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We recently introduced Gemini Omni Flash, our first model in the new Omni family. With Omni, you can easily create and edit high-quality videos from text, image, video or audio references. We recently gave developers access to it, and since then, we’ve seen builders all over the world use Omni to create a range of personal and professional projects. Here are some of our favorite ways we’ve seen builders use Omni so far ↓ 📽️ Switch angles and perspectives You can change camera angles, switch environments, and apply cinematic zooms — all without losing the thread of your original scene. Builder @LexnLin took full advantage of this capability, capturing a woman standing in the middle of a city from about 20 different perspectives. You see her from different angles: up close and far away, head on and in profile, from above, and from below. Some shots zoom in, while others hold still. And the background shifts, too.

We recently introduced Gemini Omni Flash, our first model in the new Omni family. With Omni, you can easily create and edit high-quality videos from text, image, video or audio references. We recently gave developers access to it, and since then, we’ve seen builders all over the world use Omni to create a range of personal and professional projects. Here are some of our favorite ways we’ve seen builders use Omni so far ↓ 📽️ Switch angles and perspectives You can change camera angles, switch environments, and apply cinematic zooms — all without losing the thread of your original scene. Builder @LexnLin took full advantage of this capability, capturing a woman standing in the middle of a city from about 20 different perspectives. You see her from different angles: up close and far away, head on and in profile, from above, and from below. Some shots zoom in, while others hold still. And the background shifts, too.

AI Is Moving Beyond “Generating Videos” — Toward “Generating Worlds” Over the past two years, AI video models have advanced at an astonishing pace. From Runway and Pika to Sora and Veo, AI-generated videos have become increasingly realistic and more consistent with the physical laws of the real world. Many people believe the next objective is simply to generate videos that are longer, sharper, and more lifelike. But if we take a step back, we can see that the real transformation is not happening in video itself. It is happening in world models. What Is a World Model? In 1943, psychologist Kenneth Craik proposed an idea that would influence artificial intelligence research for decades. He argued that the human brain does not merely react to the outside world. Instead, it maintains an internal model of how the world works. Because we have this internal model, we can predict the outcome of an action before we actually take it. Before crossing a road, we estimate whether a car will pass by. Before catching a ball, we predict its trajectory. These abilities come from continuously simulating the world in our minds, rather than relying entirely on trial and error. This idea later became known by a more formal term: World Model. A world model does not describe a single image or a fixed video clip. It is an internal representation capable of continuously simulating the rules and dynamics of the real world. Why Is AI Research Turning Toward World Models? Because predicting “what comes next” is becoming increasingly central to how AI systems work. Language models predict the next token. Image models predict the next step in the denoising process. Video models predict the next frame. A world model, however, attempts to predict something broader: What should the world look like in the next moment? In 2018, David Ha and Jürgen Schmidhuber proposed in their paper World Models that an intelligent agent could first learn a model of the world, and then use that internal model to plan its actions. The Dreamer series later demonstrated that many complex tasks could be learned by training agents inside an “imagined world.” At the same time, the development of video models such as Sora and Veo led researchers to another realization: A model capable of continuously generating video has already learned, at least implicitly, many of the rules governing the real world. As a result, these two research directions have gradually begun to converge. But Video Is Not Yet a World This is where the distinction is often misunderstood. For a world model to support meaningful real-time interaction, it must solve several critical problems. Most video models today are essentially answering one question: What should the next frame look like? A true world model needs to answer much more: What happens if I take one step forward? If I walk behind a building and then return, will the building still be there? If I suddenly change the camera angle, will the entire space remain consistent? If I enter a command such as: “Summon a dragon.” Will the world respond immediately? In other words, a world model must do more than generate content. It must understand space. It must understand time. It must understand causality. And it must understand interaction. Moving from watching to participating is where the real difficulty of world models begins. World Models Are Entering the Interactive Era One of the latest attempts in this direction is Alaya World, recently open-sourced by Alaya World, or @alayastd. Instead of generating a fixed video clip, it generates a world that users can explore in real time. Users can begin with text, an image, or a video, enter the generated scene, move freely through it, and introduce new prompts at any moment during generation. The world responds immediately. According to the publicly released information, Alaya World provides: Real-time streaming generation at 720p and 24 FPS Stable continuous exploration for more than one minute The ability to switch prompts and trigger skills or events during generation Model weights and inference code released under the Apache 2.0 License Training code and datasets planned for future release What makes these capabilities important is not simply the technical specifications. It is that the generated “world” can now support continuous interaction. The official demo shows that users can genuinely control, transform, and explore the generated environment. AI Is Evolving From a Tool Into an Environment Over the past few years, most discussions around AI have focused on content generation. Generating text. Generating images. Generating videos. But world models raise a fundamentally different question: Can AI generate an environment that people can inhabit, explore, and continuously evolve? If the answer is yes, the impact will extend far beyond video generation. Game development, robotics training, embodied intelligence, digital twins, virtual production, and many other fields could be transformed by the development of world models. World models are still at a very early stage. Yet from Craik’s proposal of an internal mental model more than eighty years ago to the emergence of today’s interactive world-generation systems, a clear evolutionary path is beginning to take shape. Perhaps what AI is ultimately learning has never been limited to images, videos, or language. Perhaps it is learning the world itself. References GitHub: Technical Report:

Eight democracies. One message to Beijing. Australia, France, Germany, Japan, New Zealand, Poland, South Korea and the UK issued a joint statement on September 22 opposing any unilateral change to the Taiwan Strait status quo. It came out of a meeting on the sidelines of the UN General Assembly, where officials called today's security environment more volatile than a year ago. Their language was direct: "We encourage dialogue and oppose any unilateral attempts to change the status quo across the Taiwan Strait." The same day, the US, Japan and South Korea issued a separate statement making the same point, and also backing Taiwan's participation in international organizations. Taiwan's foreign ministry welcomed the statement and said it would keep building self-defense and deepen ties with democratic partners.

The World is Changing: AI For Creativity By Jeffrey Katzenberg A few months ago, I sat in my office in Silicon Valley and watched as a tech founder showed me something extraordinary. On the screen was a fully realized, beautifully lit, well-composed animated scene. It was stunning and it made me feel exactly what I felt in 1986 watching Luxo Jr. That was the first time I watched a computer-animated 3D character take a breath and seem, against all reason, to have life. It left me in awe. Later that day, I received a text from an artist I've known for thirty years, 350 miles to the south, in the city where I spent most of my career. After seeing a similar video, she texted: "Is this the end of us?" My answer was, "Certainly not.” I have spent the better part of the last decade in Silicon Valley, but the heart of my career has been in Hollywood. Being deeply connected to both worlds means I have deep loyalties to each and a responsibility to speak honestly to both. In 2023, I said that these new AI tools would cut the time and cost of producing world-class animation by as much as ninety percent within three years. Some colleagues were alarmed, many were furious. There is growing fear and resistance surrounding AI within the creative community. I deeply understand it, because I've spent countless hours walking through animation studios watching gifted artists bent over their desks, rebuilding a single second of film for the tenth time because the ninth version wasn't quite right. I've sat in screening rooms where four years of people's labor played out in minutes, and I knew the name of every person that had spent countless hours bringing those images to life. The creative process is a calling, there's really no other way to describe it. From the outside some see resistance. From the inside, it is love. People do not fight this hard for things they don't care about. The pushback coming out of Hollywood represents the collective effort of people who are deeply passionate about their craft. Is History Repeating Itself? The history here is more complicated than either side may realize. In 1906, the most famous composer in America, John Philip Sousa, published an essay titled “The Menace of Mechanical Music." He warned that the phonograph would become "a substitute for human skill, intelligence and soul." Sousa's fight was not really about the machine, it was about money. The machines were playing his compositions, and the men who built them weren't paying him a cent. His campaign helped create the Copyright Act of 1909. He did not stop the technology. He changed the terms under which it could use his work. A hundred years ago, sound came to the movies. We remember it now as a miracle, and it was. What we forget is who paid for it. Before sound, tens of thousands of musicians made their living in the orchestra pits of movie houses, scoring every film live, every night, in towns all over the world. When the soundtrack arrived, the work of one composer and one orchestra was recorded for a film that went into thousands of theaters. The union fought back with everything it had, taking out newspaper ads across the country warning against the menace of "canned music," one of them showing a mechanical man tearing the strings out of a harp while an angel wept. They were not fools, and they were not Luddites. They were right. Those pit jobs did not come back. And yet (this is the part we have to be brave enough to admit), sound gave us the movie musical, the modern score, sfx, sound design, audio engineering, and an art form vastly larger than the one it disrupted. And it helped keep Hollywood in the forefront of world entertainment for the rest of the century and into the next. The loss was real. And yet the art form expanded. This is a story that has been told over and over again. To resist technology is to risk irrelevance. Just look at Kodak or Blockbuster. To embrace technology is to open doors of new possibility. Just consider Apple and Netflix. What I Learned From Walt Disney In the mid-1980s, I was tapped to lead Disney's animation division at a moment when the studio was at an inflection point. Animation wasn't just another business unit. It was the soul of the company, a medium revered because of Walt's genius and his passion. But the production system was cumbersome and unforgiving. A single movie was 125,000 individual hand-drawn and painted cels, photographed one frame at a time. Every revision carried a cost measured in months. These degrees of difficulty shaped the kinds of stories we could tell. We found our way forward in an unexpected place: Walt himself. The Disney archives held astonishing recordings of Walt explaining his creative process. His own writings. His notes and storyboards. Work product captured at every stage of his process. This was truly a gift. Listening, reading, sitting with the work itself, we heard him talk about character, about emotion, about how an audience feels when a character truly comes alive. He talked about making bold choices and refining a scene until it genuinely moved people. We didn't hear a word about pencils or paintbrushes. In fact, Walt was famous for being a technologist, forever hunting for state-of-the-art tools, often inventing them himself to achieve the images he saw in his head. But he never defined animation by the tools. He defined it by whether the audience believed the character. His principles were timeless. The tools were not. That realization changed everything. We co-developed the Computer Animation Production System (CAPS) with a young Northern California company called Pixar, replacing hand-painted cels with CGI. In The Little Mermaid, the final scene shimmered with a dimensionality and light that the old process simply couldn't achieve. In Beauty and the Beast, the ballroom sequence moved with a cinematic sweep that placed the audience inside the emotion of the moment. In Aladdin, the Cave of Wonders felt vast and alive, and the Magic Carpet became an intricate, compelling character all its own. In The Lion King, the stampede carried a scale and intensity that raised the emotional stakes beyond anything we'd done before. Technology didn't diminish the craft, it expanded the canvas. It gave artists more room to create. A decade later, the canvas expanded again. When Disney released Pixar's Toy Story, it wasn't simply a technical milestone. It was proof that a fully computer-animated film could carry real emotional weight, that it could make audiences laugh, cry, and believe. At DreamWorks, we made the difficult decision to sunset hand-drawn animation and become a fully computer-animated studio. It was the right thing to do, but it was not without pain. It cost talented people their place in an industry where they had worked their whole lives. Some made the leap to the new tools and did the finest work of their careers. Some never did. Tools are never the point. The instruments change with every generation. What endures is taste and imagination. The magical ability to make an audience feel. One of the greatest storytellers of our generation, George Lucas, succinctly captured the eternal essence of this issue: “It’s not the how, it’s the why.” A Distinction With a Difference I asked one of the leading AI models a question that has been challenging me for months. What is the difference between reasoning and creating? Its answer changed how I think about almost everything happening in this industry. It said . . . Reasoning and creating are two distinct cognitive modes, though they also work together. Reasoning is fundamentally evaluative and analytical. It operates on what already exists: facts, premises, evidence. It moves toward a conclusion that was in a sense already implied by the input. Reasoning is constrained by logic and truth. Its goal is to arrive somewhere correct, not to invent somewhere new. Creating is fundamentally generative. It produces something that didn't exist before. And crucially, there's no single right answer waiting to be found. A blank page has infinite valid responses. Creation involves choices that can't be fully justified by logic alone. Taste, intuition and vision fill the gap where deduction runs out. Reasoning is what Silicon Valley has been perfecting. Creating is what Hollywood has been practicing for more than a century. AI today operates almost entirely on the reasoning side of the line. It can deduce, evaluate, optimize, and pattern-match brilliantly. And while it can create, there is a real distinction to being creative. What it doesn’t yet have is those things that make us human: empathy, devotion, serendipity, the kind of creativity that comes from a person trying to say something only they could say. When the bot generates a piece of art, it is not trying to communicate anything. It is statistics, not soul; it is emulating things that have been done. By contrast, human creativity isn’t about repeating patterns of zeros and ones; it is about doing something new. One day, AI may close this gap. Three years ago, the leaders building AI would have called what they are achieving today, improbable, if not impossible. Impossible is no longer improbable. Today, the line between reasoning and creating is real. Even the leading technologists acknowledge we are not there yet. There is no scientific path to crossing this divide that anyone in the field can articulate today. Understanding that gap is where we will find common ground. A Path Forward In 2016, I closed one chapter in Hollywood with the sale of DreamWorks and opened another in Northern California, co-founding WndrCo. We’ve backed more than 50 founders building the next generation of technology and watched how breakthroughs in Silicon Valley emerge, first as experiments, then as platforms, and finally as infrastructure that reshapes entire industries. It's worth remembering that the last great revolution in animation also came from the north. Pixar was a Northern California company, forged not in the conventions of the Hollywood studio system, but in the technological breakthroughs of Silicon Valley. I've spent years on both sides of this bridge. For sure, I don’t have all the answers (take Quibi, for one!). But, from my past and present vantage points of my long career, here is what I see . . . Brilliant people in Northern California building this technology have made something extraordinary. They have earned the right for the rest of us to be, if not believers, at least optimistic that what comes next will be remarkable. But they have not made an artist. The tools are powerful, but they are not what makes a story matter. That knowledge lives 350 miles to the south, inside people whose life's work has informed the very models you are building. The right path forward includes them by design, with credit, with consent, and with compensation. Build this with the storytellers. Not on top of them. Taste is not something that can be synthesized, it is uniquely human. At the same time, Hollywood needs to accept that AI is not going away. The energy they are spending trying to make it disappear is energy they are not spending deciding the terms on which it will exist. And the terms are everything. The north needs something from it that they cannot build and cannot buy: creativity. The kind that takes a blank page and conjures a single right answer where there was none and has held audiences for a century. Without it, the most powerful reasoning engine ever invented will still be missing the only thing that makes a story worth telling. The artists who learn to wield these new instruments will do things the engineers never dreamed of. They always have. Edison invented the motion picture but made terrible movies. It took Chaplin, Lloyd, Keaton and so many others to make movies emotional. Now, the canvas is about to expand yet again. We should decide now that we intend to paint on it. There are so many valuable lessons in history. This has happened many times before, and it was never settled by the technology. It was settled by the terms. Sousa did not stop the phonograph; he helped write the law that made sure composers got paid. And two years ago, when the writers and the actors walked out, they were fighting for the very things Sousa was fighting for in 1906. Consent, compensation, the basic recognition that human creative work has a price that must be paid. The terms of that fight are still being negotiated, but the principle is older than any of us. The tools-versus-no-tools argument is a trap. First, we must all agree that there should be terms. Then we can have the crucial debate about what fairness requires. What I Learned From Steve Jobs Years ago, Steve Jobs said, "It's in Apple's DNA that technology alone is not enough. It's technology married with the liberal arts, married with the humanities, that yields us the result that makes our hearts sing." He was describing a device. But he could just as easily have been describing this tale of two cities. What I See Coming Soon As the barriers and the costs come down, more films will get made, not fewer. Studios will get to take more risks. There will be more seats at the table, and very soon entirely new forms of storytelling. In the 1980s, animation was dismissed as a niche corner of the business. Today it is one of the most beloved and profitable forms of storytelling in the world. In live action, filmmakers like Steven Spielberg, James Cameron and Peter Jackson embraced new visual tools not as shortcuts, but as instruments, and expanded cinema in the process. Every time storytelling has met a genuine technological shift, from synchronized sound to color to computer animation, it has redefined the boundaries of the medium and grown larger in the process. Assuredly, I don’t have all the answers, but I am confident that the creative opportunities will expand yet again. How we come through this is a choice. The north has the new tools. The south has the creative soul. The best future will draw on the best of both worlds.

Today, we are announcing the second generation of Agentic Document Extraction (ADE). It is faster, more accurate, and more affordable than ever before. ADE Gen2 delivers higher performance while optimizing cost for every document. Pricing has been completely overhauled. Customers running mixed workloads should see 25% to 80% cost reductions. Groundings and citations now reach the word level following a page > block> line > word hierarchy. This allows every extracted value to point to the exact location on the page it came from. The outputs from the v2 Parse and Extract APIs are fully agent-ready and agent-friendly. Your agents get a clear hierarchy, stable IDs, and clean, standardized Markdown designed just for them. ADE Gen2 is a step change in document intelligence not an incremental update. Read the full announcement on the blog (link in comments). Create an account and get started for free at

A director who doesn't come up to the builder's heels makes a four-hour film about him. Yesterday in Venice, Alex Gibney's nearly four-hour documentary "Musk" had its world premiere. It is a classic case of someone who has spent a career telling other people's stories taking on a man who actually builds those stories with rockets, cars, satellites, and infrastructure, not slides. Alex Gibney is an acclaimed documentarian. An Oscar for Taxi to the Dark Side, Emmys for Going Clear on Scientology, high-profile films on Enron, Elizabeth Holmes and Theranos. His specialty is exposing corporations, cults, and frauds. He does it skillfully and with a thesis. The problem starts when he applies the same method to someone who is not selling an illusion, but hardware that either flies or blows up in front of the entire world. Gibney's fuel is controversy. Elon's fuel is the pursuit of truth hard, engineering truth, the kind that either works on the test stand or it doesn't. It would have been enough to make a film based on facts. Instead we got another rut that fits the slogans of provocation: megalomaniac, confidence man, threat to democracy, an AI avatar reciting old quotes, ex-wives, his father, a former partner. Musk said in 2023 it would be a hit piece. After the premiere, a large share of reviewers effectively agreed with him. I don't know about you, but four hours of falsified formulas would bore me. Instead I watch how much Elon has already done. His energy is extraordinary. Tesla changed the car industry. SpaceX brings rockets back. Starlink works. Starship stands on the pad and prepares for the next flight. This is not a PowerPoint. It is steel, fuel, engines, and people who cannot hide failure in the edit suite. A weak documentary like this is a crumb on the shoulder of his jacket. Now it depends on us when and how quickly that blown-off crumb a utopian attention vampire is simply starved of attention. You could list the names of people who tried to take Elon's energy. Energy is the most precious thing we have. Anyone who steals it with slogans, gossip, and a four-hour indictment that excludes the main subject is sowing under his own feet. Gibney: you reap what you sow. If you have a shred of shame, look at the list of Elon's accomplishments. Look at what kind of person he is for the world and what he does around himself so that things get better cars that drive, internet from orbit, rockets that return, attempts at a brain-computer interface, AI that is supposed to be more than another chatbot. You can dislike his tweets, his political alliances. You cannot honestly erase the scale of what was physically built. A good documentarian should stand, at least for a moment, in the shoes of the person he is portraying. Gibney did not just fail to do that. He took a measure cut for Enron and Holmes and held it up to a man who lands rockets. He left Elon's shoes in the edit suite. Elon walked on barefoot and kept building. One man tells stories about the world from an editing chair. The other moves that world. A four-hour film will not change that. At most it will confirm what people who already disliked Musk already believed. Everyone else can blow the crumb off the jacket and keep going. History does not judge a man by the length of a film. It judges him by what is still in the air when the camera has stopped running. Controversy feeds on attention. Building feeds on repetition. One vanishes when you look away. The other keeps flying. You can cut a man together in four hours. You cannot cut a landing together. A documentary can be switched off. The work cannot.

⚡️The early Bitcoin holder may be one of the cleanest wealth outcomes capitalism can produce. Think about what happened to the rare person who accumulated meaningful Bitcoin very early and actually held it. They did not need to build a 10,000-person company. They did not need customers. They did not need employees. They did not need a board. They did not need to manage LP money. They did not need to continually recreate the economic engine that made them wealthy. They made one extraordinarily consequential capital-allocation decision, survived years of uncertainty, and eventually the asset itself did almost all of the scaling. That is an incredible lifestyle outcome. A founder worth $100M may technically have the same net worth, but much of it can be trapped inside a company requiring their attention, carrying payroll, lawsuits, competition, customers, executives, financing, and constant strategic decisions. The early Bitcoin holder can have $100M sitting in an asset that requires almost no organizational complexity to own. Enormous wealth. Tiny operating surface area. That combination is rare. There is also something profound about how the wealth was created. They recognized a new category before the world agreed the category was real. The wealth came from carrying uncertainty. Bitcoin looked ridiculous. Then dangerous. Then speculative. Then legitimate. Then institutional. Every step upward removed uncertainty while also removing asymmetry. The earliest holders were compensated for occupying the period when the world could still plausibly say the entire thing was worthless. But survivorship bias here is enormous. Thousands of people also concentrated into things they believed were revolutionary and lost everything. Even among people who bought Bitcoin early, many sold at 2x, 5x, 10x, or 50x. Others lost keys. Others got destroyed by exchanges. Others overleveraged. Others simply could not psychologically carry an asset through repeated 70% to 90% drawdowns while everyone around them told them they were insane. So the extraordinary outcome required several things to happen together: see correctly very early, size enough for being right to matter, survive enormous volatility, preserve custody, and resist selling when the gain already looked life-changing. That is almost impossibly difficult in real time. The highest form of wealth creation may actually be finding a very small number of generational capital-allocation decisions rather than continually maximizing labor output. One Bitcoin-like decision can compress decades of economic effort into ownership of the right thing at the right moment. Afterward, the entire purpose of wealth can change. You no longer need to optimize for more work. You can optimize for autonomy. Time. Privacy. Research. Relationships. Travel. Building things because they matter to you rather than because they need to pay you. And compared with becoming a billionaire CEO whose phone can never truly be turned off, the anonymous person who quietly owns enormous permanent capital may have won a different and arguably more valuable game. The founder builds a machine powerful enough to create freedom later. The generational investor finds an asset powerful enough to make the machine unnecessary. That second outcome is incredibly rare. But when it happens, the lifestyle asymmetry is almost absurd.

A TON OF THINGS HAPPENED IN THE STOCK MARKET TODAY. Here's a full recap: 1. The U.S. reportedly offered Iran a deal to halt the siege and lift sanctions in exchange for reopening the Strait of Hormuz and ending proxy attacks, according to Al Arabiya. Axios also reports that Rubio told several foreign counterparts the U.S. does not plan new strikes on Iran for now, with pressure shifting toward the naval blockade and new sanctions campaign instead. Crude Oil fell 4% and the 10-year treasury bond fell from 4.72% to 4.62%. 2. Global physical gold-backed ETFs $GLD attracted $6.4B of inflows last week, their largest weekly intake since January and the 3rd-largest weekly inflow on record. North America led with $4.4B, followed by Europe at $1.7B and Asia at $300M. This marked the 7th straight week of inflows, with global gold ETFs pulling in $16.4B over that stretch. Total AUM in global gold ETFs rose by $33B last week to $615B, the highest level since the second week of May. 3. Intuit $INTU reported Q4’26 revenue of $4.4B, beating estimates of $4.27B and up 14% YoY. Adjusted EPS came in at $4.03 versus $3.58 expected. Global Business Solutions revenue rose 14% YoY to $3.4B, the Online Ecosystem grew 17% YoY to $2.6B, Consumer revenue increased 14% YoY to $930M, and Credit Karma revenue rose 16% YoY to $743M. For FY27, Intuit guided revenue to $23.3B–$23.5B versus $23.72B expected, while adjusted EPS guidance of $22.88–$23.12 came in well below the $27.32 estimate. The company also raised its dividend 15% YoY to $1.38/share, bought back $5.5B of stock, and has $7.9B remaining on its authorization. Management said its strategy is to win as an AI-driven expert platform while staying disciplined on investments and scaling its big bets. 4. President Trump said the U.S. Navy has removed and/or detonated all mines from international waters in the Strait of Hormuz. He said Iran has been notified that any ship or boat placing new mines will be “immediately and systematically destroyed.” Trump added that Space Force is monitoring every square inch of the Strait, along with Pickaxe Mountain and the three previously destroyed nuclear sites, and said a “Zero Tolerance” policy on mine placement is now in full effect. 5. Canada is responding to U.S. tariffs with new tariffs of its own. The country is raising steel tariffs to 50% from 25%, while roughly 700 products will face new tariff rates of 15%, 25%, and 50%. The measures are set to take effect on September 8, marking another escalation in the U.S.–Canada trade dispute. 6. Anthropic is expected to tell IPO investors its total addressable market exceeds $30T, topping SpaceX’s $28.5T estimate, according to WSJ. The figure represents the potential value of work Anthropic believes AI models could eventually perform, not a direct revenue forecast. Anthropic generated $11.6B in Q2 revenue and could seek to raise as much as $100B at roughly a $2T valuation. IPO documents are expected within weeks, potentially setting up a September or early October listing. 7. OpenAI’s data-center head Chris Malone left the company last week, according to WSJ. Malone joined in March 2025 shortly after Stargate was announced and played a key role overseeing OpenAI’s massive data-center buildout. He previously led data-center strategy at Meta and earlier worked on data-center technology at Google. The departure comes just weeks after OpenAI also replaced its chief revenue officer, adding another senior leadership change as the company races to scale infrastructure, revenue, and compute capacity. 8. ClickHouse has surpassed $350M in annual recurring revenue, up 40% since May, as AI agents drive demand for database and observability infrastructure. OpenAI’s usage has reportedly grown roughly 10x over the past year to more than 30 petabytes of data per day, or around 30T events daily. OpenAI has also shifted parts of its log-management workload from Datadog to ClickHouse over the past year. ClickHouse was valued at $15B in January and says gross margins currently range from 50%–70%. Earlier this year, the company acquired Langfuse to expand deeper into monitoring AI applications and agents. Nebius $NBIS owned a 28% stake in ClickHouse as of May 2025, though that stake has likely been diluted by subsequent fundraising. 9. JPMorgan reiterated its Overweight rating on SpaceX $SPCX with a $240 price target, saying the company’s AI ambitions are coming into sharper focus and that it is increasingly positive on Grok. The firm highlighted SpaceX’s completed acquisition of Cursor on 8/14 as an important step in building enterprise AI capabilities. Cursor brings roughly $4B of ARR as of June 2026, with about 75% coming from businesses, which JPMorgan says should help streamline go-to-market and provide valuable model-training data. The firm also said Cursor data is already showing up in Grok’s supplemental training, with tangible improvements in recent model performance. 10. OpenAI says its new Broadcom-built Jalapeno AI chip outperformed Nvidia $NVDA GB300 in both throughput per watt and response latency during internal testing, according to Bloomberg. The chip is built specifically for inference, not training, and runs at roughly 700 watts. OpenAI plans to begin deploying Jalapeno for its models later this year, saying the performance gap widened on larger workloads, including Moonshot’s Kimi model, and that the chip has also performed well on unreleased OpenAI models. The key caveat is that Jalapeno was tested against GB300, not Nvidia’s newer Vera Rubin generation. OpenAI says a second-generation chip is already nearing tape-out, while work on a third generation has begun. 11. The top 10 most active options today by contracts traded were $NVDA with 1.8M contracts, $TSLA with 1.8M contracts, $AAPL with 636K contracts, $SPCX with 548K contracts, $INTC with 540K contracts, $AMZN with 498K contracts, $MU with 483K contracts, $AMD with 403K contracts, $PLTR with 361K contracts, and $SOFI with 359K contracts. 12. Raymond James raised its Nvidia $NVDA price target to $352 from $330 and reiterated a Strong Buy rating. The firm says Nvidia’s CPU opportunity is becoming more important, especially for agentic AI workloads, even though CPUs are only about 3% of sales today. Raymond James expects CPU revenue to reach roughly 5% of total revenue by CY28 and believes Nvidia could potentially become the world leader in CPU revenue within several years. The firm also argued the stock remains inexpensive, trading at less than 15x CY27 GAAP earnings, below the S&P 500 at 18.6x, despite sales and net income growth still expected to exceed 20% in CY28. Its new $352 target is based on a 22x multiple on CY28 estimates, which Raymond James views as conservative given Nvidia’s leadership, CUDA moat, GPU performance, free cash flow, and history of trading at much higher multiples. WALL STREET IS THE GREATEST SHOW ON EARTH.