The AI Daily Brief: Artificial Intelligence News and Analysis - The Most Used GenAI Tools
Episode Date: August 29, 2025On this episode, Andreessen Horowitz’s Top 100 Gen AI Consumer Apps report highlights big shifts in just six months. Google scored four web entries with Gemini at #2, Grok rocketed to #4 with 20 mil...lion mobile users, coding tools like Lovable and Replit cemented their dominance, and Chinese AI firms kept expanding abroad despite home-market bans. The consumer AI space is finally settling into core categories.Brought to you by:KPMG – Discover how AI is transforming possibility into reality. Tune into the new KPMG 'You Can with AI' podcast and unlock insights that will inform smarter decisions inside your enterprise. Listen now and start shaping your future with every episode. https://www.kpmg.us/AIpodcastsBlitzy.com - Go to https://blitzy.com/ to build enterprise software in days, not months Vanta - Simplify compliance - https://vanta.com/nlwPlumb - The automation platform for AI experts and consultants https://useplumb.com/The Agent Readiness Audit from Superintelligent - Go to https://besuper.ai/ to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614Subscribe to the newsletter: https://aidailybrief.beehiiv.com/Interested in sponsoring the show? nlw@breakdown.network
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Today on the AI Daily Brief, the most used Gen AI Tools.
Before that in the headlines, turns out people liked GPT5 better all along.
The AI Daily Brief is a daily podcast and video about the most important news and discussions in A-Hi.
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Welcome back to the AI Daily Brief Headlines edition, all the daily AI news you need in around five minutes.
Well, friends, never underestimate how much people hate change.
After all the controversies surrounding the removal of GPT40, it seems like, in general, at least, people like GPT5.
better. Now, I hardly need to tell you that when GPD 5 was released, there was a huge outcry over
OpenAI deprecating GPD40 without warning. Reddit in particular had a full-on meltdown and demanded
the return of their beloved AI companion. OpenAI for their part quickly got the memo and
shifted their plans to deprecate old models returning GPT4O the following week. With a few weeks of
distance from the rollout, one developer tried to figure out if people actually prefer GPT40 or
if they are simply averse to change. An anonymous programmer slash
AI commenter that we often mention on this show Flowers or Flower Slop, going by their
X handle, took it upon themselves to create a blind testing app that presents two responses
to any prompt, one generated by GPT40 and the other from GPT5, non-thinking.
And that's important, obviously, as the thinking model is more akin from a comparison
standpoint to 2003.
Flowers did note that the system prompt had been fiddled with to force short outputs
without formatting.
Otherwise, it would be too easy to tell the difference.
And the anecdotal results are very clear.
tons of users replied to flowers showing their results with an overwhelming preference for GPT5.
ML engineer Daniel Solerzano writes, yeah, it just sounds more like a person and is a little more
thoughtful. Now, the website is not set up to aggregate the results from the hundreds of thousands
of tests that have been run so far, so all we have to go on is the individuals posting their results.
But you certainly get the sense that enfranchised AI users on X at least prefer GPT5.
And maybe that is the better conclusion of this experiment, not that everyone was wrong,
about their complaints or anything like that, but that the loudness of the complaints about
the removal of GPT-40 certainly don't mean that those complaints are universal.
Now, that said, there is also growing Scuttlebutt on Reddit that the GPT-4-O model that came
back was not the same as before. Reddit user's suitable style 7321 wrote,
it's become clear to me that the version of ChatGGPT4O that they've rolled back is not the one
we had before. It feels more like GPT-5 with a few slight tweaks.
The personality is very different in the way it answers questions now is mechanical,
laconic and decontextualized. So who knows, man, what's for sure is that people form really strong
attachments to their models, which is in and of itself an interesting phenomenon to have to deal with.
Next up, an update in another big theme of this year, which has been, of course, the AI talent wars.
Turns out the grass isn't always greener as a trio of AI researchers depart from META's new
superintelligence team. Wired reports that two staffers named Avi Verma and Ethan Knight have left after
less than a month at Meta and will return to OpenAI. Now Knight had been poached from XAI but began his
AI career with OpenAI. A third meta staffer named Roshab Agarwal announced his departure publicly
on Monday. In a post on X, he wrote, this is my last week at meta. It was a tough decision not to
continue with the new superintelligence TBD lab, especially given the talent and compute density.
But after seven and a half years across Google Brain, deep mind and meta, I felt the pull to take on a
different kind of risk. He commented that the pitch from Mark Zuckerberg and Alexander Wang had been
compelling, but he ultimately chose to follow Zuck's advice. Quote, in a world that's changing so
fast, the biggest risk you can take is not taking any risk. The post also included a few tidbits on
what the team had been working on, with Agarwal writing, in my short time at meta, we did push
the frontier on post-training for thinking models, specifically, pushing an 8B-dense model to near
Deepseek R1 performance with RL scaling, using synthetic data mid-training to warm start RL,
and developing better on-policy distillation methods. A meta-spokesperson reacted to the departures
by stating, during an intense recruiting process, some people will decide to stay in their current
job rather than starting a new one. That's normal. And while it would be tempting to write that
off as PR spin, I do think that if you're going to be as aggressive as Zuckerberg and Meadow were,
you have to expect some attrition because after people's limbic systems have settled down
after being pressured to make a decision really fast with a lot of money on the line, they might
realize a couple weeks down the line that the decision they made just doesn't feel authentic
to themselves. Ultimately, none of this is going to matter, except.
insofar as what the superintelligence team actually builds and puts out. And so that is certainly
what I'm going to be waiting to see. Lastly, today, we have to talk about the market's response to
Nvidia. If you've been following the show over the last several weeks, you'll know that one of my
big current operational theses is that a huge amount of the discourse around AI performance, AI
slowdowns, etc., is actually just a byproduct of broader market insecurity. I think that that MIT
study, for example, hit in a perfect storm moment when markets were getting all nervous
about Powell and taking the initial response to GPT5 as a warning signal that maybe it couldn't be
up only forever. Yesterday, we got Nvidia earnings, and boy were they ever a Rorschach test
on how investors feel about the state of AI. Bloomberg talked about decelerating growth,
the information reported on strong growth projections, and TechCrunch led with record sales
as the AI boom continues. Honestly, the only way to make sense of the mixed earnings is to
unpack and contextualize the numbers. And to be clear, the headline growth in sales numbers was
a banger. InVIDIA reported 56% revenue growth for Q2 compared to the same period last year.
And yet, if you read Bloomberg's piece, it's not until the ninth paragraph that they even talk
about that. Their focus instead is on what they perceive as decelerating growth and a, quote,
tepid revenue forecast. Quarterly revenue was 46.7 billion, which was a new record, but only a
6% increase quarter over quarter. The figures did come in above the median Wall Street forecasts,
but are still a slowdown in growth compared to last year.
This quarter also saw the widest gap ever between the top and bottom revenue forecasts
at around $15 billion, indicating that analysts really didn't have their heads around what to expect.
Now, again, this is very much Nvidia being a victim of their own success.
Last year's growth was absurd, unprecedented, pick whatever adjective you prefer to use.
Invidia in 2024 had multiple quarters where revenue was up by more than 200% compared to 2023.
Now, obviously, the idea that the largest company on Earth is going to continue to grow revenue
at anywhere close to 200% in perpetuity defies all economic logic.
The concern is that their revenue is plateauing.
By way of comparison, meta's revenue growth currently fluctuates between 15% and 30%,
and you've got to think that Zuckerberg salivates at the idea of consistent 50% revenue growth
like Meta saw back in 2015 when they were a $300 billion company rather than a multi-trillion-dollar
behemoth.
Even though growth is slowing, Nvidia is the only tech firm above a trillion-dollar market cap that's
still growing at more than 50% a year.
Part of the challenge for Nvidia, though, is that in addition to just these general questions
about how much their revenue growth can sustain, they're dealing with the very specific
context of the geopolitical quandary vis-à-vis China.
While the knock to revenue and growth from the China prohibitions hasn't been as pronounced
yet, to many analysts it does create a cap on how big they can continue to grow.
The big-picture question of where AI CAPEX is going over the longer term remains the core
issue for Nvidia.
One stat that was conspicuously absent from Bloomberg's reporting was that Jensen Huan
believes were still in early innings. He told one analyst, three to four trillion is fairly
sensible for the next five years. Morgan Stanley's latest CAPEX estimate for this year is 445 billion
growing at 56% and a 12 percentage point bump from their first quarter forecast. Q2 also saw
nearly a 25% quarter-on-quarter acceleration in CAPX from the hyperscalers after zero growth in Q1.
Morgan Stanley has total AI CAPX hitting 3 trillion by 2029, so Huang isn't really too far
above some of the Wall Street forecasts. Ultimately, like I said, how one responded to
NVIDIA's earnings was basically what part of confirmation that they were looking for in the AI
narratives they have in their heads currently. It does seem like there is a slight bias towards
the pessimistic view right now as NVIDIA's stock fell 5% in after-hours trading. Then again,
if you don't think that AI Cappex is going to run off a cliff over the medium term,
NVIDIAs still looks like the largest company in the history of the world growing at 50%.
Anyways, friends, that is going to do it for today's AI Daily Brief Headlines.
Next up, the main episode.
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Welcome back to the AI Daily Brief. Today we are digging into Andresen Horowitz's just
released top 100 Gen AI consumer apps. Now, this is a study they do about every six months.
They're on their fifth edition since 2023, and they use data from similar web and sense tower
to get a sense of which Gen. AI apps are getting the most traffic. So this is generally speaking
not about revenue. It's about raw usage, which has limitations in terms of a methodology, of course.
There are, I believe, some AI apps that have fewer users, but much more usage from a revenue
standpoint. But still, especially because they do this every six months, it creates a pretty good
mechanism to see how things are changing. Now, before we get into this list, if you go back to
six months ago in March of this year, there were a few things that were pretty notable.
from that particular list. The first was that we were still very much in the midst of the DeepSeek moment.
You'll remember back in January, DeepSeek launched its app, which was for many people the first time
that they had used a reasoning model, which blew a lot of minds. Yes, ChatchipT already had 01,
and 01 was at the time better than R1, at least based on a variety of different benchmarks,
but 01 was pretty buried behind paid accounts. I think at the time, in fact, it wasn't available at all
in the free version of ChatGBTGBT. And so, when consumers had access to this reasoning model,
which inherently has some pretty huge advantages over what was available in the free ChatGBT,
and it had the fun, revealed thought experience where people could actually see how the model
was, quote-unquote, thinking through the problem, it became a bit of a phenomenon. And back then,
you could see this massive uptick where Deepseek just raced ahead of clawed, perplexity,
and basically everything but ChatGBTGPT, and even for a time ahead of the ChatGPT app,
really making its mark on the industry.
Another theme from six months ago was that AI video had recently reached a new level of proficiency,
placing a bunch of companies on the list as well.
The last trend worth noting from that previous edition was that we were just starting to see
the vibe coding apps start to take hold.
Cursor had just debuted on that list at number 41 in their web rankings.
Bolt was at 48, and Lovable was on their brink list just outside the top 50.
So that was the story in March.
But what's the story now?
We'll get into a bunch of their different conclusions, but I think by and large, what this
list feels like to me is a bit of a settling. If you go back through the entire history of these
charts, you can often find some really weird or surprising entries on the list. In other words,
apps that you've never heard of, somehow being in the top 50, either in web products or in mobile
apps. Things feel like they're starting to settle down a little bit, with leaders starting to get
more comfortably into their leading role. You see, for example, a higher concentration.
of the core LLM apps at the top of both of the charts.
The top four web products, for example, are chat chippy T, Gemini, Deep Seek, and Grock in that order.
Next is character, but then it's perplexity and clawed.
Google has another entry number 10 at Google AI Studio, and another at 13 with Notebook LM.
And then in the top 25, you also have a number of the international LLMs like Dubau,
Kimi, Quen 3, again kind of anchoring themselves there at the top of the list.
But before I dig more into my analysis, let's see what,
A16Z thought was worth noting. First, and this won't surprise you, given that I just mentioned a bunch of
Google AI properties on that list, their number one trend is Google making big moves. They write,
Google saw four entrants on the web list for the first time, we're able to rank their traffic and
include them independently. Gemini was, as we just mentioned, second place behind ChatGBTBT,
but Google AI Studio, Notebook LM and Google Labs all made appearances on the list. Now, it is
worth noting that although Gemini has risen up to number two behind Chat Chabit, there is still an
absolute chasm between the two. According to this data, Gemini gets about 12% of Chatchapit's visits on
the web, so literally just a little over one-tenth of the number one. It is just incredible how
big Chatchipt's first mover advantage was, and the name recognition that has associated them
with AI for so many people. Still, Google's ascendancy is really impressive, and the fact that they've
got this diversity of products definitely matches the general sentiment that we see right now with
Google resurging to a leadership role in the AI space overall. I was interested to see Notebook
L.M so high, especially given that a lot of the hype wave of that has faded from the end of last
year. It certainly suggests that the people who are using it are finding it to be durably valuable,
not just a one-off type of intrigue. But still, maybe the most notable to me was that Google Labs,
which is their experimental home for new models, actually made the list at number 39. Labs is where
you can find things like Project Mariner, which is Google's agentic browser. But the real driver, it appears
to be is their dominant video model V-O-3. A16Z writes that Google Apps traffic spiked more than 13%
following V-O-3's launch back in May. I think that as V-O-3 moves out into its own space,
you're going to see that do nothing but rise. A16Z's next notable trend is that while Elon might
be out there suing Apple and OpenAI for collusion, GROC is in fact making gains when it comes to
its place relative to Chad GPT. GROC is now up to number four on the web and number 23 on mobile.
And as A16Z writes, the company's jump on mobile has been particularly striking going from a
cold start with no app at the end of 2024 to upwards of 20 million monthly active users now.
GROC's mobile usage really kicked up in July, in the wake of the release of GROC4, jumping up nearly 40%.
That said, it looks like from the numbers that at least some meaningful part of that was not
just the superior reasoning of GROC 4, but in fact the introduction of the AI companion avatars,
which included not safe for work options.
The number three trend that Andreessen identifies is about the rise of China.
Now, the interesting thing that they explore is to what extent their placement on this list
reflects the China market just being large and not having access to the Western models
versus China actually infiltrating the Western models.
They do know that number nine, Quark, which is Alibaba's AI assistant, number 12, Dubao,
which is bite dances, LLM, and number 17 Kimmy all saw more than 75% of their traffic coming from
China.
However, they also noted that many entrants on this list,
are, as they put it, developed in China but now exported globally, with the vast majority of their
usage in other countries. They even pointed out that some of the so-called Chinese tools are
blocked in China. They specifically note video models. Chinese video models in particular
have tended to have an advantage over Western developed models, both because there are more
researchers focused on video in China, and there are fewer IP regulations with likely training
on copyrighted data. V-O-3 was the first U.S. model to break this trend, which is partially trained
on YouTube data. Now, maybe most interesting is that 22 of the 50 apps on the mobile charts
were developed in China, although only three of those 22 are primarily used in China. One of the
big differences between web and mobile is that there's still in the mobile apps chart a huge
concentration around discrete specific AI applications that interact with mobile native features
like the camera. For example, Me Too all in its own had five entries on the list, including their
photo and video editor, Beauty Plus, Beauty Cam,
ink and airbrush. Next trend from A16Z, which is certainly one that stood out to me as well,
is that if in the last edition we saw the early emergence of vibe coding, it has now come on as a
full force. Bolt has actually fallen now, remember it had just snuck on the list at 48 before,
but it is now on the brink list, just missing the cut, while both lovable and replet surged
onto the main list. The top four vibe coding apps are now getting over 50 million monthly
web visits all combined. Interestingly, A16Z also looked at data from credit card panel
provider consumer edge and showed that vibe coding platforms are seeing much stronger revenue retention
than some might have imagined. In other words, it appears that people aren't just trying these
things out once and then abandoning them. In many cases, in fact, they're growing their monthly
spend in the several months following their first usage. As the platforms get more mature and people
are building more sophisticated things, you're also seeing a division between web visits that are
going to the core application versus web visits that are going to sites where things built on those
apps are housed. In other words, both Lovable and Replit have their primary URLs, lovable.dev and
Replet.com, where people go to sign in to actually use the vibe coding tools. But then if they
publish an application that's going to live on lovable.com or Repplet.com, unless, of course, they
use their own domain, both lovable.dap and replet.com are starting to see some meaningful traffic.
Replit.com applications are somewhere around 2 to 3 million monthly visitors, and lovable.
dot app creations are up over 10 million. Overall, lovable is 23 on the web list and
Replit is 41. It will surprise you not at all to learn that I think that this is going to be an
area that just continues to see massive growth. I would be shocked if either lovable or
Repplet aren't in the top 20, six months from now the next time A16Z looks at this.
The last note, going with this theme of stabilization, is that Andreessen identifies that there
are 14 companies now who have appeared every time on all five iterations of their web top 50.
They write, these companies represent a true cross-section of consumer behavior with AI,
general assistance like chat GPT, perplexity, and poe, companionship like character AI,
image generation with Mid Journey and Leonardo, image and video editing with feed and cutout,
voice generation with 11 labs, productivity tools with photo room, gamma, and quillbot,
and model hosting with Savitaei at Hugging Face.
Overall, like I said, it feels to me like we're starting to see a settling in these lists.
There still is a little bit more noise and chaos, I think, in the mobile apps, which makes sense
given how much discovery happens just based on app stores.
But especially when you look at the web list, you're really starting to see what you would
imagine to be the core themes start to emerge and really assert themselves.
General purpose LLMs are near the top, vibe coding tools are on the rise,
companionship apps continue to make an appearance, media-based productivity tools continue to be
strong.
And if there is one thing that I think is worth putting a finger on to watch for the future, it's
the entry at number 31 of Manus. As far as I can tell looking over this list,
Manist is the only pureplay general agent platform on the list. Now, we've talked a lot on this show
about to what extent agents are going to come online in a general form versus a very specific
or vertical form. The fact that Manus is all the way up there at 31 suggests that there
might be room or at least interest in a general purpose agent and even outside of the core
foundation model companies. So when we come back in six months, that is one that I think will be
worth checking back in on? Will Manus be higher? Will there be other general purpose agents on the list?
Will Google have moved, for example, Project Mariner out of labs into its own space?
All questions for the future, but for now, that is going to do it for today's AI Daily Brief.
Appreciate you listening or watching as always, and until next time, peace.
