$13 billion for just one AI company, all in a
single week. That's how September 2025 kicked
off. It's a number that really makes you stop
and think, doesn't it? Absolutely. Welcome, everyone.
We're looking at what you could call an... astronomical
phase of capital investment in AI. That first
week of September, it wasn't just another funding
cycle. It felt like a real seismic shift. The
AI wars, as people call them, they're definitely
heating up. We're seeing battle lines drawn with,
frankly, unprecedented amounts of money. It feels
less like just an arms race now and maybe more
like a space race. Billions pouring in, not just
to the top players, but kind of across the board.
That's a good way to put it. This week alone,
the infusion of capital created these massive
war chests across the industry. It really signals
a dramatic escalation in chasing AGI, artificial
general intelligence. You know, that idea of
AI performing any intellectual task a human can.
And it just underscores the monumental computing
power and honestly, the sheer talent needed to
even compete at this level. But what really struck
me looking at the details is it wasn't just about
classical AI, right? Not just neural networks
or LLMs. Significant money also flowed into technology
sort of beyond that, specifically quantum computing.
Yes, that's a really interesting point. It's
a clear signal, I think, that the smart money
isn't only focused on today, but on what's next.
They're betting on that next technological horizon,
the one that could fundamentally reshape AI altogether.
So for you today, we're going to unpack this
incredible week. We'll start with those huge
headline grabbing deals for the foundational
AI models. Look at the sort of different visions
getting billions and backing. Then we'll pivot
to that leap into quantum computing, maybe the
future, but clearly on the radar now. And finally,
we'll explore this fascinating range of AI applications
already changing industries, you know, health
care, customer service, all sorts. It's a deep
dive into where the money's flowing and what
it might mean for all of us. OK, so let's dive
into it. The two biggest stories from that week,
at least for me, they really showcase different
but maybe equally compelling visions for AI's
future. First up, Anthropic. The scale is just
wow. It was absolutely astounding. Anthropic,
the creators, the Claude family of LMs, they
secured an incredible $13 billion, Series F,
on September 2nd. $13 billion. It's not just
big. It's one of the largest private funding
rounds in tech history. Full stop. It's a huge
war chest. Puts them right up there as a major
competitor to open AI to Google. And it's not
just the amount, is it? It's their specific angle,
their philosophy. Exactly. Their core mission
isn't just building powerful AI. It's fundamentally
centered on AI safety. They're aiming to develop
systems that are steerable, interpretable, and
really crucially aligned with human values. And
this focus on safety is not just talk. It seems
to be a key differentiator for them, a strategic
choice. Really, in a field where, let's face
it, concerns about powerful AI are definitely
growing. They're trying to build in the guardrails
from the start. And that kind of focus, that
requires just enormous resources. So this capital,
it's going straight into funding the huge supercomputing
needed for training, right? Right. Attracting
the absolute best AI talent globally, scaling
up their enterprise offerings. It all fuels that
long -term mission. Develop safe. beneficial
agi ushering in they hope an era of responsible
intelligence a very ambitious goal now let's
shift just lately but stay with foundational
models we also saw mistral ai europe's leading
llm company many would say secure a massive 2
billion euros that's about what 2 .2 billion
us dollars in their series d on september 4th
Still a huge amount. Yeah. And this is where
you see a really fascinating contrast in strategy.
Mistral plays a different, but arguably just
as vital role. They're really a champion of open
source AI models. Okay. And they're seen as key
for European AI sovereignty. Unlike some competitors
who keep their model weights, the inner workings,
private. Mistral often releases models with open
weights. Right. So the code, the parameters,
it's out there for people to see and use. Exactly.
It's publicly available. And that open approach,
it has real strategic advantages, doesn't it?
It helps build this large, loyal community, developers,
researchers. They can all build on it, improve
it, scrutinize it. Drives rapid adoption, too,
because anyone can use and customize their tools.
It really fosters innovation and transparency.
So this funding for Mistral, it covers those
huge compute costs for training new models, but
also lets them expand their commercial side.
Precisely. expanding their commercial offerings
for businesses that want that flexibility, that
transparency that open source can provide. So
it really brings up an important question, doesn't
it? We're funding these two very different paths.
One closed, proprietary, focused on internal
safety controls. The other open, collaborative.
What kind of future are we actually investing
in here? That's the big question. And it seems
like the answer, this week anyway, was both.
Investors are backing the highly controlled,
safety -focused, anthropic model. open community
-driven Mistral model. It suggests the market
sees value in both, maybe for different reasons.
Right. Maybe not converging on one winner just
yet. So we've looked at these foundational battles,
the investments shaping AI right now. But what
about when investors look further out beyond
the immediate horizon? That's where it gets really
interesting, looking at quantum computing. Yes,
exactly. Quantinium is the perfect example. They
announced the $600 million funding round September
4th, led by Honeywell. And that really highlights
this growing synergy between quantum computing
and AI. It's fascinating. Yeah, it is. So for
people maybe less familiar, what is Quantinium
actually building? And why is it potentially
so important for AI's future? Well, what's really
interesting is they're building both the quantum
hardware and the software, the algorithms that
run on it. It's an integrated approach. Think
of quantum computers as a fundamentally new kind
of machine. Okay. Classical computers use bits,
zeros, or ones. Quantum uses qubits, zero, one,
or... both at the same time, thanks to superposition
and entanglement. This lets them explore just
vast numbers of possibilities simultaneously.
They can tackle certain problems that are just
impossible for even today's best supercomputers.
And how does that connect specifically to AI?
What are the implications? Oh, they're profound.
Imagine optimization problems where current AI
just gets stuck because the number of possibilities
is too huge. Or simulating molecules for drug
discovery or new materials with incredible accuracy.
Quantum machine learning could unlock totally
new kinds of algorithms. Not just faster versions
of what we have now. Exactly. New approaches.
Leveraging quantum principles could potentially
supercharge AI capabilities in ways we can barely
imagine today. Maybe optimizing how deep learning
models are trained, making them more efficient,
more powerful. Whoa. Imagine the possibilities
there. Solving problems we literally can't even
touch today. That really is... is a leap. So
this funding helps them push towards fault tolerant
quantum computers. Yes. Machines powerful enough
to reliably solve real world commercial problems,
not just lab experiments. So connecting this
back to the bigger picture, how soon do you think
quantum computing could really start to reshape
the AI landscape, like in a way that impacts
everyday applications? That is the multi -trillion
dollar question, isn't it? My gut says it's still
a ways off for widespread commercial impact.
But this kind of investment, especially from
Honeywell, shows serious long -term belief. Are
we talking decades, do you think? Or could a
breakthrough speed things up maybe in the next
five, 10 years for specific areas like drug discovery?
I'd probably lean towards the five, 10 year mark
for specific high value applications. The investment
signals confidence that the science is sound
and the engineering hurdles, while huge, might
be solvable within that time frame for certain
niche problems. It's definitely a marathon, not
a sprint. But yeah, the pace is picking up. Okay,
so stepping back from the foundational models
and the quantum future, what does all this investment
mean more broadly? Billions aren't just going
to those headline acts. They're flowing into
pretty much every corner of the economy. It shows
how pervasive AI is becoming. Let's look at a
few examples. Yeah, absolutely. It's not just
the giants. It's this quieter revolution happening
in so many sectors. Let's start with customer
service enterprise automation. Sierra raised
$350 million on September 4th. They're making
AI agents for customer service, but these go
way beyond symbol chatbots. Think about it. AI
that understands complex issues, pulls data from
different places, and actually resolves problems
autonomously using conversational intelligence.
It's not just reading a script. It's solving
the problem. Could dramatically change that whole
experience. That's a huge potential upside. Fewer
frustrating calls. Yeah. I think everyone can
get behind that. But it does raise questions
about the future roles for human agents too,
doesn't it? Upskilling or displacement? A really
important question. Absolutely. And then LayerX
got $100 million on September 1st. They have
an AI SaaS platform for enterprise automation,
helping big companies automate complex workflows.
Using AI to understand business data and execute
multi -step tasks across different systems. Like
connecting Salesforce and SAP data automatically.
Exactly. Processing invoices, onboarding employees,
stuff that take a lot of manual effort before.
It's like building with intelligent Lego blocks
of data and decisions. Which could mean a lot
of repetitive work disappearing for many office
workers. Then moving into health care. Drug discovery,
massive potential here. Treeline Biosciences
came out of stealth with $200 million on September
3rd. They're using AI for oncology drug discovery,
finding new cancer medicines. How does that work
exactly? Well, imagine AI analyzing just vast
amounts of genetic molecular patient data, identifying
new drug targets, maybe even designing potential
drug molecules way faster than human teams could
manage. Right. Because the traditional drug discovery
process is incredibly slow, super expensive and
often fails. AI promises to make it much faster,
much more precise, accelerating getting life
-saving therapies to patients. Yeah, potentially
by orders of magnitude. And then there's Sighted
Health, $44 million raised on September 2nd.
They're focused on early cancer diagnostics,
developing new tests using biomarkers and AI
to spot cancer signs at the earliest possible
stages. Which we know is absolutely key. Early
detection saves lives. AI sifting through complex
data to find those subtle early signals, that's
incredibly powerful. Definitely. It's about finding
those patterns humans might miss. Okay. Finally,
let's touch on identity and search. ID .me secured
$340 million on September 3rd. They're a leader
in digital identity verification, letting you
create one secure digital ID to use across different
online services. AI is critical for verifying
documents, biometrics accurately and quickly.
Yeah. In our increasingly digital world, a trusted
way to verify who you are online is essential
for security, for fraud prevention. It simplifies
things for users, but also builds trust. For
sure. And then U .com raised $100 million. Also
on September 3rd, they're challenging the big
search giant, building an AI native search engine
that gives you direct summarized answers, pulling
info from across the web instead of just that
list of blue links you have to click through.
Soft laugh. Yeah, I still wrestle with prompt
drift myself sometimes trying to get a straight
answer from search. So I definitely appreciate
models aiming for more directness, giving you
to the answer, not just near it. So, OK, given
this explosion of applications, and let's be
honest, the sheer number of things labeled AI
now. How do we as observers tell the difference
between real innovation, deserving this cash
and just, you know, AI washing? That is such
a critical question. AI washing being like slamming
an AI label on something that isn't really AI
driven just for hype or funding. But looking
at these examples, the money seems to be following
really concrete problems that AI is solving.
It's not just a buzzword. It's measurable impact,
improving customer service, speeding up drug
discovery, making digital identity more secure.
Investors seem to be looking for actual solutions
here, not just marketing spin. Got it. So look
for the tangible problem being solved. Right.
mid -roll sponsor read. Wow. Okay, recap in that
week. It was just wild. We've navigated the sheer
scale of investment in early September 2025.
I think we felt like an astronomical phase really
showing how intensely these AI wars are heating
up. It really was something. And I think the
crucial thing to take away is that dual focus
we saw. On one hand, these massive bets on foundational
AI, anthropic, Mistral, representing those different
strategic visions. Right, the closed versus open
approaches. Exactly. But then alongside that,
These really crucial investments in next -gen
tech, especially quantum computing, that's a
long -term play for the future of computation
itself. And then the broad spread of applications,
healthcare, enterprise, identity. It paints a
really compelling picture. It's not just about
a few big winners. Yeah, connecting it to the
bigger picture. This week wasn't just about funding
companies. It felt more like capitalizing the
next chapter of human innovation. laying down
the financial, the technological groundwork for
the world we're all going to live in. It's building
the infrastructure for future intelligence. It
really makes you think, doesn't it, about the
long -term effects. Here's a question for you
listening. What single innovation from this funding
spree, whether it's, say, for AI, open models,
quantum breakthroughs, or a specific application,
do you think will have the biggest, maybe most
unexpected impact on your daily life in the next
five years? And why? Give that some thought.
That's a great question to ponder. And I just
add, as we watch these technologies accelerate
so incredibly fast, developing our own critical
thinking skills is going to be absolutely essential
for all of us. Navigating this landscape isn't
just about understanding the tech, but really
understanding its ripple effects on society,
on our lives. That's a perfect thought to end
on. Thank you so much for joining us on this
deep dive into the future of AI, as seen through
one incredible week of investment. Out to your
own music.