The Weekly Think: June 19 – 25, 2026
OpenAI built a chip, Micron printed record money, Google keeps losing its best minds, and Anthropic accused Alibaba of copying its homework
Welcome back to the stage of AI history! This was a hardware-heavy week, folks! Yes, I mean you, you are the folks. And all those chips and memory are the things affecting you folks. OpenAI revealed it has been quietly cooking up its own spicy silicon, Micron reported a quarter so good (or bad, because “RAMageddon”), and Google kept losing its top researchers to Anthropic and OpenAI.
There was drama too. Anthropic sent a letter to the Senate accusing a Chinese giant of basically photocopying its homework 28.8 million times, and Getty Images made a deal with OpenAI, laughing all the way to the bank as a result. Let’s get into it.
While I was reading the news so you don’t have to:
OpenAI and Broadcom unveiled Jalapeño, OpenAI’s first home-built chip
Micron posted a record $41.5 billion quarter on the back of AI memory demand
Google keeps hemorrhaging top AI researchers to Anthropic and OpenAI
Anthropic accused Alibaba of the largest model-copying campaign it has ever seen
Getty Images struck a deal with OpenAI and its stock shot up over 200%
OpenAI built its own chip and named it after a pepper
The story: On June 24, OpenAI and chipmaker Broadcom revealed Jalapeño, OpenAI’s first custom-built processor. It’s designed for one specific job: running AI models that are already trained (the industry calls that “inference,” which is the model answering your questions, the part that comes after all the learning is done). For a company that has spent years eating up Nvidia chips like they were… chips, building its own is a real statement of intent.
What happened:
Jalapeño is a purpose-built inference chip, so it’s tuned to serve up answers fast and cheap, with six stacks of high-speed HBM memory wrapped around one big compute core.
The chip is enormous, roughly 840 square millimeters, which is about as large as current manufacturing machines can physically print on a single piece of silicon.
OpenAI and Broadcom say they went from idea to finished design in nine months, well under the typical year-and-a-half to two years, and they admit they used OpenAI’s own models to speed up parts of the design work.
Test chips are already running in the lab on one of OpenAI’s coding models, with real deployment planned for late 2026 in data centers built with Microsoft.
Broadcom claims the chip beats today’s best hardware on power efficiency, but the two companies released zero actual numbers to back that up, so for now that claim is just a promise with no proof attached.
OpenAI is following a path Google, Amazon, and Microsoft already walked, which is to stop renting all your compute from Nvidia and start making some of your own. The plain reason is money (because in this biz, it always is). When you’re spending billions a year on chips from a single supplier, designing your own starts to look less like a vanity project and more like basic math.
If you’re building anything on top of OpenAI’s models, this is a slow-burn detail to file away. Custom chips like this are how the cost of running AI eventually comes down, and cheaper compute underneath you means the tools you build get cheaper to run over time. Nothing changes tomorrow, but the direction of travel is good for the people building on top.
Micron had the best quarter in its history, and your next PC will feel it
The story: On June 24, memory-chip maker Micron reported the biggest quarter in its 48-year history: $41.46 billion in revenue, up from $9.3 billion in the same quarter a year ago. Its profit margin hit a frankly cartoonish 81%, meaning for roughly every dollar of product it sold, about 81 cents was profit (in the words of rapper Mase, “double up”). The reason is obvious: AI data centers are devouring the world’s memory supply like a kid with M&M’s.
What happened:
Revenue more than quadrupled year over year, and the company’s profit for the quarter came in around $28 billion.
The driver is HBM, the ultra-fast memory that sits next to every AI chip, and Micron has already sold out its entire 2026 HBM production.
CEO Sanjay Mehrotra said the company can only fill somewhere between half and two-thirds of what customers are asking for, which is why prices keep climbing.
DRAM, the regular memory in your laptop and phone, saw prices jump by a mid-60s percentage in a single quarter.
Only three companies on earth make this memory at scale (Micron, Samsung, and SK hynix), and all three are pouring tens of billions into new factories that won’t be ready until 2027 or later.
A few editions back I walked you through the Steam Deck getting up to $300 more expensive, and the “RAMageddon” nickname the internet slapped on the memory shortage. Micron’s record quarter is the other side of that exact coin. The same shortage making your gadgets pricier is making the memory makers obscenely rich, because they can sell every chip they produce to AI data centers at a premium. When a supplier can only meet two-thirds of demand, the supplier sets the price, and right now the supplier is naming a very high one. To illustrate that, imagine there’s a lemon shortage and the kid on the block is selling lemonade on a hot summer day for $20 (because, obviously, he’s gotta pay for that expensive AI subscription somehow).
For anyone planning to buy a laptop, a phone, a graphics card, or build a PC, the practical read hasn’t changed since RAMageddon: prices on anything with a lot of memory in it are going to stay high into 2027. If you’ve got an upgrade you’ve been putting off, you now have to pay what I like to call the “waiting tax” (more like wailing tax), because the new factories that would ease prices are still a year or more out.
Google keeps losing its best AI minds to the competition
The story: Across the week, Google lost another wave of senior AI researchers to its rivals (in a very “Giannis Antetokounmpo leaving for the Miami Heat” moment). The headline departures: Noam Shazeer, a co-inventor of the core technology behind modern chatbots, left for OpenAI, and John Jumper, who led the Nobel-winning AlphaFold protein project, left for Anthropic. Two more Gemini contributors, Jonas Adler and Alexander Pritzel, are also heading to Anthropic. Alphabet’s stock dropped as much as 7.2% on the news, its worst single-day slide since February.
What happened:
Shazeer co-wrote the 2017 research paper that introduced the “transformer,” the architecture underneath basically every modern AI model, so losing him is symbolic as much as practical.
Jumper isn’t just any researcher; he shared a Nobel Prize for using AI to predict protein structures, and now he’s taking that talent to Anthropic.
Google’s spokesperson pushed back, pointing to DeepMind boss Demis Hassabis calling it the most competitive talent market the tech industry has ever seen.
The market clearly read the exits as a warning sign, knocking 7.2% off Alphabet’s value in a single session, even though the company is still worth around $4.46 trillion.
This continues a pattern from earlier in the year, when Anthropic landed researcher Andrej Karpathy, another marquee name in the field.
This connects to something I wrote about a few editions ago, when Karpathy joined Anthropic. That migration didn’t stop; it straight up accelerated like it was Han in the Fast & Furious franchise. The people who build these models are the rarest resource in the entire industry, rarer than chips or data, because there are maybe a few hundred of them on the planet who operate at the frontier. When they move, they take knowledge that money alone can’t quickly replace, which is exactly why a few resignations can knock billions off a company’s value in an afternoon.
If you work in any field being reshaped by AI, you’re probably taking notice. The scarce, valuable thing is the human expertise, the people who actually understand how to build and direct these systems. That’s the part companies are paying enormous sums to keep, and it’s a useful reminder of where to focus your own learning if you want to stay valuable as this all shakes out like a Polaroid picture in the 90s.
Anthropic accused Alibaba of copying its homework 28.8 million times
The story: On June 24, word got out that Anthropic (the company that makes Claude) sent a letter to the US Senate accusing Chinese tech giant Alibaba (the company behind such services as AliExpress, purveyor of cheapo computer products) of running the largest model-copying campaign it has ever caught. Anthropic says operators tied to Alibaba’s Qwen AI lab used roughly 25,000 fake accounts to run 28.8 million conversations with Claude between April 22 and June 5, harvesting its answers to train a cheaper copycat.
What happened:
The technique is called “distillation,” which means using a strong model’s outputs as a teaching guide to train a weaker, cheaper model to imitate it. Think of it as a student copying a brilliant classmate’s test answers over and over until the student can fake the same results.
Anthropic says the campaign zeroed in on Claude’s most valuable skills, its coding and step-by-step reasoning, and called it turning American R&D into a subsidy for a competitor.
For scale, this dwarfs the cases Anthropic flagged back in February, when it accused DeepSeek (about 150,000 exchanges), Moonshot (3.4 million), and MiniMax (13 million) of similar tactics.
Alibaba was added to a US Defense Department list of Chinese military-linked companies on June 8 and is suing to get removed, calling the label baseless.
As of this writing, Alibaba hadn’t responded to the specific accusation, so treat this as one company’s claim that still needs proving. Worth keeping that in mind.
One thing to keep in view: this accusation lands the same month the US government switched off Anthropic’s own two newest models over a security concern. So within a few weeks, Anthropic has been on both sides of the security conversation, the subject of one government action and the source of a warning about someone else. Make of all this what you will.
What’s clear for the rest of us is that AI has become a full-blown geopolitical contest, with company letters to the Senate, Pentagon blacklists, and accusations crossing the Pacific. The models you use are now caught up in a much bigger contest between Washington and Beijing. You don’t have to pick a side to notice that the technology stopped being a neutral tool a while ago, and the fights over who gets to build and use it are only getting louder.
Getty made a deal with OpenAI and its stock went bananas
The story: On June 21, Getty Images (the company behind a huge chunk of the photos of your favorite celebs eating hot dogs at the Oscars) announced a deal to put its licensed image library directly inside ChatGPT. When you ask ChatGPT a question where a real photo helps, like a historical event or a famous landmark (or a celeb eating a hot dog), Getty’s licensed images can now show up in the answer. Getty’s stock jumped more than 200% in a single day on the news.
What happened:
The deal is display-only, meaning ChatGPT shows Getty’s images alongside answers and Getty gets paid for it, with no permission for OpenAI to use the photos to train its models.
It covers over 400 million images, including premium news, sports, and entertainment photography plus Getty’s lower-cost iStock library.
Getty had spent the prior couple of years fighting AI companies in court over images used without permission, so this is a notable pivot from suing to partnering.
The market reaction was enormous, a 200%-plus single-session jump, which tells you investors had basically priced Getty as a company with no AI future and suddenly changed their minds.
Getty had already done a smaller version of this with another AI search company last year, but the OpenAI deal is far bigger in reach.
This one’s a quieter story, but it points at something real about how the copyright fights over AI might actually end. For two years the dominant approach from media and image companies was to sue, and some of those suits are still grinding through the courts. Getty looked at that road and chose a different one: license the work, get paid every time it appears, and turn ChatGPT into a paying customer (it basically said, “hold up, actually, lemme get paid”). The 200% stock pop suggests the market thinks getting paid beats waiting years for a courtroom maybe-win.
If you make content for a living (photos, writing, music, video), this is a development to watch closely. The Getty deal is an early example of creators and AI companies finding a paid arrangement that works for both sides. Whether that becomes the norm or stays the exception will shape how much the people who actually make things get compensated when AI uses their work. For now, one company just showed that licensing can pay better than litigating.
What ties it all together
Step back and the week sorts into two big themes. The first is that AI is becoming a physical, industrial business: OpenAI is cooking up its own chips, Micron minting record billions while unapologetically fueling “RAMageddon,” the whole thing increasingly about silicon and factories and supply you can measure in tons. The second is that AI is becoming a contest between nations and titans: Google bleeding talent to its rivals, Anthropic and Alibaba trading accusations across the Pacific, Getty cutting a deal that rewrites the rules of a two-year fight.
The common thread is that the easy, abstract phase of AI is ending. A year ago this was mostly about chatbots becoming smarter. Now it’s about who controls the chips, who owns the memory, who employs the rare humans who build the models, and which country’s companies come out ahead. The technology grew up, and grown-up technology wants its license (and a later curfew). Exciting or unnerving?
I’ll let you, the reader at home, decide.
What I’m watching
Whether OpenAI’s Jalapeño chip actually ships on time in late 2026, and whether those efficiency claims hold up once real numbers exist
Whether memory prices show any sign of easing, or keep climbing into 2027 as the shortage drags on
Where Google’s departing researchers land first in Anthropic’s and OpenAI’s next models
Whether Alibaba formally responds to Anthropic’s accusation, and whether the government acts on it
Whether more media and creative companies follow Getty’s lead and cut licensing deals with AI firms while the lawsuits fade into the background
Thanks so much for reading this edition of The Weekly Think.
See you next week, fellow thinkers!
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