Fraud in financial services is a massive problem. According to NASDAQ, in 2023, banks faced $442 billion in projected losses from payments, checks, and credit card fraud. It’s not just about the money, though. Fraud can tarnish a company’s reputation and frustrate customers when legitimate purchases are blocked. This is called a false positive. Unfortunately, these errors happen more often than…
]]>Addressing software security issues is becoming more challenging as the number of vulnerabilities reported in the CVE database continues to grow at an accelerated pace. Assessing a single container for vulnerabilities requires the collection, comprehension, and synthesis of hundreds of pieces of information. With over 200K vulnerabilities reported at the end of 2023, the traditional approach to…
]]>Modern cyber threats have grown increasingly sophisticated, posing significant risks to federal agencies and critical infrastructure. According to Deloitte, cybersecurity is the top priority for governments and public sectors, highlighting the need to adapt to an increasingly digital world for efficiency and speed. Threat examples include insider threats, supply chain vulnerabilities…
]]>Generative AI is transforming computing, paving new avenues for humans to interact with computers in natural, intuitive ways. For enterprises, the prospect of generative AI is vast. Businesses can tap into their rich datasets to streamline time-consuming tasks—from text summarization and translation to insight prediction and content generation. But they must also navigate adoption challenges.
]]>Enterprises are using large language models (LLMs) as powerful tools to improve operational efficiency and drive innovation. NVIDIA NeMo microservices aim to make building and deploying models more accessible to enterprises. An important step for building any LLM system is to curate the dataset of tokens to be used for training or customizing the model. However, curating a suitable dataset…
]]>Across the globe, enterprises are realizing the benefits of generative AI models. They are racing to adopt these models in various applications, such as chatbots, virtual assistants, coding copilots, and more. While general-purpose models work well for simple tasks, they underperform when it comes to catering to the unique needs of various industries. Custom generative AI models outperform…
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