Obviously.ai
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Obviously AI AutoML
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Obviously.ai
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Based on our record, Lambda Face Recognition API seems to be a lot more popular than Obviously.ai. While we know about 27 links to Lambda Face Recognition API, we've tracked only 2 mentions of Obviously.ai. 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.
I just got access to the beta version this new tool called databite.net. I am a data science student so I do a lot of data wrangling on a daily basis, but this thing basically does all of the cleaning for you. I uploaded some CVSs and it immediately joined the files together, added a date index and interpolated missing values, etc. Just like that. I then gave me some options for plots (simple time series, scatter... Source: almost 4 years ago
What about AutoML tools like C3.ai, higgs.ai, obviously.ai ?Anyone using those for trading? With human in the loop ofc, you're right there. Source: over 4 years ago
Setup time matters too. The delta between Runpod and bare-metal providers like Lambda Labs is large. Reaching an equivalent setup on a bare VM requires provisioning the instance, configuring the OS and CUDA drivers, installing Docker, setting up your orchestration layer (Kubernetes or Slurm), deploying your inference container, configuring autoscaling rules, and wiring up your load balancer. Thatโs a realistic... - Source: dev.to / 5 months ago
Let's do the math for a representative setup: GPT-OSS-120B via Together.ai ($0.15/$0.60) vs self-hosting on H100s from Lambda Labs at $2.99/hr ($2,183/mo). A single H100 running a 70B model produces roughly 50 tokens/second on average, which works out to about 130M tokens per month. - Source: dev.to / 6 months ago
How does this compare to https://lambdalabs.com/. - Source: Hacker News / about 3 years ago
Another option is to pay for AWS server with a beefy GPU and enough RAM. It's not too cheap, but isn't expensive either if you aren't planning to run it 24/7. Or get a GPU cluster from a company that offers stuff for ML specifically, it might be easier to set up compared to AWS and in some cases cheaper. Like, for example, lambdalabs that offers H100 gpu for 2 bucks per hour. Source: about 3 years ago
I used some of the cloud GPUs on Vast.ai, but I also tried Lambda Labs, and these days I have my own docker container setup which can be deployed to a VM on Google Cloud and used more programatically. Source: over 3 years ago
Akkio - No-Code AI models right from your browser
Mattermost - Mattermost is an open source alternative to Slack.
Datawaves - Add analytics to anything
Vast.ai - GPU Sharing Economy: One simple interface to find the best cloud GPU rentals.
AI & Analytics Engine - Accessible AI for everyone. AI-powered machine learning platform to clean, transform and model your data, and deploy and manage ML projects, simply, quickly and cost-effectively.
ipinfo.io - Simple IP address information.