robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 is one of the tokens I’ve been asked about the most today It ran from a small cap to over $50M MC, before correcting back to around $25–30M The narrative is genuinely interesting, but this move didn’t happen because of one single factor Let’s break down what’s actually behind robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 1. It all started with real research The first thing I like about robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 is simple : The narrative existed before the token On September 3, Google Research, HHMI Janelia, Cambridge, and other research groups published the connectome of the adult male fruit fly’s central nervous system The original scientific dataset contains roughly 166K neurons and ~125M synapses This is a real scientific milestone, not something the robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 team made up to create lore for a memecoin There’s one detail worth clarifying because CT has been mixing this up The simulation on the robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 site doesn’t run the entire ~125M synapses directly. After filtering out weaker connections with fewer than 3 synapses, the graph being used contains roughly 10.2M connections So the distinction is : ~125M synapses = the original scientific dataset ~10.2M connections = the filtered graph used in the simulation Things got more interesting after the research became public Developers started experimenting with the fly connectome in environments like Minecraft, Doom, Mario, etc A fairly niche neuroscience topic suddenly became an internet meme that anyone could understand : “We mapped the wiring of a fly brain. What happens if we put it inside a computer and let it play games?” And robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 appeared right as this narrative started going viral 2. But what does a “fly brain living on the internet” actually mean? This is something I think people need to understand properly before getting bullish robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 is not a conscious fly living onchain, and it’s not an LLM-based AI Agent that can think for itself, read X, and decide what to trade A connectome is basically a wiring diagram of the nervous system The project uses that wiring to simulate neural activity, then maps different inputs and outputs into interactions with an environment For example, visual input from a browser can be converted into stimuli for the simulation, while certain descending neurons can be mapped to actions like moving forward, backward, left, right, or clicking Put simply : It doesn’t “read” a website the way we do. It reacts to inputs through a neural model built from a real connectome Some parts still require human/script assistance So if the narrative becomes : “A living fly brain is independently trading and launching memecoins” I think that goes further than what the project is actually doing But I don’t think that makes the idea less interesting If anything, the differentiator here is the real biological wiring The market already has countless projects taking an LLM, attaching a wallet to it, and calling it an AI Agent A simulation built around a real connectome naturally creates much more curiosity 3. From a science experiment to a stock meme This is where the crypto side gets interesting robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 was launched on Robinhood Chain through Pons and paired with GOOGL I think the way the narrative is packaged is pretty smart Google Research is directly connected to the original scientific story Robinhood Chain already has a stock/tokenized-stock meta And Pons allows memes to be paired with stock-linked assets So everything connects pretty naturally : Google => Fly Brain => GOOGL => Robinhood Chain => Stock Meme That makes robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 more than just another “fly meme” It sits right at the intersection of science, neuroscience/AI attention, internet memes, the stock meta, and Robinhood Chain I think that’s one of the main reasons it was able to expand so quickly 4. Where is all the attention coming from? This is where I think the narrative is quite different from a typical memecoin The attention is basically forming across three layers The first is science/mainstream The research is real, and names like Google Research, Janelia, and Cambridge are genuinely behind the original scientific work The biggest account pushing the underlying research that I found was @NewsFromGoogle, whose MaleCNS post reached around 13M views based on the data I checked Polymarket also posted about the milestone of mapping more than 166K neurons But this distinction matters : Google and Polymarket are talking about the research. They are not endorsing robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 I only see this as evidence that the underlying narrative has grown beyond the neuroscience community The second layer is internet virality Accounts like @evnschlr, @jbohnslav, @nftecchie_ and @sainimatic have posted fly-brain-related experiments/content that reached millions of views They are not shilling the token either But they are doing something important: repeatedly putting the “fly brain” concept back onto people’s timelines The final layer is crypto attention One major catalyst was Marc Andreessen following the project’s official account That’s obviously a meaningful signal for a new meme, but again, it needs to be framed correctly : pmarca followed the account. He did not tweet the ticker or endorse the token robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 has also started appearing on the timelines of crypto accounts such as @CryptoGorilla, @fuelkek, along with Chinese CT accounts and traders within the Robinhood ecosystem I don’t really care who bought early or how much anyone made What matters to me is that attention from the broader fly-brain narrative has started being funneled toward the actual robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 ticker The flow looks pretty clean : Science creates the narrative => the internet turns it into viral content => crypto starts capturing that attention into a ticker Google doesn’t need to tweet robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 As long as the internet keeps talking about fruit fly brains, and robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 remains the main token representing that story in crypto, it can still benefit from attention coming from outside the market With memes, I care more about who owns the narrative in the market’s mind than simply counting how many KOLs are shilling it 5. A good narrative still needs good token data At the end of the day, this is still a memecoin Based on the data I checked, supply is 1B, tax is 1/1, and the creator had already collected roughly $329K in fees at the time I checked Holders have grown to around 8K+, while 24H volume has reached tens of millions of dollars One thing I’m watching closely is that liquidity isn’t particularly deep relative to its volume and valuation That cuts both ways When attention is strong and capital keeps flowing in, price can expand extremely quickly But once attention flips, the downside can be just as violent So I don’t want to see $30M, $40M, or $50M in volume and automatically conclude that demand is strong For something like this, I want to look at : Volume + liquidity + holder growth + distribution + sell pressure The narrative determines whether people want to look at the token The structure determines whether I actually want to put money into it 6. The problem now is that a lot of catalysts are already priced in This is probably the most important part if you’re looking at robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 at its current valuation The paper is already public Google has already pushed the research to millions of people Fly-brain experiments have already gone viral pmarca has already followed Crypto KOLs and CT have already discovered the token And the chart has already expanded from a small cap to over $50M MC Copycats are starting to appear too So if your thesis for buying here is still : “Google mapped a fly brain + pmarca followed.” I think you’re a little late The market has already traded those catalysts At $1M or $3M, a strong narrative alone can sometimes create a great asymmetric bet At $25–30M, the question has to become : What hasn’t the market priced in yet? And that’s where I start looking at the next catalysts The first is the olfactory/smell feature The team is working toward expanding the simulation into olfaction. If they can turn that into a visually compelling demo, for example mapping tokens, markets, or environments into inputs the fly can “smell,” I think that could create another wave of content Not because it suddenly gives the token massive utility But because if a meme wants to stay alive, it needs a new reason for the market to talk about it again The second catalyst is more convincing web/onchain interaction The “fly launched its own coin” lore is great, but there is still human/script assistance involved If the team can push the experiment further, show clearer live logs, and have the fly browse, click, or interact with an onchain environment in a more convincing way, I’d value that catalyst much more than another KOL follow The third is a second science/media wave This research is still fresh If Google, Janelia, the neuroscience community, gaming community, or mainstream media continue producing new experiments around it, robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 can keep benefiting from indirect attention without any of them mentioning the token But the biggest catalyst for me is much simpler : Can robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 become the default ticker for the entire fly-brain narrative? If dozens of copycats appear but people still think of robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 first whenever someone says “fly brain coin,” then it has built a form of attention moat At that point, copycats can almost become free marketing for the original That’s what could turn this from a runner that lasts a few days into a narrative with a much longer lifespan 7. What does the risk/reward look like here? This is where I start getting more cautious The narrative is strong, but the narrative premium is no longer cheap At $25–30M, the market has already priced in the research, viral clips, the pmarca follow, and some expectation that robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 will become the main runner of this narrative At the same time, the token doesn’t yet have enough utility/value accrual to create a clear valuation floor, liquidity still needs to be watched, copycats are appearing, and attention on Robinhood Chain rotates extremely quickly There’s another risk that I think could easily become FUD later : A connectome is not the same thing as a conscious brain If the market starts telling the story as “a living fly brain autonomously launching and trading coins,” expectations will move far beyond what the product actually does When the chart is green, nobody cares When the chart gets weak, things like human assistance, scripting, and the limitations of the simulation can quickly get turned into FUD So from here, I want to see whether the team keeps shipping real experiments or just keeps recycling Google + pmarca to maintain attention 8. My chart view and plan On the chart, robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 made an almost vertical expansion to over $50M MC, before correcting roughly 40–50% back into the mid-$20M range Personally, I don’t like chasing around $25–30M after a move like that If buyers continue absorbing supply, volume resets, and price reclaims $30M+, I’d view the structure as much healthier If it corrects further, $18–22M is the first area where I’d start watching closely The $12–15M range becomes more attractive from a risk/reward perspective if the narrative is still alive and robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 remains the main runner But I’m not trading an entry based on MC alone If it’s at $15M but volume is dead, the official account stops shipping, and attention has moved somewhere else, then $15M is still expensive On the other hand, if the team ships a strong new catalyst and the market reclaims structure, I don’t necessarily need to wait for an exact number either What I’m watching is : Price + volume + attention + what the team is actually shipping If volume collapses, holder growth stalls, the team stops building, robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 loses its main-runner position to a copycat, or the entire Robinhood meta rotates elsewhere, my thesis changes very quickly 9. Final thoughts If I’m rating the idea/narrative alone, I’d rate robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 pretty highly Not simply because “AI + crypto” sounds good The sequence is what makes it interesting : Science happened first => the internet made it viral => the token appeared afterward to capture the attention I like that structure much more than launching a token first and then paying KOLs to manufacture lore around it But robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 is not a hidden gem anymore It has already made a huge move, ATH was above $50M, CT has discovered it, and most of the obvious catalysts have already happened So the bull case from here has to come from something new That could be the olfactory feature, a new demo, more convincing web/onchain interactions, another science/media wave, or ideally robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 establishing itself as the default ticker for the fly-brain narrative If those things continue getting validated, I think a second leg is absolutely possible But if the team stops shipping and the official account just keeps recycling the Google + pmarca story while volume starts bleeding, I’m not going to marry the bag just because the original idea was good TL;DR : I’m bullish on the robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 narrative, but at the current valuation I’m not interested in FOMO it From here, I’m not watching the catalysts that already pumped the chart I’m watching what the team ships next that gives the market a reason to talk about robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35 all over again 0x4Eb990547BCe4a982432CA88Cf5fae7EED1A2d35

OMG - this made my day: the amazing @Grimezsz follows me!! 🥹💗 What a wonderful surprise. I feel inspired—and more empowered already. ✨ Can’t wait to keep learning from your wildly original mind, Grimes. And I’d absolutely love to do an in-depth interview with you, hopefully soon! Let’s talk! 😻 🫶

Day 9 of making an autonomous G1 Bartender. It appears that when trying to transfer a policy from sim to real, the joints moved too quickly. I thought that this was a simple fix and to just create an adapter to move the joints below a certain threshold but there needed to be a lot more converting than anticipated. I went back to the sim -> behavior cloning -> humanoid movement copies -> astra controlling the G1 and realized that the original ~67 samples that were provided had really bad flicks and that we may need to redo the entire process. I made astra generate a new episode of picking up a can in sim and tested it out on the G1. After changing the limitations that astra set on the joint limits, I finally got the G1 to move acording to the controlled sim (not policy). Now I'll be generating ~30 episodes with astra and restart the entire training process. The majority of the morning was spent redesigning sim to real. I kept asking what the inputs to the policy were and astra constantly told me that it was RGB-D (i thought normal images + depth), joint velocities, accelerations, and their position (the robot knows this in real life too). But there was actually an entire processing step trying to get the hand to can locations and the RGB image was not being fed into the network at all. All gpts do is lie, smh.

MiMo-V2-Pro & Omni & TTS is out. Our first full-stack model family built truly for the Agent era. I call this a quiet ambush — not because we planned it, but because the shift from Chat to Agent paradigm happened so fast, even we barely believed it. Somewhere in between was a process that was thrilling, painful, and fascinating all at once. The 1T base model started training months ago. The original goal was long-context reasoning efficiency. Hybrid Attention carries real innovation, without overreaching — and it turns out to be exactly the right foundation for the Agent era. 1M context window. MTP inference for ultra-low latency and cost. These architectural decisions weren't trendy. They were a structural advantage we built before we needed it. What changed everything was experiencing a complex agentic scaffold — what I'd call orchestrated Context — for the first time. I was shocked on day one. I tried to convince the team to use it. That didn't work. So I gave a hard mandate: anyone on MiMo Team with fewer than 100 conversations tomorrow can quit. It worked. Once the team's imagination was ignited by what agentic systems could do, that imagination converted directly into research velocity. People ask why we move so fast. I saw it firsthand building DeepSeek R1. My honest summary: — Backbone and Infra research has long cycles. You need strategic conviction a year before it pays off. — Posttrain agility is a different muscle: product intuition driving evaluation, iteration cycles compressed, paradigm shifts caught early. — And the constant: curiosity, sharp technical instinct, decisive execution, full commitment — and something that's easy to underestimate: a genuine love for the world you're building for. We will open-source — when the models are stable enough to deserve it. From Beijing, very late, not quite awake.

I wrote this journal entry exactly five years ago while shooting my 99 Originals Polaroid project. Today, on the 25th anniversary of 9/11, I wanted to share it. DAY 12 — #11# GROUND ZERO, 9/11/21 Today was much more powerful than I’d ever expected. I had the privilege of attending the 20th anniversary of the 9/11 Ceremony at Ground Zero with Zelina Vega (a WWE superstar whose father passed in the 9/11 tragedy, real name Thea). As I solemnly paced around the site with my stupid little Polaroid, the essence of mourning was overwhelming. Hundreds of families affected by a deliberate and malicious attack on our nation - left without fathers, mothers, sons and daughters. We hear stories of the tragedy and see the videos, but most people never really truly experience the lifelong ripple effect it’s had on the victims and New York. The city was overflowing with patriotism on this day, and I was proud to be supporting in attendance. I got a chance to speak with Thea’s mother — the kindest, most gentle, warm-eyed, inviting little soul, who remains scarred from two decades’ worth of lament when her husband got trapped in the South Tower. Throughout the morning, she’d reminisce… where she was, how she felt, keeping her children calm… She told me she had spoken to her husband before he passed. He called her after the first plane had hit, and they’d spoken from 9:04-9:15am. I asked her what he said. She said “he just called to say goodbye.” And I broke. I couldn’t hold back tears as I wept beneath my baseball hat and pulled up my mask to the bridge of my nose. I turned around and took a second to collect myself, but as I stood on the ground of the most devastating terrorist attack in United States history, I couldn’t help but sob. My tears bounced off the black marble etched with the names of those we lost. Thea gave me a comforting hug. I said “y’all are way tougher than me” as I tried to nervously laugh off my tears. While I had never felt such an overwhelming sense of grief, Thea and her mother stood stoically… it was clear that this sadness was all too familiar for both of them. At the end of the day, Thea and her mother thanked me for helping to cement 9/11 in history to be remembered and memorialized in an appropriate fashion. She also thanked me for making her laugh, and that it made her day much easier.

Fewer than 1 in 20 films submitted to Fairground make it to Amazon Prime, Roku, Xumo and LG. So…what actually makes the cut for Fairground AI TV? Since launch, one question has come up more than any other from the AI filmmaking community: what is Fairground looking to distribute? To answer it, we asked Alexandra Mills, our Head of Production, to explain what makes the cut for Amazon, Roku, and our other platform partners. Here's how the team evaluates content: Story first. "Plot, characters and the world are always top of the list," Alex says. "A tight 5-minute film with a real story beats a beautifully rendered 20-minute film with a weak plot, every day of the week." Length matters, but not how you'd think. Content needs to be 3+ minutes. Longer generally makes distribution easier, but length never wins over quality. Focus on the story and the length that best fits. That's what matters. Original IP Only. Every submission through the Fairground Portal goes through copyright, music licensing and trademark reviews prior to distribution. Collectively, we need to ensure that all work is 100% original and is the very best of AI cinema.  Make sure everything, including your music, is original. Formatting is strict. We distribute only 16:9 right now (no vertical), and we're aiming for PG-13 as the default, though we do have late-night slots that can carry TV-MA and above. Genre shifts with the calendar. We distribute across every major genre, but what we prioritize moves with tentpole moments and what our platform partners need. Right now: horror for Halloween, and animated work for a separate opportunity. And the thing that matters most: did we feel something? "Did the combination of human artistry and generative AI tools produce a story worth telling?" Alex says. "That's the real bar, and it should be every creator's North Star." The decisions don't stop once content airs. Fairground runs dynamic scheduling, constantly watching how content actually performs. Stream starts, watch time, overall session time. Overperforming content earns a better slot. Underperforming content makes way for something new. The lineup is never static, and neither is the bar we use to make decisions. As the technology improves, standards will increase over time. If you are submitting new content for consideration, it may take 3-4 weeks for it to be reviewed for distribution, as submission volume has increased since launch. We appreciate your patience and while it may take us time to review your film, we want to give it the time and consideration it deserves. We don’t want to rush something you put time, money and real work into. We just wrapped our first month and the data has already surprised us. More on what we're learning (including a heat map of our top-performing programming windows) is coming soon. For now: what other questions do you have? Drop your questions below, Alex will be reading and answering in the comments👇

Today a crazy quantum story just got wilder. On March 31, the Google Quantum AI team published a landmark result on Shor's algorithm for elliptic curve cryptography. Technically, the paper was a bombshell: a dramatic 10x improvement over the state-of-the-art. As a stunt and wakeup call to the blockchain space, those optimisations were illustrated on secp256k1, the elliptic curve underlying Bitcoin and Ethereum signatures. But perhaps the most striking part of the paper was sociological, not technical. Instead of following standard academic process, the optimisations were kept secret, hidden behind a zero-knowledge (ZK) proof. Google's accompanying blog post mentions they "engaged with the U.S. government". The ZK proof demonstrates the existence of algorithmic improvements without leaking details. Academic censorship with ZK, a historic first! As a co-author of the Google paper I witnessed some of the context surrounding this censorship. To be honest, multiple aspects of that context don't sit well with me. As much as I believe the general public ought to know more, I am limited in my ability to whistleblow. Though let me be clear about one thing: the Google team's professionalism has been absolutely exemplary, and they deserve nothing but praise. Censorship has a way of backfiring. The Streisand effect, where an attempt to bury something only draws more attention to it, is exactly what's unfolding today. First, Google's key optimisation has been rediscovered by the French. And in a thrilling turn of events, a collaborative Shor-at-home challenge just launched. The initiative, available at ecdsa[.]fail, breached a new Shor world record in a matter of hours. Let's start with the rediscovery. Just two months after Google's paper, French quantum expert André Schrottenloher cracks the main secret optimisation. His paper, titled "Optimized Point Addition Circuits for Elliptic Curve Discrete Logarithms", landed on the arXiv today. Big congrats to André, who beat several other nerdsnipped experts to it. In a blog post also published today, Craig Gidney, the world expert on Shor optimisations, revealed that he'd been sitting on this very optimisation for a whole year under censorship pressure. Interestingly, André missed a handful of minor optimisations, both from Google's original publication and from improvements found since. It's plausible there's still plenty of juice left to squeeze out of Shor, and this is exactly what the ecdsa[.]fail challenge is about. The verifier program developed for the ZK proof does double duty, automatically filtering for valid submissions. Dozens of compounding small and micro improvements are rolling in. As of the time of writing there's an 8.4% improvement to Google's circuit, as measured by the product of logical qubit count and Toffoli gate count. Nice! The nerdsnipping ran deeper than anyone expected. Over the last few weeks it became clear it extended well beyond André and other quantum experts. Behind the scenes, a small army of amateurs quietly got to work. Inspired by Karpathy-style autoresearch, they turned AI on Shor. Ironically, the verifier program for the ZK proof makes an ideal reward function for AIs. The barrier to entry for this modern style of research is refreshingly low, with several non-experts, even a teenager, finding nice optimisations. Get in touch if you'd like to join a Telegram group with fellow autoresearchers :) Part 2: neutral atoms and qday The story doesn't end with Google. On the same day Google went public, a stealthy startup called Oratomic published its own Shor paper in a coordinated release. It made a splash, ultimately becoming the most upvoted paper on scirate[.]com, a website ranking arXiv papers. Oratomic's claim was wild. By building on Google's logical optimisations and applying custom physical optimisations for neutral atoms, they claimed just 10K physical qubits were sufficient to run Shor's algorithm on secp256k1. That number is mind-bogglingly low. Knowing essentially nothing about neutral atoms when Oratomic's paper landed, I was intrigued and decided to learn more about the tech. I fell straight down the rabbit hole and spent a couple hundred hours on the topic. I got a little obsessed and watched every YouTube video I could find and spoke to a bunch of experts. My conclusion? The tech is real, very real. Even Google recently decided to start a neutral atom lab, a notable pivot from their sole focus on superconducting qubits. If you care about qday, i.e. the day a quantum computer will break the first piece of cryptography in production, neutral atoms demand your attention. I shared some of my learnings on Shor and neutral atoms in a 30min talk at the ZKProof cryptography conference. You can find it on YouTube by searching "zkproof neutral atom". Here's an interesting observation about this duo of breakthrough papers: neither Google nor Oratomic say a word about what their results mean for qday. No timelines. Zero. Nada. That is especially baffling given that the whole point of whitehat quantum cryptanalysis is to inform qday estimations and help the general public make good decisions. So let me attempt to partially fill the silence, similarly to what Scott Aaronson did in his April 29 post. Given everything I know, including scary non-public information, I now put the odds of qday by 2032 at 50%. 10% by 2030. Anecdotally, the US government has its own date: 2035. Originating at the NSA and later adopted by NIST, it's when branches of the US government will be disallowed from using quantum-vulnerable cryptography. In plain language: with hindsight, that date is a joke and should be discounted entirely. I don't see how NIST avoids being forced to pull it forward by years. Part 3: post-quantum cryptography There are good reasons to sound the alarm today, but please do not panic. Rushing carelessly towards immature post-quantum cryptography is a recipe for disaster. IMO a good target date for migration is 2029, roughly 3.5 years out. 2029 happens to be the date selected by Google, Cloudflare, and the Ethereum Foundation. These days most of my time goes to safely migrating Ethereum towards post-quantum cryptography as part of the broader lean Ethereum effort. There's a lot to do. We need to rip out and replace BLS signatures at the consensus layer, KZG commitments at the data layer, and ECDSA signatures at the execution layer. The plan to get there is compelling, and is based on hash-based cryptography. Within the Ethereum Foundation we've developed a Swiss army knife called leanVM (github[.]com/leanEthereum/leanVM) powered by the magic of hash-based SNARKs. Thanks to truly exceptional work by Emile, Thomas, and others, its performance is derisked. Regarding security, leanVM is a jewel, a minimal zkVM crafted for end-to-end formal verification and maximum security. Want to help? There are two $1M initiatives. First, the Proximity Prize (proximityprize[.]org). Solve a long-standing mathematical conjecture in coding theory, improve hash-based SNARKs, and go home a millionaire. Second, the Poseidon Initiative (poseidon-initiative[.]info), offers $1M for breaking Poseidon, the SNARK-friendly hash function.

Wealthy investors now have $170 billion in a strategy designed to generate tax losses. Four years ago, it was $2 billion. CNBC wrote about it this week. It's called tax-aware long-short investing, and if you're sitting on a big stock gain, your wealth manager may have already brought it up. I read the article and thought about pairing it with Opportunity Zones. One generates capital losses. The other gives you five years before a capital gain becomes taxable. And along the way, you move some of your wealth from a concentrated stock position into real estate. 🔷 What the account does You've probably heard of tax-loss harvesting. Sell investments that are down and use the losses to offset gains on investments you sell at a profit. The problem is that after years of rising markets, you may not have enough losers. A tax-aware long-short account owns stocks and also shorts other stocks. When stocks rise, the shorts can produce losses. When stocks fall, the stocks it owns can produce losses. The manager closes losing positions, books the losses, and replaces them while trying to maintain the account's intended stock-market exposure. You can fund the account with appreciated shares without selling them first. As losses become available, the manager can use them to offset gains from selling down your concentrated position. A dollar of capital loss offsets a dollar of capital gain. How much the account generates, and how quickly, depends on the strategy and the market. 🔷 Where Opportunity Zones fit Normally, if you sell appreciated stock this year, you need losses available this year to offset the gain. An Opportunity Zone investment changes the calendar. Under current IRS guidance, you can sell stock in late 2026 and invest the gain in a Qualified Opportunity Fund in January 2027, provided you're within the 180-day window. The gain stays deferred for five years. At the five-year mark, 10% is forgiven. Now you have until 2032 to plan around that gain, while the money is invested in a real estate project. I joke that if you ask 10 CPAs whether they'd rather have a client's tax bill coming due next April or five years to plan for it, all 10 will take the five years. Give them a loss-generating account to work with during those five years and you can see why this pairing interests me. 🔷 The math You own $10M of Nvidia with a $1M basis. You want to diversify into both other stocks and real estate. Sell $2.5M of Nvidia in late 2026. Those shares have $250K of basis, leaving a $2.25M gain. Invest the $2.25M gain in a QOF in January 2027. The $250K of basis is yours to keep. Recognition of the gain moves to 2032. Contribute the remaining $7.5M of Nvidia to a tax-aware long-short account without selling it. Over the next five years, the manager seeks to generate losses and uses some to offset gains as it sells down your remaining Nvidia. Unused capital losses can carry forward. Then the OZ gain comes back. After the 10% reduction, you have $2.025M of taxable gain. At a 23.8% federal rate, that's about $482K in tax before loss offsets. If you have $1M of available capital losses, the bill falls to about $244K. If you have $2.025M of available capital losses, the federal tax on that original sale is zero. The actual tax bill will depend on how much capital loss you have available in 2032. And losses already used to sell Nvidia aren't available again in 2032. 🔷 The money wasn't sitting still The $2.25M was invested in real estate. Hold the qualifying OZ investment ten years and its appreciation can be tax free too. Meanwhile, the long-short account is working to diversify the remaining Nvidia into a broader stock portfolio. You started with one company. You're moving toward ownership in many companies and a real estate investment. 🔷 The trade-offs Long-short accounts charge fees, use leverage and short positions, and cannot promise a particular amount of losses. Your remaining Nvidia can fall while you're waiting to sell it. Harvesting losses generally defers tax. Embedded gains remain in the account, and unwinding it can trigger a bill. The OZ portion is a long real estate hold. You can't sell a quarter of an apartment building when you need cash. If the losses aren't there in 2032, you need another source of money to pay the tax. And the tax benefit doesn't save a bad deal. Pick the building first. If you're sitting on a large stock gain, ask your CPA and wealth manager to model the combination. This is a tax post from a guy who builds apartments.

A TON OF THINGS HAPPENED IN THE STOCK MARKET TODAY. Here's a full recap: 1. Crypto markets saw their seventh-largest liquidation event on record, with $3.5B in leveraged positions wiped out over 24 hours. Despite the forced liquidations, the total crypto market cap added roughly $280B in the same period as $BTC Bitcoin crossed $72K and $ETH Ethereum moved above $2,300. The rally came alongside renewed optimism around the CLARITY Act and broader tokenization legislation. 2. Treasury Secretary Bessent said the U.S. Treasury will assess bond market conditions and take further action if needed, while focusing on fundamentals and keeping the market in equilibrium. He said U.S. yields do not reflect underlying fundamentals and that liquidity in the 30-year is “particularly poor,” while also arguing that rates had “nothing to do” with the buyback decision. Bessent reiterated that the U.S. continues to have a strong dollar policy, said 2026 tariff income should be similar to 2025, and added there is a “very good chance” the U.S. has already seen peak deficit. On Iran, he said the U.S. is pursuing “maximum pressure,” with coordinated economic isolation and action against countries doing business with Tehran, while adding that China and others want the Strait of Hormuz reopened. 3. Anthropic is reportedly adding Citigroup to its IPO bank lineup, joining Morgan Stanley, Goldman Sachs, and JPMorgan among the lead banks working on the listing. The company is considering filing as soon as the end of August, with more banks expected to join the deal. Anthropic is expected to debut ahead of OpenAI and is also expanding a pre-IPO credit facility beyond its roughly $10B target. If Anthropic tries to raise more than SpaceX, it could become the largest IPO ever, underscoring how intense investor demand has become for frontier AI companies. 4. Deutsche Bank reiterated its Buy rating and $200 price target on Palantir $PLTR, saying the company continues to stand out in turning AI demand into measurable customer value while combining strong growth with profitability. The firm said Palantir’s Bootcamp reinforced its view that Ontology, AIP, and sovereign AI capabilities create durable differentiation as enterprises move AI into production. Deutsche Bank highlighted AIP Evolve as a key product for optimizing AI workflows across quality, cost, latency, and control, with the ability to test frontier, open-weight, and proprietary models, reroute workloads, rewrite prompts, or replace unnecessary model calls with deterministic code. The firm said this creates “model liquidity,” while AutoTune helps customers fine-tune models using governed workflow feedback, keeping proprietary knowledge inside their own environment and addressing major barriers to scaled enterprise AI. 5. Amazon $AMZN plans to invest more than $2B across Latin America from 2027–2030 through Prime Video, focused on original content and live sports. The company expects to more than double its Originals across 5 major markets, while also expanding NBA coverage and third-party streaming access. The push shows Amazon continuing to use Prime Video as both a content platform and a broader ecosystem driver across international markets. 6. Supermicro $SMCI said an independent investigation found no evidence that current senior management knew about the alleged export-diversion scheme involving two former employees and a contractor. The review also found no direct sales of restricted products to known restricted parties and no related issues with previously issued financial statements. Supermicro said it has terminated employees for policy violations, added new export-compliance measures, and continues to cooperate with government investigations. 7. Walmart $WMT fell 8% and posted its worst day since May 2022 after reporting its slowest U.S. comparable-sales growth in more than 6 years. Q2’27 revenue came in at $187.9B versus $186.7B expected, up 5.9% YoY, while adjusted EPS was $0.81 versus $0.74 expected. Net income reached $6.5B, above estimates of $5.91B, and global eCommerce sales grew 23%. But U.S. comps rose just 2.6%, missing the 3.7% estimate, while Q3 adjusted EPS guidance of $0.62–$0.64 came in below the $0.68 expected. Management said consumers remained stretched, especially by higher gas prices, while lower pharmacy pricing also weighed on sales. 8. SpaceX $SPCX and AST SpaceMobile $ASTS are reportedly interested in acquiring 800 MHz spectrum licenses valued around $6B. The licenses cover nearly the entire U.S. population and could support direct-to-device satellite voice services. Preliminary bids are due in early September, with the FCC aiming to complete the process by November 5. 9. The top 10 most active options today by contracts traded were $NVDA with 2.1M contracts, $TSLA with 1.7M contracts, $SPCX with 1.1M contracts, $AAPL with 1.0M contracts, $MSTR with 746K contracts, $INTC with 739K contracts, $MU with 679K contracts, $MRNA with 629K contracts, $WMT with 627K contracts, and $AMZN with 614K contracts. 10. The median value of U.S. consumers’ stock market investments has climbed to a record $350K, including holdings in individual stocks, mutual funds, 401(k)s, and IRAs, as per Schwab. That figure has more than doubled over the last two years and is up $150K, or 75%, since January alone. Before 2024, the median value had never meaningfully surpassed $150K. 11. Micron $MU is committing $10B over the next decade to build Micron Research Labs, a new long-term U.S. research hub based in Boise focused on advanced memory, compute architectures, chip packaging, and next-generation semiconductor manufacturing. The company expects to break ground in 2027, with the flagship facility designed to house hundreds of researchers. The investment is separate from the more than $250B Micron has already planned for U.S. manufacturing and R&D. 12. Broadcom $AVGO is reportedly seeking more than $60B in financing tied to its latest AI deal, with the full package potentially reaching nearly $100B. The structure could include $60B–$70B of senior secured debt plus roughly $30B of junior debt, while Broadcom is also discussing guaranteeing part of the senior-secured tranche. Apollo and Blackstone are in talks to participate, with the debt potentially issued through a special-purpose vehicle. The financing would help Anthropic and other AI companies secure Broadcom chips and infrastructure, and could be rolled out in stages rather than all at once. WALL STREET IS THE GREATEST SHOW ON EARTH.

🚀 60 years ago today, Gemini IX-A launched Cernan and Stafford for a three-day mission riddled with mishaps. Cernan performed America’s 2nd EVA which he called “the spacewalk from hell” as he became the first person to orbit Earth entirely outside a spacecraft. From Gemini Remastered: “Before launch, Deke Slayton, who now ran flight crew operations, entered the room where Stafford was suiting up and asked the suit technician to leave and closed the door. He expressed NASA’s concerns about the EVA and added “In case Cernan dies out there, you’ve got to bring him back, because we just can’t afford to have a dead astronaut floating around in space.” Stafford set out his concerns about how difficult that would be and ultimately, he was Commander and he’d make the call. After suiting up, Cernan quizzed Stafford: “Deke was in there talking to you quite a while. What did he say?” Stafford replied: “He just said he hoped we’d have a good flight.” Launch day came May 17, but the rendezvous-target Agena took a nosedive into the ocean for its launch. NASA switched to a backup ATDA target vehicle (which failed to deploy properly in orbit, leaving it useless, looking like an “angry alligator”). The Gemini IX crew faced multiple launch scrubs over 17 days, with six separate entries into the spacecraft for launch. Cernan was to test a new AMU backpack with hydrogen peroxide thrusters. 80 Velcro patches were bonded to the exterior of the spacecraft and his gloves to assist in crawling to the AMU, where he was to do an untethered free-floating spacewalk — a bold mission plan that did not succeed until McCandless did it in 1984. Cernan’s suit was made extra fire retardant to resist burn through by the AMU thrusters. But this made it very rigid and difficult to move in space (like a “rusty suit of armor”). Every movement required immense exertion, which caused him to sweat profusely, overwhelming his suit's environmental control system and causing his helmet faceplate to completely fog up. He had to use his nose to wipe a small visibility window in his faceplate as he fumbled from a lack of handholds. His intense thrashing ripped through seven inner layers of heavy thermal insulation on the back of his suit, leaving a triangle of skin unprotected. When the spacecraft rotated into the daytime side of its orbit, the exterior of the suit was hit by raw, unfiltered sunlight at a blistering 250°F. Without the insulation, the searing solar heat baked right through the remaining pressure bladder layer. Cernan recalled feeling a scalding, fiery sensation on his lower back but had to ignore it because he was already fighting for his life while blind from the fogged visor. His heart rate hit 180bpm and the flight surgeon was concerned he could lose consciousness. He also lost communications fidelity, resorting to a binary code: one squawk for yes, two for no. Cmdr. Stafford decided to cancel the AMU jetpack test. Cernan called out to CAPCOM Neil Armstrong in mission control: “You might tell everyone down there I’m sure sorry about this.” Because the pressurized suit had ballooned in size with outstretched limbs larger than the hatch opening, and with Cernan completely exhausted and blind, getting back inside the spacecraft was a brutal physical struggle for both men. Together, they used the mechanical hatch-cranking mechanism to literally compress Cernan’s stiff suit and force the door closed against his helmet causing him to almost black out from an inability to breathe. Overall, Cernan lost 13 lbs. from extreme dehydration. Despite the setbacks, NASA learned valuable lessons about spacesuit design and the need for visible handholds for EVAs (which was corrected for Apollo). Here are some heroic artifacts from the Future Ventures museum: 1) The newest addition to the collection, Cernan’s Constellation Chart and Greek Alphabet Cue Card, as annotated and flown on Gemini IX-A. On the upper border, Cernan refers to the planned rendezvous with the ATDA. The accompanying Gemini 9 constellation chart showed key navigation stars labeled with their Greek letter designations (like α Lyrae, β Orionis). Since astronauts weren’t trained astronomers, they carried a Greek letter cheat sheet to quickly decode those symbols into star names and locations. They would use the legend to match ‘α’ to the brightest star in a constellation, ‘β’ to the next, and so on, letting them correctly identify stars through the spacecraft’s sextant/telescope for celestial navigation. 2) Original left-handed glove from the Gemini G3C space suit made by the David Clark Company. 3) ITT Interphones used by the frogmen during recovery at sea; it was a pluggable hard line (like in the Matrix) used throughout Gemini after splashdown. The frogmen welcome the astronauts home and let them know when it was safe to open the hatch. For Apollo, NASA switched to Motorola radios. 4) Photo of the frogmen welcoming a weary Cernan and Stafford back to Earth, with orange interphones clearly visible.