Big Data Management
Microsoft | September 22, 2023
AI models rely heavily on vast data volumes for their functionality, thus increasing risks associated with mishandling data in AI projects.
Microsoft's AI research team accidentally exposed 38 terabytes of private data on GitHub.
Many companies feel compelled to adopt generative AI but lack the expertise to do so effectively.
Artificial intelligence (AI) models are renowned for their enormous appetite for data, making them among the most data-intensive computing platforms in existence. While AI holds the potential to revolutionize the world, it is utterly dependent on the availability and ingestion of vast volumes of data.
An alarming incident involving Microsoft's AI research team recently highlighted the immense data exposure risks inherent in this technology. The team inadvertently exposed a staggering 38 terabytes of private data when publishing open-source AI training data on the cloud-based code hosting platform GitHub. This exposed data included a complete backup of two Microsoft employees' workstations, containing highly sensitive personal information such as private keys, passwords to internal Microsoft services, and over 30,000 messages from 359 Microsoft employees. The exposure was a result of an accidental configuration, which granted "full control" access instead of "read-only" permissions. This oversight meant that potential attackers could not only view the exposed files but also manipulate, overwrite, or delete them.
Although a crisis was narrowly averted in this instance, it serves as a glaring example of the new risks organizations face as they integrate AI more extensively into their operations. With staff engineers increasingly handling vast amounts of specialized and sensitive data to train AI models, it is imperative for companies to establish robust governance policies and educational safeguards to mitigate security risks.
Training specialized AI models necessitates specialized data. As organizations of all sizes embrace the advantages AI offers in their day-to-day workflows, IT, data, and security teams must grasp the inherent exposure risks associated with each stage of the AI development process. Open data sharing plays a critical role in AI training, with researchers gathering and disseminating extensive amounts of both external and internal data to build the necessary training datasets for their AI models. However, the more data that is shared, the greater the risk if it is not handled correctly, as evidenced by the Microsoft incident. AI, in many ways, challenges an organization's internal corporate policies like no other technology has done before. To harness AI tools effectively and securely, businesses must first establish a robust data infrastructure to avoid the fundamental pitfalls of AI.
Securing the future of AI requires a nuanced approach. Despite concerns about AI's potential risks, organizations should be more concerned about the quality of AI software than the technology turning rogue.
PYMNTS Intelligence's research indicates that many companies are uncertain about their readiness for generative AI but still feel compelled to adopt it. A substantial 62% of surveyed executives believe their companies lack the expertise to harness the technology effectively, according to 'Understanding the Future of Generative AI,' a collaboration between PYMNTS and AI-ID.
The rapid advancement of computing power and cloud storage infrastructure has reshaped the business landscape, setting the stage for data-driven innovations like AI to revolutionize business processes. While tech giants or well-funded startups primarily produce today's AI models, computing power costs are continually decreasing. In a few years, AI models may become so advanced that everyday consumers can run them on personal devices at home, akin to today's cutting-edge platforms. This juncture signifies a tipping point, where the ever-increasing zettabytes of proprietary data produced each year must be addressed promptly. If not, the risks associated with future innovations will scale up in sync with their capabilities.
Business Wire | September 29, 2023
Radiant Logic, the Identity Data Fabric company, today announces the completed integration of Brainwave GRC following the April 2023 acquisition. These new capabilities solidify Radiant Logic’s entrance in the Identity Analytics market and position our platform in the Identity Governance and Administration market, as seen in the recent Gartner® Market Guide for IGA. With a new website launching today and the release of the full RadiantOne Identity Data Platform, including Identity Analytics, the company celebrates the final integration of Brainwave into Radiant Logic.
Radiant Logic, the longtime leader in Identity Data Management, enters the field of Identity Analytics with unprecedented capabilities including Observability, Governance, and Compliance. With 90% of organizations experiencing at least one identity-related breach in the past year, according to the Identity Defined Security Alliance (IDSA), organizations are realizing the essential role of identity data quality and visibility within cybersecurity and overall IT operational maturity best practices.
Identity data is the lifeblood for all access decisions, and must be made accessible as the authoritative source for all authentication, authorization, and administration engines. In a recent research note, Gartner recommends that organizations: “Accelerate IAM data improvements for their IAM program by increasing the priority of visibility/observability improvements, including applying the visibility, intelligence, action model to program prioritization decisions."
The new release from Radiant Logic represents a major step forward in the ability to use identity data management and identity analytics in cybersecurity and governance practices. Access to the right identity data, at the right time, is critical for any IAM tool, process, or policy. Visibility into all identity data and infrastructure gives clear insight into who has access to what and uncovers outliers and over-privileged access, which helps identify and close security gaps. It’s a powerful combination for any organization.
We’re thrilled to announce the full integration of Radiant Logic and Brainwave GRC as one company, one website, and one platform. The new RadiantOne Identity Data Platform will strengthen operational maturity for customers, improve regulatory compliance and audit responses, and enable data-driven security best practices, said John Pritchard, Chief Product Officer, Radiant Logic. We are only seeing the tip of the iceberg regarding the potential for leveraging data science and artificial intelligence in IAM, and we believe that by pairing vast amounts of identity data with analytical inferencing, the possibilities for innovation are endless.
With the new capabilities from RadiantOne, identity data can be supplied in a flexible and automated way, allowing organizations to base their security and policy decisions on the most accurate and complete data available. The addition of Identity Analytics brings visibility and intuitive visualization techniques, allowing organizations to use comprehensive identity data to find anomalies, add risk scores, easily respond to audits, and improve their overall security posture.
Complete documentation is now available on the Radiant Logic developer portal, the support function is integrated via the customer support portal, and the full platform will be available as an integrated SaaS offering in Q4. The integrated platform combining Identity Data Management and Identity Analytics capabilities will accelerate Zero Trust projects, enable digital transformation, and simplify audit and compliance. Visit our new website at www.radiantlogic.com to learn more.
About Radiant Logic
Radiant Logic, the identity data experts, helps organizations turn identity data into a strategic asset that drives automated governance, enhanced security, and operational efficiency.
Our RadiantOne Identity Data Platform removes complexity as a roadblock to identity-first strategies by creating an authoritative data source for real-time, context-aware controls. We provide visibility and actionable insights to intelligently detect and remediate risk using AI/ML-powered identity analytics.
With RadiantOne, organizations are able to tap into the wealth of information across the infrastructure, combining context and analytics to deploy governance that works for the most advanced use cases.
Oracle | September 20, 2023
Oracle introduces AI Vector Search, enabling semantic search and fast similarity queries by storing semantic content as vectors.
Oracle Database 23c, "App Simple," streamlines interactions by declaring outcomes, incorporating AI Vector Search, and offering natural language interfaces.
RAG combines large language models (LLMs) with private business data for precise responses to natural language queries while maintaining data privacy.
Oracle has announced a significant enhancement to its Oracle Database 23c, introducing semantic search capabilities powered by AI vectors. This innovative collection of features, dubbed AI Vector Search, encompasses a suite of functionalities, including a novel vector data type, vector indexes, and SQL operators. This empowers Oracle Database to store semantic content from various sources, such as documents and images, as vectors and use them to run fast similarity queries.
Notably, these advancements also facilitate Retrieval Augmented Generation (RAG), a groundbreaking generative AI technique. RAG combines large language models (LLMs) with private business data to deliver precise responses to natural language queries. Importantly, this approach maintains data privacy by excluding sensitive information from LLM training data.
Furthermore, Oracle will enable applications built on Oracle Database and Autonomous Database to add an LLM-based natural language interface. Thus allowing end-users to gain a simplified and intuitive way to request the data they need by framing natural language questions. Additionally, Oracle Database tools such as APEX and SQL Developer will receive enhancements with generative AI capabilities, empowering developers to use natural language for creating applications and SQL queries with ease, eliminating the need for manual coding.
Oracle Database 23c, codenamed "App Simple," simplifies the way data professionals, developers, and data users interact with data by stating their desired outcomes rather than hand coding. Data systems will generate solutions using new database technologies such as JSON Relational Duality Views and AI Vector Search with new natural language interface capabilities. Additionally, by merging these technologies with Oracle's low-code APEX development framework, developers will be able to create complete apps. This method represents the future of data and application development and will offer huge productivity increases.
Juan Loaiza, Executive Vice President of Mission-Critical Database Technologies, Oracle, stated:
Oracle Database is the leading repository of business data, and the combination of business data and semantic data is what enterprises need to implement artificial intelligence solutions,
[Source – Cision PR Newswire]
Searches on a combination of business and semantic data became easier, faster, and more precise when a single database managed both types of data, stated Loaiza.
He further explained that by adding AI Vector Search to Oracle Database, Oracle enables customers to quickly and easily access the benefits of artificial intelligence without compromising security, data integrity, or performance. He emphasized that using Oracle AI Vector Search does not require machine learning expertise and that all database users, including developers and administrators, could learn to use it in less than 30 minutes.
The latest updates to Oracle Database services and products include:
Modern Oracle Database and AI Application Development
Oracle Autonomous Database
GoldenGate 23c Free
Oracle Autonomous Database Free Container Image
Next-generation Oracle Database Product and Services
Oracle Database 23c
Oracle Globally Distributed Autonomous Database
Oracle Exadata Exascale
Autonomous Database Elastic Resource Pools
Trusted Data Fabric for AI
Oracle GoldenGate Veridata 23c (Beta)
Oracle Database Appliance X10
Oracle Database infrastructure for small and medium businesses