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Centralized clouds charge you up to 70% more than you need to pay for GPU compute. Not because their chips cost more. Because you're also paying for their electricity, cooling headaches, software bundles, and egress fees. We broke down every option for GPU compute with the actual numbers. Full guide:

Bybit Open Interest (OI) data is getting an upgrade. Starting June 11, we’re moving to single-counted OI for a cleaner, industry-standard way to track market activity. 📊 The numbers change. Your positions, margin, and P&L remain untouched. See what’s changing:

Friday’s $TON space is not going to be another “which meme pumps next” discussion. We’re going deep into how real money was actually made inside the TON ecosystem. How @plugontele turned $2,000 into $5M+ by understanding TON primitives before the crowd arrived. Why usernames, anon numbers and NFTs exploded in value. Why Telegram distribution changes everything. Why liquidity on TON behaves differently from most ecosystems. And why only a few memes right now can actually absorb serious whale size without collapsing structure. We’ll also discuss: • $UTYA • $REDO • $YODA • TON NFTs & collectibles • Whale psychology • Early accumulation behavior • How smart money positions before narratives go mainstream Featuring @plugontele , @fragontele , @sarah_talley_ , @enigmaeye_ , @realAlexDJ, @moontroncrypto and more. This space is for people who want to understand the TON cycle deeply before the masses fully wake up. May the Force be with you.

Just wrapped one of the best $TON spaces we’ve had so far. Huge thanks to @plugontele , @fragontele , @sarah_talley_ , @enigmaeye_ and @realAlexDJ for joining. Tons of alpha was shared: • How whales actually accumulate early • Why $TON feels structurally different • Meme coin psychology & conviction • NFTs, anon numbers and TON culture • Why many still underestimate $UTYA $REDO $YODA A lot of deep insights were dropped tonight. If you missed it, listen to the recording. The Force is strong with $TON believers.....

Microsoft just banned its own engineers from using AI. The tool was literally costing MORE than the humans it was supposed to replace. They lied to you about AI adoption and now the whole narrative is blowing up: Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it. Engineers loved it and adoption exploded. But then the invoices arrived. Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead. The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much. Uber's story is even worse... Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April. Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems. Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session. The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money. Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote: "For my team, the cost of compute is far beyond the costs of the employees." This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans. Think about what this means for the entire AI narrative. Every CEO on every earnings call for the past two years has said the same thing: AI will make us more efficient, reduce headcount, and cut costs. The stock market rewarded every company that said it. Fired workers, stock goes up. Announced AI adoption, stock goes up. But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill. Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools. Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible. Both companies are spending hundreds of billions on AI infrastructure this year alone. And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control. The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP. This is the gap nobody on Wall Street is pricing in. $725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work. What do you think?

"This really does feel like a silent IPO." James Seyffart (@JSeyff) is the ETF analyst at Bloomberg Intelligence. Spent his career inside the machine that tracks every dollar flowing through US ETFs. Predicted the spot Bitcoin ETF approval timing months before Wall Street consensus. Now tracking what advisors are actually doing, not what they're saying. "Q1 2026 was the most successful quarter Bitwise ever had. Selling Bitcoin ETFs to wealth advisors. Despite the price not doing well at all." We cover: — Why advisors loaded up on Bitcoin while retail was selling — The "silent IPO" frame: ETFs in, MicroStrategy in, retail out, and what happens when that flips — Why the Iran weekend was the real Bitcoin turning point nobody talked about — The Facebook moment thesis: why ETF growth keeps compounding even as crypto-native traders lose interest — Six years ago people asked if Bitcoin would be banned, what changed in DC — Why gold ETFs went from $130B to $300B+ and what that means for the next BTC leg — The basket ETF and prediction market ETF wave coming through SEC pipeline right now — Why James can't be more bullish than he is on ETF structure and the inflow numbers backing it up — Which wealth advisors are now writing Bitcoin into 60/40 portfolios as a structural allocation — The Clarity Act window and why his colleague has never put odds below 60% Thanks to James for joining us again on @new_era_finance. Highlights: 00:00 - Intro 02:13 - The Iran Moment Shock 02:33 - Bitwise's Best Quarter Ever 03:34 - Crypto's Inverse Adoption Curve 12:08 - Tokenization & The Stablecoin Cliff 20:00 - Gold ETFs vs Bitcoin ETFs 21:00 - Six Years Ago vs Now 24:48 - The Gold Bull Run Explained 30:15 - Basket ETFs Coming 32:50 - Clarity Act Odds 33:40 - Why ETF Inflows Hit New ATHs 36:08 - The Silent IPO Frame