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PilotANN: A Hybrid CPU-GPU System For Graph-based ANNS

Researchers have proposed a hybrid CPU-GPU system called PilotANN for graph-based Approximate Nearest Neighbor Search (ANNS).
PilotANN addresses the limitations of existing ANNS implementations by utilizing both CPU and GPU resources.
The system employs a three-stage graph traversal process, combining GPU-accelerated subgraph traversal, CPU refinement, and precise search with complete vectors.
Experimental results show that PilotANN achieves significant speedups and cost-effectiveness compared to CPU-only approaches, making high-performance ANNS more accessible on common hardware configurations.

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Siliconangle

269

Image Credit: Siliconangle

Security do-over: How Palo Alto Networks sees the reset

Automation and AI have rendered traditional cybersecurity approaches ineffective as attackers can scale up attacks at unprecedented rates, overwhelming human capabilities.
Palo Alto Networks suggests consolidating security tools into a single platform for real-time AI operation to simplify operations and enhance security.
The volatility in global trade policies and supply chains affects IT spending confidence, but cybersecurity investments are seen as more resilient due to the essential role of safeguarding data.
Cybersecurity market sees growth with a focus on AI-driven outcomes and automation, while a crowded market presents challenges and opportunities for vendors.
Different vendors like Microsoft, Google, CrowdStrike, and Cisco pose competition in the cybersecurity market, emphasizing the need for integrated security platforms.
Platformization versus best-of-breed remains a debate in cybersecurity, with Palo Alto's strategy focusing on unified security platforms despite market trends favoring multiple vendors.
AI's role in cybersecurity is growing, with vendors emphasizing the need for AI-driven threat detection and response to stay ahead of evolving cyber threats.
Cybersecurity sector is expected to see more competitive AI-driven solutions, where success will depend on efficient data pipelines, seamless integrations, and threat correlation at machine speed.
Palo Alto's platformization strategy aims to offer simplicity, data efficiency, and reduced latency in threat detection, challenging the momentum of best-of-breed solutions.
The cybersecurity industry is evolving with a focus on consolidating security stacks and leveraging AI, but challenges such as quantum threats and market competition remain.
The future of cybersecurity remains uncertain, with providers needing to balance innovation and market demands to succeed in the ever-changing landscape.

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Dev

115

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10 Must-Read SQL and Database Design Books for Software Engineers

SQL is a crucial skill for Software Engineers, akin to System Design and Coding.
Understanding advanced SQL concepts beyond basic queries is essential for full-stack developers.
The article lists 10 recommended SQL and Database design books for software engineers.
Books like 'Head First SQL' and 'SQL All-in-One For Dummies' cater to beginners and experienced professionals alike.
'Read Practical SQL' focuses on using SQL for data analysis and storytelling.
'SQL Antipatterns' helps avoid common SQL mistakes, while 'Joe Celko's SQL for Smarties' is great for improving SQL query skills.
'Learning SQL' offers a comprehensive guide from basics to advanced features.
'SQL Performance Explained' by Markus Winand is highly recommended for understanding SQL indexing.
'SQL for Data Analysis' covers advanced techniques like time series analysis and A/B testing for data transformation.
The article emphasizes the importance of continuous learning in SQL for both developers and data engineers.

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Dev

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Tired of writing repetitive MySQL code in Node.js? Here’s a simple helper I built! - mysql2-helper-lite

A new utility package called mysql2-helper-lite has been published to simplify working with mysql2/promise in Node.js.
The package wraps common operations like insert, getOne, updateById, etc., eliminating the need for repetitive SQL code and ensuring cleaner and DRY code.
Usage of the package is simple, with functions such as insert, getOne, updateById making the code shorter and more readable.
This utility package provides a convenient way of handling MySQL operations in Node.js, reducing code complexity and improving efficiency.

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Gizchina

183

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Hackers Steal Data and Blackmail U.S. Hospitals in Oracle Breach

Hackers breached Oracle's servers, stole sensitive patient data, and blackmailed several US medical institutions.
The breach highlights security concerns in the healthcare sector and the need for improved security protocols for patient records.
Oracle notified affected firms and authorities are investigating the ransom demands.
The incident emphasizes the importance of collaboration between healthcare and technology companies to protect patient data and privacy.

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11 Likes

Medium

366

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How to Connect PostgreSQL with Python

To connect PostgreSQL with Python, you need to install the psycopg2 library.
Once installed, you can use the following Python code to establish a connection with the database.
After connecting to the database, you can retrieve the cursor to traverse the records.
To retrieve data, you can execute SQL queries and use fetchall(), fetchone(), or fetchmany() methods.

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Arstechnica

318

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Oracle has reportedly suffered 2 separate breaches exposing thousands of customers‘ PII

Oracle has reportedly suffered 2 separate breaches exposing thousands of customers' PII.
The first breach, in February, affected Oracle Health, resulting in the unauthorized access and theft of patient data from US hospitals.
The second breach involved an anonymous person claiming to possess 6 million records of authentication data from Oracle Cloud customers.
Oracle has not provided any official comments on the reported data breaches.

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Cybersecurity-Insiders

286

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Oracle Health data breach related to hospitals

Oracle Health, formerly known as Cerner, experienced a data breach that led to the leak of over 6 million records.
The breach occurred on legacy servers and the leaked data is linked to Cerner, a healthcare software services provider, which was acquired by Oracle in 2022.
The attacker compromised the servers, potentially copying sensitive information, including patient data from electronic health records to a remote server.
The breach poses significant risks to both the organization and the affected individuals, with potential consequences such as social engineering attacks, phishing schemes, identity theft, and reputational damage.

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Hackernoon

323

Image Credit: Hackernoon

Oracle’s New AI Platform Lets You Build Chatbots That Tell Medieval Tales

The article introduces beginners to Oracle Cloud Infrastructure (OCI) Generative AI service, covering creating an account, setting up the environment, and running the first AI task in Python.
OCI offers AI services like GPU infrastructure and GenAI-powered apps for tasks like text generation, summarization, and embeddings.
Generative AI in OCI has Large Language Models (LLMs) for various tasks, and users can fine-tune models with custom data sets and deploy them on dedicated AI clusters.
Models like Meta Llama and Cohere's Command R and R+ are accessible through OCI SDK in Python, Java, and Node.js.
Initial steps include creating an account, navigating the OCI Console, generating an API key, and creating a configuration file for authentication.
Setting up the environment involves installing necessary libraries in a virtual environment using tools like venv or conda.
Running the first AI task involves creating a Python script, setting up authentication with OCI Generative AI client, and interacting with model endpoints.
Examples are provided for using OCI models like Meta Llama and Cohere's Command R by composing chat requests and displaying the generated responses.
The article concludes by highlighting the steps for getting started with OCI Generative AI and encourages users to refer to the documentation for more information.

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19 Likes

Soais

235

TOSCA Sections

Tosca Commander consists of several sections, including the Module Section, Test Case Section, Test Case Design Section, Execution Section, Requirement Section, Issues Section, and Configuration Section, each serving a specific role in the testing process.
The Module Section holds technical data categorized into Standard Modules (provided by Tosca) and User-defined Modules (created by users).
Tosca modules are further classified into Classic Modules and XModules based on their creation process.
Manual testing and automation testing are both supported by Tosca Commander, with test case creation being dependent on the module section for automation.
The Test Case Section is where new test cases are created, and the Test Case Design Section helps in planning and designing test cases efficiently.
Execution Section is where test scripts are executed, and results are saved, facilitating the execution of both individual test steps and complete test cases.
Requirement Section deals with gathering use case requirements for testing, while the Issues Section logs any bugs or errors found during test case execution.
In the Configuration Section, necessary configurations like API setups for performance testing or mobile testing are specified.
Overall, TOSCA's various sections streamline and enhance the testing process by providing structured workflows for test case creation, execution, and issue tracking.

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Mclaughlinsoftware

162

PL/SQL List to Struct

This post shows you how to take a list of strings and convert them into a struct(ure) of a date, number, and string.
Oracle implements IDL (Interface Description Language), which means the solution requires creating an attribute data type (ADT), a user defined type (UDT), and a collection of the UDT object type.
The code example provides the data definition language (DDL) for the required structures, as well as a function named cast_strings that performs the conversion.
By applying the cast_strings function to a list of strings, you can obtain a struct(ure) object type containing the parsed values of date, number, and string.

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VentureBeat

264

Image Credit: VentureBeat

The TAO of data: How Databricks is optimizing AI LLM fine-tuning without data labels

Labeled data is crucial for training AI models but collecting and curating it can be time-consuming and costly for enterprises.
Databricks introduced Test-time Adaptive Optimization (TAO) to fine-tune AI models without the need for labeled data, outperforming traditional methods.
TAO uses reinforcement learning and exploration to optimize models with only example queries, eliminating the need for paired input-output examples.
The approach includes mechanisms like response generation, reward modeling, and continuous data improvement to enhance model performance.
TAO utilizes test-time compute during training without increasing the model's inference cost, making it cost-effective for production deployments.
Databricks' research shows that TAO surpasses traditional fine-tuning methods in terms of performance while requiring less human effort.
TAO has demonstrated significant performance improvements on enterprise benchmarks, approaching the capabilities of more expensive models like GPT-4.
By enabling the deployment of more efficient models with comparable performance and reducing labeling costs, TAO offers a compelling value proposition.
The time-saving element of TAO accelerates AI initiatives by eliminating the lengthy process of collecting and labeling data, thus expediting time-to-market.
Organizations with limited resources for manual labeling but a wealth of unstructured data stand to benefit the most from TAO's capabilities.

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Hrexecutive

46,000 employees reveal the true value of frontline worker engagement

Organizations with over 75% of workers reporting favorable engagement scores experience a 12-month turnover rate of 85%.
Another report shows that engaged employees are 88% more likely to perform well financially.
Leadership gap identified with only 63% of employees believing their managers create a trusting workplace.
Technology plays a role in driving engagement, with app-free tools and digital solutions recommended.

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5 Likes

Medium

286

Image Credit: Medium

9 Database Optimization Tricks SQL Experts Are Hiding From You

In my years of database consultation work, I’ve encountered countless applications buckling under slow queries that could have been fixed with a few targeted optimizations.
Here are nine powerful SQL optimization tricks that can transform your database performance, sometimes by orders of magnitude.
Most developers know about indexes, but few use partial indexes — one of the most powerful ways to speed up specific queries while minimizing index overhead.
A covering index includes all columns needed by a query, allowing the database to satisfy the query using only the index without touching the table at all.

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17 Likes

Soais

122

Workforce Compensation

Workforce compensation plans are used to allocate budgets to managers and compensation to groups of employees during a compensation cycle.
Compensation can be monetary or non-monetary, such as stock allocation or perks.
The workforce compensation process involves preparing for the cycle, administering individual and workforce compensation plans, and closing the cycle.
Key roles in the workforce compensation process include Compensation Administrator, Compensation Manager, Line Manager, and HR Specialist.

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