To The Moon

CES is increasingly less about flashy demos and more about credibility checks for the next phase of AI monetisation. What the market is listening for Investors are no longer impressed by raw compute claims. The focus is on deployment readiness. For Nvidia, this means evidence that its data-centre dominance can extend into physical AI, robotics, and edge inference without eroding margins. For AMD, CES is an opportunity to show that its heterogeneous computing strategy can translate into design wins and real volumes, not just competitive benchmarks. Consumer AI remains the weak link Earlier AI devices struggled because they solved no urgent consumer problem or relied too heavily on cloud backends. This time, the bar is higher. On-device AI must demonstrate clear advantages such as latency re

As CES opens, my focus is less on flashy demos and more on how Nvidia $NVIDIA(NVDA)$  and AMD $Advanced Micro Devices(AMD)$  frame the next engine of AI growth. Data centers remain the earnings backbone, but the conversation is clearly shifting toward what comes after large-model training. CES has increasingly become the venue where chipmakers test investor appetite for new AI narratives, and this year the spotlight feels firmly on physical AI, robotics, and edge computing. From my perspective, robotics is no longer a distant concept story—it's becoming a capital allocation question. Advances in sensors, inference chips, and real-time

$Tiger Brokers(TIGR)$ can cash out please help

$NVIDIA(NVDA)$ $Tesla Motors(TSLA)$  $iShares Silver Trust(SLV)$  Today’s Most Active Stocks and Options 30Dec25 🇺🇸 | 31Dec25 🇳🇿🥳 Top 5 symbols controlling the tape: $NVDA $TSLA $SLV $MU $VOO 📊 Flow and Volume, Big Money Has Already Voted I’m watching $NVDA dominate activity with 286,134 total contracts and a +27,892 net imbalance across stock and options. That is not speculative churn. That is capital rotating with intent. Structure remains intact, momentum rebuilt, and prior downside attempts resolved into a clean bear trap. Flow has flipped back toward leadership. 🧠 M&A Optionality, Talent Over Headlines NVIDIA is reportedly in advanced

$NVDA$For January, the most reliable sell put strike is undoubtedly still 160. A large block trade opened, selling the January 30th 160 put $NVDA 20260130 160.0 PUT$ , with 36.9k contracts opened.On the call side, the January 16th 190 call $NVDA 20260116 190.0 CALL$  saw 30k contracts added in new opens, leaning towards the sell side, bringing total open interest to 100k contracts. The market message is that it will be difficult for the price to break above 190 before January 16th.However, referencing last January's price action, if the broader market does not correct after the New Year but maintains its current consolidation, given the scale of open in

⚡🧠 Jensen Huang: “AI makes people dumb” is usually a user problem, not an AI problem I don’t think AI makes you “less smart.” Misusing AI does. If you treat AI like a brain replacement, you’ll outsource the hardest part: thinking. And over time, your decision muscle weakens. The real leverage is different. AI is the “hands.” Your brain stays the “operator.” You don’t ask AI to think for you. You force yourself to define the problem, set constraints, pick the tradeoffs, and decide what “good” looks like. That process is the thinking. AI just helps you move faster once the thinking is clear. The people who get scary-good with AI aren’t the ones who copy-paste prompts. They’re the ones who can ask sharper questions, challenge assumptions, and iterate like an engineer. If AI is making someone

$NVIDIA(NVDA)$ $Tesla Motors(TSLA)$  $iShares Silver Trust(SLV)$  Today’s Most Active Stocks and Options 30Dec25 🇺🇸 | 31Dec25 🇳🇿🥳 Top 5 symbols controlling the tape: $NVDA $TSLA $SLV $MU $VOO 📊 Flow and Volume, Big Money Has Already Voted I’m watching $NVDA dominate activity with 286,134 total contracts and a +27,892 net imbalance across stock and options. That is not speculative churn. That is capital rotating with intent. Structure remains intact, momentum rebuilt, and prior downside attempts resolved into a clean bear trap. Flow has flipped back toward leadership. 🧠 M&A Optionality, Talent Over Headlines NVIDIA is reportedly in advanced

As CES opens, my focus is less on flashy demos and more on how Nvidia $NVIDIA(NVDA)$  and AMD $Advanced Micro Devices(AMD)$  frame the next engine of AI growth. Data centers remain the earnings backbone, but the conversation is clearly shifting toward what comes after large-model training. CES has increasingly become the venue where chipmakers test investor appetite for new AI narratives, and this year the spotlight feels firmly on physical AI, robotics, and edge computing. From my perspective, robotics is no longer a distant concept story—it's becoming a capital allocation question. Advances in sensors, inference chips, and real-time

$NVDA$For January, the most reliable sell put strike is undoubtedly still 160. A large block trade opened, selling the January 30th 160 put $NVDA 20260130 160.0 PUT$ , with 36.9k contracts opened.On the call side, the January 16th 190 call $NVDA 20260116 190.0 CALL$  saw 30k contracts added in new opens, leaning towards the sell side, bringing total open interest to 100k contracts. The market message is that it will be difficult for the price to break above 190 before January 16th.However, referencing last January's price action, if the broader market does not correct after the New Year but maintains its current consolidation, given the scale of open in

CES is increasingly less about flashy demos and more about credibility checks for the next phase of AI monetisation. What the market is listening for Investors are no longer impressed by raw compute claims. The focus is on deployment readiness. For Nvidia, this means evidence that its data-centre dominance can extend into physical AI, robotics, and edge inference without eroding margins. For AMD, CES is an opportunity to show that its heterogeneous computing strategy can translate into design wins and real volumes, not just competitive benchmarks. Consumer AI remains the weak link Earlier AI devices struggled because they solved no urgent consumer problem or relied too heavily on cloud backends. This time, the bar is higher. On-device AI must demonstrate clear advantages such as latency re

⚡🧠 Jensen Huang: “AI makes people dumb” is usually a user problem, not an AI problem I don’t think AI makes you “less smart.” Misusing AI does. If you treat AI like a brain replacement, you’ll outsource the hardest part: thinking. And over time, your decision muscle weakens. The real leverage is different. AI is the “hands.” Your brain stays the “operator.” You don’t ask AI to think for you. You force yourself to define the problem, set constraints, pick the tradeoffs, and decide what “good” looks like. That process is the thinking. AI just helps you move faster once the thinking is clear. The people who get scary-good with AI aren’t the ones who copy-paste prompts. They’re the ones who can ask sharper questions, challenge assumptions, and iterate like an engineer. If AI is making someone

$Tiger Brokers(TIGR)$ can cash out please help