It’s getting harder to tell where normal tech ends and malicious intent begins. Attackers are no longer just breaking in — they’re blending in, hijacking everyday tools, trusted apps, and even AI assistants. What used to feel like clear-cut “hacker stories” now looks more like a mirror of the systems we all use. This week’s […]
Is Your Model Time-Blind? The Case for Cyclical Feature EncodingTowards Data Science How cyclical encoding improves machine learning prediction
The post Is Your Model Time-Blind? The Case for Cyclical Feature Encoding appeared first on Towards Data Science.
How cyclical encoding improves machine learning prediction
The post Is Your Model Time-Blind? The Case for Cyclical Feature Encoding appeared first on Towards Data Science. Read More
A typosquatted domain impersonating the Microsoft Activation Scripts (MAS) tool was used to distribute malicious PowerShell scripts that infect Windows systems with the ‘Cosmali Loader’. […] Read More
OpenAI is testing a new ChatGPT feature called “Skills,” which will be similar to Claude’s feature, also called Skills. […] Read More
This AI Paper from Stanford and Harvard Explains Why Most ‘Agentic AI’ Systems Feel Impressive in Demos and then Completely Fall Apart in Real UseMarkTechPost Agentic AI systems sit on top of large language models and connect to tools, memory, and external environments. They already support scientific discovery, software development, and clinical research, yet they still struggle with unreliable tool use, weak long horizon planning, and poor generalization. The latest research paper ‘Adaptation of Agentic AI‘ from Stanford, Harvard, UC
The post This AI Paper from Stanford and Harvard Explains Why Most ‘Agentic AI’ Systems Feel Impressive in Demos and then Completely Fall Apart in Real Use appeared first on MarkTechPost.
Agentic AI systems sit on top of large language models and connect to tools, memory, and external environments. They already support scientific discovery, software development, and clinical research, yet they still struggle with unreliable tool use, weak long horizon planning, and poor generalization. The latest research paper ‘Adaptation of Agentic AI‘ from Stanford, Harvard, UC
The post This AI Paper from Stanford and Harvard Explains Why Most ‘Agentic AI’ Systems Feel Impressive in Demos and then Completely Fall Apart in Real Use appeared first on MarkTechPost. Read More
The Machine Learning “Advent Calendar” Day 24: Transformers for Text in ExcelTowards Data Science An intuitive, step-by-step look at how Transformers use self-attention to turn static word embeddings into contextual representations, illustrated with simple examples and an Excel-friendly walkthrough.
The post The Machine Learning “Advent Calendar” Day 24: Transformers for Text in Excel appeared first on Towards Data Science.
An intuitive, step-by-step look at how Transformers use self-attention to turn static word embeddings into contextual representations, illustrated with simple examples and an Excel-friendly walkthrough.
The post The Machine Learning “Advent Calendar” Day 24: Transformers for Text in Excel appeared first on Towards Data Science. Read More
Programmatically creating an IDP solution with Amazon Bedrock Data AutomationArtificial Intelligence In this post, we explore how to programmatically create an IDP solution that uses Strands SDK, Amazon Bedrock AgentCore, Amazon Bedrock Knowledge Base, and Bedrock Data Automation (BDA). This solution is provided through a Jupyter notebook that enables users to upload multi-modal business documents and extract insights using BDA as a parser to retrieve relevant chunks and augment a prompt to a foundational model (FM).
In this post, we explore how to programmatically create an IDP solution that uses Strands SDK, Amazon Bedrock AgentCore, Amazon Bedrock Knowledge Base, and Bedrock Data Automation (BDA). This solution is provided through a Jupyter notebook that enables users to upload multi-modal business documents and extract insights using BDA as a parser to retrieve relevant chunks and augment a prompt to a foundational model (FM). Read More
AI agent-driven browser automation for enterprise workflow managementArtificial Intelligence Enterprise organizations increasingly rely on web-based applications for critical business processes, yet many workflows remain manually intensive, creating operational inefficiencies and compliance risks. Despite significant technology investments, knowledge workers routinely navigate between eight to twelve different web applications during standard workflows, constantly switching contexts and manually transferring information between systems. Data entry and validation tasks
Enterprise organizations increasingly rely on web-based applications for critical business processes, yet many workflows remain manually intensive, creating operational inefficiencies and compliance risks. Despite significant technology investments, knowledge workers routinely navigate between eight to twelve different web applications during standard workflows, constantly switching contexts and manually transferring information between systems. Data entry and validation tasks Read More
Agentic QA automation using Amazon Bedrock AgentCore Browser and Amazon Nova ActArtificial Intelligence In this post, we explore how agentic QA automation addresses these challenges and walk through a practical example using Amazon Bedrock AgentCore Browser and Amazon Nova Act to automate testing for a sample retail application.
In this post, we explore how agentic QA automation addresses these challenges and walk through a practical example using Amazon Bedrock AgentCore Browser and Amazon Nova Act to automate testing for a sample retail application. Read More
Optimizing LLM inference on Amazon SageMaker AI with BentoML’s LLM- OptimizerArtificial Intelligence In this post, we demonstrate how to optimize large language model (LLM) inference on Amazon SageMaker AI using BentoML’s LLM-Optimizer to systematically identify the best serving configurations for your workload.
In this post, we demonstrate how to optimize large language model (LLM) inference on Amazon SageMaker AI using BentoML’s LLM-Optimizer to systematically identify the best serving configurations for your workload. Read More