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IBM Guardium Data Security Posture Management (DSPM is a comprehensive solution designed to help organizations discover, classify, and secure sensitive data across cloud and SaaS environments. By leveraging advanced AI-powered data discovery and classification, DSPM enables businesses to identify and protect their data assets efficiently, mitigating risks associated with data sprawl, unauthorized access, and compliance violations. Its agentless deployment ensures rapid implementation without the need for prior knowledge of data locations or credentials. Key Features and Functionality: - Automated AI-Powered Data Discovery and Classification: Continuously identifies sensitive data across cloud environments, including hidden "shadow data," without requiring prior knowledge of data locations or passwords. - Risk and Vulnerability Mitigation: Proactively detects and prevents data leakage between accounts and environments, identifies and remediates exposed secrets, and offers ransomware vulnerability detection through data flow analysis and access intelligence. - Third-Party Data Access Monitoring: Provides comprehensive visibility into third-party data access, streamlining vendor assessments, detecting anomalies, and assessing potential impacts of data breaches to ensure compliance and protect against unauthorized access. - Compliance and Privacy Assurance: Ensures adherence to regulatory requirements concerning data privacy by continuously monitoring data access, enforcing security policies, and generating audit reports, thereby reducing the risk of costly data breaches and protecting brand reputation. Primary Value and Problem Solved: IBM Guardium DSPM addresses the challenges posed by increasing data volumes and dispersion in modern cloud and SaaS environments. By automating the discovery and classification of sensitive data, it reduces the risk of data leaks, breaches, and unauthorized access. The solution enhances compliance with data privacy regulations, optimizes resource utilization, and strengthens overall data security posture, enabling organizations to protect their sensitive information effectively and maintain trust with stakeholders.
Deep learning frameworks such as TensorFlow, PyTorch, Caffe, Torch, Theano, and MXNet have contributed to the popularity of deep learning by reducing the effort and skills needed to design, train, and use deep learning models. Fabric for Deep Learning (FfDL, pronounced “fiddle”) provides a consistent way to run these deep-learning frameworks as a service on Kubernetes.
IBM Spectrum Conductor Deep Learning Impact is add-on software to IBM Spectrum Conductor. It enables you to build a deep learning environment that allows data scientists to focus on training, tuning and deploying models into production. Quickly get started working your data for deep learning, avoid highly manual and repetitive steps and bypass the need for specialized domain knowledge. The solution deploys with simple software downloads that give data scientists everything they need to build a distributed deep learning environment in hours rather than days or weeks—and easily manage it as the environment grows.
Bi-directionally service-enable Natural applications by providing or calling services in Java, .NET, Web services and Software AG's Digital Business Platform. Read more
IBM Managed Security Services offer the industry-leading tools, technology and expertise to help secure your information assets around the clock, often at a fraction of the cost of in-house security resources. IBM Security Operations Center Portal, a single window into your entire security world, is included in every managed security service.
Optimize the runtime of open source technologies, including Apache Spark, Anaconda and Python, and gain insights from data at its source.
Granite-4.0-Tiny-Preview is a 7-billion-parameter fine-grained hybrid mixture-of-experts (MoE) instruction-following model developed by IBM's Granite Team. Fine-tuned from the Granite-4.0-Tiny-Base-Preview, it utilizes a combination of open-source instruction datasets and internally generated synthetic data to address long-context problems. The model employs techniques such as supervised fine-tuning and reinforcement learning-based alignment to enhance its performance in structured chat formats. Key Features and Functionality: - Multilingual Support: Handles tasks in English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese. - Versatile Capabilities: Excels in summarization, text classification, extraction, question-answering, retrieval-augmented generation (RAG), code-related tasks, function-calling, multilingual dialogues, and long-context tasks like document summarization and question-answering. - Advanced Training Techniques: Incorporates supervised fine-tuning and reinforcement learning for improved instruction adherence and tool-calling capabilities. Primary Value and User Solutions: Granite-4.0-Tiny-Preview is designed to handle general instruction-following tasks and can be integrated into AI assistants across various domains, including business applications. Its multilingual support and advanced capabilities make it a valuable tool for developers seeking to build sophisticated AI solutions.
Enables handheld visual inspections using IBM Model Builder or IBM Maximo Visual Inspection to run Core ML models on iPhone or iPad.
Firewalls and security groups are important in securing your cloud environment and the information stored in it, as well as preventing malicious activity from reaching your servers or users.
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