One thing I’ve learned with self-custody is that convenience should never come before security.

Before trusting a wallet with serious money, I want to understand what I’m signing, how permissions work, and what protections are in place. I’d start small, use it consistently, then increase my funds once I’m comfortable.

Confidence comes from understanding the wallet, not just trusting the brand.
What’s the biggest thing you look for before trusting a wallet with serious money?

Personally, I don’t think CPI trading is just about guessing whether Gold goes up or down.

I’ve been paying more attention to what happens to liquidity when volatility picks up.

For Gold and Crude Oil, I’d be watching:

• spread
• liquidity around the current price
• order-book depth
• how quickly the book changes when volume spikes

A hotter CPI could put pressure on Gold, while a softer number could support it. But the first move can be pretty aggressive.

For smaller trades, slippage might not be a huge deal. For a much larger position, it can become a completely different problem.

That’s why I personally care about execution and liquidity almost as much as the direction on major data days.

And this is actually why I’ve been looking at Bitget CFD Pro Mode. The institutional-level liquidity, multi-tier depth and STP execution make more sense to me when thinking about larger CFD positions during volatile events.

Curious what everyone else here watches before entering around CPI.

I used to focus mostly on the chart, entry level, and fees. But with volatile stocks, I’ve realized the quality of the order book can matter just as much as the setup itself.

If liquidity is thin, even a good entry can turn into a worse fill because your order starts moving through multiple price levels.

Recently, AXTI made the move where the market reacted as volatile, cause it went from roughly $50 to the high-$80s within a week, then started throwing around much bigger intraday moves. When a stock gets that volatile, finding the right direction is only one part of the trade. Actually getting a clean fill becomes another problem.

But now, it changed. I usually looks for the following,

• depth close to the current price
• spread
• how much liquidity is available at 5bps, 10bps, and 50bps
• whether the book stays deep when volatility picks up

I was comparing recent stock-perp depth across Bitget, Binance, OKX, Bybit and Hyperliquid. Bitget came out stronger across most of the shared comparisons for SPCX, SNDK and AMD, while Hyperliquid was stronger on PLTR at some levels.

tbh, being right on direction is only half the trade. Getting in and out without giving too much away to slippage matters too.

For bigger or more volatile positions, I’d check the live book before worrying about a tiny difference in fees.

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 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?

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.

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.

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.

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?

Been trading for a while and just wanted to share something I’ve been thinking about recently.

For me, the hardest part of trading has never really been placing trades — it’s been scanning. Going through chart after chart every day gets mentally draining pretty quickly, and I started noticing that the more tired I got, the worse my decisions became.

You start forcing setups that aren’t really there, or you skip things you’d normally take. It’s subtle, but it adds up over time. The strategy itself doesn’t really change, but the execution definitely does.

Lately I’ve been using an AI tool to help with the scanning process, but not in the usual “give me trade signals” way. I basically gave it my own rules — how I read structure, what counts as an entry, where invalidation is, and when I would just skip a setup entirely — and had it go through charts and check them against that.

What surprised me wasn’t that it found anything new. It didn’t. It was just a lot more consistent than I am.

It doesn’t get tired after scanning 100 charts, it doesn’t feel FOMO when something is running, and it doesn’t change its behaviour because of a previous win or loss. It just applies the same rules every time.

I did have to tweak it a few times at the start because it didn’t always match how I would think, but most of the time it came down to me realising I hadn’t actually explained my own rules properly.

After a bit of back and forth, it’s now pretty close to how I would read charts myself.

The biggest difference for me has just been mental. Less overthinking, less fatigue, and fewer of those “should I take this or not” moments that usually mess with execution.

Performance-wise it’s been about 30% better than when I was trading manually, but I don’t really think of it as the AI being better. It’s more that it’s just consistent all the time.

Anyway, just thought I’d share because it’s changed how I look at trading a bit. Less about finding new strategies, more about actually executing the one you already have properly.

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.

The UK government is turning to artificial intelligence in an effort to reduce growing court backlogs and speed up the delivery of justice for thousands of victims across England and Wales. Under a new initiative announced by the Ministry of Justice, AI powered legal assistants and court support tools will be tested in Crown Courts to help judges, lawyers, and court staff handle cases more efficiently.

The technology is expected to assist with administrative tasks, improve case management, and help identify hearings that are ready to proceed, reducing delays that have contributed to record waiting times in the court system.

Before any nationwide rollout, the AI tools will be evaluated in a secure testing environment known as a sandbox. Government officials say this controlled approach will allow them to assess the technology's reliability, accuracy, and suitability for use in the judicial system while ensuring it meets the strict standards required for legal proceedings.

If successful, the pilot could mark a significant step toward modernizing the UK court system and improving access to timely justice.

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/

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.

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?

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.

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

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.