To The Moon

$Apple(AAPL)$ New 53 week high. My best investment ever.

$HELUS PHARMA INC(HELP)$ $COMPASS Pathways plc(CMPS)$ Started healthy positions here today. Excited about it. Sold MindMed too soon and I won't make the same mistake. $Lucid Group Inc(LCID)$  $Apple(AAPL)$ 

$Apple(AAPL)$ Apple and Meta announced a new collaboration on October 15, 2026. The companies worked together so developers can run Meta's Muse Spark Open, an 816-billion-parameter open-weight AI model. Mark Zuckerberg publicly thanked Apple CEO John Ternus, and Ternus replied positively. This is notable because the companies have long been rivals. Cutting out the noise, this strengthens Apple's story as a premium on-device AI hardware platform, validates its silicon and software stack, and opens the door to more partnerships under Ternus, while fitting Apple's privacy-first approach. It is more about positioning and ecosystem signaling than a near-term earnings catalyst. Longer-term value depends on whether local AI inference grows, whether

$Microsoft(MSFT)$ Volume has been picking up on up days and drying up on down days, which fits an accumulation pattern.

$Apple(AAPL)$ Apple at $400. There's a lot of noise and phony stories floating around in the daily news, but I wouldn't put much weight on any of it.

It's interesting to see the major hyperscalers all clustering in the 5.7% to 12.84% YTD gain range, except for ORCL. That compares with SPY's 11.34% YTD gain. Ranked by best YTD performance: $Microsoft(MSFT)$ , $SpaceX(SPCX)$ , $Amazon.com(AMZN)$ , $Alphabet(GOOGL)$ , META.

No need to overcomplicate it. $Apple(AAPL)$  and $Microsoft(MSFT)$  are really all you need as forever holds. Add on weakness.

Commoditization isn't the end of the AI profit pool. The internet became a commodity too, and the most valuable businesses were built on top of it. AI models are heading down the same path — the value accrues to whatever gets built on them. $Alphabet(GOOGL)$  $Meta Platforms, Inc.(META)$  $Microsoft(MSFT)$ 

$Microsoft(MSFT)$ Microsoft unveiled Maia 300, saying Maia will become its primary inference system, with multi-gigawatt deployments starting in 2027. Most of the upgrade is in memory. Compared with Maia 200, compute FLOPs rise 36%, HBM bandwidth rises 2.5x to 18 TB/s, and capacity rises 33% to 288 GB. Microsoft expects 40% more tokens per megawatt than leading GPU-based systems, though it doesn't name the system it's comparing against. Full racks double to 96 accelerators, which helps get to the 7x rack throughput figure. Production deployments start in 2027. Evercore ISI estimates Maia will still be only about 10% of Microsoft's AI chip spending by the first quarter of 2027 (via CNBC).

BairesDev data shows developers writing half or more of their code with AI jumped from 12% to 42% in a year, yet only 12% merge it without manual review. 78% of CTOs raised review budgets. The bottleneck moved from generation to validation. Less author, more auditor. $Microsoft(MSFT)$  $GitLab, Inc.(GTLB)$