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Lambda Face Recognition APIHeap is recommended for medium to large companies, product managers, marketing teams, and data analysts who need a platform that offers detailed, user-level insights and robust analytics features without the complexity of setting up extensive tracking code. It is also well-suited for teams that want to make data-driven decisions quickly and efficiently.
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Based on our record, Lambda Face Recognition API should be more popular than Heap. It has been mentiond 27 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.
Heap.io โ Automatically captures every user action in iOS or web apps. Free for up to 5,000 visits/month. - Source: dev.to / almost 4 years ago
Check out Heap for React Native - https://heap.io. Source: almost 4 years ago
How heavily does the site depend on heap.io for its core functionality? Like, say Heap went under completely out of the blue (god forbid) and you had to switch to Google analytics, how much tech debt are you in? Source: about 4 years ago
Aren't services like Heap effectively worse versions of this? On their landing page they outright list this as their value prop: > Heap collects all the data on your customers - automatically. What they click. Where they go. What they do, even when youโre not looking. All without the need for engineers. [1]: https://heap.io/. - Source: Hacker News / over 4 years ago
Author here, surprising to see this blog post of mine trending, but it has held up pretty well! Happy to answer any questions about my time at Stack Overflow. I've since moved on to Heap (https://heap.io/) and we are hiring. We're virtual first so we don't have private offices, but we have the same values about treating developers well and giving them the space they need to do deep work. We're hiring for basically... - Source: Hacker News / almost 5 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
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Mattermost - Mattermost is an open source alternative to Slack.
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Vast.ai - GPU Sharing Economy: One simple interface to find the best cloud GPU rentals.
Adobe Analytics - Adobe Analytics is an industry-leading solution that empowers you to understand your customers as people and steer your business with customer intelligence.
ipinfo.io - Simple IP address information.