Amazon S3 Reviews

Supermemory Reviews

Amazon S3 mentions (214)

• Document Generation for Developers: Security, Compliance, and Build-vs-Buy Decisions for the Template-Plus-Data Pipeline

  TLS at the API boundary encrypts the payload in transit, but your application is responsible for what happens to the document after the response arrives. If you're writing the rendered PDF to disk, a message queue, or cloud storage, that persistence layer needs its own encryption at rest. An unencrypted file sitting in an Amazon S3 bucket with overly permissive ACLs falls outside what the API provider's TLS covers. - Source: dev.to / about 2 months ago

• Dynamic Looping Comes to AWS SAM

  SAM CLI generates the SAMCodeUriServices mapping so that each collection value resolves to its own build artifact. At package time, those paths become Amazon S3 URIs. I don't need to manage any of this. - Source: dev.to / 2 months ago

• AIP-C01 last-minute revision: exam traps, memory hooks, and quick notes

  Fine-tuning adapts an FM to a specific use case with proprietary training data. Titan, Cohere, and Meta models support fine-tuning via Amazon Bedrock. Text models need labelled prompt-completion pairs; image models need Amazon Simple Storage Service (Amazon S3) paths linked to descriptions. Secure training data with Amazon Virtual Private Cloud (Amazon VPC) + AWS PrivateLink. - Source: dev.to / 3 months ago

• Why AWS Certified GenAI Developer stands apart from other AWS certs

  You need to understand vector stores for semantic and hybrid search using Amazon OpenSearch Service and Amazon Simple Storage Service (Amazon S3). Prompt caching helps reduce costs by reusing previously processed prompts. Amazon Bedrock Prompt Management simplifies the creation, evaluation, versioning, and sharing of prompts to help you get the best responses from foundation models. Flow orchestration with Amazon... - Source: dev.to / 3 months ago

• Fine-Tuning 14B SLMs for 3GPP Root Cause Analysis on Amazon SageMaker

  All fine-tuning used Amazon SageMaker Training Jobs — no instance provisioning, no SSH, no manual teardown. You provide a training script and an S3 dataset path, specify the instance type, and SageMaker handles the rest. - Source: dev.to / 4 months ago

Supermemory mentions (3)

• Building an autonomous Slack agent with OpenCode

  Memory. I use Supermemory for this. Before, Pipa loaded context files and knew to update them. A memory tool adds teammate-like recall: goals, preferences, latest business state, and small details that should carry across runs. Good memory tools also know how to supersede and delete memories, which matters once the agent has more autonomy. - Source: dev.to / about 1 month ago

• Build a Real-Time Voice RAG Agent for Your Documentation

  We wire everything up with Vision Agents as the voice agent framework, Stream for WebRTC audio and video, OpenAI Realtime for speech in and speech out, Anam so the agent shows up as a face on the video, and Supermemory so answers come from search over your uploaded documents instead of guesswork. The code stays small and most of the behavior lives in one registered function that asks the memory store for relevant... - Source: dev.to / 2 months ago

• Ask HN: What are you working on (August 2024)?

  My friends and I are working on https://supermemory.ai, an AI second brain to help you remember content from saved webpages and notes. - Source: Hacker News / almost 2 years ago