Co-Founder of Industry Dive. We are a digital media company that publishes business news and original analysis for executives in different industries. industrydive.com
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I think a better way to regulate content moderation would be to pass laws that regulate content moderation. Not backdoor regulations through very broad interpretations of product liability.
HN surely has some underage users. If they look at their analytics and tweak the interface to improve time on site, are they also intentionally creating a product that is addictive to children?
These types of lawsuits seem dangerous. But Meta is a pretty awful company and deserves some sort of comeuppance. I worry about what it leads to though. Hard cases make bad laws.
No, you can't just "average" different studies and I'm not sure what "neutral" means in the context of some studies showing a benefit and others not showing a benefit.
Obviously there are advantages to not having to do work yourself.
But for a benchmark with the goal of picking a model to replace a human on some task? I really think the human should judge which is best.
I haven’t gotten very far yet but I had an idea for a personalized benchmark tool that walks through your git history and helps you craft prompts for tasks that bugs or features already implemented by hand so you can compare how different LLMs would do it.
Fireworks.ai is solid. And if you care more about speed than cost they have a "fast" variant that I think just throws more hardware at the model for about 2x the cost.
Seems like a pretty straightforward approach to collecting session logs from a bunch of different people/devices would be to have them all set their base url to proxy.deepseek.whatever which logs the data and forwards to the real API.
There's really no comparison between a model that Anthropic allows Google and Amazon to host with one that has been downloaded hundreds of thousands of times and has dozens of public inference providers.
I'm skeptical of how fast "up to" 750t/s really means. Maybe if they make it extremely expensive so it frees up enough capacity?
GPT‑5.3‑Codex‑Spark currently runs on Cerebras chips and it's giving me around 150t/s. Still relatively very fast, but nowhere near the 1,000t/s they claimed at launch. (Also it's not a very good model.)
That said, I'm super bought in to faster models being better for most use cases than smarter models.
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