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Based on our record, GitHub seems to be a lot more popular than Google Cloud TPU. While we know about 2470 links to GitHub, we've tracked only 17 mentions of Google Cloud TPU. 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.
This is why eval and observability ship as a unit, not as separate purchases. agent-eval scores and gates the output โ the tiers above, drift, hallucination. AgentLens captures the trace of how the agent got there: every model step and tool call, the resolved inputs, the raw outputs, the trajectory. Two things fall out of that:. - Source: dev.to / 7 days ago
The real fragility is in trying to constrain arguments. The docs are explicit that a pattern like Bash(curl http://github.com/ *) fails to do what it looks like it does. It won't match curl -X GET http://github.com/... (option before the URL), curl https://github.com/... (different protocol), curl -L http://bit.ly/xyz (redirects to GitHub), URL=http://github.com && curl $URL (variable), or curl http://github.com... - Source: dev.to / 8 days ago
Fallback chains โ og:title โ twitter:title โ- SSRF protection โ if you fetch user-supplied URLs, you MUST block
localhost, RFC-1918 ranges, and internal hostnames, or your preview endpoint is a proxy into your own infrastructure- Caching โ you do not want to re-fetch a URL on every render
- Rate limiting โ a public...
- Source: dev.to / 10 days ago
$ git pull Remote: Repository not found. Fatal: repository 'https://github.com//.git/' not found. - Source: dev.to / 11 days ago
// ==UserScript== // @name GitHub -> Obsidian Task // @namespace obsidian // @version 1.0 // @match https://github.com/*/*/issues/* // @match https://github.com/*/*/pull/* // @grant GM_setClipboard // ==/UserScript== (function () { 'use strict'; function getTitle() { return document.querySelector("bdi")?.textContent.trim(); } function copyTask() { ... - Source: dev.to / 14 days ago
I think the third company (likely Google) is going to make LLMs financially feasible with: - dedicated hardware (https://cloud.google.com/tpu) - optimized models (https://research.google/blog/turboquant-redefining-ai-efficiency-with-extreme-compression/). - Source: Hacker News / about 2 months ago
Previous TPU generations, including last year's Ironwood, were pitched as unified flagship chips. Google's internal experience running Gemini, its consumer AI products, and increasingly complex agent workloads apparently showed that a single architecture forces uncomfortable trade-offs. So they split the roadmap. - Source: dev.to / 3 months ago
Tensor Processing Units are a technology developed and owned by Google. While you can find GPUs in every cloud provider offer, the TPUs are currently only available through Google Cloud Platform. Situation when you invest in a technology or a service that is not available anywhere else is called vendor lock-in โ it's something the sales people love, while customers try to avoid it. What does this look like for... - Source: dev.to / 3 months ago
Google's model is cloud-based. You can't buy a TPU to put in your server. Instead, Google keeps them in their own data centers and rents access exclusively through this. This allows Google to control the entire stack and they don't have to pay the "NVIDIA Tax". - Source: dev.to / 6 months ago
While I don't use Gemini, I'm betting they'll end up being the cheapest in the future because Google is developing the entire stack, instead of relying on GPUs. I think that puts them in a much better position than other companies like OpenAI. https://cloud.google.com/tpu. - Source: Hacker News / 7 months ago
GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
machine-learning in Python - Do you want to do machine learning using Python, but youโre having trouble getting started? In this post, you will complete your first machine learning project using Python.
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python-recsys - python-recsys is a python library for implementing a recommender system.