Transcript: Jaikumar Ganesh, Anyscale, on Reliable AI — Interview with Alexy

Hi, my name is Jaikumar Ganesh. I'm the head of engineering at Any Scale. Any scale is the company behind Ray, the popular software for scaling AI and machine learning systems. I think AI has enabled so many use cases. You know there is a small company called Halter in New Zealand which makes farmers a lot more efficient with their cow and they use AI to figure out where the cow should be going um in that particular farm on that particular day. So there is biioarma companies using AI for drug discovery. Right? So there is a lot of such use cases in different verticals which have impacted humanity in a positive way, improved efficiency and improved productivity. So that's what excites me about AI. I think reliable AI is a really deep topic. So reliable AI can mean different things for different people, right? So if you pull up chat GPD and it just works, that may be reliable for someone. And if you ask the same question, if you keep getting the same answer, that may be reliable for someone. That doesn't happen by default because of the way LLM's uh work. But reliability for me is more at a higher level. If a user wants to do X and whatever the AI system that they're using allows them to do X in a very efficient way without coming in the way and enables to achieve their goal. Um that's what a reliable AI is. It's like you know the magic moments. If AI can create those magic moments it can be a magic moment in a mundane task. It can be a magic moment in an exploratory task. when the user gets satisfied that for me is reliability. Yeah. So I think we at least people living in the Bay Area here uh are in a bubble and you know we talk about the latest AI advancements we talk about like GPU availability all those are real problems but there is a huge huge world outside of the Bay Area there are so many different industries which can benefit uh with AI. So coming back to my definition of reliability using AI techniques, AI agents, using AI applications, working with all these industries that Bay Area does not think on a day-to-day basis is what I believe Bay Area should focus more on. Some people call it quote unquote the boring AI. Uh but it's very very impactful. The AI stack has fundamentally changed as the technology has changed. Um, previously it used to be the LAMP stack, Linux, Apache, MySQL, PHP. Now we have a new stack. We're calling it the park stack. Pyarch, AI foundation models, agents, frameworks, ray, and kubernetes. P A R K park stack. And it's kind of funny because it has got AI within the AI stack in a recursive way. So this stack we are seeing adoption across lots of companies Pinterest, Uber, Roblox, Netflix, Apple, Shopify, cursor, bunch of these companies are adopting some form of this stack. So this is the AI infrastruct 3 to 5 years.