Rob!n

$SNAP and $QCOM signed a multi-year deal to power future Specs eyewear with Snapdragon XR chips. Snap says the standalone AR glasses launch later this year with a focus on on-device AI, graphics and shared experiences.

Google $GOOGL stock hit new all time highs today 🟢🟢🟢🟢

$NVDA HITS A NEW ALL TIME HIGH

@nrossolillo Our time will come 💪🏼

Oh hey I guess my $QCOM investment isn't dead money after all! Possible OpenAI smartphone supplier within the next couple of years.

$QCOM 👀 up big in premarket

@oguzerkan LMAO 🤣

Micheal Burry: > Closes the fund saying he doesn’t understand the market anymore. > Starts writing a blog. > Buys $ADBE, stock keeps going down. > Shorts $NVDA, stock keeps going up. > Ends up going long $MSFT. He should have stayed as the Big Short legend..

$NVDA Cost per Token Is the Only Metric That Matters disq.us/t/52xevjj

$AMD's new Ryzen 9 9950X3D2 is already the 10th best-selling CPU on Amazon, despite its $899 price tag Intel’s best-performing CPU on the list is only around 17th place, showing that AMD still has much stronger momentum in the gaming CPU market

@StockMKTNewz Well is not enough to cover the deficit but its a start

The 🇺🇸 Government's stake in Intel $INTC is now worth $36 Billion up ~4x - Bloomberg

Rumor: Qualcomm’s ARM data center CPU is scheduled to launch in June.

@ondrejslunecko Hell yeah 🤓

Are we having fun? $AMD

$AMD is pumping 🤓

Purpose-built for autonomy Cybercab in production now at Giga Texas

@bluechipdaily As am I 😎

Overhead on X: "no CEO in American history has made shareholders this much money this fast" - as $TSLA. Fact is Jensen Huang at $NVDA generated more market cap (value) from October 2022 - Jan 2024 than the entire $TSLA market cap. The $NVDA move in just the past 24 months is 2x the $TSLA market cap. I'm holding both.

You want scale: 960,000 NVIDIA Rubin GPUs in a multisite cluster “At Google Cloud Next, Google announced A5X powered by NVIDIA Vera Rubin NVL72 rack-scale systems, which — through extreme codesign across chips, systems and software — deliver up to 10x lower inference cost per token and 10x higher token throughput per megawatt than the prior generation.  A5X will use NVIDIA ConnectX-9 SuperNICs, combined with next-generation Google Virgo networking, scaling to up to 80,000 NVIDIA Rubin GPUs within a single site cluster and up to 960,000 NVIDIA Rubin GPUs in a multisite cluster, enabling customers to run their largest AI workloads on NVIDIA‑optimized infrastructure” blogs.nvidia.com/blog/google-cl…

Very insightful interview with a $AMZN AWS employee explaining how the demand dynamic of GPUs and power looks like today: 1. According to him, in Q1 for AWS, there was around 20% deficit of what their needs were for GPUs, meaning they couldn't get enough GPUs. The deficit used to be smaller than 20% in the past (even in Q3 2025, when they had the highest demand spikes). 2. He mentions the problem of many clients wanting to upgrade to $NVDA's B300, and that they didn't have that problem with B200. Now, a lot of B200 orders have moved to B300, and he thinks a similar situation will happen with Rubin. 3. In his view, in terms of performance, he thinks $NVDA is best at inference as they have 35 times better throughput per megawatt for inference than any other GPU in the market. For training, $NVDA is still one of the best, but he does mention that a lot of companies, $AMZN, $GOOGL have really good training chips, but they are not selling them directly. 4. He talks about other constraints outside of GPUs, like power, that are tapering down growth. He would probably need 4GW of power quickly, but he can probably get half of that. It is also hard to get power, as you are competing with other hyperscalers that also want that much power. 5. In his view, the GPU cycle is 3-5 years. He also mentions the problem of clients now wanting to switch to the newest models sooner. He also explained that when a newer model comes out, the older racks are probably about 25% cheaper, and towards the end of their life, they lose most of their value. My comment: The compute shortage is real and getting more severe. found on @AlphaSenseInc

@Dr_Crossroads Capex rising won't help, FCF going to zero comming quarters doesn't sound good for the stockprice, but it seems there are more catalysts then ever, buy on weakness, HODL , a small position is better than no position I guess

$TSLA I've sold the last of my Tesla position. Tesla has been in a weird place for me for a while. I love the product. I am enamored with how amazing FSD (in a HW4 stack) is, and how excellent the vehicle is. My wife and I aren't likely to buy any vehicle that isn't a Tesla, and I'm already thinking of that nice upgrade (3-4 years from now) for my '22 Model 3. I also would love to own an Optimus at some point. I love the vision, the vertical integration, and wouldn't bet against Elon. Yet the stock is not the company. Tesla has always traded at a premium, but that premium is increasing over time. That's fine if it's in anticipation of significant future acceleration, but it's questionable when that happens. On the call, they stated, “over time, we expect our hardware-related profits to be accompanied by an acceleration of AI, software and fleet-based profits,” but were effusive on the dates. That's probably for the best, as Elon timelines usually need to be extended. Gross margins have improved, and the P/FCF looks like it's improving, but with the CapEx they're needing to do, this ratio will soon be negative. I don't mind buying a stock with extreme multiples, but I see easier opportunities with clearer runways for acceleration elsewhere. Tesla hasn't been a meaningful position for me for over a year, but I'm out for now. I'll still be rooting for the company (and shareholders) even while hoping the stock comes down to more reasonable levels where the R/R fits my portfolio better.

Q1 2026 Shareholder Update #quarterly-disclosure" target="_blank" rel="nofollow noopener">ir.tesla.com/#quarterly-dis… We continued to make meaningful progress on the build out of the infrastructure & AI software that underpins our Robotaxi & future robotics businesses in Q1. That meant commencing the ramp of new factories across AI compute, battery & battery materials, as well as preparing lines for start of production of Megapack 3, Cybercab & Tesla Semi. Demand for our vehicles continued to grow in APAC & South America markets, with a rebound of demand in EMEA markets & North America. As trade and geopolitics become more uncertain, we're further regionalizing and vertically integrating critical supply chains to ensure access to key materials & componentry in each region across vehicle, energy & AI. Automotive – Optimizing our vehicle product portfolio with an emphasis on vehicles designed for a fully autonomous future – More affordable trims of Model 3/Y & rollout of Model Y L in markets outside of China – Began deliveries of Cybertruck in the UAE – Volume production of Cybercab & Tesla Semi this year Energy Generation & Storage – Good progress with new Megafactory outside Houston (will produce Megapack 3 for Megablock). Start of production on track for later this year – We began meaningful customer deployments of Tesla’s first in-house designed solar panel produced at Giga New York Robotics – Preparations for our first large-scale Optimus factory will begin shortly in Q2. First-gen line designed for 1M robots/year will replace Model S/X lines in Fremont Factory, second-gen line is being prepared at Giga Texas (long-term annual capacity of 10M robots/year) AI Training Compute – Cortex 2 is now online & has started running training workloads – Also ramping on-site training infrastructure to ensure sufficient compute resources for AI products & services – Continuing with custom silicon development (Dojo 3) to reduce training cost over time Battery – Ramping new battery & material factories, including LFP cells in Nevada, cathode material & lithium refining in Texas – Battery vendor cell availability continues to be a limiting factor on ramping vehicle production, so we're working on initiatives to de-bottleneck, including using 4680 cells at Giga Berlin Other Supporting Infrastructure – Giga New York is now producing V4 Supercharging cabinets (3x power density & 2x the number of stalls vs V3) – Alongside the ramp of Tesla Semi, we're deploying public Megachargers, including our first one in SoCal – Over 2,200 new Supercharger stalls, growing the network 19% YoY AI Software – FSD 14.3 launched in April – Upgraded Reinforcement Learning (RL) stage to better handle long-tail edge cases, enhanced the neural network vision encoder for sharper perception in low-vis scenarios & rewrote the AI compiler to accelerate model iterations & cut inference latency by 20% (faster reaction time for FSD!) This accelerates our efforts to eventually deploy unsupervised autonomy to both the Robotaxi fleet & customer owned vehicles – Digital Optimus: our next evolution of AI development. We're working on automating digital workloads, building an intelligence layer that will complement real-world AI in vehicles & robots AI Inference Compute – Expanding our scope of manufacturing to include semiconductor fabrication (coinciding with Robotaxi & Optimus ramps) = step towards ensuring sufficient & resilient chip supply – Partnership with SpaceX aims to build the largest chip fab ever, vertically integrating logic, memory & advanced packaging to allow for rapid iteration – Completed final chip design of AI5 (our next-gen inference processor) in April Automotive & Other Software – Rolled out Spring Update which includes a new Self-Driving app with tutorials & stats, "Hey Grok" wake word w/ location-based reminders, accent lights for blind spot alerts, updated Pet Mode & more Robotaxi – Paid Robotaxi miles doubled sequentially in Q1 – Cybercab will begin replacing Model Y fleet once in production & be the largest volume vehicle in the fleet over time – Continuing to lay the groundwork for expanding into new cities (testing, permitting), so we can launch quickly once ready. Safety remains top priority – Expanded unsupervised ops in Austin & launched in Dallas & Houston in April FSD Supervised – Record net new FSD subscriptions in Q1 – Received approval to deploy FSD Supervised in the Netherlands in April, clearing the path for potential approval in other EU countries – Continuing to make progress on approval in China Automotive Services – Safety Score v3.0 enables every mile driven with FSD Supervised engaged to receive a score of 100. Higher Safety Score over time = lower premiums for Tesla Insurance customers

TESLA $TSLA JUST REPORTED EARNINGS EPS of $0.41 beating expectations of $0.34🟢 Revenue of $22.4B missing expectations of $21.9B🟢 Tesla says Cybercab, Tesla Semi and Megapack 3 are on schedule for volume production starting in 2026 Once in production, expect Cybercab to begin to replace existing Model Y fleet and will be largest volume vehicle in fleet over time Preparations for first large-scale Optimus factory will begin in Q2 Are expanding scope of manufacturing to include semiconductor fabrication in AI inference compute

@JuanRodrig07 Results first 👀

$PYPL PayPal Ads Brings Purchase Attribution to Connected TV Through PayPal Curated Ads “Curated Ads ties PayPal's Transaction Graph to premium Connected TV inventory. Targeting and attribution that traces back to real product purchases across 30M+ merchants.” “Curated Ads activates this signal end-to-end, enabling audience creation based on observed purchase behavior rather than inferred or cookie-based data. Inventory is sourced directly from premium CTV and open web publishers, including Spectrum Reach, Tubi, and Warner Bros. Discovery. Attribution is then closed back to verified PayPal transactions, delivering measurement based on actual purchases rather than clicks or modeled conversions.” "PayPal Ads specifically targets audiences based on actual transaction data, and the measurement comes back to real purchases, not proxies,” said Casey Hurbis, CMO, BetMGM. “That's a critical differentiator when we think about how our marketing performs.” Well… this could be something.