AI Enterprise - Databricks & Glean | BG2 Guest Interview

Think we have AGI. Mhmm. I think we have artificial general intelligence. We really have. You you hear these 95% of projects fail, but, like, you know, like, that's that's that's actually what you want. I I think the LLM is a commodity. People are not saying that, but it is a commodity. Like, you can get gas from this gas station. You can get gas from that gas station. It doesn't matter. Just compare price. Is AI in a bubble? There is an AI bubble. Okay. Okay. So then green is also in the bubble. Everybody's in the bubble. No. I would I would say there is a bubble. I I would say those three camps. Yeah. There is a super intelligence quest camp. Mhmm. I would be very worried there. There's a second. The researchers doing the, you know that's definitely not in a bubble. They're like the They're sober. Yeah. They're they're super sober and nobody cares about them. And then there's right? And they're probably the ones that are right, unfortunately. And then there's the third camp, which is us trying to make this valuable. We're not in a bubble in a sense that we're not spending huge amounts of capital on what we are doing. We're just trying to get actual economic value inside of these organizations. Two legendary builders, Ali, Irvin, I'm so thrilled to get into this with you because both of you have seen every super cycle I've lived through, Internet, mobile, cloud, data and AI, not just through the super cycles, but also through the hype, the trough of disillusionment, and this time, it's different. Today, we're gonna chop it up on the state of AI. You know, let's let's start with a 20,000 feet view. Take stock of where we are. AI, we've seen consumer AI, billions of users, Chad GPT said the guns went off three years ago, cloud, perplexity, Chad GPT. People use it in the room. On the SMB and developer side, you've got hundreds of millions of users with cursor and codex and cloud code and and and so on. Enterprise, on the other hand, there's a lot of divide. It's hard to see a lot of fog of war. On one side, you've got models that are earning math benchmarks and science benchmarks and engineering benchmarks. But on the other side, you've got the MIT report that's saying 95% of AI deployments don't work. What's the reality? Bridge that gap for us. Lay it out as you see it. View from the top. So I think, first of all, I think we we we should know that people use AI in their personal and work lives both. So there's not so much of a divide. Like, you know, everybody in your company is probably using ChargeGPD, and cloud and and other tools, on a daily basis. The, the the thing that I I feel, you know, is happening in enterprises, you you hear these 95% …