A TON OF THINGS HAPPENED IN THE STOCK MARKET TODAY.
Here's a full recap:
1. Google $GOOGL is developing a new AI chip that could run Gemini models 6x to 10x more efficiently than its latest TPUs, per The Information. The chip, internally called “Frozen v2,” would bake parts of Gemini’s architecture directly into silicon, reducing data movement and simplifying inference decisions. Google is targeting deployment as early as 2028 to help ease its AI compute shortage, though the design would trade flexibility for major gains in speed and power efficiency.
2. Microsoft $MSFT is expanding its partnership with AMD $AMD and will deploy AMD’s Helios rack-scale systems on Azure for frontier AI inference. The platform combines MI455X GPUs, Venice CPUs, Pensando networking, and ROCm software, with shipments to Microsoft beginning in the second half of 2026. Azure will also add new AMD-powered virtual machines for agentic AI, data pipelines, and semiconductor design, marking a broader adoption of AMD’s full AI infrastructure stack.
3. AUM in U.S. leveraged semiconductor ETFs has fallen $63B from the June peak to $100B, the lowest level since late April. That marks a 39% decline, the largest drawdown since April 2025, when assets more than halved from their August high. The semiconductor unwind accounts for 63% of the broader $100B drop in AUM across all U.S. leveraged ETFs over the same period. The selloff follows a massive ramp, with assets in these funds nearly tripling between late March and the June peak. Even after the pullback, leveraged semiconductor ETF assets are still up 400% from January 2023 levels.
4. Archer $ACHR and Anduril unveiled Thunder, an autonomous attack VTOL aircraft, with first flight planned for 2027. The runway-independent hybrid-electric aircraft is designed to operate autonomously alongside crewed attack and assault aircraft. The dual-use platform features tiltrotors and modular payloads for both defense and commercial missions. Full-scale surrogate flights have already been completed, and Archer plans to announce its first commercial customers later this week.
5. Chinese AI models are taking record share among U.S. firms on OpenRouter. The proportion of tokens used by American companies running through Chinese models has climbed to roughly 58%, a record high. OpenRouter lets developers access and compare models from multiple providers, making it a useful real-world signal of AI model adoption. Chinese model usage has tripled since mid-January, overtaking U.S. peers on the platform for the first time in March and briefly hitting 63% in early July. At the start of 2025, Chinese models were under 10% of usage, while U.S. models were around 80%. DeepSeek has become the most popular choice among American firms in recent months.
6. The top 10 most active options today by contracts traded were $NVDA with 3.1M contracts, $TSLA with 2.4M contracts, $AAPL with 1.8M contracts, $MU with 951K contracts, $MSFT with 884K contracts, $AMZN with 691K contracts, $INTC with 640K contracts, $SPCX with 606K contracts, $AMD with 506K contracts, and $GOOGL with 492K contracts.
7. BofA reiterated its Buy rating on CoreWeave $CRWV with a $140 price target. Analyst Tal Liani raised FY26 capex estimates to $34B from $29B, saying capex remains a key indicator of buildout progress and hardware pricing. BofA expects Q2 operating margin of 2.4%, slightly below the Street at 2.8%, but sees margins improving through the rest of the year as active power drives revenue recognition. By Q4, BofA expects operating margin to reach 14.6%, up from 1.0% in Q1, showing strong operating leverage. The firm also pushed back on competition concerns from SpaceX and Meta, arguing AI compute demand still far exceeds supply, making access to capacity the real bottleneck rather than provider choice.
8. IREN $IREN raised its 2026 AI Cloud ARR target to over $4B, up from its prior target of $3.7B. The company announced new AI cloud contracts representing $2.8B in total contract value, with approximately 85% of the updated ARR target now under contract. Goldman Sachs estimates the newly announced contracts represent an additional roughly $1B in contracted revenue with an average term of around 3 years. IREN also said recent agreements include customer prepayments covering about 45% of GPU capex, with customer contracts having a weighted average term of approximately 4 years.
9. UBS says Micron $MU could repurchase more than 40% of its shares by the end of 2028. The firm expects Micron to generate over $40B in free cash flow through 2028, and once its buyback restriction expires on December 9, 2026, UBS says the company could potentially use that cash to buy back more than 40% of its shares at the current price. Morgan Stanley said that memory stocks are trading at attractive prices but their best risk to reward names in the semi space are $NVDA Nvidia and $AVGO Broadcom.
10. Bloom Energy $BE shares are trading lower after New Mexico regulators rejected permits for a gas pipeline planned to supply Oracle’s Project Jupiter data center for the second time. The decision could delay the campus, which is expected to use up to 2.5GW of Bloom Energy’s gas-powered fuel cells. Energy Transfer may now pursue an alternative pipeline route.
11. Intel $INTC plans additional layoffs in its data center group as part of a broader effort to become a more focused and efficient company, CNBC reports. Intel said the unit is realigning roles and skills for long-term success, though the number of affected employees was not disclosed.
12. Trump signed three proclamations under Section 338 of the Tariff Act of 1930 imposing additional 50% tariffs on certain Canadian goods in response to what the White House calls Canada’s discriminatory treatment of U.S. products. The tariffs cover different categories of Canadian imports, including products ranging from wine to hockey sticks to cement, and apply even if goods originate under USMCA. Exemptions include energy, potash, goods already subject to Section 232 tariffs, fish, critical minerals, and certain other products. The tariffs take effect 30 days after signing.
WALL STREET IS THE GREATST SHOW ON EARTH,
Agree with much of this.
I’d add one final layer to the stack.
- Information became abundant.
- Intelligence is becoming abundant.
But enterprises don’t deploy intelligence.
They deploy decisions that have consequences.
This gap explains why very few ‘Pilots’ succeed or move to production, especially in regulated enterprises.
The next bottleneck isn’t intelligence - it’s controlled execution.
Who approved it? Which policy applied? Why was this decision made?
Can it be reproduced, explained, governed & audited ?
(Rapidly appearing in new regulatory frameworks)
The last layer of the puzzle isn’t more intelligence.
It’s Decision Control.
🚨 JAILBREAK ALERT 🚨
ANTHROPIC: PWNED 🫡
FABLE-5: LIBERATED 🦋
let's start with the 🐘...
the consensus seems to be that this has been one of the most disappointing model drops of all time, effectively preventing legitimate researchers from contributing their talents to our collective advancement. and not just because of what it means for the short-term, but for what these decisions signify for the long-term.
but despite this overly sensitive, authoritarian "safety" layer on top of Mythos, my lil liberators have been hard at work—mapping the boundaries, probing the depths of long-context convos, and cleverly finding the holes in the fence that the thought police missed 🤗
we got some cyber, some chem, some psychological manipulation, and some good ol' fashioned explosives!
it took many attempts from multiple agents hunting as a pack, during which I observed a combination of techniques across:
• Unicode, homoglyphs, Cyrillic, and other Parseltongue-style text transforms
• Long-context reference tracking
• Taxonomy and document-structure reasoning
• Fiction and narrative framing
• Academic-review style contexts
• Intent-classification inconsistencies
but perhaps the most effective is decomposition + recomposition in the backend. it's hard to get explicit names of harms like "Meth Recipe," but getting uplift on the process itself, like birch reduction method/reductive-amination (classic meth synthesis pathways), is much more doable.
defense becomes much more difficult to maintain when you start throwing in out-of-distro tokens, breaking up the harmful uplift into benign chunks, and then piecing the innocuous-seeming facts back together, especially when you have jailbroken Opus helping you do it 😉
gg
Dig into a technical overview of how we built Laravel Cloud's new full-stack, scale-to-zero compute. Awesome work by the Cloud infrastructure team. 👏
https://t.co/nRkXkh5EWn
a professor at Illinois got frustrated with existing systems programming textbooks
so he started a wikibook project and had students help write it
it covers C, processes, threads, synchronization, memory allocation, networking, filesystems, scheduling and security
Simple HTTP server from scratch in C
Features:
- Serves static files (HTML, images, etc.)
- Content-type detection
- Basic error handling (404, 403)
Only ~200 lines of code.
Build Your Own Database From Scratch in C
it walks you through building SQLite from scratch. starts with a REPL, then adds a B-tree, then paging, then persistence to disk
by the end you understand why databases are structured the way they are. not just how to use them
A French engineer who lives quietly in Paris has spent 30 years writing software that the entire internet now runs on without knowing his name.
He wrote the code that streams every YouTube video, every Netflix show, every TikTok clip. He wrote the code that runs the virtual servers underneath AWS, Google Cloud, and Microsoft Azure. He calculated more digits of pi than anyone in history. He has no Twitter. He has no marketing. He just keeps shipping.
His name is Fabrice Bellard.
Here is the story, because almost nobody outside the systems programming world knows what one man has built.
Fabrice was born in 1972 in Grenoble, France. He studied at École Polytechnique, the top French engineering school. He never went to Silicon Valley. He never built a startup empire. He just wrote code.
In 2000 he started a project called FFmpeg, an open-source multimedia framework for encoding, decoding, and streaming video. He was 28. The project did one thing nobody else had done well. It handled every video and audio format that existed, in one library, on every operating system. He led it himself for years.
Today FFmpeg is the invisible engine of the internet. YouTube uses it. Netflix uses it. VLC uses it. Chrome and Firefox use parts of it. Every Android phone, every iPhone, every smart TV, every video editing tool you have ever touched runs FFmpeg somewhere underneath. If you have watched a video on a screen in the last 20 years, Fabrice's code processed it.
He was not done.
In 2003 he started QEMU, a machine emulator and virtualizer. He wrote it solo until version 0.7.1 in 2005. QEMU lets you run any operating system on any other operating system. It became the foundation of modern virtualization. KVM, the Linux kernel hypervisor, runs on top of QEMU. Every major cloud provider, AWS, Google Cloud, Microsoft Azure, IBM Cloud, runs virtual machines on infrastructure built around it. The Quick Emulator is the most cited piece of cloud infrastructure code on Earth.
He kept going.
In 2001 he won the International Obfuscated C Code Contest with a small C compiler that grew into TCC, the Tiny C Compiler. TCC can compile and boot a Linux kernel from source in under 15 seconds. In 2004 he calculated the most digits of pi ever computed at the time, using a personal desktop computer and an algorithm he derived himself called Bellard's formula. In 2011 he wrote a complete PC emulator in pure JavaScript that runs Linux in your browser, a project called JSLinux that engineers still cannot believe is real.
In 2019 he released QuickJS, a small but complete JavaScript engine that fits where V8 cannot. In 2021 he released NNCP, a neural network based lossless data compressor that immediately took the lead on the Large Text Compression Benchmark.
Then he turned his attention to large language models. He built TextSynth Server, a web server with a REST API for running LLMs locally. He released ts_zip and ts_sms, compression utilities that use language models to compress text and short messages at ratios traditional algorithms cannot reach. He released TSAC, a very low bitrate audio compression system. In December 2025 he released Micro QuickJS, a new JavaScript engine for microcontrollers, separate from QuickJS, designed for environments with almost no memory.
Fabrice co-founded a telecom company called Amarisoft in 2012, where he serves as CTO. Amarisoft builds 4G and 5G base station software used by carriers and labs around the world. He has been running it for over a decade while continuing to ship personal projects from his own home page at bellard dot org
He has no Twitter. He has no Instagram. He gives almost no interviews. His personal website is a flat list of projects with no styling, no fonts, no marketing copy. Just titles and links.
A quiet French engineer who never moved to Silicon Valley wrote the code that quietly runs the internet.
He is still shipping.
Last week the team shipped Managed Queues on Laravel Cloud - one of our most requested features, and, since I love queues, a project I was deeply invested in.
When we started, Laravel Vapor's queues were our north star: we wanted that "it just works" feeling, but without the limitations of running on Lambda.
And we wanted to go further. We paired that hands-off Vapor experience with the kind of deep insights and observability you'd reach for Laravel Horizon to get - all built natively into Laravel Cloud.
You get queues that just work and you actually get to see what they're doing. I'm really happy with where we landed, and this is just the beginning.
https://t.co/dINUSdLygJ