$AVAX
Cooling DownSnapshot Window: 2026-07-13 21:00 UTC · ← Back to Crypto Overview
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We just added more $IonQ . Before they complete the 2026 roadmap, it's now or never. [Spoken audio]: Yeah, well, I think I think it's gonna be much broader, but for that we need a lot more participation as we spoke about earlier But you know keying into something Lee was saying along those lines right things that I think you referred to you know Something that was put on the back shelf 20 or 30 years ago because it was too slow, right? It was a classical problem that just didn't look good enough and then other algorithms You know kind of came up and became them the mainstream approach which, you know, this is very true in a lot of areas, a lot of fields. You know, maybe, I don't know, as an example in chemistry, right? Certain molecules, we just no longer, we stopped studying certain molecules and molecular structures because they were too complex or too hard, right? We stopped using certain algorithms because they didn't work with the architecture we had at hand. And now we have a new architecture, right? We have a new computing system. And so it's really interesting to look at how algorithm design, this new algorithm design could unlock methods that we actually did put on the back shelf 20, 30, 40 years ago. And with that, also, I think when we think about, say, molecules, maybe we're addressing 90, maybe 5% we put on the shelf, and 95% we've been addressing well. And that 5% now, it sounds like a small number. But if we actually dig into it, maybe that has potential, right? That 5% now becomes a huge field if you're able to use it well. So, you know, strongly, you know, where do we use quantum computing? In the molecular space, we're looking more where there's strongly correlated electrons, heavy metals, things that are very hard to approximate well classically. That set, now we can start to look at quantumly and it may prove very, very, very useful. Can you flesh that out for me? So in a very practical example, what would that look like? What, you know, a company has had a hard to solve problem, now quantum makes that potentially one that can be more tractable. What comes to mind? Well, pharmaceuticals might be an example or materials, right, where certain, you know, as I was saying with molecular structures, right? When it's strongly correlated, we can't get a high accuracy, right? And so we want to now look, there's things like in catalysis, right? Catalytic conversion, you have the like chirality, chirality matters, you wanna drive chirality so that you drive towards the more therapeutic drug as opposed to the harmful one and you wanna drive that chirality through a reaction. You have to drive that reaction with a catalyst. And so studying catalysts that can drive, you know, a right-handed chirality versus a left-handed chirality, which means therapeutic versus harmful, driving that reaction efficiently is very interesting. And so what we can start to do with quantum computers is for those reactions that have strongly correlated molecular structure, we can study that more accurately on a quantum computer and start to understand that reaction very precisely.