heipei

That's just Germany for ya. Source: Am German

So what is the alternative? It took me a while to get around the data schema / modelling that a database like Cassandra imposed, but when it finally clicked it really clicked for me, so much so that I wish I could have the same performance footprint of consistent hashing / sharding with other databases.

We are using ScyllaDB, but since they discontinued their Open Source version we're stuck on the last supported version, and reading about the operational headaches of Cassandra does not inspire confidence to give it a go.

Legitimate file hosting services present the biggest total volume of newly discovered phishing pages / unique hostnames. Another (similar) angle is using unrelated legitimate domains which are compromised (think insecure Wordpress) to host phishing sites in subdirectories. A lot of traditional ML scoring and blocking approaches fall flat if the hosting domain is on a very legitimate and hard-to-block domain, such as a government website.

Can we please stop posting here every time Claude or OpenAI are down? These are not critical services like AWS / S3 where downtime means that your application is offline. Nothing is easier than switching to another provider, mid-session even.

Cloudflare is really good at launching features that facility low-friction deployment of malicious content (such as phishing) on the Internet, piggybacking on their hosting reputation and the fact that you can't easily block their ASN or domains.

This is gonna be amazing for phishing, like most of the features Cloudflare offers (free Turnstile for fresh accounts, CF tunnels, pages.dev, r2.dev).

It is smart enough that I use for all my coding tasks, and a lot of other mundane tasks.

It is probably not smart enough for "design this whole architecture of this complex system from scratch, make no mistakes", but that is not something I want from a coding tool anyway. I want a model that I can point to a file and tell it to make some changes to the file and related files. Or that I can ask to review a PR with regards to certain aspects.

My suggestion is to simply try it and see what it feels like.

Depends on what you mean by "local". On your Macbook, large dense models like Qwen 3.6 27B will be slow, sure. On a local workstation with a dedicated RTX card you can get > 100 tps, which is more than good enough to work with it, and faster than cloud models in many cases.

No KV cache quant, context length 50% of original, MTP absolutely. These are the relevant cmdline attributes. Getting around 100t/s with this setup, even when watt-limited to 450W.

  --temp 0.6 --top-p 0.95 --top-k 20 --min-p 0.00 --presence-penalty 0 --metrics --jinja --chat-template-file chat_template.jinja --chat-template-kwargs '{"preserve_thinking": true}' --spec-type draft-mtp --spec-draft-n-max 2 --spec-draft-p-min 0.75 -ngl 99 -c 131072 -fa on -np 1 -hf unsloth/Qwen3.6-27B-MTP-GGUF:Q6_K

Same here, I use Qwen 3.6 27b (Q6 quant) with llama.cpp on an RTX 5090 using the pi agent exclusively now. The fact that it's local means that I never have to think about token pricing, quotas, time of day, or data sensitivity. I have limited the GPU from 600W to 450W which means the system stays whisper quiet during inference.

I have become so "lazy" (in a good way), so far that I've started using the model for lots of daily mundane things on top of just coding:

  * "commit this on a branch, push, create a PR and assign $nickname for review"
  * "Use the Stripe CLI to download all open and overdue invoices and reconcile them with this CSV export from our bank account."
  * "Use these Elasticsearch credentials to summarise what kind of operations are causing load at the moment."
  * "Tell me if our codebase already supports X and where it's  implemented."

$5B valuation on a $30B run rate for Anthropic?

Local AI models are already more than capable enough writing code that surpasses the ability of any bad or even mediocre engineer. That is not something we need to worry about.

In a way, this is less of a cost issue than the fact that some/many engineers do not seem to be willing or able to host things themselves anymore and will happily outsource every part of their stack to managed services, be it CDN, hosting, databases, etc. I don't know why that's not more alarming than the LLMs.

Serious question: Who actually builds stuff on Cloudflare workers? I mean large software projects / services, and not just side projects where the ability to scale-to-zero is perhaps more important than the scale-to-infinity direction. I feel like Cloudflare keeps pushing workers with its full force yet I fail to see the appeal.

I just saw the headline fly by yesterday and thought that this was just another dumb bug in what is the slow decline of GitHub. To find out today that this was very much intentional is even worse.

This is amazing, thank you for launching it. I know this webapp itself will make me more likely to look at raw photos on my Fuji once again.