Big Data Management
Kinetica | September 22, 2023
Kinetica, a renowned speed layer for generative AI and real-time analytics, has recently unveiled a native Large Language Model (LLM) integrated with Kinetica's innovative architecture. This empowers users to perform ad-hoc data analysis on real-time, structured data with the ease of natural language, all without the need for external API calls and without data ever leaving the secure confines of the customer's environment. This significant milestone follows Kinetica's prior innovation as the first analytic database to integrate with OpenAI.
Amid the LLM fervor, enterprises and government agencies are actively seeking inventive ways to automate various business functions while safeguarding sensitive information that could be exposed through fine-tuning or prompt augmentation. Public LLMs, exemplified by OpenAI's GPT 3.5, raise valid concerns regarding privacy and security. These concerns are effectively mitigated through native offerings, seamlessly integrated into the Kinetica deployment, and securely nestled within the customer's network perimeter.
Beyond its superior security features, Kinetica's native LLM is finely tuned to the syntax and industry-specific data definitions, spanning domains such as telecommunications, automotive, financial services, logistics, and more. This tailored approach ensures the generation of more reliable and precise SQL queries. Notably, this capability extends beyond conventional SQL, enabling efficient handling of intricate tasks essential for enhanced decision-making capabilities, particularly for time-series, graph, and spatial inquiries. Kinetica's approach to fine-tuning places emphasis on optimizing SQL generation to deliver consistent and accurate results, in stark contrast to more conventional methods that prioritize creativity but yield diverse and unpredictable responses. This steadfast commitment to reliable SQL query outcomes offers businesses and users the peace of mind they deserve.
Illustrating the practical impact of this innovation, the US Air Force has been collaborating closely with Kinetica to leverage advanced analytics on sensor data, enabling swift identification and response to potential threats. This partnership contributes significantly to the safety and security of the national airspace system. The US Air Force now employs Kinetica's embedded LLM to detect airspace threats and anomalies using natural language.
Kinetica's database excels in converting natural language queries into SQL, delivering responses in mere seconds, even when faced with complex or unfamiliar questions. Furthermore, Kinetica seamlessly combines various analytics modes, including time series, spatial, graph, and machine learning, thereby expanding the range of queries it can effectively address. What truly enables Kinetica to excel in conversational query processing is its ingenious use of native vectorization. In a vectorized query engine, data is organized into fixed-size blocks called vectors, enabling parallel query operations on these vectors. This stands in contrast to traditional approaches that process individual data elements sequentially. The result is significantly accelerated query execution, all within a smaller compute footprint. This remarkable speed is made possible by the utilization of GPUs and the latest CPU advancements, which enable simultaneous calculations on multiple data elements, thereby greatly enhancing the processing speed of computation-intensive tasks across multiple cores or threads.
About Kinetica
Kinetica is a pioneering company at the forefront of real-time analytics and is the creator of the groundbreaking real-time analytical database specially designed for sensor and machine data. The company offers native vectorized analytics capabilities in the fields of generative AI, spatial analysis, time-series modeling, and graph processing. A distinguished array of the world's largest enterprises spanning diverse sectors, including the public sector, financial services, telecommunications, energy, healthcare, retail, and automotive industries, entrusts Kinetica to forge novel solutions in the realms of time-series data and spatial analysis. The company's clientele includes various illustrious organizations such as the US Air Force, Citibank, Ford, T-Mobile, and numerous others.
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Data Visualization
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
Oracle APEX
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
GoldenGate 23c
Oracle GoldenGate Veridata 23c (Beta)
OCI GoldenGate
Oracle Database Appliance X10
Oracle Database infrastructure for small and medium businesses
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Big Data Management
WebWire | September 29, 2023
SAS, a leader in AI and analytics, is helping to revolutionize the use of clinical trial data so new medicines can be delivered to patients faster than before. After a thorough evaluation, SAS has been chosen by global biopharmaceutical company AstraZeneca to help increase efficiency and drive automation in the delivery of statistical analyses for clinical and post-approval submissions to regulatory authorities, via SAS’s cloud-based software and technologies.
SAS will support the redesign of clinical and patient data flow by delivering industry-leading analytics and AI, manage changing trial designs in a fast-evolving regulatory environment, enable data re-use, and help accelerate reporting and submission timelines. It will also deliver increased capacity, automation, interoperability, and flexibility to bring in and analyze diverse and novel patient data sources – such as those coming from wearables, sensors and precision medicine – as part of the submissions process.
This will be achieved by supporting the analysis and reporting phases with SAS® Life Science Analytics Framework and SAS® Viya®, a scalable and powerful cloud-based industry platform enabling swift decision-making regardless of data volumes or complexity using modern cloud technologies. This has the potential to provide significant productivity gains by driving faster time to market and reduced IT costs. The SAS and AstraZeneca partnership will enable teams across the organization to collaborate and increase clinical research innovation.
Christopher J Miller, VP Biometrics at AstraZeneca, said, This partnership with SAS supports the transformation of how we use clinical data to support our patient-centric approach and focus on getting medicines to patients faster than ever before. It will also allow us to introduce new ways of working and embrace new technologies and trial models to accelerate our portfolio.
Bryan Harris, SAS Executive Vice President and Chief Technology Officer, said, “I’m delighted that SAS is building on the strong relationship it has had with AstraZeneca over many years by being part of this transformation program. The work they do positively impacts the lives of millions of people around the world.
“This is exciting because we have solidified a great foundation between our companies, but we also recognize we are just scratching the surface. We pay attention to technology and the advancements in AI, and we thrive on thinking through how our technology blended with AstraZeneca’s expertise and insight can create new medical solutions for their customers.”
About SAS
SAS is a global leader in AI and analytics software, including industry-specific solutions. SAS helps organizations transform data into trusted decisions faster by providing knowledge in the moments that matter. SAS gives you THE POWER TO KNOW®.
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