The dispersion inside the S&P 500 this year has been massive. While 99 stocks are up more than 20%, 63 names are down at least 20%, showing just how selective this market has become. Top movers include: ◾ $SNDK +539.4% ◾ $INTC +230.7% ◾ $AMD +107.9% Meanwhile: ◾ $PLTR -24.0% ◾ $TSLA -6.4% ◾ $ORCL -0.8% The S&P 500 itself? Just +8.2%.

Leopold Aschenbrenner's 13F finally dropped and X is already full of the DUMBEST interpretations possible! Please read this. 1. The 13F shows what the fund held as of quarter-end: March 31. 2. A huge part of the positions are PUTS. Does this mean he's bearish today? -> WE DON'T KNOW! Everyone is just guessing. It is completely possible that he bought those puts during the quarter as the Iran war escalated, to hedge, and they increased a ton in value. They might have started as small positions that simply grew a lot. He might have sold them at the exact bottom, perfectly timed the market, and gone 100% long for the massive rally that started on April 1. OR he was insanely bearish, bought a lot of puts, kept them, and completely screwed up by being massively positioned in puts before the craziest rally ever. He could have made the most genius move or the dumbest move possible and now look like an idiot. WE DON'T KNOW. This is the issue with such delayed reports. But of course today, you will see everyone on X go crazy with: "Leopold went short aaaaaaaaaaah, the sky is falling, he's calling for a crash." But that was months ago, in the middle of the Iran volatility! We have no idea if he added to his puts or if he's currently 100% long or maybe even bought calls?! We don't know if his move was good or bad. So while you're reading all these takes on X today, know that you're going to read a ton of complete nonsense from people who have no idea what they're talking about. But here are some things that stand out to me! While he decreased his $BE exposure, Bloom Energy was still his biggest position (6.4%) Closely followed by $SNDK (5.3%) He also cut $CRWV from 8% -> 4% I honestly can't believe he missed $NBIS so badly. He also reduced his $IREN position from 6% to 3% (even though he net added shares). Big $CORZ cut aswell from 7.6% -> 3% HUGE cut in his $CRWV calls from 14% -> 1% A lot of $TE investors are getting excited he built a position, which is definitely bullish, but it's worth mentioning that was most likely before the big drop after the disappointing earnings and it's a tiny 0.3% position for him. One of the funniest positions is a 0.15% $GLW Put lol. 100% / Completely went out of: $INTC Calls (13.5% -> 0%) $CIFR (2.8% -> 0%) $EQT (2.4% -> 0%) Photonics: $LITE (8.6% -> 0%) That one is super interesting to me. Also cut $TSEM and $COHR from 1.5% -> 0%

Foreign born population of each country : Jan 2001 Jan 2025 🇦🇹 8.7% 22.5% 🇧🇪 8.4% 20.2% 🇩🇰 4.8% 14.4% 🇫🇷 5.5% 14.0% 🇩🇪 8.9% 20.5% 🇬🇷 6.9% 11.0% 🇮🇸 3.1% 21.8% 🇮🇪 4.0% 23.3% 🇱🇺 37.5% 51.5% 🇳🇱 4.1% 16.8% 🇳🇴 4.1% 18.7% 🇸🇮 2.1% 15.5% 🇪🇸 3.4% 19.3% 🇸🇪 5.3% 20.8% 🇬🇧 4.3% 20.0% Now add children born to foreign parents and the situation looks even worse. We are living through the demographic annihilation of the people of Europe.

NVIDIA $NVDA has missed revenue expectations just once in the last 5 years: 🟢 Q1 2022: $5.66B (+4.6%) 🟢 Q2 2022: $6.51B (+2.8%) 🟢 Q3 2022: $7.10B (+4.3%) 🟢 Q4 2022: $7.64B (+3.0%) 🟢 Q1 2023: $8.29B (+2.1%) 🔴 Q2 2023: $6.70B (-6.9%) 🟢 Q3 2023: $5.93B (+2.8%) 🟢 Q4 2023: $6.05B (+0.7%) 🟢 Q1 2024: $7.19B (+10.3%) 🟢 Q2 2024: $13.51B (+20.9%) 🟢 Q3 2024: $18.12B (+12.0%) 🟢 Q4 2024: $22.10B (+7.5%) 🟢 Q1 2025: $26.04B (+5.9%) 🟢 Q2 2025: $30.04B (+4.5%) 🟢 Q3 2025: $35.08B (+5.8%) 🟢 Q4 2025: $39.33B (+3.1%) 🟢 Q1 2026: $44.06B (+2.3%) 🟢 Q2 2026: $46.74B (+2.4%) 🟢 Q3 2026: $57.01B (+4.3%) 🟢 Q4 2026: $68.13B (+3.9%) NVIDIA reports next earnings this Wednesday. 97% chance they beat it. Trade here →

$HIMX Q1’26 EARNINGS HIGHLIGHTS 🔹 Revenue: $199.0M (Est. $195M) 🟢 🔹 EPS Per Diluted ADS: $0.046 (Est. $0.03) 🟢 🔹 Gross Margin: 30.4%, at high end of guide (Est. 30%) 🟢 Q2 2026 Guide: 🔹 Revenue: +10.0% to +13.0% QoQ (Est 5%) 🟢 🔹 Gross Margin: Around 32% (Est. 30.8%) 🟢 🔹 EPS Per Diluted ADS: $0.086-$0.103 Segment Performance: 🔹 Large Display Driver Revenue: $24.2M; +11.7% QoQ 🔹 Large Display Driver Revenue Mix: 12.2% of total sales 🔹 Small & Medium Display Driver Revenue: $135.8M; -2.4% QoQ 🔹 Small & Medium Display Driver Revenue Mix: 68.2% of total sales 🔹 Non-Driver Revenue: $39.0M; -7.7% QoQ 🔹 Non-Driver Revenue Mix: 19.6% of total sales Other Metrics: 🔹 Automotive Driver Sales: Declined double digits QoQ in Q1 🔹 Smartphone IC Sales: Increased QoQ, driven by new OLED solutions entering mass production for a leading smartphone brand’s mainstream model 🔹 Tablet IC Sales: Increased QoQ, driven by renewed mainstream demand and shipments for a new premium OLED tablet 🔹 Automotive Tcon: Hundreds of secured design wins across a broad customer base 🔹 WiseEye: Adopted by a leading brand for smart glasses, with mass production expected later this year 🔹 CPO Gen 1: Small quantity shipments expected in 2H26 🔹 CPO Gen 2: Nearing completion of customer product validation for AI data center applications 🔹 FOCI Stake: 5.36%, valued at NT$4.96B / $156M as of May 7 close 🔹 Patents: 2,564 granted, 331 pending as of March 31, 2026 Financials: 🔹 Operating Profit: $10.2M 🔹 After-Tax Profit: $8.0M 🔹 Operating Expenses: $50.3M; -8.4% QoQ, +9.9% YoY 🔹 Operating Margin: 5.1% 🔹 Cash, Cash Equivalents & Other Financial Assets: $287.6M 🔹 Long-Term Unsecured Loans: $27.0M, including $6.0M current portion 🔹 Inventory: $151.7M 🔹 Accounts Receivable: $190.9M 🔹 DSO: 86 days 🔹 CapEx: $2.9M Capital Return: 🔹 Annual Cash Dividend: $0.252 per ADS 🔹 Total Dividend Payout: $44M 🔹 Dividend Payout Ratio: 100% of previous year’s profit 🔹 Dividend Payable Date: July 10, 2026 Commentary: 🔸 “We expect upward momentum through the remainder of 2026, supported by a meaningful number of new automotive projects scheduled to enter mass production in the second half.” 🔸 “The positive outlook is also supported by the anticipated growth in our non-driver IC businesses, particularly Tcon and WiseEye AI.” 🔸 “Despite ongoing macro uncertainty, Himax continues to expand beyond its traditional display IC business, focusing on key growth areas including smart glasses, ultralow power AI and CPO.” 🔸 “These emerging technologies present significant growth opportunities that help diversify our revenue base into areas with attractive gross margin profiles and profitability while also strengthening our overall competitiveness.”

In the last 6 months at @Ahrefs, we analyzed over 1 billion data points across 14 studies. Here's what we learned about AI search optimization: 1) "Best X" blog listicles are the single most prominent content format cited by AI chatbots. They make up 43.8% of all page types cited by ChatGPT specifically. 2) 67% of ChatGPT's top 1,000 citations come from sources marketers can't influence: Wikipedia (29.7%), homepages (23.8%), app stores (6.6%). Only 32.3% are influenceable content like educational pages, reviews, news, and blog posts. 3) 28.3% of ChatGPT's most-cited pages have zero Google organic visibility. These pages get cited repeatedly by ChatGPT despite not ranking in Google at all. A completely separate discovery layer. 4) ChatGPT only cites about 50% of the URLs it retrieves. It fetches dozens of pages per query but uses half as background context without attribution. This means that being retrieved and being cited are very different things. 5) Adding schema markup had zero meaningful impact on AI citations. AI Overviews actually dipped −4.6%, while AI Mode (+2.4%) and ChatGPT (+2.2%) showed changes indistinguishable from zero. 6) YouTube mentions have the highest correlation (0.737) with AI brand visibility out of all the factors we studied (including all the conventional SEO metrics like backlinks, page count, DR, etc). This held true for both Google-owned and OpenAI products. 7) AI Overviews reduce clicks to the #1# result by 58%. That’s up from 34.5% just 10 months earlier. The trend is accelerating. 8) 99.9% of AI Overviews appear on informational intent queries. Transactional, navigational, and local searches are almost entirely AIO-free. Shopping triggers AIOs just 3.2% of the time. 9) For a given search query, Google’s AI Mode and AI Overviews reach the same conclusions 86% of the time — but cite almost entirely different sources (only 13.7% citation overlap). 10) AI Overviews change every 2.15 days on average, with 70% of content differing between consecutive observations. But semantic similarity stays at 0.95. The words, sources, and entities constantly shuffle, but the actual meaning barely moves.

OpenAI just ordered 100,000 Blackwell GPUs from NVIDIA. A Chinese developer put one of NVIDIA's $3,999 desktop AI boxes on his office desk and ran the same robot simulator the big labs train on $50,000 racks. The demo was a single empty cube floating in an empty world. Fifty frames per second. He posted the clip with one line. Is this how home robotics starts or is this an expensive toy. The clip went viral the same week NVIDIA shipped the second batch of Sparks to developers. 1.8 million views in 72 hours. Every American hardware engineer shared it as proof you could finally own the rig. Every Chinese commenter left the same Mandarin reply: pause at 1:42. Pause at 1:42. Ignore the empty cube on the screen. Ignore the FPS counter. Look at the memory readout in the top bar. 2.4 GiB used. 87.4 GiB available. The cube is sitting in three percent of the memory. The empty 84 gigabytes of memory was not headroom for a future robot scene. The empty 84 gigabytes was already running. ColdMath. $138,168 profit. Joined November 2025. Bio: Edge Compounds. He had not bought the Spark to train robots. He had bought it because robots were the only workload NVIDIA shipped a 128 gigabyte chip for. The slow memory that ruined the box for real robotics was perfect for what he was actually running. Twelve hundred ensemble weather simulations in parallel. Robot training needs fast memory because every frame is a step in a training loop. Weather ensembles need huge memory because every city is a parallel simulation that does not talk to the others. The Spark's chip is six times slower than a gaming card. It is also five times larger. The trade off only matters if you know what you are running. He knew. Wellington 16C on March 28. Tokyo 16C on March 20. Every city in the wallet was a city the ensemble had simulated three hours before the public forecast posted. Comments turned into a detective board. Someone slowed the clip to 0.25x. Someone else compared the wallet's trade timestamps to the timestamps the public forecast services updated their data. Every trade landed during the three hour gap. The Spark had been catching it. Six months ago a 14 year old in Shenzhen pushed an AI agent to GitHub. Judges said no real world application. 3,100 forks later. The developer in the office cubicle had been one of them. He had wired the agent into the Spark the same week NVIDIA shipped his box. The empty cube was not a benchmark. The empty cube was a screen saver running while the agent occupied the other 84 gigabytes. The Isaac Sim install was not the project. The Isaac Sim install was the proof he could justify buying the box on company expenses. The question about whether this was a real tool or an expensive toy was the only thing in the video designed to be answered by the audience. He was not a Chinese developer testing whether home robotics had arrived. He was the first developer to figure out that the box NVIDIA had marketed for the wrong workload was the cheapest weather simulator on the market. The clip is at 1.8 million views. The forum thread is still arguing about the six times memory penalty. The Spark on his desk is still running. The wallet is still hitting cities the public forecast services have not updated yet. The cube is still floating in three percent of the memory. The country with the better robotics demo has the smaller wallet. The dev with the wrong tool for the job has the bigger one. He just had to install a robot simulator for one afternoon.

The CoinDesk 20 is currently trading at 2169.26, up 0.4% (+8.61) since 4 p.m. ET on Wednesday. Thirteen of 20 assets are trading higher. Leaders: $TAO (+1.7%) and $XRP (+1.6%). Laggards: $ICP (-5.2%) and $NEAR (-1.7%).