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CloudFix scans your AWS accounts, identifies cost savings opportunities, and automatically implements fixes around the clock. Unlike tools that just show you where to save, CloudFix does the work — applying AWS-recommended, non-disruptive fixes across EC2, EBS, S3, RDS, Lambda, and more. Fixes applies vis AWS Systems Manager, so you're always in control
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CloudFix's answer:
CloudFix's answer:
Most AWS cost optimization tools show you where to save, CloudFix actually does the saving. It automatically implements AWS-recommended fixes across your accounts, 24/7, without requiring manual intervention. Every fix follows AWS best practices, is non-disruptive, and goes through AWS SSM so you stay in control. Savings compound over time rather than being a one-off result.
CloudFix's answer:
CloudFix is the only platform that combines continuous automated fix execution with full approval control via AWS Change Manager. Tools like ProsperOps, Cloudability, and CloudZero identify savings opportunities but CloudFix implements them. It covers 50+ AWS advisories per week across compute, storage, networking, and database services, and delivers 15–60% savings per AWS service.
CloudFix's answer:
Engineering and FinOps teams at mid-to-large enterprises running significant AWS workloads typically $80K+ in monthly AWS spend. CloudFix suits companies using multiple AWS services who want ongoing cost optimization without dedicating engineering resources to manually track and implement AWS advisories.
CloudFix's answer:
CloudFix was built by the team behind one of AWS's largest customers, managing 120+ SaaS products across thousands of AWS accounts. Keeping costs optimized at that scale without breaking anything was a constant challenge. They built CloudFix internally to automate it, proved it cut costs by 10–20%, and turned it into a product.
CloudFix's answer:
CloudFix is built natively on AWS. It uses AWS CloudFormation for deployment, AWS Cost and Usage Reports (CUR) and CloudWatch Metrics for analysis, and AWS Systems Manager to orchestrate and control fix execution. IAM roles handle secure, read-only cross-account access with no long-term credentials.
Based on our record, Unsloth seems to be more popular. It has been mentiond 6 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.
Unsloth Desktop is what people have been waiting for. It's just been released as a beta. It's pretty much a single-click install. You download the installer and run it, and from there Unsloth Desktop handles everything else for you. Behind the scenes it scans your machine and determines what needs to be installed. It puts a wrapper around llama.cpp and MLX, which gives you all the power of the top open source... - Source: dev.to / 3 days ago
Unsloth is primarily a fine-tuning tool — it makes QLoRA training 2-5x faster with 50-70% less VRAM. It does NOT run inference. For inference, use Ollama/llama.cpp/MLX. - Source: dev.to / 5 months ago
LoRA is the breakthrough that democratized fine-tuning: by training only 1% of model weights, it reduces GPU/VRAM needs by 10-100x. QLoRA takes it further — quantizing to 4 bits enables fine-tuning 65B+ parameter models on a single consumer GPU with just 3GB VRAM (Unsloth). - Source: dev.to / 5 months ago
Unsloth AI is designed to optimize large language model fine-tuning on modest hardware. It leverages efficient training algorithms to allow even GPUs with 24GB VRAM, like consumer-grade cards, to fine-tune models such as Llama 3 without massive resource demands or overheating risks. - Source: dev.to / about 1 year ago
Lot's of tools for each of those separately (RAG and fine-tuning). We're working on combining them but it's not ready yet. You don't need a big GPU cluster. Fine-tuning is quite accessible via both APIs and local tools. Some suggestions: - getkiln.ai (biased, my tool): let's you try all of the below, and compare/eval the resulting models - API based tuning for closed models: OpenAI, Google Gemini - API based... - Source: Hacker News / over 1 year ago
Fireworks AI - Use state-of-the-art, open-source LLMs and image models at blazing fast speed, or fine-tune and deploy your own at no additional cost with Fireworks AI!
ProsperOps - Cost optimization tools and expertise from the creators of AWS' largest Managed Service Provider. Our customers increase savings an average of 34%.
Ollama - The easiest way to run large language models locally
Cloudability - Cloudability lets you monitor, manage and communicate your cloud costs with one easy tool.
Plexe - Build and deploy ML models from natural language
Usage AI - Usage's Automated Reserved Instance Manager buys/sells Flex RIs(3-yr-no-upfront RIs under the hood) to maximize your coverage and minimize your compute spend - up to a maximum 57% savings!