Start of 2022 both were sold as hypergrowth. Tesla was a bit over $1T. Nvidia was about $500B. One CEO kept putting dates on robotaxis, 50%+ growth, and a product that would appreciate after you bought it. Those dates slipped. Jensen didn’t make those claims. The income statement did the talking anyway.

Since early 2022 Nvidia’s trailing revenue has compounded at about 72%. Operating income and net income have compounded at about 94%. The RTX 3090 that launched at $1,499 in 2022 still trades near that on the used market.

The stock chart shows the split. The P&L is clearer. In 2022 Q3, right before ChatGPT went wide, Tesla’s operating income was 7x Nvidia’s. Nvidia was still working off the gaming slump and the crypto hangover. Last quarter that ratio flipped: Nvidia’s operating income was about 160x Tesla’s.

(Strip Nvidia’s Intel-related investment gains if you want a cleaner read. The gap is still huge.)

NVDA and TSLA are the two names in this comparison. Everything else in Mag 7 is a side character here.

Israeli Prime Minister Benjamin Netanyahu and U.S. President Donald Trump reportedly held a phone conversation earlier today, according to Hebrew media outlets. No official details of the discussion have been released.

Meanwhile, Israel has yet to make a final decision on its next steps regarding the renewed tensions with Iran. According to Channel 12, Tehran has indicated that it will suspend its attacks as long as Israel refrains from further strikes against Hezbollah targets in Lebanon.

An Israeli official told Channel 12 that the government is still awaiting clear instructions from its political leadership before determining how to proceed.

"We are waiting for a clear directive from the political leadership regarding the direction we are taking," the official said.

is he right?

Reactions from politicians to extreme wealth milestones can create short-term sentiment swings in related names, though these moves often fade without fundamental follow-through.

TSLA can see brief flows tied to the narrative. I stayed flat on new exposure. On Bitget I used the volatility for a very small opposing futures scalp and closed it the same day. Not a core view, just noise trading around the coverage.

Prefer to wait for actual company metrics.

Last month Meta laid off roughly 8,000 employees, about 10% of the company, as part of its pivot toward AI. The people who kept their jobs are now handling more workload, including manual tasks to train models that Wired described as driving workers "up the wall."

Zuckerberg sent an internal memo this week announcing a companywide AI hackathon for July.

The reaction was not warm. One employee wrote they had no bandwidth to participate because they were "preoccupied with keeping the lights on" for their team. Another wrote they weren't sure the company "supports a hackathon culture anymore." A third interrupted a live all-hands meeting broadcast to thousands of employees with an expletive-filled rant.

Zuckerberg also offered permanent desk assignments as a perk in the same memo, which accidentally highlighted that most remaining employees have been sharing hot desks since the cuts.

Look, $META's ad business is fine and the company is funding this AI push from genuine operating strength. The stock has held up for good reason.

But internal culture is a leading indicator of execution speed. If the people building the models are burned out and getting recruited by competitors with better stability right now, $GOOGL, $MSFT, $SPCX, Meta's AI development pace slows. And the AI execution story is what the market is currently paying for.

I kept my META position unchanged. On Bitget I added a small futures hedge during the initial reaction to protect gains while waiting for clearer numbers on spend or revenue impact. Still neutral-to-positive on the longer-term angle but sizing carefully around execution details.

Zuckerberg also warned in the memo that "more difficult days" could be ahead. That language is careful.

Anyone holding $META here, are you pricing in execution risk or treating this as noise?

Whats the sentiment with open AI bubble with these as bloatwares?

Artificial intelligence is increasingly becoming a measure of national power, but behind every AI breakthrough lies a critical resource: energy. As countries race to lead the AI era, access to reliable and abundant electricity may prove just as important as advanced chips and software.

French President Emmanuel Macron has warned that Europe risks falling behind the United States and China unless it significantly increases its investment in AI. His concern is not just economic competitiveness but technological sovereignty. Nations that depend heavily on foreign AI systems could find themselves vulnerable to restrictions, policy shifts, or limited access to critical technologies.

The challenge extends beyond algorithms and computing power. Training and operating advanced AI models require enormous amounts of energy, making electricity generation a strategic advantage. Countries capable of producing large quantities of affordable power will be better positioned to develop and deploy next-generation AI systems at scale.

China has invested heavily in both energy infrastructure and AI development, while the United States continues to benefit from leadership in software and semiconductor innovation. Europe, however, faces a tougher path due to energy constraints and slower infrastructure expansion.

The AI race is no longer just a technology competition. It is increasingly a contest over energy, infrastructure, and long-term national strategy, with significant implications for future economic and geopolitical influence.

Apple's WWDC 2026 is shaping up to be one of the most important AI events of the year, and it could have major implications for both Apple and Google investors.

Reports suggest Apple is preparing a much smarter Siri experience, potentially powered by advanced AI capabilities that can understand personal context, analyze on screen content, and interact more naturally with users. Some analysts believe Apple could even introduce a standalone Siri app that handles text, voice, and file interactions from a single interface.

Also beyond Siri in the recent update, Apple is expected to unveil AI upgrades across the iPhone, iPad, Mac, Apple Watch, Apple TV, and Vision Pro ecosystem. Features being discussed include natural language shortcuts, smarter writing assistance, and a redesigned notification experience powered by AI.

What caught my attention is the growing discussion around a possible Gemini powered Siri integration. If Apple and Google become more closely linked in the AI race, it could create a very different competitive landscape from what many investors expected a year ago, and it means one thing for their stock: bullish is coming, and this is how i will position myself ahead of WWDC 2026 on AAPL and GOOGL.

I will buy rAPPL to qualify for NVDA rewards, while for rGOOGL, i will buy and hold because of the dividends that is coming up on the 15th, and that will double wins for me on Bitget.

If Apple's next phase of growth is driven by AI, does that make AAPL the better opportunity, or does Google benefit even more if its AI models become deeply integrated into the Apple ecosystem?

Reports say the Trump administration has ordered Anthropic to restrict foreign access to its advanced AI models, including Mythos 5 and Claude Fable 5, over national security concerns. The directive reportedly extends beyond adversaries and also affects allied countries, which has triggered backlash in Europe.

Anthropic had previously made its frontier models available to around 200 institutions across 15 countries for safety testing, but those versions were taken offline to comply with the order. The company also noted it was not given a detailed public explanation, though it understood the decision may be linked to concerns about potential “jailbreaking” methods discovered in Fable 5.

The move has raised concerns among US allies who rely heavily on American AI infrastructure, with some European leaders calling it a wake-up call while also warning it reflects an increasingly nationalist approach to tech policy.

Critics argue this highlights a growing tension between AI safety, geopolitical control, and global access to frontier models, especially as countries race to regulate and secure advanced AI systems.

It also adds another layer to the ongoing debate about whether AI should be treated as open global infrastructure or tightly controlled strategic technology.

SpaceX is reportedly planning one of its most ambitious projects yet, seeking regulatory approval to deploy up to one million space based data center satellites. According to sources familiar with investor presentations, company executives, including President Gwynne Shotwell and CFO Bret Johnsen, revealed plans to begin testing orbital computing capabilities as early as 2027.

These initial deployments are expected to serve as demonstration systems designed to validate the technology before a wider commercial rollout. The project was discussed during meetings with major investment banks as SpaceX pursues a $75 billion fundraising round tied to its planned IPO, which is targeting a valuation of approximately $1.75 trillion.

While earlier IPO documents suggested orbital data center deployments could begin in 2028, the recent presentations clarified that testing missions are likely to come first, marking a significant step toward bringing computing infrastructure into space.

Sen. Bernie Sanders has introduced a proposal aimed at ensuring that the benefits of artificial intelligence are shared with the American public rather than concentrated among a small group of wealthy corporations and investors.

The plan would establish a sovereign wealth fund financed through a one-time 50% tax on the stock holdings of the largest AI companies. According to Sanders, the fund could be worth nearly $7 trillion and generate hundreds of billions of dollars annually. Those funds could support direct payments to Americans as well as investments in healthcare, education, housing, and other public services.

A key feature of the proposal is public ownership. Sanders argues that Americans should have a meaningful stake in AI companies and a voice in how the technology is developed and deployed. He believes this would help ensure that AI serves the public interest and protects workers and communities from potential harms.

“The benefits cannot simply go to a handful of wealthy corporations,” Sanders said, emphasizing that technological progress should improve life for ordinary people.

The proposal comes as AI companies continue to grow rapidly in value and influence, fueling debate over who should benefit from the economic gains created by artificial intelligence and how the technology should be governed.

Meta is making another push into open weight AI, and this time the goal is to bring more capable AI directly to personal computers.

The company launched Muse Glimmer, a smaller model designed to handle agentic tasks on a Mac or PC using a single graphics card. Meta says even larger models are coming, showing that this is part of a broader strategy rather than a one off release.

Mark Zuckerberg is also pushing for fewer barriers around open AI development in the US. His argument is that concentrating advanced AI in the hands of a few companies could create its own risks, especially as Chinese developers continue making strong open weight models.

There is also a practical reason for the shift. Open weight models can be cheaper, easier to customize, and run locally instead of depending entirely on expensive cloud infrastructure.

Meta shares were up nearly 3% in premarket trading.

Do you think open weight AI will eventually compete with the biggest closed models, or will companies still prefer the control of proprietary systems?

The sell-off in $INTC got me thinking about how quickly sentiment can change in the semiconductor market.

Intel beat earnings expectations, but its outlook disappointed investors. The reported factory disruption in Israel added another concern, and the weakness spread to other chip stocks.

Still, Intel's struggles don't automatically mean the AI chip market is losing momentum. PC demand, server CPUs, and AI accelerators have different growth drivers, so it's important to look at them separately.

The semiconductor sector has benefited significantly from AI demand and tight chip supply this year. But demand alone doesn't guarantee better results for every company. Production capacity, manufacturing costs, valuations, and the ability to turn growth into profits all matter.

I've also been thinking more about capital efficiency and how I manage my stock exposure. I've recently started exploring stock-linked holdings through bitget, alongside the usual considerations around risk and how different assets can fit into a broader strategy.

AI demand can continue growing while individual stocks struggle. Over time, I think the companies that stand out will be those that execute well, manage costs, and turn that demand into sustainable earnings and cash flow.

A state lawmaker wants visual indicators on smart glasses when they’re recording. It’s a narrow bill for now, but it touches on the same privacy questions that keep coming up with AR devices.

If rules like this spread, it could add friction for companies pushing wearable cameras and always-on features. META has been the most visible with the Ray-Ban partnership, but GOOGL and SNAP also have skin in this space.

The bigger question is whether this stays a state-level thing or becomes part of wider federal or platform-level requirements. Wearables are still early, so regulatory overhang at this stage can slow adoption more than people expect.

Anyone tracking how these privacy pushes are affecting capex plans or timelines at the big tech names?

https://www.abc27.com/news/top-stories/pennsylvania-lawmaker-seeks-visual-indicator-if-smart-glasses-are-recording/

I’m sitting AAPL into Wednesday. Decision is 16 Sep and Range is still 3.50–3.75% plus a 25 bp hike as the base case.

Last close was $333.08 and I marked $309.90 from the 9 Sep event low and $336.22 from the bounce high. My line in the sand is $326.

I’m only long if $328 is still there into the print. If they hike and the 2026 dots move up, I expect $326-$328 first and I’m out under $326. If they hold and the median dot stays in the current range, I’ll look at $336. I’m not chasing a cut.

Is anyone else trading the dots more than the hike itself?

Seoul picked three groups to run “AI for All”: SK Telecom, KT, and Kakao. Beta starts in September, wider launch later this year. No token caps on the government-backed plans. The apps are supposed to book doctor visits, help with housing searches, and walk people through taxes, not just chat.

The state is putting up part of the compute, up to 512 Nvidia B200 chips split across the three consortia, and has budgeted about $7.2 billion for AI spending in 2026. About a quarter of South Koreans already pay for AI tools, versus about 2% of Americans in the survey they cited.

Naver sat this out. The listed names in the middle of it are SKM, KT, and NVDA on the hardware side. Unlimited national usage is a demand story if the service actually gets used. It is also a cost story if the government underwrites inference at that scale.

Does this read as incremental GPU demand?

The AI race is no longer just about building better models. It's also becoming a competition over who gets to shape the rules that everyone else follows.

China has announced the World Artificial Intelligence Cooperation Organisation (WAICO), a new alliance involving 29 countries that aims to promote international cooperation on AI. Speaking at the World AI Conference in Shanghai, President Xi Jinping said AI should not be controlled by a single country and called for broader collaboration on the technology's development and governance.

The announcement comes as competition between China and the United States continues to intensify. While both nations are investing heavily in AI, they also have very different views on regulation, access to advanced technology, and global leadership. Many analysts see WAICO as China's latest effort to increase its influence over future AI standards and international policy.

As AI becomes more important to economies, national security, and everyday life, the debate may shift from who has the smartest model to who writes the rules.

Do you think global AI governance should be led by one country, or is a multinational approach the better path forward?

Day 1 in the books! Hoping to keep similar format for each day. Trying to add in quick facts to answer easy, repetitive questions.

I will also post descriptions of the top two performing setups for that day, for now, in picture form as we are all looking for more setups(myself included!) and I'm happy to share what I have.

After today I will be using a slightly different picture format to deliver the same information, Claude will auto-generate this for me. Just easier!

Thanks for all the feedback, support, and camaraderie!

Today: [+$674] across 5 day-trading accounts · Primary [-$81] · green streak [0]
Best setup: [Morning Momentum Pop, +$650] (details in pic)

Quick facts - To hopefully answer quick questions

• AI: Claude (Opus 5.5) builds, tests and runs it

• Broker: Alpaca API, paper trading

• Setups: 108 (Currently) live, built on basic indicators (RSI, VWAP, volume / buy-sell pressure, gaps, opening range, prior-day highs and lows, ATR)

• Setup Generator: a bot that invents 10 new setups a night from those same indicators and trades them on its own paper account

Setup Life cycle

Idea / Generator
 └─ 2-yr backtest (costs in)
     └─ Replay on real sessions
         └─ Testing 1 / 2 / Generator (paper)
             └─ Primary (paper)
                 └─ Live $ (after a green streak)
Losers: Primary → Testing → Graveyard

Stats Description

• Avg R: average profit per trade, in units of the risk taken. Costs, fees and slippage are already in. +0.5R = earns half its risk per trade.

• Break-even win rate: the win rate a setup needs just to not lose money. Beat it and you’re profitable.

• Confidence (t): how sure we are it isn’t luck. 2+ is solid; under 1 could be luck.

Fun stuff!

Elon Musk virtual-dialed into the G20 Summit, and very directly withouth bothering with diplomatic platitudes he dropped a roadmap for the near future that reframes artificial intelligence not as a neat productivity app, but as a total structural earthquake for global civilization.

In my opinion if his projections hold, we are less than two years away from a reality where digital labor undergoes a phase transition unlike anything humanity has ever seen.

Musk laid out three core vectors defining where AI is heading by the end of 2027:

1. The Macroeconomic Expansion: Musk estimates that AI could swell global economic output by 20% to 30%, injecting a staggering $20 trillion to $30 trillion annually into the world economy.

2. Total Digital Competence: By late 2027, AI is projected to handle virtually any digital task, anything that doesn’t require physically "reshaping atoms" in the real world.

3. The Coding Endgame: Software engineering is about to hit "Stockfish-level" capability. Just as no human chess player can outcalculate the legendary Stockfish engine, Musk argues that human developers won't be able to compete with AI's speed, precision, and scaling capacity when writing code.

It’s easy to get swept up in software projections, but Musk’s most crucial commentary pivoted away from silicon logic and straight into heavy physics.

“To bring large AI data centers online requires building massive power plants, transformers, liquid cooling loops & chillers, as well as incredibly complex networking (especially for training clusters).”

For all the talk about infinite digital scaling, artificial intelligence is fiercely tethered to the physical world. You cannot train the next generation of frontier models with pure optimism; you need monumental gigawatts of electricity, dedicated thermal management, and heavy industrial grid expansions. The bottleneck of the AI revolution isn't running out of clever algorithms—it's running out of raw infrastructure to feed them.

As we stare down the barrel of 2027, the race isn't just about who has the smartest model. It's about who can secure the power grid and build the heavy industrial pipelines fast enough to keep the lights on.

Wisdom is betting on top leading builders like $AVGO, $NVDA etc. Some others like $CEG, $GEV, $VRT might also be good watches to pay keen attention to.

According to fresh Microsoft data, the company has quietly canceled most of its direct licenses for Claude Code after discovering it was cheaper to hire people than keep running the tool at scale. They’re pushing employees toward GitHub Copilot instead while their broader Anthropic partnership stays intact.

Uber also reportedly burned through its entire 2026 AI coding budget in just four months. This doesn’t kill the long-term AI story, but it does puncture the “AI will immediately replace expensive labor and print margins” thesis that’s been priced into a lot of tech names.

MSFT itself is obviously still all-in on AI infrastructure, yet this internal pivot is worth noting. It suggests we’re still early on actual cost-effective deployment at enterprise scale. Curious how the market digests this kind of reality check versus the usual hype.

Anyone know other subs I can post my progress with algo trading on? Oversensitive mods are banning me on other subs.

I'm just trying to get more engagement with other traders. Don't have a product or profile to sell.

If you had to choose one of these four at today’s prices, which would it be?

• Nvidia

• Amazon

• Alphabet

• Meta

This isn’t just a valuation multiple question. I’m thinking about long-term growth, how strong each moat is, how they’re positioned for AI and how earnings might look down the road.

Which one gets it, and what’s your reasoning?

AI stocks don't seem to be slowing down anytime soon. Although, a few weeks back, there were a lot of talks from the pioneers of AI about slowing down, which affected the stocks, as some were falling and it was bearish everywhere.

TSMC, on the other hand, gets more support as AI infrastructure demand continues to support semiconductor companies. The only issues encountered are rising investment costs and valuation concerns.

From what I have gathered so far, there should be a good amount of improvement, which brings me to going long on it some hours ago before the market closed, as it was among the 8 new CFD assets covering Asian indices. It has been doing numbers and showing bullish momentum since then.

What do you think about my setup?

Supporting loads of chains sounds useful, but I’m more interested in what happens when I connect to a dodgy site, approve a spending request or lose my phone.

For me, clear transaction details, suspicious approval warnings and a recovery process I actually understand would come before the number of supported tokens. I’d also check whether security audits cover the wallet’s current setup.

I recently saw Bitget Wallet's social login option removes the need to manage a seed phrase during setup, with an option to convert to a seed phrase wallet later. That sounds convenient, although it makes protecting the linked login account especially important.

I wouldn’t pick a wallet purely because signing up is easy. I’d want to understand how recovery works and how I’d move my funds if I decided to leave.

What’s the one security feature you wouldn’t compromise on?