Inferact co-founder Simon Moe explains how arbitrary API safety guardrails interrupt low-level GPU kernel research by misinterpreting invalid memory access errors as security threats.
Opinion
Moe: Open and closed AI models have no capability gap today
“In the end, there's not much differentiation. It's more about the distribution strategy and go-to-market strategy. And the capability wise, I don't really see a big gap, not even today, because for how these models are coming to being, they're really starting …”
Opinion
Moe: Model distillation is not the primary driver of Chinese AI progress
“So I really don't think from currently what we're seeing this is a big cornerstone of what's powering the progress today. In the end, what's powering the progress is still just really smart people with very interesting algorithms, data environment, and they wi…”
Assertion Supported
Moe: Open-weight inference can hit 500 tokens/sec, 2-3x faster than proprietary APIs
“But for open weight, when you are running it, every provider can offer potentially even 10 different levels of speed going from like the slowest mode, which can be a lot cheaper to 400 tokens per second almost up to 500 in many cases for some workloads. And th…”
Assertion Not checkable as stated
Moe: Most AI API services use open-source inference engines under the hood
“And this is where kind of, this is why open source inference is the current leading way right now instead of closed source inference engine. And frankly, right. All the, a lot of the open, a lot of the open, sorry. A lot of the influence cloud and API as a ser…”
Prediction Not checkable as stated
Simon Moe: Users will default to open-weight AI for trusted use cases
“In the future, we'll also see for the trusted use case, people will go to open way by default because that is where you know for sure that the guardrail is lessened or you can control your guardrail for trusted use cases.”
Insight
Moe: LLM serving differs fundamentally from traditional ML workloads
“Serving large language model is a fundamentally different problem. Because serving it requires to run it on accelerators like GPUs or TPUs, and it is a computationally intensive process that will require a lot of engineering and ensuring that for each request,…”