In February 2023, I said buy $NVIDIA(NVDA)$ at $18 before AI explosion. Then I called out: $Micron Technology(MU)$ at $80 → $1150 $AST SpaceMobile, Inc.(ASTS)$ at $2 → $130 $IONQ Inc.(IONQ)$ at $7 → $72 $Roundhill Memory ETF(DRAM)$ at $25 →$76 (safest play so far) Right now, these are still super cheap: $ServiceNow(NOW)$ at $95 $NEBIUS(NBIS)$ at $287 $Applied Optoelectronics(AAOI)$ at $162 $Broadcom(AVGO)$ at $41

10 days ago, I called out $Tesla Motors(TSLA)$ bottom for 2000% play. Here's 4 super AI stocks about to reverse too: The 1st is $ARM Holdings(ARM)$ Its down 46% from its all time highs $452. Without $ARM CPUs, $NVIDIA(NVDA)$ AI system can't even function. It's CPU architecture behind every AI data center's host processors and power efficiency. Look at this chart. I'd buy LEAPS for sure Jan 2028 $500 for $40. If this is too expensive try this one here: For $ARM, you can get Mar 2027 $400 calls for a swing. There 3 other super stocks super cheap are: $Marvell Technology(MRVL)$ -28% from ATH ($330 → $237) Custom AI silicon a

$SPDR S&P 500 ETF Trust(SPY)$ is holding above key support at $765, with the $762 double bottom still intact. The main level to watch now is the 766.69 Gamma Flip, which could determine whether today remains range-bound or shifts into a trend-driven session. There is roughly $1.64B in net positive stacked above $SPY. In a positive-gamma environment, dealers are net long gamma and typically hedge by selling into rallies and buying dips, which absorbs volatility and keeps price action contained. As long as $SPY remains above 766.69, the setup favors range trading, mean reversion, and fading short-term extremes rather than chasing breakouts. Below the Gamma Flip, however, the trading regime changes. Dealer hedging can begin to reinforce the direct

16 years ago, $Tesla Motors(TSLA)$ IPO'd at $17. It returned 445x and transformed the car industry. Here's 5 robotics companies that will 100x-200x exactly like TSLA: 1. $Ouster Inc.(OUST)$ — Digital lidar + AI cameras giving robots 3D vision to see and navigate the physical world. Customers: Komatsu, FieldAI, AIM Intelligent Machines, warehouse/logistics operators. Special note: Only US-aligned, at-scale lidar+camera perception stack after acquiring Stereolabs (90K+ deployed ZED cameras), now the sole non-Chinese option in federal procurement. 2. $Aeva Technologies Inc.(AEVA)$ — FMCW 4D lidar-on-chip that measures instant velocity, not just distance, for real-ti

The biggest bottleneck of AI is memory right now. Memory stocks like $SanDisk Corp.(SNDK)$ spiked 4661% already. Here's the bottleneck company for robotics: First, this is the bottleneck: precision actuation (motors + gearboxes + integrated force/torque sensing) Not compute, not lidar, not even batteries it's the actuator/joint system. Here's why: 1. It's the single biggest cost and engineering line item. McKinsey breaks the humanoid hardware stack into five domains, and actuators alone account for 40–60% of the bill of materials more than double any other subsystem. 2. The supplier base is tiny and not built for volume. Fewer than 10 global suppliers can currently produce actuators with the precision required, and the humanoid supply chain is exp

99% of traders will never tell you where to sell. I will. This year, Kate turned $1000 into $215,000 in 1 month. I don't sell early to make 50%-100% when you can make 700%-2000%. Here's the 1 cheatcode to hold any stock longer: It all comes down to TRUST. You sell early because you don't trust the price action, your setup, or yourself. The market didn't force you out. Fear did. Every time you cut a winner short, you're telling yourself: "I don't believe this trade can reach my target." The best traders don't make more predictions. They trust their edge enough to let probabilities play out. Why traders don't trust their trades: 1. They never fully accepted the risk before entering. 2. Their position size is too large. 3. They don't have a written profit target. 4. They focus on every candle