A critical misconfiguration in Amazon Web Services (AWS) CodeBuild could have allowed complete takeover of the cloud service provider’s own GitHub repositories, including its AWS JavaScript SDK, putting every AWS environment at risk. The vulnerability has been codenamed CodeBreach by cloud security company Wiz. The issue was fixed by AWS in September 2025 following responsible […]
Verizon has confirmed that yesterday’s nationwide wireless outage was caused by a software issue, though the company has not shared additional details about what went wrong. […] Read More
A critical vulnerability in Google’s Fast Pair protocol can allow attackers to hijack Bluetooth audio accessories like wireless headphones and earbuds, track users, and eavesdrop on their conversations. […] Read More
The upcoming Winter Games in the Italian Alps are attracting both hacktivists looking to reach billions of people and state-sponsored cyber-spies targeting the attending glitterati. Read More
How to Run Coding Agents in ParallelTowards Data Science Get the most out of Claude Code
The post How to Run Coding Agents in Parallel appeared first on Towards Data Science.
Get the most out of Claude Code
The post How to Run Coding Agents in Parallel appeared first on Towards Data Science. Read More
Google Antigravity: AI-First Development with This New IDEKDnuggets Google Antigravity marks the beginning of the “agent-first” era, It isn’t just a Copilot, it’s a platform where you stop being the typist and start being the architect.
Google Antigravity marks the beginning of the “agent-first” era, It isn’t just a Copilot, it’s a platform where you stop being the typist and start being the architect. Read More
Scale creative asset discovery with Amazon Nova Multimodal Embeddings unified vector searchArtificial Intelligence In this post, we describe how you can use Amazon Nova Multimodal Embeddings to retrieve specific video segments. We also review a real-world use case in which Nova Multimodal Embeddings achieved a recall success rate of 96.7% and a high-precision recall of 73.3% (returning the target content in the top two results) when tested against a library of 170 gaming creative assets. The model also demonstrates strong cross-language capabilities with minimal performance degradation across multiple languages.
In this post, we describe how you can use Amazon Nova Multimodal Embeddings to retrieve specific video segments. We also review a real-world use case in which Nova Multimodal Embeddings achieved a recall success rate of 96.7% and a high-precision recall of 73.3% (returning the target content in the top two results) when tested against a library of 170 gaming creative assets. The model also demonstrates strong cross-language capabilities with minimal performance degradation across multiple languages. Read More
Safeguard generative AI applications with Amazon Bedrock GuardrailsArtificial Intelligence In this post, we demonstrate how you can address these challenges by adding centralized safeguards to a custom multi-provider generative AI gateway using Amazon Bedrock Guardrails.
In this post, we demonstrate how you can address these challenges by adding centralized safeguards to a custom multi-provider generative AI gateway using Amazon Bedrock Guardrails. Read More
Build a generative AI-powered business reporting solution with Amazon BedrockArtificial Intelligence This post introduces generative AI guided business reporting—with a focus on writing achievements & challenges about your business—providing a smart, practical solution that helps simplify and accelerate internal communication and reporting.
This post introduces generative AI guided business reporting—with a focus on writing achievements & challenges about your business—providing a smart, practical solution that helps simplify and accelerate internal communication and reporting. Read More
How the Amazon AMET Payments team accelerates test case generation with Strands AgentsArtificial Intelligence In this post, we explain how we overcame the limitations of single-agent AI systems through a human-centric approach, implemented structured outputs to significantly reduce hallucinations and built a scalable solution now positioned for expansion across the AMET QA team and later across other QA teams in International Emerging Stores and Payments (IESP) Org.
In this post, we explain how we overcame the limitations of single-agent AI systems through a human-centric approach, implemented structured outputs to significantly reduce hallucinations and built a scalable solution now positioned for expansion across the AMET QA team and later across other QA teams in International Emerging Stores and Payments (IESP) Org. Read More
