01:29:49 · Jeffrey Morgan, John Coogan
[01:29:49] S3: 65,000,000. The lead was Tamash Tungus, and we had existing investors participate too, like that. [01:29:57] S1: Awesome. Fantastic. So tons of GitHub stars. Why how does this fit into, like, the the value add to, businesses versus just, downloading the model themselves from, from an open platform, getting the the actual, the weights themselves, deploying things, or just going with an API? Like, how are you talking to Fortune 500 customers about, how you will actually improve their experience with something like GLM 5.2?
01:30:31 · Jeffrey Morgan
[01:30:31] S3: You know, the power of open source is how fast it can build trust with developers around the world. And it ends up a large number of developers work at work at companies that work at, you know, a lot of those in the Fortune 500 or Global 10,000. And open source has a special, you know, capability where you can deploy it in your own environment and not have to think about a ton of security and compliance. And what that means is, look, you can take an open model, which already has open weights, that's kind of why open models are perfect for these use cases, and run them without any approval really as a developer and get real successful results all without having to expose your data or even incur big costs. So that's really been the driving force of being able to get into these large businesses. And to your point, look, just the way it's being open isn't enough. You need a way to deploy them, to run them, to make sure it works on your hardware. For the cloud models, you know, you really need to make sure that you're running them in a secure environment where your company can access them. You know, a lot of a lot of businesses we talk to, especially Fortune 500, they need these open models hosted in The US and in Europe. And that's just a requirement, and it's it's a need they have. And so, you know, put put that all together, it's it's so surprising and incredible how fast it can get adopted.
01:31:43 · John Coogan, Jeffrey Morgan, Jordi Hays
[01:31:43] S1: So what does I mean, you say you're you're you're talking to these Fortune 500 companies, but I imagine that the fact that you have so many GitHub stars means that there's a lot of self serve activity. When does a customer cross over to an enterprise relationship with you? [01:31:56] S3: Yeah. Generally, it starts with the individual dev. Right? They bring it they bring it to work. A lot of them use it, you know, for personal productivity. Sure. And they bring it to their team. And once you're using a team, it's not a one one person store anymore. Right? There's there's a team there. Right? And everything from security to technical architects, IT teams. You know? And and these folks, they they need not just a product that's really, you know, easy to use and self serve, but they need a solution that really kind of end to end covers things like safety and monitoring and logging and data storage and protection. These are all components of a successful agent deployment. And so that's when it becomes a multi party environment. And as we know, that's when you need a solution. And on our side, we need a team to be there to help those customers. [01:32:39] S0: What set of models are you most excited about for the back half of this year in the open weights world?
01:32:39 · Jordi Hays, Jeffrey Morgan, John Coogan
[01:32:39] S0: What set of models are you most excited about for the back half of this year in the open weights world? [01:32:47] S3: I mean, I think with DLM five point we just had another massive moment in open models. And, you know, Olana by far, at least from what we know publicly, is the highest token volume of accessing DLM 5.2. And so I'm excited for that. I think there's going be a series of new models that are long horizon. They're focused on these really hard agentic use cases, and there's going to unlock so many use cases in enterprise that the prior generation of open models couldn't. The gap between open models and the frontier models is shrinking, And so, you know, I I think at that point, you we're able to get to these incredible use cases that just weren't there, you know, three or four months ago. [01:33:23] S1: Take me through some of the game theory in the open source community around those rumors that we heard that there might be export controls on open weights models coming out of China soon. If if if we stop getting frontier or or or near frontier open source models from China for free. Is the next step that you would see an American company step up, NVIDIA, or maybe Meta changes their strategy? How are you thinking the open source ecosystem would evolve if China changes their strategy?
01:34:02 · Jeffrey Morgan
[01:34:02] S3: Yeah. We like to work backwards from our customers. What are they trying to do? By and large, they may have preference on specific geographies where the models are from, but by and large, they're adopting both. And some mix of open models and frontier models as well. And to your point, I think The US models are absolutely stepping up. They're incredible. The Nemotron three Ultra model is just amazing and is able to accomplish some of these long running agent tasks. And then also, you know, one of the most downloaded models on the llama is a US model. It's the Gemma models. You know, this is like a super amazing team at at DeepMind that's bringing them out. The new ones are, you know, agent ready. Like, can run coding agent loops. They can accomplish much harder tasks. And so, look, I think it's really up to the customer. If they want a US entirely US built model designed from scratch, that's there. If they want a Chinese model, which is often the case, they it's less about where the model's from. It's like, where does it run? And is it running next to your data, which, you know, a lot you can deploy it locally and then are you able to deploy with safeguards? And ends up a lot of customers, they're not looking for, like, where the model's from. They just want make sure that they're running it properly and safely so I think, you know, they can have a a understanding of what's gonna you know, what could go wrong, but what could go right. And and there's a lot of safety tooling that can be deployed to help with that. They have tons of appetite for that.
01:35:19 · John Coogan, Jeffrey Morgan, Jordi Hays
[01:35:19] S1: What do you see your role as in terms of benchmarking reality checking, vibe checking, different models, helping enterprises that work with you to make the right decision, pick the right tool for the job? [01:35:34] S3: You know, our job fundamentally is to connect the 9,000,000 developers on Ollama to the right model for the right task. And that's that's step one. And so just by having that sheer volume and that this critical mass of devs, we're able to already understand just from, you know, our community which models are performing right for the right tasks. That's a starting point. I think from there, it's really collaborating with the Model Labs and we're launch partners with every major Model Lab and just making sure that the best parts of the model are shining through through Alama, including what are they capable for, what are their benchmarks, how can customer customers benchmark it for their own use cases. Sure. It it all comes down to a lot of software tooling and and and and and, you know, a community in a in a network. And that's Mhmm. Kind of what we built and and it's what makes Ollama special for developers. [01:36:20] S1: Got it. $65,000,000 raised. Is this like, what are you using the money for? Because you don't have the crazy training costs because you're more of a gateway. Is this head count off [01:36:31] S0: 2,000 BDRs. [01:36:33] S1: Is that what banging down here. Wait. Wait.