Amazon S3
AWS Lambda
Google Cloud Storage
Amazon CloudFront
Amazon EC2
DynamoDB
Google App Engine
Amazon AWS
MemoryBase.app
Cursor Memories
EVA Online AI
knowbase.ai
LLM OneStop
MemMachine
MemoryPlugin
Memory Sync
Amazon S3 (Amazon Simple Storage Service) is the storage platform by Amazon Web Services (AWS) that provides an object storage with high availability, low latency and high durability. S3 can store any type of object and can serve as storage for internet applications, backups, disaster recovery, data archives, big data sets and multimedia.
MemoryBase is a cross-platform memory layer for people who use multiple AI tools daily. It syncs your conversations across ChatGPT, Claude, Claude Code, Cursor, and Gemini, so whatever you tell one AI is available to all the others.
Conversations get captured automatically as they happen, organized into projects and topics, and the relevant pieces surface in whichever tool you open next. You stay in control of what gets stored and what loads where.
Available as a Chrome extension and web app at memorybase.app. Free and Pro plans, with more integrations on the roadmap including OpenClaw, Slack, and Google Docs.
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Based on our record, Amazon S3 seems to be more popular. It has been mentiond 214 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
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 / 2 months ago
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 / 3 months ago
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
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 / 4 months ago
All fine-tuning used Amazon SageMaker Training Jobs โ 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 / 5 months ago
AWS Lambda - Automatic, event-driven compute service
Cursor Memories - Memory system for Cursor agents
Google Cloud Storage - Google Cloud Storage offers developers and IT organizations durable and highly available object storage.
EVA Online AI - EVA is an all-in-one AI workspace that lets you chat with ChatGPT, Claude, Gemini, Grok, Perplexity, DeepSeek and more from a single interface โ with one unified credit system and side-by-side model comparison. Free plan available.
Amazon CloudFront - Amazon CloudFront is a content delivery web service.
knowbase.ai - Knowbase is Dropbox and ChatGPT combined. You store your files and have access to all the information collected in them, by asking a question on the chat.