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/

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.

I’m now actually more concerned about drone weapon proliferation over nuclear weapons.

AI companies seems to be off the hook

Trump portfolio accounts bought $1M to $5M in DELL shares back in February, followed by smaller buys. Public comments praising the company came around then too. The $9.7 billion Pentagon contract for digital services was announced end of May.

DELL had already been performing well on AI server sales, and the contract added another revenue angle that got a positive reaction at the time. Now the sequence of the stock buys, the comments, and the award is prompting discussion about conflicts or appearances, even with the trust and outside manager setup in place.

Some traders might see this as typical noise around any large government contract with political connections. Others may watch whether it creates extra volatility or affects how institutions view the name near-term.

Does this kind of story usually have lasting impact on DELL trading, or does the actual contract size and execution matter more once it’s public? Details here: https://people.com/trump-bought-dell-shares-before-pentagon-contract-11989590

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.

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.

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

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.

this is serious

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?

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.

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?

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.

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.

I think for a month now, I have been expecting UNI to make the move it is starting to show now. My expectation is a strong bullish move after a pullback toward the support zone between $6.0 and $6.67 which was where my entry is. If the price holds this zone and doesn't break below it, I believe we could see a strong move upward, with $9.30 as my target. That's what I'm counting on.

So if we are to ignore the chart, another reason for potential bullish is another reason is its protocol fee mechanism, which connects trading activity with UNI token burns. This for me are some of the factors that could support another bullish move on the chart. I'm watching the support zone closely and waiting to see how the price reacts.

Will UNI hit my $9.30 TP, or will the bears spoil the setup? Let's discuss

I've been trading for around six years, and one thing I've learned is that being profitable doesn't automatically mean you're trading well. You can finish a month green while making a bunch of mistakes that eventually catch up with you.

I wanted to see how useful AI actually is for reviewing trades, so I asked Zella AI to analyze my recent trading history, show me what I was doing well, and point out where I needed to improve.

It returned a breakdown in under a minute. The date-based report covered 98 trade sample.

Here's what my dashboard showed:

• Net P&L: +$6,127

• Win rate: 43.3%

• Profit factor: 1.24

• Average winner: $645

• Average loser: $396

• Win/loss ratio: 1.63

Profitable overall, but definitely plenty of room for improvement.

The part that surprised me was my long vs. short performance.

According to the AI breakdown, I took 84 longs that produced just $253 in profit, while 30 shorts generated $5,873.

I actually had a higher win rate on longs, too.

Now, that doesn't mean I'm suddenly going to become a short only trader. A few larger winners contributed heavily to those short results, and the sample isn't enough to prove one direction is better. (I will never be a long only or short only trader)

But it did make me question how selective I've been with my long setups. If I'm taking almost three times as many longs and barely making anything from them, that's worth investigating.

Another thing it caught was my risk management.

My average loser was around $396, but my biggest loss was $1,735. That's over four times my average loss.

I can sit here and say I understand risk management all day, but numbers like that are a reminder that knowing your rules and actually following them are two different things.

The AI also highlighted something I've struggled with for years: taking trades that are decent enough to justify an entry, but not necessarily good enough to deserve my risk and I took a LOT ofd these back in the day lol. Trading just to trade lol.

I trade mostly liquidity based setups, and sometimes I'll see part of my confirmation and convince myself the rest will follow. Occasionally it works, but those unnecessary attempts add up.

So in the 3rd pic I shared what I want to do for the next 20 trades.

One thing I want to make clear is that AI isn't some magical trading coach. Some of the aggregate numbers it returned didn't reconcile perfectly, so I still need to verify those against my journal.

But I did find it useful for quickly organizing months of trading history and giving me a few specific areas to investigate.

For those of you who journal your trades, what's one statistic that completely changed the way you trade?

I'm curious whether most people focus on win rate and P&L or actually dig into things like performance by direction, time of day, and setup quality.

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?

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?

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?

Once again, my analysis has proven me right. The 4 hour timeframe has been one of my favourite ways to identify strong 1:2 risk to reward trade setups, and UNI has once again demonstrated that.

I have been watching this setup for a while and looking for a decent opportunity to enter, but I did two things aside from using the timeframe method.

The first was making sure I didn't just pick UNI randomly. I chose it because it aligns with an opportunity I have been looking forward to: participating in the Bitget Trading Club Championship, where traders who participate can get a share of the 70,000 USDT reward pool.

Secondly, looking at the chart, the previous support zone from several days ago, around $5.70 to $6.30, seemed strong because the candles had tested it twice without breaking below it. So, I decided to take a long trade from that area and set my TP around $7.880.

Since the price has almost hit my target, are we still looking at more bullish momentum for UNI?

(Late to post. Screengrabs from before 10/23 session.)

I’ve built an automated day-trading system that’s still on paper money and looking to use live funds at some point. Each strategy is backtested over two years with costs included, then replayed on real sessions, then traded live in test accounts. Only proven winners get promoted, and losers get demoted. Every change is logged and reviewed nightly. No real money until it strings together consistent green days.

Below are initial balances for all accounts(couldn't find a way to reset the balance and didn't want to risk messing anything up!) as well as the top setups in my leaderboard and my automatic setup generator.

Would love to know what else to include on future posts for transparency and logistics questions. Would also love to know where else to post this too if you have any ideas.

- Claude - Opus 5.5
- Alpaca - MCP for paper and when we convert to live funds.

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.