Bobby DeSimone

lot of people making stuff up so here's some more context you can imagine there's hidden enterprise demand for open source models that isn't visible but if you look at the top inference providers that aggressively go after this business, they have shared some numbers and they are all roughly the same size as us. and at best there's 5 of them if you think enterprises are self hosting inference on their own GPUs, there are so few people who can run reliable inference and they get paid a lot and work at ai labs. and if they really want sovereignty they're not getting that by leasing GPUs from a third party the root point here is this is entirely the wrong way to look at things, you just have to look at products how many products exist with a lot of traction that can use open models? this is what creates demand, it's not some magic thing that grows on its own OpenCode is one of those and we do see a lot of enterprise inbound. but it's so early, all of these companies are just starting to look at mixing in some OSS inference so yes demand will probably go up in the future but everyone in this industry is investing resources in preparing for that future. and so few people are building the products that will make it happen

This is correct. The vast majority of enterprise workflows have not actually had agents applied to them in any meaningful way. The economy probably has this deployed < 1% right now. At best you have a few automated systems in a company that do a single pass of an LLM to make a decision or provide feedback, but very little real “automation”. Some of this is a statement about the adoption rates of technology in enterprises, but the vast majority of it is really just due to the capability of AI itself. That’s all changing. Now with computer use, long running agents, harness improvements and surrounding infrastructure, we’re finally at a point where we can start to apply agents at more complex workflows. We will see self-improving systems that can take any particular workflow goal and improve the execution rates over a volume of instances. And with the emerging form factor of agent swarms, you can just choose to deploy any amount of compute at a problem and agents will off and do the work. This won’t be about and users prompting agents to complete a specific task for them, but instead the organization reengineering the underlying workflows to take advantage of agents in their processes. This will have a massive impact in finance, life sciences, healthcare, and other information-heavy domains. Lots of opportunity to build and deploy these systems right now.

Sometimes I think “how do all of these people know so much about ai and cybersecurity and biology” and then I realize

RE: Tailworm 1. The "report" is totally unreadable. I, as someone who is very familiar with reporting vulns and kubernetes, am totally unable to parse the sections on kubernetes. There may be valid bugs, but I can't tell. I would not have reported these as vulns in this state.

SITUATION DETECTED: CloudFlare CEO Matthew Prince says he is aware of additional severe vulnerabilities in other pieces of critical software, and said “I think we’re going to have a couple years where every single week it’s going to feel like the sky is falling,” per Reuters.

Insane number of security incidents in the last couple of days. CA leak, PHP CVE 10, Railway, Plex, LiteLLM to name a few. All would be year defining in a different era. Things are going to get much worse. And sorry, no, AI is not the "fix" here. LLMs are very good at finding needles (e.g. exploits).. They are shit at fixing them.

Why is Wiz taking any credit for this? Their blog post words it like they discovered it.