To The Moon

$Alphabet(GOOG)$  GOOG is on sale. Buying opportunities like this dip are rare... adding here.

$Meta Platforms, Inc.(META)$ It had a nice bounce off the $540 support level. The wedge is formed... let's see if this stock can finally make a move. Strength would be confirmed above $596-600.

$SPDR S&P 500 ETF Trust(SPY)$ The most important thing this week is that we're reaching month-end and portfolio managers are doing window dressing. It's not about PCE, not TA, not valuation—it's about making the books look good. Turn off the financial news and follow this simple rule: if a stock has done well this month, it gets bought; if it's done poorly, it gets sold and taken off the books. Everything else is noise. This is about keeping your job, which is why if a stock has been beaten up this month, you buy it.

$Microsoft(MSFT)$ $Meta Platforms, Inc.(META)$ $NVIDIA(NVDA)$ $Alphabet(GOOG)$ The NASDAQ is up 2.18% today, largely driven by big tech companies like Microsoft, NVIDIA, Apple, Amazon, Alphabet, and Meta.

$Meta Platforms, Inc.(META)$ Meta plans to use Qualcomm's C1000 CPU in its data centers, which marks a notable hyperscaler design win for Qualcomm's AI infrastructure ambitions. Meta is exactly the type of customer the market pays attention to. The company continues to invest heavily in AI infrastructure and has strong incentives to diversify its compute stack as inference workloads scale. As AI deployment expands, CPUs are becoming increasingly important alongside GPUs, particularly for inference, orchestration, and broader data center efficiency. That trend could create a meaningful opportunity for Qualcomm in the enterprise AI ecosystem.

$Carnegie Clean Energy Ltd.(CWGYF)$ When the wind stops and solar output drops, the ocean keeps moving. The consistency of wave energy contributes to grid stability. Carnegie Energy, in collaboration with $Hewlett Packard Enterprise(HPE)$ , has developed a technology aimed at addressing future energy demands. Electricity prices in South Australia spiked to over $20,000 per MWh during the worst one-day wind drought in the NEM in two years. At the same time, large waves were hitting Australia's south coast. Wave energy technology, like that from Carnegie Energy, can provide power when it's needed most.

$NVIDIA(NVDA)$ $Amazon.com(AMZN)$ $Alphabet(GOOG)$ $SpaceX(SPCX)$ The market is borderline at extreme fear, with consensus expectations still pointing to rate hikes, of all things. Meanwhile, Hormuz traffic has normalized, and Gulf commodities are hitting new post-conflict lows every day. The market is bracing as if we're back in the pre-Bidenflation era, which mathematically isn't possible.

$Meta Platforms, Inc.(META)$ Retirement account update. Still my biggest holding, and yeah... I added a bit more again on today's dip. Nothing dramatic here, just staying with what's been working for me. Business is still solid, cash flow is strong, and the AI angle still feels early, not crowded yet. Not trying to time anything perfectly, just letting it compound slowly over time. Feels boring sometimes, but that's usually the point.

Some tech stocks look incredibly cheap on a forward P/E basis right now – the market might be mispricing their growth. $Meta Platforms, Inc.(META)$  - Still a cash cow, with the AI and advertising scaling story intact. $Salesforce.com(CRM)$  - Enterprise software rotation, and the valuation reset is creating an opportunity. $Netflix(NFLX)$  - Streaming dominance and pricing power remain underappreciated. $Adobe(ADBE)$  - AI transition plus recurring revenue stability, but trading at a discounted multiple. $PayPal(PYPL)$  - A deep-value fintech turnaround

1300Before ER. Post-ER, looking at $1400+. I'll be honest, the market still feels a bit slow to fully re-rate this name. Everyone's focused on the "AI winners" at the top layer... but not enough people are thinking about what actually makes the stack work underneath. AI demand isn't just increasing, it's getting heavier, more memory intensive, more infrastructure dependent. And that's where Micron sits. Quietly, but right in the flow. With AI buildouts accelerating and big ecosystem deals in the background, this is starting to feel less like a chip trade and more like a supply chain bottleneck story. The money flow is pretty straightforward when you strip the noise: more training → more compute → more memory usage $Alphabet(GOOGL)$