In addition, Alphabet has reached an agreement to sell $10 billion of stock to Berkshire Hathaway Inc. in a private placement, comprised of $5 billion in Class A Common Stock at a price of $351.81 per share and $5 billion in Class C Capital Stock at a price of $348.20 per share.
This investment by Berkshire Hathaway adds to the position it has built since Q3 2025.
Recently I have been asking YouTube's new AI about some videos ("when is Steam metrics mentioned in the video?" for example), which means they also index videos. This is an unthinkable amount of data.
I'm actually impressed at how bad Alphabet is with LLMs since they invented the thing as we know AND have all the data to train on, yet OpenAI and Anthropic are eating their pie.
Google's main revenue is ads based on search. LLMs are a competitor to search. Creating better LLMs will cut into search volumes.
In any large organisation this is extraordinarily difficult to manage - they have to incentivise the new tech that is actively harming the current revenues, while maintaining as much of the old revenues as possible, without creating internal conflict between these two parts of the organisation that will kill it.
Though in fairness to Google they do seem to realise this and are trying to adapt - they're letting the LLM folks mess with search. It'll be interesting to see how this goes.
I'm actually impressed by how much the Hackernews crowd is sleeping on Google & Gemini. Yes, it's lagging behind in coding, but it's consistently much better and more reliable at literally everything else.
Also there was a period of time when Gemini was the best model out there...
It's actually incredibly useful if you just want to summarize a video, or my use case, want a text tutorial of something that's a video.
I'm still on Anthropic models to code but I'm on Gemini 3.5 Flash for everything else. How can you say Google is bad at LLM when their little flash model is literally SOTA on many benchmarks?
> ... yet OpenAI and Anthropic are eating their pie.
They're eating nobody's pie: it's a new pie. Google is a $4.5 trillion company, the 2nd biggest in the world as I type this.
Seen that fact and seen how good Gemini 3.5 Flash is, I'm not really sure Google is "bad at LLMs".
Google knows LLMs are the new UI, not the new IDE.
Doing a little bit of RAG on the transcript hardly sounds impressive.
Not my impression. Lately I think Gemini is superior to ChatGPT and Claude in coding (I'm mostly using it with scientific stuff in Python).
And they have a massive amounts of TPUs. And yet... their models are way behind.
Auto Dubbing on the other hand is incredible, translating Russian/Ukranian speech with different voices and accents for each speaker, during a fire fight is wild.
I know GAAP accounting won't recognize any capital gain on these treasury operations, but from an economic standpoint this financial judo creates a lot of value for existing shareholders.
I don't know who's going to win the llm battle, but googles finance team has been doing their job fantastically.
Tech firms should always have a buffer and never get too close to the optimal debt ratio.
I think they have learned a lot re. what happens if you are asleep at the wheel now.
https://www.sec.gov/ix?doc=/Archives/edgar/data/0001652044/0...
I guess they don't want to burn it down to $40B?
High cap companies use debt for this: bank loan is located in the market where it's needed most, and the debt is serviced by interest earned from securities in other markets. The net taxes are a small percent (think 3%) relative to simply transferring funds within the company. Yes, this is the low effective tax rate the EU is quite upset about.
Other reasons for not touching their holdings usually have a similar explanation. The securities are fungible for accounting purposes but not fungible enough for actual day-to-day operations. Result: securities get "stranded" and the large company grows a hedge fund appendage.
The market thinks Alphabet is most able to efficiently turn $80B into more money by investing in AI infrastructure.
So, Alphabet is happy to oblige them, given the favorable terms.
Literally nobody.
Every company from megacorps to small fish are spending well in excess of profits on these capex expansions. No ROI timelines yet established....
Even if Alphabet has $80B sitting in the bank, they could quite reasonably arrive at a comparable decision.
All these big tech firms are spending wildly to make sure they are the one on top at the end of it all. But whoever that ends up being there’s going to be one hell of a lot of fallout underneath them.
Why do you think there will only be one winner?
"Alphabet announced that its 2026 capital expenditures are expected to be $180-$190 billion, and that it expects 2027 capital expenditures to significantly increase [...] over the 12 months ended March 31, 2026, Alphabet generated $174 billion of operating cash flow"
Like how the early railroads or oil companies shook out and cost more than expected.
At least not yet.
There's not that much cash sitting around.
Something is gonna need to get sold to transfer into those assets.
Unless central banks are just going to print money to invest in these companies, I don't know who else is going to be able to take on enough debt to prevent massive sell offs somewhere for this.
It's not like ~$400B is pocket change...
(2) Middle east oil money (Saudi Aramco's profit every year is $100B+)
(3) Public traders have been and are looking to cycle out of other investments into higher growth areas.
It's easy as fuck for Google to raise this money because they are a money printing business. They are the most profitable company in the world, so for anyone this is basically the same as buying US debt.
Not nitpicking your answer, I just don't understand.
Capital raising is best done when markets are favorable, and Alphabet has the ability to choose how and when to raise.
Recall the froth of follow-on offerings hot circa 2000
So being down 1.7% is literally exactly what you'd expect.
It's insightful to put such documents into Claude and see how they use many different financial mechanisms to raise the money. $15B sold directly to the big banks, $40B sold to the market (but also facilitated by these banks), a direct investment (PIPE) from Berkshire. Pretty cool how financial markets do these things.
Stock based comp is another $350B a year in US markets alone. So if you think about public markets as an avenue for companies to raise capital, post-IPO firms are doing it to the tune of more than half a trillion a year.
At least part of this is slated for employee stock comp. Could be to keep their talent from running.
This is an interesting change. Essentially just gives more timing control?
I would have thought we have over built Datacenter before even AI came. There are enough Datacenter Rack space that replacing 5 - 8 years old server to newer 256 Core CPU would have increased their CPU per Rack by factor of 4 - 5. Saving significant space for future growth.
Instead we are so behind in Rackspace we are now building out Datacenter faster than ever.
More than a quadrillion high quality tokens per year. Pretty soon they will have an automated team of scientists doing basic and advanced research in every field. All those tokens will be fed back and make the model much more inference efficient.
