I am honestly disappointed with a lot of investors and popular accounts. They clearly didn't do their homework on $CBRS and were talking absolute rubbish. Let me clear this out. 1. Insider selling: The claim that the CEO sold 99.8% of his shares is flat wrong. Class A is what you and I trade. Class B is what founders hold, and it only converts to Class A when they sell. So the CEO shows just 17,659 Class A shares but still holds ~13.9M Class B. Did people actually read the second table? Since the IPO, insiders sold ~$400M, under 1% of the company. About 80% was pre-planned sales of old options bought at $1-8, and the rest came from VC board members and forced tax sales. Stake each still holds - CEO Feldman ~98% - CFO Komin ~97% - CTO Lie ~87% - COO Mallick ~50%, the only outlier The real short-term scare is the lockup, with ~39M shares (~16%) unlocking on Oct 14 and Oct 28. These are old shares that can now trade, not new ones. That's pressure on the stock, not dilution. 2. $NVDA competition: People are saying Nvidia just launched OpenAI's "Ultrafast" mode on Blackwell, so Cerebras is done. That's not the whole picture. Every AI chip trades speed against volume. Nvidia wins on volume. One GPU holds 288GB of memory, so it serves lots of users at once, the cheapest way to run big models for the masses. The catch with $NVDA is speed. Its memory sits next to the chip, not on it, so every token has to travel back and forth. To go fast anyway, Nvidia runs each GPU with only a few users, which wastes most of the chip. That's why Ultrafast costs 6x the normal price and still tops out around ~300 tokens/sec. Cerebras wins on speed per user. The whole model sits on the chip, and data moves thousands of times faster (21 PB/s vs ~8 TB/s on a GPU). Cerebras ran OpenAI's Ultrafast at 750 tokens/sec in August, on a smaller model, and the new CS-4 does 4,400+. The catch with $CBRS is memory and bandwidth. Each wafer holds 44GB, so big models get split across many wafers that talk to each other slowly, about a sixth of one Nvidia GPU. That's likely part of why the new tier went to Nvidia. But CS-4 links wafers 6x faster per rack, and more memory is coming. And speed is where a lot of the demand is heading, not just scale. AI agents work for one user or one task at a time, and every second they wait is lost work. Companies will happily pay for that. That's why $AMZN and $AMD pair Cerebras with their own chips instead of replacing it. Theirs reads the question, and Cerebras writes the answer. 3. OpenAI and concentration: Yes, OpenAI is the biggest customer, with a $20B+ deal through 2028 and about a third of last quarter's revenue. One launch on Nvidia doesn't cancel a multi-year contract though. And the list is growing with Amazon, AMD, $META, Mistral, Perplexity, Cognition, $CRWD and more. Wall Street already expects ~$3B of revenue and the first real profit in 2027, then ~$7.5B of revenue and ~$3B of free cash in 2028, with ~60% gross margins long term. 4. The $450M loss: $377M was stock comp, and $274M of that was a one-time IPO catch-up. It's non-cash, and without it the business lost only ~$7M. Stock comp keeps engineers from leaving for Nvidia, OpenAI or Google, and should run ~$100M+ per quarter until ~2028. The cost is dilution from new grants, roughly 1-2% a year, not cash. Where I land: Long term, Cerebras owns a specific job in the AI stack that gets more valuable as demand for fast AI grows. I'd love to see more chip sales, since ~61% of revenue is cloud today, plus the memory and bandwidth upgrades. The risks are real, but none of those break the story. - OpenAI is most of the backlog today, but it won't stay the only big customer. - Nvidia could get "fast enough" with the Groq technology it licensed, but the market is too big for just one winner. - Dilution is real, and the lockup plus Q3 earnings could bring short-term volatility. Do your homework before you panic. Not financial advice.

$MU earnings BULLISH notes: - SCAs went from 16 to 26 and RPO from $100B to $150B in one quarter - Q1 FY27 is the gross margin floor for the year, and margins go higher from there - Memory and storage get much tighter in 2027 and 2028, and Micron has no line of sight to DRAM supply and demand returning to balance - Physical AI can become a significant driver of memory and storage demand by the end of the decade - Building the industry's first custom HBM4E with NVIDIA (NVHBM), with a strong roadmap beyond it - Server units are growing in the high-teens in 2026 and 2027, while industry DRAM bits grow in the low-20s in 2027 and 2028 and stay supply constrained

When everyone is looking at the same thing and rooting for that to go up, the market will cause major drawdowns to make it seem less obvious or that the trade is over. The noise could even make some question the original thesis and ask themselves if they still have the same conviction as they did before. Those who pass the test will be rewarded simply by showing character and not falling into the trap. Think of it like waves that go up and down. Sometimes really big ones do come your way. But ultimately things settle down and flow in the natural direction of things. Fundamentals take over. $NBIS $MU $INTC $BE $MRVL

If U.S. starts putting tariffs on Korean semiconductors, that means the value of domestic manufacturers keeps increasing and their ASPs rise significantly. A few winners that I see: 1. $MU (memory) 2. $AAOI (photonics) 3. $INTC (foundry) 4. $AMKR (packaging)

The world will need insane amounts of compute, memory, power and networking infrastructure until 2030. It has been less than two months since the drawdown in AI stocks happened and many are already questioning and panicking, asking themselves whether the trade is still alive. The answer is: YES! It is. - Capex won’t stop which means more demand for infrastructure and energy. - ROI is showing up for Hyperscalers and AI labs. - Businesses are becoming increasingly efficient and dependent on AI now. Think ahead. Bigger than all the daily headlines that can slowly crowd your mind with too much information and make you confused on something that is so obvious. Here are FIVE names that are incredibly important going ahead for the buildout: 1. $NBIS - #1# AI cloud & hyperscaler with a strong software ecosystem 2. $MU - US-based memory giant across the stack 3. $MRVL - The next Broadcom in ASICs, memory & photonics 4. $BE - BTM solution for all Hyperscalers 5. $INTC - The TSMC solution for the US

Just a TL;DR on why $SIVE is doing the right things: > US listing in 2027. 99% confirmed, they just can't say it yet for legal reasons. > 7 pluggables customers, with $JBL ramps coming soon. > New SAM opening up for their SOAs in optical circuit switches. > Opportunity pipeline sitting at $1.2B, and it keeps growing, tied to every new PO they sign. > $GFS, Ayar, and $POET are also giving them CPO exposure into the two supply chains that matter most, NVIDIA and AMD. > Capacity is increasing, so once InP laser qualification finishes and ramps start, they're set up to actually execute. > LiDAR customer ramp by end of this year, that's $AEVA, who's now looking into photonics too. > $NOK, Celestial, Lightmatter, and Lightelligence are potential customers, not confirmed yet. > Partnerships with SemiNex and O-Net to develop different photonics modules.

I’ve received a fair amount of criticism over the last few days. I want to address it directly and honestly. First, the research on the AI buildout will always remain free. Earnings coverage, supply chain work on names like $SIVE, and the broader technological analysis will continue to stay open. That does not change. The subscription is simply a way to give early access to a smaller set of ideas, trades, and direct conversations to the people who choose to support the work. It is not a paywall on the core research. It is an edge for those who want it. Most of the alpha has been free, and most of it will continue to be free. The subscription (and the Substack I plan to launch) is what allows me to do this every single day. I already have a job and earn well. This is not about needing the money. It is about turning something I care deeply about from a side project into something I can fully commit to. A lot of people charge thousands for thin research with little real context. That is not what we do here. I will always share the ideas and trades publicly, just with a delay. I will never use anyone as exit liquidity. That is a hard line. If a stock is overpriced or the company is weak, I will not recommend it. I focus on businesses I believe can win over the long term. Giving subscribers earlier access, especially from a trading angle, feels fair to me. Everyone is entitled to their own view on this. My goal is to keep this space honest, open, and respectful. I do not want it to become a place where people feel things are being hidden or manipulated. I’m writing this simply to be transparent about where I stand. One last note from the bottom of my heart: I would never recommend something I wouldn’t be comfortable recommending to my own family. I think about staying true to my values every single day, and I always will. I’m also human and far from perfect. If you ever feel I’m not balancing this the right way, I’m open to hearing it. I genuinely want to listen to your perspectives. Because that is what actually matters. Much love 🩷 - Athu