paramount.
iLE's commitment is backed by a comprehensive and advanced framework. The company says that this framework ensures transparency and explainability, robust security, safety and unwavering adherence to human-centered values and fairness in the applied AI platform. This commitment is not static but a living reality, constantly refined by iLE through ongoing interactions with its clients.
A Pathway Forward
AI is rapidly transforming the global landscape in many ways, but it should not come at the expense of information security as it opens up higher productivity levels. AI-powered tools automate tasks, streamline processes and replicate human-like understanding, reasoning and decision-making. However, to fully harness this potential, businesses must address challenges like data quality, privacy and siloed enterprise systems and bring machine cognition and comprehension with AI. iLE’s applied AI platform enables organizations to do this by creating AI Engines on the platform, utilizing specialized data sets with a focus on security.
Featured photo by Markus Spiske on Unsplash.
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