Ep 501: Inside Google Cloud Next: Gemini AI updates that create new possibilities.

Topics Covered in This Episode:

1. New announcements at Google Cloud Next
2. Google Gemini 2.5 Pro and 2.5 Flash updates
3. Deep research capabilities in Google Gemini
4. Canvas in the Gemini app and use cases
5. Veo video generation and live API availability
6. Google Firebase Studio evolution from Project IDX
7. Gemini 2.5 Pro use cases and performance
8. Live API in AI Studio and future work interfaces

Episode Keywords:

Google Cloud Next, Google Gemini, Google Gemini AI Studio, Logan Kilpatrick, Google DeepMind, AI updates, Google Gemini 2.5 Pro, Google Gemini 2.5 Flash, Developer tools, Deep research, Gemini Advanced, Canvas feature, Vibe code, Video generation model, Veo, Live API, Android integration, Google ecosystem, MCP, Internet sentiment analysis, Competitive analysis, AI-powered creativity, AI in business, Connected data, Personalization feature, Google search history, Creative tools, Vertex AI, Text-to-music, Updated Chirp, Firebase, Firebase Studio, Project IDX, Integrated development environment, Browser-based development, AI-powered coding, Multimodal capabilities, Live API, AI interface, AI advancements.

Podcast Transcript

Jordan Wilson [00:00:16]:
There's so much new that was just announced at Google Cloud Next. I'm having a hard time wrapping my head around it. It seems like there was dozens of new AI updates. So I said, what better than to bring in one of their leaders to help us make sense of it all? So, we're gonna talk a little bit today about what's new inside Google Gemini, Google, Gemini AI Studio, like, everything, with Logan Kilpatrick, the senior product manager at Google DeepMind. Logan, thank you for joining us a second time.

Logan Kilpatrick [00:00:49]:
Yeah. Round two. This is gonna be I don't even remember what we were talking about for round one. It feels like it was it was super recently, but, there's a ton of new stuff to talk about, so I'm happy to be back.

Jordan Wilson [00:00:58]:
Yeah. Absolutely. So, you know, top to bottom, I mean, we saw new updates with, Google Gemini 2.5 Pro being rolled out in other places, a new model in Google Gemini 2.5 Flash. Right? So many things for developers, but where do you start? Or maybe, like, what are you most excited about that was just announced here at Google Cloud Next?

Logan Kilpatrick [00:01:17]:
Yeah. That's a great question. So I've been continually excited about 2.5 Pro. I think, like, we're we're seeing 2.5 Pro sort of rolling out across our developer products, our consumer products. It just landed in deep research yesterday, which, like, folks have been super jazzed about. I think if you're a if you're an advanced, Gemini advanced user, you get, like, 20 deep research queries. You know, our customers prefer the sort of Gemini Advanced to two, with 2.5 Pro, sort of two to one versus sort of other products in the market, which I think is just sort of a nice proxy of, like, actually, this model unlocks new stuff from a deep research perspective. From a Canvas perspective, getting to see if folks haven't tried Canvas yet, in the Gemini app, being able to sort of vibe code and agentically sort of write code for you without having to be a developer is, like, such a such a cool and special experience.

Logan Kilpatrick [00:02:04]:
So that's what I've historically been most excited about. I think today now at at Cloud Next, we're, you know, tons of new stuff launched. Veo is available for developers, which if folks haven't seen, is our sort of state of the art, video generation model, which has been awesome. We just announced the live API, which I think a lot of folks and actually, like, in parallel to that, the live mode is rolling out to some customers in in Android, I think, as well. So, like, there's everything happen like, one of the things that I've been most happy about is it feels like more and more we're getting to the place where as these new capabilities come online, they end up sort of ubiquitously across the Google ecosystem, which is really cool because, like, you know, some people are a Gemini, you know, user. Some people are Google AI Studio user. We've got enterprise users. We've got people in search.

Logan Kilpatrick [00:02:45]:
And, like, I think it's awesome to sort of get to a place where new thing launches available everywhere for for the world to use. So I wanna quickly dive into two of those things that you mentioned there. So the deep research, I've been blown away, not just by, you know, I

Jordan Wilson [00:03:00]:
I think there's a couple times you guys updated it. First to two point o, and now I think to 2.5 pro. And, yeah, you talked about some of the benchmarks that came out in terms of, you know, the preference. I'll say it. It's against OpenAI's, right, which I thought was a great, you know, a great offering. But, you know, now seemingly, your guys' is way, way better. You know, what are you even using the deep research tools for? Like, I I love asking the people that build it. Like, what are you using it for? Because I think people can learn from what you're using it for.

Jordan Wilson [00:03:28]:
Yeah. That's a great question.

Logan Kilpatrick [00:03:29]:
I think some of the stuff, like, not, the the two use cases that have been top of mind for me. One, I was looking up, like, what the general sentiment is about MCP. If I haven't been following, there's this we won't we won't dive into the MCP thread in this conversation, but you haven't done MCP before, haven't looked into it, use deep research. It gives it actually, like, pretty robust answer and, like, gave me a bunch of supporting materials. I'm, like, not just how people on Twitter are thinking about MCP people. Like, it's an agentic way of interacting with, with tools. So that was one of the use cases because I was just very intrigued to know, like, what happens when you do that. The other one is I've been doing a bunch of, like, sort of competitive analysis of just, like, as we think about, you know, how we're showing up in the market, what do we look like comparatively against other providers? And this is a really interesting like, I think for me, the deep research conduit has been really interesting because what deep research is actually able to capture is sort of, like, the information that's available on the Internet.

Logan Kilpatrick [00:04:28]:
And I think it's like, you know, could I go and talk to customers and, like, get this perspective? Yes. That's actually a really interesting and useful perspective, but it's actually also interesting to capture, like, what is sort of the codified perspective on the Internet of, like, how people think about, you know, the Gemini API or AI Studio or something like that. So it's been really interesting just to, like, have that experience. And, like, it it actually, like, diverges from in some interesting ways, like, what what people tell me in person about, like, how they think of the product is used and all this stuff. So re really interesting if folks haven't done that exercise. If you have, like, a product that you built or you have, like, a favorite thing, like, just, like, ask the deep research, functionality in in the Gemini app, like, to put together a report and, like, see how that differs from your point of view or from, yeah, your perspective.

Jordan Wilson [00:05:13]:
Yeah. And another thing you just talked about there is kind of, like, you know, vibe coding in Canvas. So Canvas has been out, what, like, two weeks? Two weeks. Something like that. Right? Like, I use it so much already for a tool that's only been out two weeks. But maybe walk people through some of the, you know, practical applications. I think a lot of people are, you know, like, oh, like, let's, you you know, create a game and, like, that's fun to get started. But Yeah.

Jordan Wilson [00:05:33]:
You know, in terms of, you know, business utility, what are you all seeing as as some of the more, impressive or useful applications for the new Canvas mode inside Gemini?

Logan Kilpatrick [00:05:44]:
Yeah. I still think we're in the era of, and and I think, like, chatbots in general were in that place for a long time, and I think they've sort of just have in the last, like, six to eight months, like, gotten out of just, like, being sort of a novelty item. And I and I think, like, Canvas is sort of still in that realm where it's, like, it can do interesting things to your point, like, building games from scratch. Like, I it would take me a long time to program a game from scratch right now. You know, be AI being able to do that is awesome. But, like, where does the practical business value come in? I think for a lot of people, the practical business value comes in, like, when you're connecting this thing to your company's data and, like, all the and, like, that's the kind of stuff that doesn't exist yet today, at least in the sort of Canvas environment that we have. And it's what I'm most excited about because I think, like, ultimately, for these tools to be useful, like, you need to connect a bunch of your stuff to them and sort of let them, you know, have access to your email, and then I can sort of build a tool around my email to do it. So I'm I'm really excited about that.

Logan Kilpatrick [00:06:36]:
And I think from my, like and I'm I'm not, I'm not a product manager on the Gemini app, but I'm a I'm a consumer of the Gemini app, and I and I love it. And I think it's a it's a great product. One of the things that I'm most excited about is, like, this trend of the Gemini app sort of becoming this AI interface and this AI conduit Mhmm. To, like, all of the things that are happening inside of the Google ecosystem. And, like, the the sort of pertinent example of this is the Gemini app also, in addition to all the other Canvas stuff and deep research and everything else going on, it has a personalization feature. And the personalization feature is actually built based on your Google search history. So you can opt in to be like, hey. You know, basically, personalize the answers that the model's giving based on Google search.

Logan Kilpatrick [00:07:16]:
And, like, that sounds very, like, uninteresting at the surface level, but it starts to get to a world where, like, AI is this interface to, like, connect to this, like, vast set of data. And I think about this for myself in the work context, in the personal context. Like, I'm on YouTube all the time. I'm at Gmail all the time. I'm searching stuff all the time. I'm in docs all the time. So, like, it's really wonderful to be able to sort of bring all that experience together. And I think Canvas is, like, the first step of that with Docs specifically, with code now.

Logan Kilpatrick [00:07:43]:
So I'm I'm super excited.

Jordan Wilson [00:07:45]:
Yeah. And and, you you know, if you haven't had the time to use, Canvas yet, I highly recommend it. Right? It's literally being able to, you know, run and render code. You don't have to be able to even know coding. It's it's so easy. So, another thing, Logan, there that you mentioned is is, v o two, and and, you know, some of the new capabilities, in that that are available, in in Vertex as well, you know, adjusting camera angles. Right? What does this do for creatives? Right? There are so many new things I wasn't even expecting that were announced today. You know, the the the text to text to music, right, the updated chirp.

Jordan Wilson [00:08:19]:
Like, what is this gonna do for creatives, and and how does this all unlock, you know, both in Vertex and AI Studio?

Logan Kilpatrick [00:08:26]:
Yeah. I think my I think the general trend that gets me excited is, like and I was just having a conversation actually with the folks in the Vertex team about this and they and they sort of agree, which is, like, this general up leveling of people to be able to, like, go to the next level. Like, I'm not a creative. Like, I'm also not a game designer. Like, in the game design use case, I couldn't build a video game. I've tried before. It's horribly difficult. It's not it's not fun to sort of bash your head against the wall trying to do that.

Logan Kilpatrick [00:08:48]:
I think there's a lot of cases where that's true in the video use case. Like, you and me, like, you you we're talking off camera. Like, editing video is, you know, tough, and there's a lot of great tools out there that help do it. But, like, it's still kind of a pain in a lot of cases. And to be able to have all these AI tools, like, start to take those steps and, like, up level the people who are really excited and, like, take out the stuff that I'm not interested in doing, I'm super excited. I think, like, Veo specifically has been the one that folks have done, like, losing their mind for a long time. And this is actually, like today is the first time that this with the exception of YouTube where it's, like, set up at a very specific product experience, it's the first time the, like, raw model is, like, generally available to the world to actually get their hands on, which feels like a crazy, Yeah. I don't think it's been as crazy of, like, a public moment yet as I think it actually is in reality, but, like, the world's best video generation model is, like, now available for people to actually use and start building.

Logan Kilpatrick [00:09:40]:
So I think we're gonna see the technology start showing up in lots of new interesting ways.

Jordan Wilson [00:09:44]:
Yeah. And it it it was impressive. And we'll share in the newsletter today, the demo that they did. I'm sure that Google's gonna be posting that online. Right? But being able to, you know, kind of do the the live shots of Las Vegas and animate them and put them to music, super impressive. Something another new, you know, update here, Fire Firebase, is is is that what it is? Right? Like, did Google just release, like, an IDE out of nowhere? Like like, tell us tell us what Firebase is. How does it work? Yeah. Yeah.

Jordan Wilson [00:10:15]:
Yeah.

Logan Kilpatrick [00:10:15]:
This is a great question. So there this is some slight developer context. So if you're not a developer, some of this stuff might not, it might not be relevant or might not make too much sense. But so the original incarnation of that product, which today became Firebase Studio, was a was something called Project IDX, which we announced last year at, at Google IO. And the intent of project IDX was like, how can we build a next generation, IT integrated development environment for developers to actually use, in the browser, which I think was the unique like, today, developers, like, download a local, ID onto their computer and they do their development locally. This was bringing the IDE to the develop to the to the browser. And sort of the next iteration of that product suite, and this was being created by the Firebase team, which is why it ended up as Firebase Studio. The next iteration of that product is how do you actually not just, like, do the basic developer environment, but how do you infuse AI into that? And how do you sort of help developers bootstrap actually going and creating apps and and products and stuff like that? So I'm super excited for Firebase Studio.

Logan Kilpatrick [00:11:16]:
I think it's like the, for folks who aren't close to Firebase, like, Firebase has a lot of, like, street cred as being, like, an incredibly, like, developer centric team and product surface. So I think I I haven't spent a bunch of time with, I spent a lot of time with IDX. I haven't spent a bunch of time with Firebase Studio yet, but I I have full conviction that that team is is gonna knock it out of the park. And, hopefully, we'll see, like, more of these tools that enable, folks who aren't developers actually to, like, start coming in and and and building stuff like they couldn't before.

Jordan Wilson [00:11:45]:
Yeah. You know, one thing just getting back to, you know, 2.5 pro. I, like, I think it's worth gushing about it a little bit, and I love that in the keynotes. So, you know, it was mentioned that the LM Arena and, you know, I think it came in with, like, a 39, lead over the second models when it was released. How good is Gemini 2.5 pro? It's it's mind boggling to me. Like, when I use it inside AI Studio, like, I feel like I'm stealing something because it's so good. It can handle so much data. Like, and it's free.

Jordan Wilson [00:12:15]:
And and and it's free inside AI Studio. Like like, talk talk about, like, maybe some of the the best use cases that you're seeing for Gemini 2.5 pro. Yeah. That's a great great example.

Logan Kilpatrick [00:12:23]:
And I actually think one of the interesting thing and I had this conversation with some of the folks on the DeepMind team is, like, sometimes actually you see, like, a 40 jump on some benchmark somewhere, and, like, it actually doesn't even tell the story to the completeness of, like, just how much better it is. There's also this, like, other and then I'll I'll answer your question directly. There's also this other thread, which is, like, every time a new model comes, there's, like, an entire class of new companies that weren't possible before that, like, just become possible. And, like, it feels like that's true when you get this, like, massive jump in capabilities. I think 2.5 pro is actually one of those models where, like, there's a bunch of new companies now that are possible. I think there's a lot of coding stuff. It is interesting that it's, one of the things that makes me most excited is that as you see these, like, general purpose frontier models, like take a step function change in capability. It's like across every use case.

Logan Kilpatrick [00:13:17]:
So like you, like, I think the one that's like, didn't work really well before that now works really well is coding. So like lots of people are like very excited about the model's ability to do code, but like I've seen tons of creative writing examples. I've seen tons of people using 2.5 Pro as, like, a harness to build Adjantic products, which is a little bit, like, in the weeds behind the scenes. Yeah. So and and I think this actually we haven't even gotten to, like, a bunch of the yet yet to be released, like, a bunch of the multimodal stuff that I think we're seeing with two point o Flash, which was another thing I think that happened since the last time we caught up. There's too much stuff going on. It's hard.

Jordan Wilson [00:13:50]:
It is certainly hard to keep up with. Alright. So it it is hard to keep up. You know, Logan, I know you're a busy guy. You have you have to go speak to, you know, thousands of people. But, you know, as we wrap up today's expedited, conversation, because, you know, maybe we'll have to get you on a third time. But, you know, what are some of the you know, even speaking of kind of like a new class of companies. Right? Which is great with, like, a great way to think bit with Gemini two point five Pro.

Jordan Wilson [00:14:14]:
But, you know, what are you most excited about from this weekend? And, you know, or maybe for the average, you know, everyday business leader, what are you most excited for them Yeah. To get their hands on? And how do you think, you know, kind of like there's, oh, a new class of companies now. Is there going to be a a new class or a new way that we do our everyday work because of what was announced here?

Logan Kilpatrick [00:14:36]:
I think the live API is that. And we we hadn't talked about it yet, but the live API is is basically this. And I I don't remember if we did demos at what I don't think so. When we do before. But if folks haven't tried this out, ai studio, .google.com/live has this experience where you can come in and you can talk to the model. You can share your screen. The model can actually look at your camera if you give it permission. And, like, it creates this really, what what I think is this, like, future of how people are going to work, which is the models can actually see the stuff that you see, which I think unlocks, like, it takes it takes the drudgery out of having to use AI tools, which like my personal perspective is today, the challenge with using AI is that you, as the user of the AI product, have to go and do a bunch of work to bring all the context of the model.

Logan Kilpatrick [00:15:19]:
And, like, oftentimes, like, for me as the person who wants to use AI, I'm like, the context is already there. I'm looking at it on the screen. Like, why is this so much work to, like, take that information and go bring it over to whatever AI product? And it's, like, a very simple thing that all of these new that back to the thread of, like, new classes of companies to be built, all of these new companies and products to be built, you just flip that switch and then all of a sudden, like, you know, whatever the random product is that you're using can see your screen and, like, help you reason through whatever the problem is that you're trying to solve. It can, you know, bring in real information in real time from Google search. It can execute code on your behalf, like, all of this, like, really, really interesting stuff that I don't I don't actually think we've seen products built yet with this technology, which gets me excited because I think it's it's gonna

Jordan Wilson [00:16:01]:
be wicked. Alright. It's it's an exciting one. A fast but furious interview, just like what we've seen so far out of this this conference, Fast and Furious updates. So, Logan, thank you so much for taking time out of your day to join Everyday AI. We really appreciate it.

Logan Kilpatrick [00:16:15]:
Yeah. And for folks who aren't watching on video, Jordan has a sweet Everyday AI, Nike shirt, which looks awesome.

Jordan Wilson [00:16:23]:
Yeah. Now You're crushing it. Now now now would it be, any like, just drowning out with requests for it. Alright. Well, hey. Thanks, thanks again, Logan. And if you want more, we talked about a lot in a very short amount of time. It's all gonna be in the newsletter.

Jordan Wilson [00:16:35]:
So if you haven't already, please go to youreverydayai.com. Sign up for the free daily newsletter. Let me know. Should we bring Logan on for the third time, the first person ever after five hundred episodes to be on a third time? Alright. Thanks for tuning in. We'll see you back tomorrow and everyday for more everyday AI. Thanks, y'all.