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New details emerge about Project Stargate as Meta discloses $60B+ AI investment

New details have emerged about Project Stargate, the $500 billion initiative through which OpenAI hopes to build a cluster of artificial intelligence data centers.
The project currently lacks a fully developed plan and finalized funding, according to sources.
OpenAI, SoftBank, and Oracle unveiled Project Stargate to build a network of data centers optimized for AI workloads.
Separately, Meta Platforms Inc. disclosed a $60 billion investment for building data centers and hiring AI experts.

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Medium

PostgreSQL Functions for Python Programmers

SQL functions can improve performance by minimizing server calls and handling computations directly in SQL
SQL requires explicit declaration of variables and uses semicolons to terminate statements
Control flow in SQL is defined using BEGIN ... END; and loops are defined using FOR ... LOOP with explicit END LOOP;
SQL supports function overloading and allows embedding queries directly within functions

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Pymnts

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This Week in AI: Trump Repeals Biden AI Rules but Launches Stargate

President Donald Trump has overturned Joe Biden's 2023 artificial intelligence rules, which covered policies around AI's advancement. However, Trump kept Biden's orders in place restricting exports of advanced AI chips and Biden's executive order on AI cybersecurity. Trump also announced an up-to-$500bn project called Stargate, aiming to build big AI-focused data centres in the US. Stargate's first equity partners include SoftBank, OpenAI, Oracle and MGX. Meanwhile, a long-rumoured AI agent, Operator, has been revealed by OpenAI, which plans to make it capable of using a computer like a human.
Stargate will build 10 data centres initially for the first stage of the project, which is being funded by SoftBank, and later expanding to 20. Oracle Executive Chairman Larry Ellison said the first 500,000-square foot data centre is being built in Abilene, Texas, according to a PYMNTS report published on Monday. In addition to SoftBank, OpenAI, Oracle and MGX, Microsoft, Arm and Nvidia will each be the project's technology partners.
Elon Musk questioned the credibility of the funding of the Stargate project, posting: "They don't actually have the money." OpenAI CEO Sam Altman hit back, claiming Musk was "wrong, as you surely know" before inviting him to visit the first data centre site.
At the World Economic Forum conference, AI was a dominant topic of discussion. Google DeepMind's CEO Demis Hassabis said that AI-designed drugs could be brought to clinical trials this year. Meanwhile, Anthropic CEO, Dario Amodei, said AI-powered advances in biology could lead to a doubling of human life span.
OpenAI is developing an AI agent called Operator that can use a computer like a human. Users can ask it to order groceries, reserve tables and purchase event tickets while it is able to interpret screenshots and interact with computer screens.

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Cloudblog

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Tchibo brews up 10x faster customer insights with AlloyDB for PostgreSQL

Tchibo, a well-known coffee retailer and lifestyle brand based in Germany, migrated to AlloyDB for PostgreSQL database to manage vast amounts of customer feedback for its diverse product offerings and sales channels.
With AlloyDB, Tchibo is now able to leverage advanced analytics and AI capabilities to streamline data retrieval and provide real-time insights that empower teams to respond quickly to customer needs.
Tchibo faced several issues with its previous cloud database solution, due to limitations in speed, scale, and data complexity, leading to slow query speeds, labor-intensive feedback compilation, and difficulty in extracting actionable insights from diverse data sources.
AlloyDB provided a flexible and efficient approach to data storage, with traditional queries, advanced nearest-neighbor (NN) searches, and reranking/filtering steps that enable real-time feedback analysis.
AlloyDB’s advanced analytics capabilities, built-in vector search, and familiar PostgreSQL foundation offered the speed, adaptability, and usability Tchibo needed to serve up insights as fresh and fast as its coffee.
With AlloyDB, Tchibo’s Customer Voice application compiles data from product reviews and other sources into actionable summaries that answer questions like, “How do customers feel about our new coffee pad machine?” with concise, actionable summaries.
AlloyDB has transformed Tchibo’s approach to data by enabling faster, deeper, and more scalable access to the customer feedback and analytics needed for data-driven decision-making.
AlloyDB’s fully managed operation has reduced operational overhead, simplifying Tchibo’s ability to scale as data demands grow, with 99.99% SLA availability providing valuable reliability for supporting long-term goals.
Beyond Customer Voice, AlloyDB also supports broader AI initiatives, such as an internal chatbot for intranet queries, giving Tchibo the flexibility to scale various retrieval-augmented generation (RAG) use cases efficiently across the organization.
Partnering with Google Cloud, Tchibo is positioned to explore new data solutions to serve up richer insights, driving growth and innovation at the company.

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TechCrunch

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OpenAI’s Stargate project reportedly doesn’t have the money it needs

OpenAI's Stargate project lacks a fully developed plan and sufficient funding.
Stargate aims to build data centers to support OpenAI's AI workloads with a potential investment of $100 billion to $500 billion.
Current commitments from stakeholders, including SoftBank and OpenAI, amount to over $15 billion to start.
Elon Musk has criticized Stargate on social media, questioning its claimed funding, causing controversy.

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Dev

268

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PRAGMA AUTONOMOUS_TRANSACTION in ORACLE PLSQL - Use case

In the airline industry's cargo management system, autonomous transactions can play a critical role in ensuring the integrity and consistency of operations without affecting the main transactional flow.
During operations there are auxiliary tasks for logging, auditing, or updating external systems, which should occur independently of the main transaction that handles cargo updates.
An example of booking cargo, updating cargo status in main and logging of such status is being described.
For such cases of asynchronous operations, PRAGMA AUTONOMOUS_TRANSACTION can be used.
The autonomous transaction should execute independent of the main transaction and even if any failure occurs, it should not restrict successful execution of main transaction.
This approach helps in maintaining transactional integrity, separating concerns and compliance.
PL/SQL code example is provided to understand the use of PRAGMA AUTONOMOUS_TRANSACTION.
Overall, the approach ensures that the logging process occurs independently for the audit trail purpose.
It also minimizes disruption to the core functionality of the system.
This can be used in any systems like cargo management, asset management, etc.

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Analyticsindiamag

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Oracle’s Larry Ellison is the ‘CEO of Everything’

Oracle's Larry Ellison is being referred to as the 'CEO of Everything' by US President Donald Trump.
Oracle has partnered in a $500 billion investment in US AI infrastructure and has a stake in TikTok Global.
Oracle is assisting the US government in building data centers for AI infrastructure and collaborating with OpenAI and NVIDIA.
Ellison discussed AI's potential in healthcare, including early cancer detection and personalized vaccines.

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Cloudblog

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Migrate Oracle-based applications to Google Cloud and simplify operations

Google Cloud and Oracle have partnered up to help businesses migrate their Oracle databases and applications to Google Cloud.
Google Cloud provides various migration paths, from fully managed services to customized options that offer flexibility depending on your business's needs.
The partnership is designed to provide businesses with the flexibility they need to deploy and manage Oracle applications on Google Cloud, accelerating migration, modernization, and innovation.
Google Cloud also offers containerization support, which gives developers versatility and scalability for their Oracle-based applications built with Java, Python, .NET, or runs on WebLogic.
Google Kubernetes Engine and Cloud Run are two powerful container orchestration platforms run for running containers smoothly, reliably, and efficiently on Google Cloud.
Oracle databases can be run on virtual machines, giving you control and flexibility for lift and shift migrations, while Oracle pluggable databases can be deployed using OraOperator, Oracle's Database Operator for Kubernetes.
Oracle GraalVM creates native Java applications, converting Java bytecode directly into native executables, which enable them to start quicker and consume fewer resources like CPU and memory. Using Java native images also enhance the security posture of your containers and minimize the potential attack surface.
Google Cloud has partnered with experienced Oracle experts to help make your migration smooth and successful. They can guide you through the process and offer solutions that will fit your migration needs.
The Oracle migration solutions on Google Cloud provide businesses an opportunity to modernize their applications to Java 21, adopting its advantages of long-term support, increased runtime performance, and security patches.
Migrating older Oracle applications to GKE or Cloud Run is a good opportunity to modernize them to Java 21 at the same time.

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Hackernoon

385

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9 Big Takeaways From Data Analytics This Year

The global data analytics market is projected to exceed $140 billion by 2025, highlighting its crucial role in today's hyperconnected business landscape.
Augmented analytics leverages AI and machine learning to automate key aspects of the analytics process, such as data preparation, insight generation, and explanation.
Data governance is no longer just a theoretical priority — in 2025, it’s about implementing tools and strategies that embed governance into daily practices while unlocking AI capabilities.
Python's versatility in tasks like data cleaning, manipulation, and machine learning make it a dominant player in the data analytics field.
80% of global data is unstructured, presenting challenges in storage and specialized tools like NLP and computer vision are needed to analyze it.
NLP will reshape how users interact with data by making insights accessible to everyone, regardless of technical expertise and will empower faster, more informed decisions.
Over 50% of analytics workloads predicted to transition to lakehouse platforms by 2025, which blend data lakes and warehouses for cost-effective scalability.
Embedded analytics and real-time insights, replace reliance on standalone BI tools and enhance productivity by providing real-time decision-making capabilities.
Explainable AI produces more understandable AI operations, enhancing trustworthiness and fosters user confidence.
Edge computing processes data closer to its source, reducing latency for real-time analytics and critical for IoT-driven industries like healthcare and manufacturing.

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Oracle-Base

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Hugepages in 19c : It’s the same but completely different!

The article discusses the changes in the handling of Hugepages in Oracle Database 19c.
The author received a suggestion to update their Hugepages article due to the changes in Oracle 19c.
The confusion arises from the new values added to the USE_LARGE_PAGES parameter.
The blog post provides more information on the changes and their implications.

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Javacodegeeks

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MariaDB4j: Embedded MariaDB Example

MariaDB4j is a Java library that allows developers to run MariaDB in an embedded mode, which is highly useful for testing and development environments.
MariaDB4j handles the downloading, extraction, and management of MariaDB binaries dynamically, ensuring that the database is up-to-date and ready to use with minimal effort.
This dynamic management means that MariaDB4j can automatically set up a temporary database environment that can be started and stopped programmatically.
MariaDB4j helps in creating self-contained applications that are easier to deploy and maintain.
MariaDB4j also supports custom configurations, such as specifying the port number, data directory, and additional startup options.
You can use MariaDB4j from the command line by installing the library and utilizing its built-in commands.
MariaDB4j can be easily integrated into Java applications.
MariaDB4j is particularly useful for writing isolated tests.
MariaDB4j provides a powerful way to use MariaDB in embedded mode for development and testing purposes.
Whether you use it from the command line or integrate it into your Java applications and tests, MariaDB4j is a handy tool for developers.

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Dbi-Services

251

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Creating your private cloud using OpenStack – (5) – The Compute service

In this article, the author describes the procedure for setting up the compute service in OpenStack, also known as Nova.
Nova interacts with OpenStack Identity for authentication, OpenStack Placement for resource inventory tracking and selection, OpenStack Image service for disk and server images, and OpenStack Dashboard for the user and administrative interface.
The article explains how to prepare and configure the database backend, create service credentials and endpoints, install required packages, and configure Nova in detail on the controller and compute nodes.
It also covers how to install and enable libvirt on the compute node.
Lastly, the author demonstrates how to discover hosts, attach them to a cell, and verify the image service and placement API are working properly.
The article concludes with a diagram of the final OpenStack deployment, and a hint at the next article which covers the Network Service (Neutron).

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Medium

247

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SQL for Product Managers: Why You Should Consider It an Essential Skill

SQL, or Structured Query Language, is an essential tool for product managers.
Learning SQL allows product managers to unlock valuable data stored in databases.
SQL is the language used to retrieve data from databases.
Grasping SQL empowers product managers to make informed decisions.

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Amazon

358

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Diving deep into the new Amazon Aurora Global Database writer endpoint

Amazon Aurora Global Database is a MySQL- and PostgreSQL-compatible relational database designed for globally distributed applications.
The newly released Aurora Global Database writer endpoint is a fully managed endpoint for a global database that enables fast local reads with low latency, and provides disaster recovery for applications in case of a single-region impairment.
The Global Database writer endpoint offers a seamless and secure solution for routing write requests to the appropriate writer instance.
Global Database consists of a primary region and up to five read-only secondary regions for low-latency local reads; Aurora asynchronously replicates data to the secondary region database clusters with latency typically under a second.
Remote cross-region access pattern enables your application stack to remain in its current region and automatically connects to the same endpoint following a global database switchover or failover operation across regions.
The local access pattern requires your application stack to move with the database to the same region as the primary cluster in case of a rare regional outage.
Aurora generates additional RDS events, helps minimize disruption after a switchover or failover, and provides best practices when using Global Database writer endpoints.
Connect your applications to the Global Database writer endpoint, which you can find on the Amazon RDS console.
Aurora now automatically creates the endpoint when you add a new region to your single-region Aurora cluster.
The Global Database writer endpoint points to the current writer DB instance, streamlines the application architecture, enhances operational efficiency, and provides secure communication with DB instances.

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Dev

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Best way to learn SQL

SQL (Structured Query Language) is a language we use to communicate with relational databases.
Learning SQL is essential to search, filter, edit, and manipulate data in your relational databases.
There are several resources available for SQL beginners like tutorials, online courses, and practicing with real-time data.
Practicing with real data and utilizing SQL to solve real problems will improve your SQL skills swiftly.
SQL core commands consist of SELECT, WHERE, JOIN, GROUP BY, ORDER BY, INSERT, UPDATE, and DELETE.
As your SQL skills grow, you must focus on improving query performance and learn indexing to make queries run faster.
Stack Overflow has a vast library of SQL questions and solutions which can assist while learning SQL.
Asking other developers, data engineers, or Artificial Intelligence (AI) can help you when you face issues while resolving real-time problems.
You can start learning SQL using online resources like Outerbase, W3Schools, or Codecademy.
You only need enough SQL knowledge to answer your own questions without depending on others.

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