YouSaid · the spoken record

Zed Inam

lines on the record: 45
first: 2023-05-15
most recent: 2023-05-15
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, and on the customer side, I could see how it could actually be, you know, you could even say fun or entertaining with the integration of technology. Imagine that you're talking to a bot and not only does it serve your problem, but it's also in the voice of like your favorite cartoon character. And it's telling you answers in a way that you're actually following a story. And actually, oh, because they've done all this back-end research based on these customer conversations that actually you leave the conversation with a better deal than you had before. And you didn't have to spend three hours on the phone to get there. Like actually, as we're talking about this, I'm like, wow, you know, you go from, as you said, a negative NPS industry, you could actually imagine that these things could be fun and frictionless.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Building. And then for the stuff that people want, like frictionless experiences, there will be things that they don't want to interact with the human about at all. And those are like, we can provide those in a fully digital sort of frictionless manner that they can deal with if they want to deal with a bot. And I think that's where it's headed. Because once you have systems that handle the repetitive, like reactive things and you move to become strategic and proactive.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“What I think it looks like is this concept of like, I remember when we started the company, Tim and I, we got this video from our first customer that brought us a video of what their vision for the contact center of the future looked like. It was one of our first customers who basically had this idea that they had a contact center of people that didn't sit at computers anymore. They just would walk around, they'd have a piece that they were using to talk to customers. And all they were focusing on was the interaction with the customer and the relationship building aspect. And on the back end, like the system is doing the data entry, the filling of the form, all these things. It's like taking care of all the stuff on the back end. And like the agent's not typing anything, they're not doing any data entry. They're not doing any summarization. They're not looking up the customer record. That stuff is handled by the machine and it's handled in a way that the human can just like focus on how do I build a good relationship and resolve this customer's problem or like help find them the right product for their solution. And that's naturally what humans are great at, which is that sort of empathy and connection and sort of relationship.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“As we close out, let's return back to where we started the contact center. Let's say we're in 2023. Let's jump to 2028, five years from now. Given the technology that we have today, also the change in the cost curve that you mentioned, which sounds really fundamental, what is the context center look like in 2028?”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“With all these considerations, it's easy to get caught in the weeds. So let's take a step back and imagine a future where companies have successfully deployed this technology. Not as a gimmick, but in a way that successfully gets their customers closer to their goals.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“It's also not zero risk. A lot of companies intentionally delete their data. People will have retention policies on email. But by doing that, Eliminating knowledge, and that knowledge could be useful sort of like in the first instance, just like I want to go back and search. That's the thing I think a lot of big companies deal with as they start to have record retention things, but there's also second order value to that in terms of could that inform a model or a potential different applications for how you could learn from what your organization has done historically. So I don't know where we're going to wind up on that. I do think you're right that a lot of companies are realizing the value of their data and their IP and thinking about that in a deeper way. And once again, I'll just say I think already operating in the data space, both at Hex and previously, we already have this appreciation for people being really paranoid about their data, people really caring about where their data goes. And so in some ways, there's nothing new for us here, but I think there's all sorts of really exciting opportunities on how you could use data that customers are trusting you with making sure you're continuing to earn that trust.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Think one interesting facet of all this is that there's kind of this realization of the value of data. And I think we're going to see a lot more companies retain their data for longer, collect more data from their products or from their users. And so there's this, again, this privacy security posture of like, okay, we want to have this data. We're probably going to keep it for longer. How do we keep it safe? But then there's also a cost element, right? It's not necessarily free to retain data. It's also not free to run these models. And so how do you...”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I mean, that's such a great point that the search engine itself still has utility to find all the information that at the end of the day feeds into the language model. Brings up a really important point around price. These models are not free and we're still in the early innings of figuring out the right business models for LLMs. How much should they cost? What value add would allow certain providers to charge way more? And is it worth integrating into multiple models to reduce price or platform risk? Something else that feeds this equation is the cost to maintain data, which is also not free. Here is Barry reflecting on the deep relationship between dollars and data.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Ship a white label ChatGPT. They combined that with being searched on the back end and I think combining Of the language model as sort of like the reasoning engine, but you still need kind of like an information retrieval engine to make that truly powerful. And the unison that really... Is valuable. And that's maybe I'm speculating here, but like maybe had something to do with the being price hike. Like it is not true that language models make search engines unnecessary. If anything, they make the search engines more valuable because now all that data that you can search becomes like 10x more powerful because you can use that to get to your answer with like, you know, one tenth the effort or in one-tenth of time.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Exactly how we're thinking about it. And for us, it's kind of like there's so much innovation happening in that space. We don't want to be kind of tied to any one provider. So I think a lot of the value that we can provide is really about combining the language model with the pieces of context and the structured understanding of code that we have. And it's funny that you mentioned the kind of bing price hike. I thought that was like a big proof point and people noticed because like when ChatGPT first came out, I think a lot of people said like, hey, this kind of replaces search engines, right? Like I could just chat with this thing and it would tell me the answer instead of me having to go and click through a bunch of different results and figure out the answer myself. But then as people started to use language models a bit more, they started running into more hallucinations. And I think it was like the release of Bing where people finally realized like being released integrated chat GPT or GPT-4, you know, one of those like awesome like open AI models. But they didn't just like”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“That's amazing because something that also relates to is cost, right? Like each of these different models has a different cost. I think a couple weeks ago Bing like 5x their pricing overnight, right? You have a dependency as well, both source graph, but also that ends up filtering down to your customers. And so every one of these models, I mean, I think we're still in the early innings and there's going to be so many more developed. And each one will, to your point, will have a different security posture. It'll have different pricing scheme. It'll probably, you know, there'll be a range in terms of its efficacy or specialty in certain areas. And so, you know, it never dawned on me that actually, you know, you could offer.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Give you the option. So, right now you can use Claude, which is Anthropics flagship model. You can use ChatGPT, which is kind of the OpenAI model. And we're looking to integrate additional models too. And there's also kind of like different models that we plug in in different pieces of code, right? So there's kind of like the chat-based models, which are often like the largest ones. But there's also things like the embeddings model, right? That's what we use to generate. The embeddings vector is that we use to do really good kind of like fuzzy semantic level code search. And we have an open source model that we fine-tuned, and that's actually like the best embeddings model that we have. But I think our mentality is just like the language model aspect of this. We want to make as pluggable as possible.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“That they built that they want to use, and some are like, hey, can you give us something that we can self host? Desire as a business is to do what's best for our customers and users. And right now, that just means whatever's the latest and greatest on the market, let's try to plug it in and see how it does.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“It's especially pertinent to us because we have a lot of enterprise customers that are very security and privacy sensitive to the point where one of the reasons we made it self-hostable is because we wanted to enable companies that didn't want to put their code bases in the cloud to still have like awesome understanding and code search tools. So the space is fast evolving and our mentality is like, look, we have a wide range of customers from like very conservative large enterprises to like fast moving startups that have different risk and security profiles. The language model in our overall architecture is just one component. The other components being the source graph code graph and the various other developer tools that we want to integrate in kind of an open way. And so we want to make it possible to kind of like bring your own language model to the table. Some of our customers have negotiated separate deals with model providers as they want to use that model. Some have in-house models.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“A lot of these companies that are integrating AI are building off of just a few models, right? A lot of people are familiar with OpenAI's API that came out recently. But there's also that very interesting dynamic that a lot of the same companies that may even consider themselves competitors are using similar models. And so how did you think about that? And also there's this kind of layered question as it relates to security and privacy because depending on the company that you are, your code is actually. Potentially somewhat all the way to extremely proprietary, right? If you're talking about like a self driving car company.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Like social apps benefit from network effects, it's actually not crazy to imagine that even if certain products are built on the same models, first movers that incorporate customization may maintain an advantage. Because if you spent months or even years personalizing a model to your specific needs, would you want to do that again? But as these platforms collect more information about your preferences and potentially even train models on your data, certain companies may build a data moat. But that's also where privacy comes into play The future of privacy and security in AI is a complex and evolving issue, especially since your competitors may be on the other side of that API call. Companies are rightfully asking questions about data collection and data storage.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Thing too is, and I talk about the team all the time, like it's kind of what we've already been doing, which is building really thoughtful, well-constructed user experiences and UIs. Like you could say that there's very little moot for a lot of things we or a lot of other SaaS companies do inherently in their products. It's really how do you put these pieces together and how do you build a really great user experience, both from the pixels on the screen to thinking about performance behind the scenes to things like docs. that all sort of combines to being a really superior product experience and it's stuff that we're three and a half years into taking super seriously then i do think that long-term generative ai large language models they will change a lot of like fundamental assumptions”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Being hosted on the cloud is not a differentiator in any way these days. I think there's a few places where potential moats emerge. One is we do have a pretty great data advantage. Already having hundreds of customers, thousands of users writing millions of lines worth of SQL and Python, we can use that sort of rich information. We're not using it to train models, I should be very clear. Like that's one thing we've been very upfront with our customers about. We're not training models where they would expect to ever have some code they've written be a completion for someone else, which is a problem in other places. But it's more like using that actually to personalize for that person and their team, like, you know, again, like which schemas you're using, what is their code style been like in the past? Like having all of that information in people who are already doing that work in Hex gives us a big advantage.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“We've already seen that Done to some UI elements that look very familiar. Yeah, the models themselves are commodities, and that's going to accelerate even in the next couple years. We're going to see a ton of different types of models emerge. We're going to see the costs plunge even further down. I think the ability to plug these in will become as ubiquitous as like using cloud services. It's just like everyone does it.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“A model in terms of the amount of context you're passing. And so we've been really thoughtful on iterating through and finding what's the right level of context to pass through between what else is going on in the project or the underlying data schemas. It's everything you're doing before you're sending requests to that API of like building the right context, understanding how you're iterating on how different models are going to respond to different types of prompts and different amounts of context, how you're potentially even chaining together different types of models or different modalities of models together in one sequence in US and then how you're giving that feedback to the user.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“A bunch of things here. I think there's some UI things we've done as an example in Hex, you know, we kind of have these code cells that you use. And so we put a lot of thought in that like, what's the right way to interact with that? Is it like a comment completion? I think giving people feedback on what's happening, some of these models like the latency is still really high. So even something small, like just being really thoughtful on like how you're exposing to the user, what's going on and why they're waiting. I think one of the things that we've observed sort of more on the back end in terms of increasing completion rates is when you're building prompts, I think we were tempted early on to try to shove as much context as we could in. You kind of figure like the more I can tell this model, the better. You realize you can pretty easily confuse.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Will generate the code AI sure can feel like a black box. So designing a UI that actually guides the user is also becoming a differentiator, at least for the time being, where you're effectively nudging users to want to interface with these new tools, but also come back. Learnings in terms of what is increasing completion rates, what is getting people to actually interface with this new in some ways superpower within the app, because there is the flip side where if it's hallucinating or if it's not helping them or in some cases it may even be hindering their workflow, they're not going to return to it. So how are you thinking about designing that?”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Even look at things like this is the typical way this organization is formatting their charts and infer how they might want their visualizations to look. And so there's a ton of context we get because we're incorporating this in an existing set of workflows that can help us create the right context and create the right prompt to pass to the model. And I think with all of this right now, again, our focus really is on augmenting the data professionals. Like this is not like, you know, trying to build some black box thing. It's actually like we have a rule as we're building these features. It's like we don't run the code for you. Like we will generate the code. We will show it to you. But we want to keep the human in the loop.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Under the hood, we are doing a ton in terms of constructing the right prompts and parsing responses back from the model APIs we're using. And so again, we have thousands of people already writing SQL and writing Python and doing data work in Hex every day. So we have a ton of information we've got. We're connected to their database schemas. So we see the structure of their data. We see past queries and past code they've written. So we know which tables and columns are most frequently referenced. We have information about the project they're building. So we know like, oh, this project is already referencing as part of the schema and that's probably the relevant data for this.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Opportunity, I think that exists in the market is that you can do that exact same thing if you can collect proprietary data sets that are unique and at that same scale. And you can actually sort of train foundation models that are available to do even more. So like the internet or the web pages are fairly static sort of language modeling task where you're sort of doing a task and you're trying to complete the next token or the next word. But the kind of things interact with in the contact center, which is like what dialogue and action on you're interacting with someone and then you're working with enterprise software and systems of record to like fill out basic things. It's both sort of this intersection of two sets of data sets that don't really exist together. And then that sort of enables us to then train.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“So we learn from Beyond that what you feed models really matters, and that may be an opening for differentiation relative to competitors. But part of that equation is just the data that you have access to. Here Zed commenting on the value of creating proprietary data sets.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“And I think it'll make it possible for us to build a much more pluggable ecosystem. Like when you think about the wide, wide world of context that you might want to pull in to answer a question in your mind as a developer, it's not just the source code or the markdown documentation. Maybe you're searching through your issue tracker. Maybe you're searching through chat messages. Maybe you're searching through. Google Docs Notion for the latest product spec. And by virtue of being open source, we make it much. Better and friendly kind of ecosystem into which we can plug in other developer tools and other pieces of context that aren't necessarily tied to a proprietary compute platform.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“The other major distinction I would draw from a lot of other offerings on the market is we are trying to build this as much in the open as possible. So like Cody, the other extension, we've released as open source under the Apache 2 license. And we think that's kind of like the right mentality to build the standard AI editor assistant that every dev should use. We think that there's like a natural inclination among developers. I'm a developer myself. I prefer to use open tools.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Human, you might go back through some recent history in your editor to see how does that code work? How did that code work? And use that as a pattern matching reference point for the thing that you're currently writing. But more often than not, I think you're doing stuff like go to definition, find references. Let me see a couple of examples of how to use this particular API that I just imported. I think that that's going to lead to much better results. I think it's also going to lead to much more kind of introspectable results. So getting beyond this like, oh, Elms are magic. How do they work? Is it AGI? You know, whatnot? Cody will actually tell you, like, hey, I read these files, and these are the files I'm using to generate an answer. And if it completely returns a lie or is wrong, you can usually... An answer.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“I think the way we think about it, as far as I know, Cody is the only AI enabled editor assistant in our coding tool today that fetches context as broadly as we do. You can ask Cody a question like, hey, where is the SAML auth provider to find my code base? Or where's the GraphQL search API defined? And Cody will actually go and convert that to a couple of search queries, his source graph, and surface these relevant snippets of both code and documentation. Use that as like concrete references to answer the user's question. And that's in contrast to the way that Copilot works today. It's purely kind of like autocomplete driven. And the context that they fetch to do that autocompletion is kind of like recent files that you've opened in your editor. So it's kind of like this very local context, which works amazingly well. I mean, like huge credit to that team. We think that the next evolution of that is providing more relevant context and essentially emulating what a human kind of does when you're trying to write code, right? Like you as a”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“They don't really know the answer. And so that's a place where we thought we could be uniquely positioned to help because SourceGraph, you know, with all the pieces of context that we have around searching for code and finding references and verifying things actually exist, we are kind of like the perfect fact checker, if you will, for the language model and perfect relevant context provider to the language model.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Our first kind of major push, I would say, is this editor extension called Cody. And essentially what it does is it's a chat-based interface, but also allows you to search for stuff in context in the code. And the idea is that we wanted something in our editors that took full advantage of the power of language models, but also kind of addressed a lot of the challenge that people have encountered with large language models, namely the tendency to hallucinate facts when they don't really know the answer.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“And so, in that case, I do think leaning towards transparency is the best sort of thing there because long term, you want to sort of be known as a company that doesn't mess around or you tell the customers as it is. And it becomes like an interesting topic as well on the topic of accent masking, right? Because that's another use case of the technology that's sort of coming to market where folks can use this technology to sort of mask accents or change accents or these kinds of things. And it's the same thing, right? Where if you're not upfront about it and like there's like some edge case that comes up and it becomes like clear do you want to take that risk to your brand reputation or not?”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“At the end of the day, if you are a brand, you are fundamentally building trust with your subscriber or customer base, right? And your brand value is like sort of, hey, I can call up this company and they'll take care of me or I can trust them.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Earlier this year, we launched the closed beta of what we call Hex Magic. Magic is basically a set of AI tools built right into the Hex UI. And so it lets you generate an edit code. For example, this morning I asked it, you know, what's our count of paying customers broken down by pricing tier with summer revenue? And it wrote me a SQL query that did that. Or you can say refactor this Python code to be a function and it will do that for you. It also has features to document your codes, which is really useful if you're staying at like a super complex query or something that someone else wrote. It's like, what's going on with this? You can ask it. I'll tell you.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“And that's like the missing piece of all this it's a bi directional thing, right? It's like you're serving the customer, but you're also serving the business. Information in all this. For me, it wasn't spreading example of this. It's actually Andy Gross. Intel was originally a memory business for a very long time. And the start was a memory business. And then there was like what Andy calls a strategic inflection point where there was a 10x difference in the cost of memory production. And so all these Japanese manufacturers were sort of able to produce memory in like this 10x difference and it sort of completely changed the dynamics of that market. And it's funny like the way he phrased it, but the salespeople at Intel came back to headquarters, a Japanese salespeople, and they would say the customers are no longer as respectful as they were. Like that was like the first signal that he got that something is different in the market. But that was an input to him that ultimately led to him traumatically pivoting and changing the strategy of the company to become a microprocessor company because they realized that the market is completely changing. Customers are changing customer reception to their products is changing and to their salespeople and that they need to hard pivot the company.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Same, and that's ultimately the best way to build companies and products. And artificial intelligence is amazing at that because what's possible now with large language models, what's possible now with sort of very advanced deep learning is that you can summarize, you can sort of synthesize, you can pull together information and context in ways that they can take huge amounts of data, make it super simple to understand, and get to insight and get to understanding really quickly in ways that the conversations were unstructured, not parsable, like they were sort of on legacy on premise, like audio files that you'd have to listen to one by one for 20 hours to figure out what the heck's going on. And now you have like this super advanced human level speech transcription to human level summarization, human level sort of question answering that sort of helps these companies get to just the next level of iteration as a business.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“There's just a lot of nuance and data and understanding okay, how does my customer perceive when I make this offer? What is the context that they're coming in with? And that really informs their market strategy in terms of what's the new product that they should launch, what's the new package or pricing that they should bring to market. Like that's a way that a company can accelerate its development based on just having a very, very close ear to the ground and like a real strong pulse of the customer.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“So, like a great example of it is when you have thousands and hundreds of thousands of conversations with your customers, the nuggets of information about product feedback that you can use to sort of improve your product or improve your how you position your products in the market or how competition is changing. Specifically, we work with companies that are large telecommunications companies that sort of are constantly looking at evaluating how are the pricing and packaging their various phone bundles or various cable bundles bundles.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“When you look at artificial intelligence, I think there's really two ways to look at it. There's one way to look at it, which is lazy artificial intelligence. And that's basically I have an existing process that my business does right now. I'm going to take that process end-to-end and I'm going to automate it. And AI is really good at that. There's another way to leverage AI, which is more like an accreative approach, which is understanding my job or my role as a business is to deliver the best possible customer experience or the best possible product experience. And so the information and the knowledge that's in my conversations with my customers is one, like just really great ways to build strong relationships with my customers. But two is just like a goldmine of data information about my product, my market, my competitors, what's happening, how the world is changing.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Absolutely. I feel like most people don't need a reminder of how brutal that job can get because they've been on the other side. Now, many people jump to thinking that AI should replace the context center in customer service agents, but Cresta instead has its eye on transforming a historically low NPS job into one of mastery and creativity.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“Not employee net promoter score for contact centers often less than zero. So generally, it's not a role that folks sort of end up sticking with for a long time for a few different factors, sort of seasonal demand for increased contact center volume, you have relatively low wages and then sort of high inflation environment. And then you have overall sort of pretty high stressed job. It's like sort of taking phone calls, frustrated customers and customers in that kind of environment, those things add up and leads to like sort of a relatively higher turnover environment.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“But looking ahead, that may not be the case. The same way that your users don't care if your web app was built with Angular or React, or if it happens to be running on AWS or Heroku, the use of AI alone will not be enough to win over users in the long run. Instead, there will be a whole host of ways that companies differentiate as they cleverly embed AI with a nod towards solving their customers' core problems. And that's precisely what seems to be the topic of conversation in every boardroom. CEOs are asking how to best integrate this new superpower, but they're also asking important questions around data privacy, competition, cost, accuracy, and also doing all of this really quickly.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“2022 was a breakout year for AI. As several new tools gained mass adoption. In fact, many have even claimed that ChatGPT is the fastest growing app of all time. And despite machine learning being embedded in many applications already, for millions of users, these tools felt like their first real world encounter with AI. And that's because tools like ChatGPT or Midjourney have put AI at the forefront.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source
“It is not true that language models make search engines unnecessary. If anything, they make the search engines more valuable because now all that data that you can search becomes like 10x more powerful.”
2023-05-15 · a16z Podcast · Embedding AI: The Questions Every CEO is Asking · IDENTIFIED FROM THE TRANSCRIPT · source