The Fast and Curious blog series you know and love is back! This time, we are bringing you all things AI. Watch the 3-minute video below to learn how we break down the enterprise barriers to GenAI adoption (or you can read the full transcript that follows).

Below is a transcript of the video:

Welcome to Season 2 of Fast and Curious – the AI Edition. Everyone, everywhere is talking about Generative AI and Large Language Models. Having said that, large enterprises have not widely adopted Generative AI, and for some very legitimate reasons.

In this series, we’re going to talk about three of the big enterprise barriers to GenAI adoption and wait for it, how we’ve solved for them. So, let’s get started.

Number one on our list of GenAI blockers is: Intellectual Property Restrictions.

The basic problem is that, how can I know whether the text or responses that we’re getting back from an AI system are okay for us to use? That is, how can I be assured that the AI is not using some source material that might have a copyright restriction or an IP restriction because that might make me liable as a result. The flip side of that is, how can I be guaranteed that whatever I send to an AI model won’t be used by the model and sent to someone else at some other company? 

The press about employees inadvertently doing just that has been pretty scathing, so everyone and every company will want to avoid that.

That is the number issue that we have seen that gets talked about. While it’s the biggest issue, it’s not the only one.

Number two on the list of concerns is: consistency.

Experts talk about GenAI as being stochastic models. What they mean by this is that there is some randomness in the results that they generate. Sometimes AI can even generate false answers. The kinder euphemism is to say that the models hallucinate. But, a wrong answer is still a wrong answer. If you are an expert in the field, you may be able to figure out how to tell the difference. The advantage of these systems, available to everyone, is that you don’t have to be an expert, so errors going unnoticed are a real risk.

Last but not least, number three is: cost or availability of the system.

GenAI models use GPUs generally rather than CPUs, and that is expensive and it’s in short supply. Maybe I should say, they are in short supply, so they are very expensive. This is the reason that NVIDIA became a trillion dollar company last year. Even big players like AWS and Microsoft Azure have a scarce supply of GPUs, so you can imagine how in demand they are.

To recap, issue one is IP Protection, issue two is Consistency and fighting hallucinations, and issue three is Cost.

If you are an enterprise CIO, CISO, or Chief Data Officer trying to figure out how to provide GenAI to your employees that all of your users are clambering for and are trying to overcome these barriers, watch out for the next episode of Fast and Curious about these solutions.

Can’t get enough of these Fast and Curious videos? Well, we want to hear from you! What topics should we cover next? Drop a note in our inbox to let us know: info@solvewithvia.com.

In the fifth and final installment of our summer learning series, we talk about zero-knowledge proofs and how they can be done right in just three ways. Watch the video and read the transcript below as we give the summer edition of the Fast and Curious a farewell for now!

Below is a transcript of the video:

Welcome back to Fast and Curious, the 2023 Summer edition.

Happy to have the opportunity to speak today. We’re going to talk a little bit about zero-knowledge proofs and particularly, doing them right.

It’s great that this mathematical obscurity from the 1990s has now become commonplace in certain parts of the Web3 and blockchain world. Software libraries and technologies are developing quickly in this space. We’re happy to have the opportunity to be involved with that.

But, they’re not as easy as they seem. And there are three practical tips that we’re gonna give here. Three tools to help people identify how they could be better in this space or make use of it.

First is, how do you create the ZKP?

It turns out that this is a more complicated endeavor than your average website or HTML page. It does involve some math. It is a mathematical property, and so you do need somebody who has some math skills for the specific application that you are creating. There is some good news about that, though. It’s getting easier. There are more tools and libraries available, and there are more and more ZKPs being created by others and being offered. And you may, for your specific use case, be able to just borrow or license the ZKP you need for your application.

Point two, how do you know whether the ZKP works?

By definition, the whole point of the zero-knowledge proof is zero knowledge. So, in that world, do you just trust that the code is working as promised, that the guarantee is real? Well, we think independent testing or having a third party who is trusted to be able to validate and say, “Yeah, that thing does what it says it’s gonna do,” is the best possible way. From our perspective, look for the people who are, or that is a trusted authority, and you can work with to validate and verify your zero-knowledge proofs.

And then the third one here is around cybersecurity.

We talk about blockchain. We talk about Web3. But it’s all just software. And software that is doing anything valuable at all, is going to be attacked. We live in this world where you can expect that. And so constant vigilance, as they say in Harry Potter, is the word of the day. You need to make sure that the software you’re writing is cyber secure and meets some cybersecurity standards, but also that you’re keeping up with a list of critical vulnerabilities and updating your software to make sure that there aren’t new vulnerabilities or it doesn’t become susceptible later.

With that in mind, from a VIA perspective, we work with a lot of folks in the Department of Defense. If you follow us at all on our blogs and announcements, you’ll have seen that. It’s not a secret. And one of the big reasons is that the DoD has terrific cybersecurity standards and a very published and public list of what they’re looking for. And we feel like if we’re meeting their standards, then we’re meeting a standard that could be met in the external world.

For our zero-knowledge proof specifically, most of the ZKPs are actually in energy. Did someone turn down their thermostat? Did they charge their EV at a certain time? Did they not charge their EV when they were supposed to? The Department of Energy has stepped in and offered help for testing and validating our zero-knowledge proofs, and we’re excited to see, so far so good, very positive results from that. And, we feel like having that imprimatur from third parties is valuable.

Can’t get enough of these Fast and Curious videos? Well, we want to hear from you! What topics should we cover next? Drop a note in our inbox to let us know: info@solvewithvia.com.

In the third installment of our summer learning series, we give a quick introduction to zero-knowledge proofs and an example of how they can be applied in cryptocurrency.

Below is a transcript of the video:

Welcome to Fast and Curious.

A question we often get around zero-knowledge proofs is “That sounds complicated.” So, we’re going to do a super high-level overview here for folks. In data privacy and data security, historically there have been two extremes of methods or approaches.

On the one hand, you’ve got an option which is keeping the data so private and so secure that no one has access to it. That’s beneficial to data security, but basically not very beneficial to anybody who wants to make use of it.

There’s a second option on the other extreme, which is: I’m going to sign some paperwork, provide a file or access to somebody, and I’m going to trust that they do the right thing with it and keep it private and confidential. That’s the other opposite end of the spectrum.

At VIA, we had a notion when we were in our very early days that there had to be a better, software intermediated way of dealing with that. We bet that blockchain and Web3 technologies were going to be the foundation of it. And it turned out to be true. So, the Goldilocks way is not too restricted, not too risky. The Goldilocks way is actually through something called zero-knowledge proofs, and we’ve been working in that space for a little while.

You ask the question, what is a zero-knowledge proof? And how does that actually work?

I’ll give you the quick example from cryptocurrency. Zero-knowledge proofs have been around since the 1990s. They more recently came into popularity from a software perspective because of cryptocurrencies.

So meet Mary and José – not their real names! Their identity has been protected. Mary is saying, “hey, I’m gonna send some cash to José.” José says “that’s terrific.” But then he says, “wait, I didn’t get the money. Did you send it, Mary?”

How are they going to resolve this dispute? In the old days, if Mary was going to wire money or send money to José, they would probably know each other, they would know each other’s names, and they would have a bank that would intermediate that transaction.

In the newfangled cryptocurrency, NFT, blockchain world, Mary and José by definition don’t know each other, right? Part of the benefits of blockchain-based transactions is anonymity, and the other benefit or the other challenge in this case is its peer-to-peer. There is no intermediary. So how can José reconcile the fact that he did or didn’t get what he was expecting from Mary and vice versa. Mary says, yep, I did or can verify that transaction.

And that’s what zero-knowledge proofs are.

It’s essentially a piece of software code that can verify this transaction happened. José got it or didn’t get it without revealing either José or Mary or their identities or any details about their bank accounts.

And if you’re interested, there are actually terrific videos by experts that explain a little bit more detail about exactly how that works, from both professors as well as Up and Atom, that you can find at solvewithvia.com on our blog page.

That gives you the nickel summary. We’re excited to have the opportunity to use and leverage that same zero-knowledge proof technology in new areas like energy transactions and identity. And you can read or see more about that in the upcoming Fast and Curious.

Disclaimer: In the spirit of staying current with the fast moving tech world, these videos are done in one take! The result is they are fresh but may be a little rough around the edges. Enjoy!