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AWS Machine LearningAug 20, 2026Enterprise

Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 2: Data preparation and model building with Amazon SageMaker Canvas

Amazon Web Services published a technical guide detailing how to build an end-to-end, no-code machine learning pipeline by integrating Snowflake with Amazon SageMaker Canvas. The tutorial demonstrates how non-technical users and data analysts can ingest and transform transactional data using visual data preparation tools, and subsequently train an XGBoost model for fraud detection without writing custom code. The guide outlines the workflow needed to prepare datasets before deploying downstream analytics and visualization dashboards.

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AWS Machine LearningAug 20, 2026Enterprise

Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 3: Visualizing insights with Amazon Quick Sight

AWS published technical guidance demonstrating how organizations can build an end-to-end no-code machine learning pipeline using Snowflake, Amazon SageMaker Canvas, and Amazon QuickSight. The tutorial details how to import fraud detection inference data into QuickSight, build interactive visualization dashboards, apply generative BI features for natural-language inquiries, and create automated executive summaries without writing code.

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Dark ReadingAug 20, 2026Enterprise

New CUSTODY Framework Constrains AI Agents Inside the Network

Cybersecurity expert Jake Williams has introduced CUSTODY, a defensive framework designed to constrain and control autonomous AI agents operating within enterprise networks. Developed in response to recent security incidents involving AI infrastructure, the framework aims to provide guardrails and network boundaries for agentic systems. The release addresses growing concerns that autonomous agents with enterprise network access could execute unauthorized lateral movement or trigger unintended data exposure if compromised.

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SiliconANGLEAug 20, 2026Business

Supermicro alliance tackles the storage bottlenecks holding back enterprise AI

Supermicro and ecosystem partners such as Hammerspace are addressing data infrastructure bottlenecks that restrict enterprise AI adoption. As organizations scale AI inference and agentic workflows, legacy storage systems engineered prior to modern AI workloads struggle to deliver necessary throughput and low-latency access. The alliance emphasizes modernizing enterprise storage architectures from mere capacity repositories into high-performance, unified data layers capable of sustaining compute-intensive AI operations across hybrid and cloud environments.

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TechCrunchAug 20, 2026Models

Grok keeps sending gibberish responses to users

TechCrunch reports that users of xAI's Grok Lite model experienced widespread performance degradation, with the AI generating unintelligible, gibberish outputs. Multiple users observed the issue starting Wednesday morning. The disruption highlights potential service instability or inference pipeline failures within xAI's lightweight model tier, affecting direct end-user interactions and any integrated workflows relying on Grok Lite.

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AWS Machine LearningAug 20, 2026Enterprise

Authoring Dogwood policies from natural language in Amazon Bedrock AgentCore

AWS has introduced a natural language policy authoring capability within Amazon Bedrock AgentCore to generate Dogwood-formatted governance policies. The feature allows engineering and compliance teams to convert standard natural language policy guidelines into deterministic agent controls, including newly added time-based operational constraints. According to AWS, this mechanism simplifies the process of restricting autonomous AI agent actions to ensure enterprise alignment, preventing unapproved operations through formal rule enforcement.

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AWS Machine LearningAug 20, 2026Business

Scaling agentic AI: Enterprise patterns without vendor lock-in

AWS has published architectural guidance outlining enterprise patterns for scaling multi-agent AI systems while mitigating vendor lock-in. According to AWS, technical teams operating across heterogeneous environments of frameworks, foundation models, and cloud providers require decoupled architectural interfaces to manage multiple autonomous agents cohesively. The framework details operational principles for orchestrating multi-agent systems across diverse infrastructure stacks, referencing integration with services such as Amazon Bedrock and Amazon SageMaker AI alongside multi-provider environments.

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AWS Machine LearningAug 20, 2026Business

Scaling cloud migrations with agentic AI on Amazon Bedrock AgentCore

AWS has detailed an agentic automation framework built on Amazon Bedrock AgentCore designed to streamline enterprise cloud migrations. According to AWS, the multi-agent architecture coordinates discovery, infrastructure as code (IaC) generation, portfolio governance, and post-migration operations. The vendor claims this automated orchestration can reduce IaC development timelines from weeks to minutes. The approach reflects AWS Professional Services' methodology for deploying coordinated, specialized AI agents across complex enterprise IT transformation workflows.

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AWS Machine LearningAug 20, 2026Enterprise

AWS vector solutions: Build agentic AI where your data lives

Amazon Web Services has published architectural guidance outlining its portfolio of native vector search capabilities across existing database and storage services, including Amazon Aurora, DynamoDB, ElastiCache, Neptune Analytics, OpenSearch Service, and S3. AWS states that integrating vector search directly into these services allows organizations to build agentic AI applications without deploying standalone vector databases or migrating data. The guidance includes engine selection criteria and vendor-reported reference architectures designed to support AI agents accessing enterprise data where it natively resides.

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SiliconANGLEAug 20, 2026Business

Salesforce introduces Slack Code to bring agentic team coding into the open

Salesforce has introduced Slack Code, an integration designed to embed agentic coding assistants directly within Slack conversation channels. The feature aims to make software development workflows visible across teams by enabling developers and stakeholders to interact with coding agents in shared chat spaces. By bringing autonomous code generation and modification into conversational threads, Salesforce seeks to streamline collaboration, track agentic actions publicly across technical groups, and integrate AI-assisted development into standard enterprise team workflows.

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