No Priors: Artificial Intelligence | Technology | Startups
00:23:00 · Lip-Bu Tan
[00:23:00] S0: Thank you. Thank you. I just enjoy building it. But more important, I will look at this, first of all, on the investment side, I always look at where is the bottleneck? What are you trying to solve? For example, I invest in a company called Cradle Semiconductor, Australia Lab. Is this interconnect become the bottleneck? So I decided to back and also back Celestial AI in the optical side. And then because speed become more important in the interconnect, in the cluster, so I think optical become very important. Look at Jensen. He invest in almost every company is photonic related. And then the other part I'm looking at is, okay, what are the solution that need? Like, for example, we talk about design and then the complexity and also the cost. Can you find some using AI machine learning to drive a better design and better solution. So a couple of new startup actually go into the EDA related area to drive performance improvement. I think it's a gold mine to do that. And then the other part, you look at the new material. We talk about this indium phosphide. That's why I invested in INFI, and then Val bought it. And then you invest into some of the new material, the gallium nitride and the silicon carbide, and then some of the companies starting to being acquired, include one of them doing power management, and ADI is a sport called mPower. And so again, this IVR, that's a very, very good area in power management become bottleneck now in term of converting from 40 volt down to one volt. And then those in term of that conversion, you lost a lot of power. And how you do it through the power improvement? So I think power, thermal, those become the bottleneck. So I think I always look at from what is the problem we try to solve? Is it real? Is customer crying for it? And then I starting to invest. The next thing is look at it's very important from day one, you'd have to target the first customer. And usually, I like the customer is hyperscale. They have the scale. If they like what you have, they're willing to pay millions of dollars next few years, and even giving some warrant is worth it because you have a big one customer you can scale. So I always look at some of the formula, how do you do that, and then where do you get the talent? And then, yeah, you know, sometimes it's very important to find the talent.
00:25:22 · Lip-Bu Tan, Sarah Guo
That's why I'm really interested in US and then Silicon Valley and then some Austin, and then the other part is Israel. A lot of talent. So I backed quite a few, quite a significant amount of my investment in Israel. And then because they have very disruptive, innovative entrepreneur, They work really hard. Even in this war time, they still have conference call. And sometimes they say, okay, there's a warning. I have to go to underground. And then the internet may not be good. Maybe we just use voice. In some ways, it's kind of fun. They're kind of resilient entrepreneurship I really enjoy. So I think all in all, I felt that there's a lot of opportunity, and especially in the AI. And right now, beside the agentic AI, now you're looking at physical AI. It makes a mixed big frontier. And then you had to really look at a full stack. That's why I'm still involved with a lot of this frontier model that we very familiar and some of the investment I've made because I really like open source frontier, you know, technology for physical AI. I think that's a gold mine. [00:26:27] S1: You mentioned the opportunity to make certain parts of the design and test of chips faster, cheaper, more creative with AI. Given your Cadence experience, like, do you think is most fertile? Is there anything you think is already working?
00:26:27 · Sarah Guo, Lip-Bu Tan
[00:26:27] S1: You mentioned the opportunity to make certain parts of the design and test of chips faster, cheaper, more creative with AI. Given your Cadence experience, like, do you think is most fertile? Is there anything you think is already working? [00:26:45] S0: Yeah. I think, you know, for almost fifteen years with Cadence, and I'm so happy. One of my highlight is able to find my successor, Underwood, and I train him, and he becomes super great CEO. And then he really embracing the AI, driving the agentic AI to drive more efficient. But there's a good part, I think synopsis. Sachin also tried to do that, and they have an investment from Nvidia, 2,000,000,000, I think helping him to do a lot, and he acquired Ansys to move into the whole system design. So I think all in all, they all do the best thing they can, but also some opportunity for startup to do some of the more disruptive. And then eventually, they can either go public or being acquired by both of them or Siemens to acquire them. So I think there's opportunity for all, depending on what the entrepreneurial vision. And then as long as I always have philosophy. If entrepreneur want to sell the company, and there's quicker way for exit, you don't have to lock up. You don't have to worry about quarter to quarter earning. And then some entrepreneur, from day one,
00:27:52 · Elad Gil
[00:27:52] S2: they want to go IPO. For being a VC, I think three of you, with three of us, we all VC, we support the entrepreneur, their dream, and then help them to fulfill their dream. Yeah. If you look at the different areas that you mentioned in terms of future, either product development or impact of AI on the semiconductor industry, there's companies like Periodic doing materials. There's, to your point, folks working on the EDA side and design and other aspects and sort of throughout the chain as manufacturing. Do you think that either Intel or a future semiconductor company ten years from now looks radically different from today, given AI? And if so, how?
00:28:28 · Lip-Bu Tan
[00:28:28] S0: Yeah. I think so. I think, first of all, back to, Sara, your question about capital intensive and a little bit unpredictable and cyclical. So you have to kind of put that into factor into your decision making investment. And I usually like to go in very early, put a team together. It's kind of fun to do that. I think you also do that. And then secondly, you try to find the right investor that can co partner with you. It's not just whatever the brand name firm. I usually go for the individual. And then who are the individual that really knowledgeable in this space, you can The most important to find a partner to difficult time and good time. A lot of the time people are very enjoyable working with you is a good time. When the company don't trouble, they just walk away. I like to have partner that really work through a lot of successful company. They have multiple time almost bankrupt that eventually take off. So I think it's important to find a partner willing to do that. And then the other part is look at what are the strategic investor that can help you either in manufacturing or memory connectivity or various way to add value to the company. And also have a couple of friends that are in the growth stage and also in the hedge fund, and I really enjoy them because they have a different perspective. They know about the public market. They can guide the company entrepreneur where not to go. And so those can be very helpful. So I think all in all, I think it's just fun to do that, and then just realize is that engineering for startup is like problem solving. Each step of the way, you have to find people to help you to solve the problem. And then if you trigger that, then great, next frontier to work on. And then frankly speaking, I look back, nine of the 10 company I invest, halfway, they change their business plan because market have changed. Yeah. So I like to have entrepreneur as team, not just one person. Secondly, open mind. Willing to listen and listen to getting coaching from us. And then eventually they formulate their own plan. It's not just do what they want, it's more they figure out, the best thing is you give them enough feedback, they draw their own conclusion that you exactly what you like and all different, that you can embrace is the right decision. That's kind of fun of doing startup. They get much faster.
00:30:55 · Lip-Bu Tan
So back to your question, if you look at it ten years from now, what will be the winning company? This is just my personal view. The one that articulate and laser focus on one niche area and also find the right partner and also able to scale the company. And so in some way, and back to my point about full stack, so in the way you need to have a full stack solution. And so it can be a big company, they transform themselves to be looking at big platform, like Jensen, I admire him. You know, he focused on CUDA. He focused on Illipro. I want to be a platform company. And he did it. And so in some way, you can do that. Or startup company like Anthropic, OpenAI, they find a way to do it in a bit more elegant way. They change the game, and then it startup move fast, speed of light, you can really become a dominant player. And hopefully Intel can play the role because we have the XPU, and we have the advanced packaging, and we have Foundry. If you put that all together, can build some of the purpose built silicon for different workload. I think that's where I'm going.