YouSaid · the spoken record

Beyang Liu

lines on the record: 82
first: 2026-01-20
most recent: 2026-01-20
sittings or episodes: 1
sources: podcast

Every line below is reproduced as it was said and linked to the record it came from. Nothing here is summarised or generated. Directory · Search · Corrections

“Yeah, regulatory lock and that sort of thing. Essentially, don't let the Internet Explorer versus Netscape thing play out the way it did in Internet 1.0 with the AI ecosystem.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Do as much as possible to ensure a dynamic and competitive AI ecosystem within the US. I mean, the best thing that we can do, I mean, we're America. Like the best thing we can do is to take a step back and let the free market function. And so to that end, like ensuring there's kind of like a standard, like Nationwide set of regulations that's clear and well specified to be going after specific applications and application areas rather than general existential risk at the model layer, that would be good. And then two, just ensuring that there's competition at the model layer, avoiding any sort of anti-competitive behavior.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Paradoxically, this is the greatest case you could have ever given to the large social networking giants. They're the only ones that actually could have the legal teams and the policy team to navigate this stuff. And we saw this up close as investors. We're like, as soon as these things came up, it basically entrenched the incumbents who could come play.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Going to come down to some decision maker within that bureaucracy, and they're going to make a judgment call. And hopefully they lean towards going after the bigger fish in the pond before they come after you. So, personally,”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“You know It reminds me back in the day when we were looking at GDPR compliance, when that was the first thing. And I was talking with our legal team and external counsel and trying to read the text of that regulation and figure out like, oh, is this thing technically in violation? It seems kind of high level. And the answer I got was like, look, honestly, these are underspecified. And it's really like.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I think that could very well be the case. And I think the way that the regulatory landscape is evolving doesn't help at all as well. Because there was an effort earlier this year to have kind of like a federal set of standards for AI model layer regulation. But that, I think, fell apart. And so now we're kind of like slow walking, in some cases fast walking towards this patchwork quilt of state by state regulations.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Where are the US models? And why aren't they there? And I guess my best guess, I mean, again, you both can gutjack me on this, is like, actually, there's Like all of the rhetoric around developer reliability, even though it didn't happen, but there was rhetoric around it, all of the policy stuff, all the copyright stuff, all the lawsuits. My guess is that, you know, a lot of these folks are gunshy.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“You know, I honestly don't know. I don't have inside knowledge of what goes on inside a lot of these research organizations.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“We haven't seen something come out of Meta in quite a while. Are there even any open source models? So it's just very unusual for the United States not to do this. And like the efforts that have done it have seemed to be handicapped in one way. And so there's one view of the world that this isn't a tech problem. It isn't a money problem. We're already in the overhang of policy. Like that's one view. So like, I guess my specific question is, do you think that is the case or do you think we've just kind of Haven't kind of gotten to it yet, and we're going to come up with open source models.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, let me just give you an example. I don't know why OpenAI released the open source models the way they did, but it seems like they were very, very sensitive to what data was in them. And I presume this is a concern around copyright. I don't know the answer to this. I just assume that interesting.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“So, you know, you use a bunch of open source models. And there's a question that we actually debate quite a bit, which is Assume the policy environment exists as it is, even with infinite funding and infinite talent, could you still actually build competitive models or like now are we at a place that we're just at a disadvantage just because is it too late to actually assume that we can do it without actually changing policy?”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah. But then also when you think about making laws and regulations for this sort of stuff, if you've been sold on this sort of like Terminator style narrative, that's going to put you in a very different mindset with respect to how much risk tolerance you're willing to take on, how much innovation you're going to allow in the ecosystem, and your tolerance for open sourcing model weights.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Put it carefully. Yeah, I don't know, there's the old adage of like, you know, do you blame it on ignorance or malice? I honestly don't know. It's a black box, but it is like... It is clearly like nonsensical, and I think very much in the national interests to be still telling this story because it, one, it leads to kind of like overemphasis on the model as the end all be all of AI, where in reality it's like pushing the models into all these different application areas where the rubber meets the road and things become useful.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Exactly. So, like, now if you talk to practitioners, like anyone who's building it, and increasingly anyone who's using it, right? Because now, you know, ChatGBT has been out for like threesome years and everyone and their mom has used it. People kind of understand what the limitations are. So that narrative, I think, is largely been dispelled within our circles. But I think that it's sort of like taken on a life of its own in other circles and it's made its way to some of the halls of policymaking in the US”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, arguably that view of the model landscape was the right one in retrospect. And I think at the time people using these models directly kind of realize this, right? It's like you use the models. They can emulate intelligence of a certain kind, but it's like mostly pattern matching. And there's just like absolutely no danger that this thing's going to acquire a mind of its own and try to reach out to the computer and kill you.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“I guess that's the manufacturing aspect of it. But from where I stand, it's like if you go back to the quote unquote early days of the AI revolution back to 2022 or so, I feel like the narrative that was told that was like the dominant narrative was this one of like AGI at that point where it was kind of like this, it's like amazing new technology. It feels like magic, right? Like never experienced anything like this before in my life. Yeah. And then the narrative that was spun was like hey, AGI is nine. What does AGI mean? Well, either one, it's like utopia, all our problems are solved. This thing will just, you know, run our lives for us, or it's going to kill us all.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, down the street. And the U.S. still holds a lead in basically like every part of the stack, you know, whether it's chips or frontier intelligence. Basically, every place except open weight models.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“You know, so it is interesting. It's like the AI revolution was basically born and created in the West, right? On the street.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“You know, we've sampled a good portion of the model landscape because, again, we have all these sub-agents and agents, we want to find the best ones for the job. And frankly, the ones that we find most effective at agentic workloads, they're almost all, I would say they are all of Chinese origin right now. And that's not to say that there haven't been good efforts by American companies. It's just that when you plop those into an agentic application, the tool use isn't quite robust enough. It's not quite there yet.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“And so if the US Open Way ecosystem doesn't catch up, we're kind of in danger of the world migrating to a world where most systems are heavily dependent on models of Chinese origin.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so from that part, it's fine. I would say though, if you take a step back, it is fairly concerning because my view is that as the model landscape evolves, you're going to start to see a flattening in terms of model capabilities, right? Like there's going to be healthy competition at the model layer and there's going to be a number of options for choosing a model at a given point in the Predo frontier. And with that flattening, there's a strong incentive for application builders to at a given capability level use the one that's open for the reasons. Stated before. And because the most capable open weight models right now are of Chinese origin, it essentially means that like application builders around the world are choosing to post train on top of these models.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah. So, first off, in terms of our production setup, every model that we hit is hosted on American servers. So from an information security point of view, I think this is like best practice across the industry. It's like you don't hit models that are hosted in China or”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, exactly, exactly. All right, so listen, we're moving on on time here. So I actually want to get more to the policy side because I do think a lot of the way this goes is the way the model goes. The open source ecosystem, we see it all over the place, not even talking about source draft, but I would say if a company walks in now, that's a product company that's decided that they need to push train their own models. It's going to be on an open source model. And more and more of these are Chinese models. And so you mentioned that you do use open source models and Chinese models. So, how do you think about that as far as A, maybe just like the implications of the dependency and then B, what does this mean? Yeah. Maybe more holistically with the United States and the ecosystem.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, yeah. Like, it just feels like, you know, it's like we have like a Ferrari engine, but then part of our workflow still requires strapping it to this horse and buggy style thing.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“So we launched a review panel in our Editor Extension last week. It doesn't get all the way there, but I think it's the first step. And it's already like, it's way better than an existing code host review tool. It's mind-boggling to me that we live in an age where you can literally have a robot One shot a very large change, and then you pop over to GitHub PRs and you're clicking expand hunk, expand hug, expand hunk. No code intelligence can't edit.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, it's that, but also it's just like the task of reviewing code, I think, is a slog. And classical code review interfaces are just not that good. I think they were never that good. But it wasn't like blindingly obvious because the rate at which lines of code were shipping was.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, yeah, exactly. I mean, you talk to some devs and they're like, you know, I've never been more productive, but coding isn't fun anymore. And so, you know, that's one of the things that we're trying to solve for.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yes. And when you talk to practitioners today, a lot of them are very, it's like bittersweet. Because on the one hand, it's like, oh my God, like agents, they're writing all this code and they're actually pretty good at it. On the other hand, it's like, oh, I'm spending like 90% of my time like. Essentially doing code review now Which is, you know, like the one in 100 dev that you talk to that says like, I really love code review. The rest of us are like, oh man, it's such a drag.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“No, no, that's what I mean. Sorry, I just want to make sure we're talking about the same thing. Oh, yeah, yeah. Like a human has in their head of what they want to accomplish. Yes. And only the human has that in their head. Yeah, yeah. And so often that's going to require”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“You can't wish them away. And the human is the bottleneck, but I think the human is still essential and will still remain essential 10 years from now in software engineering because it's fundamentally a creative process. No, no, that's what I mean.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Make some manual edits when it gets stuck. But increasingly, like I would say by sure lines of code volume, probably more than 90% of the code that I write these days is through AMP. And I think it's only going to get higher and higher level over time. And so when we think about the interface that a human will interact with primarily, I think the future looks like something that allows you to orchestrate the job of multiple agents and crucially something that allows you as the human to understand the essentials of what these agents are outputting. And I actually think that's probably the limiting bottleneck today.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so here's my take, I don't think it's not going to be an ID that looks like any ID that exists today, and it's not going to be like a terminal that looks like any terminal that exists today. My view is that, and I don't think this is like a particularly unique view. It's just that, you know, the effect of AI on every single knowledge domain, including coding, is that it's just going to enable the human to level up, right? So the job that you do already, like that, like my job has changed so much in the past year. I think about all the kind of like toilsome like line-by-line editing that I did like a year ago today, it seems like completely foreign. I like honestly don't think I could go back at this point. Now when I'm doing stuff, it's more at the level of like telling the agent to make the specific edits or execute like a specific plan. And I'm really playing the role more of like an orchestrator. Now and then you still have to like pop in and”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“But there's like a mini Pareto frontier for each of these tasks, right? And the optimal point along that frontier is different for each task.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“There's It's basically per agent. Like every agent maps to a workflow. It's emulating some workflow That. Maybe approximately maps to something that a human used to do. Maybe it doesn't, but it's like a subroutine. This is why I go back to like the function analogy. And so for any given age”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“And once you have a specialized agent for each, then you take a look at what the agent needs to succeed and you try to get the model as small as possible while still maintaining the requisite quality bar.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“I think that's spot on, actually. It's like the very large generalist models were great, and they still are great for experimentation because it's almost like you train this thing on all sorts of data and it's almost like a discovery process where like the training team themselves don't quite know what behaviors might emerge. But once you map those to specific workloads, specific agents that you want to build, then you have much clearer target. you know, it's widely known that like a lot of the model labs do this now behind the scenes. They might expose an API that's like, you know, one model behind the scenes they're routing to smaller models. And you can also do that at the application layer. Like if you have an agent architecture like we do, there's all sorts of specialized tasks. Like we've broken down the process of software creation to various tasks like context fetching or debugging or things like that.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“You know, like there's a lot of product data out there, and there's a lot of users out there. And, like, you know, the solution domain is enormous. And so you can start building smaller models. And, you know, so it's like, you know, like A, is that correct? And B, you know, like the models that you train, do they kind of fit in that general pattern of Specific smaller models.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Probably pointless. These for special use cases, like a lot of the products that we work with, let's say just outside of coding just to like, a lot of products that we work with, you know, it just I mean, here's this general view. Free training is done Paying people to create data, we've hit economic equilibrium, right? It's like, You can keep paying people, but like, you know, we're hitting diminishing returns there because you need kind of more expensive people. Need 10 times more data. And so at some point you hit equilibrium”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean, for an agent right now, it's probably still fairly large, like talking to probably like hundreds of billions of parameters for kind of like a top-level agent. But for search agents, you could go smaller than that. And then we also have a model that does kind of like edit suggestions. So for those times where you still have to go into the code and manually edit stuff, this thing suggests the next edit that you'll make. And for that, we use a very small model, like single digit billions parameters.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“It depends on the workload. So I would say in our evaluations for kind of like the top level smart coding agent driver, we still tend to prefer sonnet or GP5. But for kind of like quick targeted edits or specific subagents, I think more and more we're preferring smaller models because they have better latency characteristics and because the complexity of the tax isn't high, like you reach a ceiling. It's like once you reach a certain level of quality, this diminishing returns and then you start optimizing for latency because that gets you more interactivity.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I mean, like, so, you know, originally there was Claude, right? Like Sonnet or Opus, that was the first agentic tool used model ushered in in the current agent wave But now, you know, there's GPT 5, there's Kimi K2, there's Quenfree Coder, GLM.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Faster, right? And so the benefit of having open weight models is you can look at the thing that you're trying to optimize for, like what that sub agent needs and post train the model to accomplish that more effectively. And the other element of open weight models that's very appealing is just the pricing aspect of it. Like there's now more and more effective open weight models that are emerging on the scene that are actually quite robust at agentic tool use. The landscape has changed immensely since like June of this year. We've gone from like, you know, there was really only one really good agentic tool use model to now there's like”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so we do use a variety of open source models. We use both closed source and open source models quite heavily. But the open source ones, I think, are becoming a bigger theme now for a couple reasons. One is with an open source or open weight model, you can post train them, right? Which means if you have a domain specific task, like AMP has a growing number of subagents that are specialized for a specific task like contact retrieval or like extra reasoning, library fetching. Those are more constrained tasks where you don't necessarily need frontier general intelligence. If anything, you want.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“That being said, I don't know, like maybe there's a third point in there that could make sense. Really just comes out of the vibes at the end of the day, like as we use this more heavily and see the usage patterns emer”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“And the fast agent is the one that's ad supported, like that we can offer for free. And the smart agent is the one where we're like, okay, we're not.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah. So, you know, it's funny that you mention this, the cheap option versus the premium option. It just so happens that AMP has two top level agents. There's a smart agent and there's a fast agent.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“But actually, as we kind of look in the market, it actually feels like most of the frontier is pretty full. Like developers are pretty sophisticated, like, you know, different, you know, there's different cost sensitivities, different price sensitivities.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“It's whether the Pareto frontier is what matters, or if it's kind of there's points on the Prater frontier that matter, right? So you can imagine, so traditional pricing psychologists You're the expensive one, or you're the cheap one. Yeah, right. And everything in the middle is called a value gap, which people don't use, right? And so originally we were like, oh, the Prater, like that happens here. So either you buy the most expensive one or you buy the cheapest one”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“This has kind of been an adjacent topic, but something that Guido and I discuss a lot is to what extent the market is Pareto efficient on the Pareto frontier. Like if you can trade off, let's say performance for cost or intelligence for cost, like will the market kind of adopt that uniformly or does it just optimize only for speed or only for correctness? Being on the front lines, we would love.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source
“Oh, they committed it, but whatever. Did it pass code review? Yeah, did the PR gangs? It was like a subtle bug introduced or whatnot. You know, did it get merged into main? Like, I mean, it just feels like, you know, yeah, yeah.”
2026-01-20 · a16z Podcast · From Code Search to AI Agents: Inside Sourcegraph's Transformation with CTO Beyang Liu · IDENTIFIED FROM THE TRANSCRIPT · source