Digital Currency Group CEO Barry Silbert says he should have just held BTC
Barry Silbert, the CEO of Digital Currency Group, said he would have secured higher investment gains by just holding the Bitcoin that he invested in early-stage crypto projects around 2012.During an April 17 appearance on Raoul Pal’s Journey Man podcast, Silbert said he discovered Bitcoin (BTC) in 2011, purchasing BTC at $7-$8 per coin. Once the price of BTC surged, Silbert started looking for early-stage crypto companies to invest in. The executive told Raoul Pal:”I was using Bitcoin to make a bunch of those investments, and you would think, if you invested in Coinbase you would have done really well. Had I just held the Bitcoin, I actually would have done better than making those investments.”Silbert’s comments come at a time when Bitcoin maximalists, including Strategy co-founder Michael Saylor, forecast a seven-figure Bitcoin price in the coming decade, and BTC receives greater attention from governments worldwide.Bitcoin price history 2011-2025. Source: CoinMarketCapRelated: Bitcoin gold copycat move may top $150K as BTC stays ‘impressive’Bitcoin could hit $1 million if US begins buying BTC Zach Shapiro, the head of the Bitcoin Policy Institute (BPI) think tank, recently predicted BTC would hit $1 million per coin if the United States government were to purchase 1 million BTC.“If the United States announces that we are buying a million Bitcoin, that’s just a global seismic shock,” Shapiro told Bitcoin Magazine in an April 16 podcast appearance.Bo Hines, the executive director of President Trump’s White House Crypto Council, signaled that the council is exploring several budget-neutral strategies for acquiring more Bitcoin for the US Strategic Reserve.These strategies included revaluing the US Treasury’s gold reserves, which are currently priced at $43 per ounce while the market rate is at an all-time high of $3,300 per ounce, and funding Bitcoin acquisition through trade tariffs.BTC has been floated as a way to eliminate or alleviate the growing national debt by President Trump and several market analysts.According to asset management firm VanEck, Bitcoin could help claw back the $36 trillion national debt by $14 trillion if the US Treasury introduces long-term bonds with BTC exposure.Magazine: TradFi fans ignored Lyn Alden’s BTC tip — Now she says it’ll hit 7 figures: X Hall of Flame
XRP: Why it’s outperforming altcoins — and what comes next
Over the past year, most altcoins have struggled to keep up with Bitcoin, but one project is breaking away from the pack: XRP.While other tokens have stagnated or slid, XRP (XRP) has surged more than 300% in just six months against Bitcoin (BTC) to quickly become one of the best-performing assets in the crypto space. But what’s really behind this rally — and more importantly, can it last?Some say it’s the fundamentals finally shining through. Others argue it’s just hype and speculation driven by a passionate community. Then there’s the legal, political, and institutional side of things — factors that could have a far greater impact on XRP’s trajectory than many realize.In Cointelegraph’s latest video, we dive deep into the forces driving XRP’s recent performance, the growing institutional interest, and the potential game-changing developments on the horizon. From exchange-traded funds (ETFs) and stablecoins to regulation and Ripple Labs’ evolving strategy, this video breaks it all down.Whether you’re an XRP holder, a skeptic, or just trying to make sense of the altcoin market in 2025, this is a video you don’t want to miss.Check out the full breakdown on our YouTube channel — and make sure to subscribe for future updates.
TWAP vs. VWAP in crypto trading: What’s the difference?
Algorithmic trading strategies in crypto Algorithmic trading has become a go-to for many traders as it lets you automate trades based on specific rules — no emotions, no hesitation, just pure logic. These strategies can scan markets 24/7, react instantly to price movements, and handle large volumes way faster than a human ever could.Some common algo trading strategies include:Trend following: riding the wave of upward or downward momentum.Arbitrage: taking advantage of price differences across exchanges.Market making: placing buy and sell orders to profit from the spread.Mean reversion: betting that prices will return to their average over time.Now, within the world of algorithmic trading, there’s a special group called execution algorithms. These aren’t about predicting where the market is going — they’re about how to get in or out of a position without moving the market too much. They’re especially useful for handling large orders discreetly.A key subset of these is passive order execution strategies. These aim to minimize slippage and get you as close as possible to a fair average price. The two big names here are:Time-weighted average price (TWAP): splits your order into equal parts over time, ignoring volume. It’s great for low-liquidity situations or when you want to stay under the radar.Volume-weighted average price (VWAP): adjusts your trade size based on market volume, placing bigger trades when activity is higher.Both help you avoid tipping off the market and are essential tools in the crypto trader’s toolkit. What is time-weighted average price (TWAP)? TWAP, or time-weighted average price, is one of the simplest and most widely used execution strategies in algorithmic crypto trading. At its core, TWAP helps traders break down a large order into smaller trades, executed evenly over a set period of time — regardless of market volume. The goal? To get an average price that reflects time, not market activity, and to avoid causing sudden price moves.This strategy is especially useful in two scenarios: when you’re trying to quietly execute a large trade without alerting the market and when you’re trading in low-liquidity environments where even moderate orders can move prices. By pacing your trades, TWAP helps reduce slippage and keeps your activity under the radar.Its biggest strength is its simplicity — it’s easy to implement and understand. But that simplicity also comes with a tradeoff: TWAP doesn’t account for trading volume. So, during high-volatility periods or sudden market shifts, it might miss key signals and give you an execution price that doesn’t reflect the true state of the market.In short, TWAP is a great option when you need to trade steadily over time, especially in quieter markets. But if volume and volatility are major concerns, it might not always give you the best result.Did you know? You can easily add TWAP (time-weighted average price) to your trading setup on platforms like TradingView by simply opening your chart, clicking “Indicators” and searching for “TWAP.” How to calculate TWAP To calculate TWAP, you take the price of the asset at regular time intervals, add them all up, and divide by the number of times you checked the price.Here is the formula to calculate TWAP:In layman’s terms, the formula looks like this:TWAP = (Price₁ Price₂ … Priceₙ) / nLet’s walk through an example.Say you check the price of Bitcoin (BTC) every 10 minutes and get the following:90,000 → 90,100 → 89,900 → 90,050Now add them together:90,000 90,100 89,900 90,050 = 360,050Then divide by the number of intervals (4):TWAP = 360,050 ÷ 4 = 90,012.5 What is volume-weighted average price (VWAP) VWAP stands for volume-weighted average price, and it’s a go-to metric for traders who want a more realistic sense of an asset’s average price throughout the day. Unlike TWAP, which just averages prices over time, VWAP factors in how much volume was traded at each price. That means prices with more trading activity carry more weight in the final average — making it a better reflection of where the market actually values the asset.Traders often use VWAP as a benchmark. If you buy below VWAP, you’re likely getting a better-than-average deal compared to the rest of the market. It’s also handy for spotting trends — if the current price is above VWAP, the market’s probably bullish; if it’s below, that could be a bearish signal.VWAP has its advantages: It gives a more accurate picture of market value and can help identify when an asset might be overbought or oversold. But it’s not perfect. It’s more complex to calculate and can get thrown off by a few unusually large trades, which might skew the average.All in all, VWAP is a powerful tool for traders who want deeper insight into market dynamics, but like any indicator, it works best when used alongside other signals.Did you know? The term volume-weighted average price (VWAP) was first introduced to the trading community in a March 1988 Journal of Finance article titled “The Total Cost of Transactions on the NYSE” by Stephen Berkowitz, Dennis Logue, and Eugene Noser Jr. In this paper, the authors presented VWAP as a benchmark for assessing the quality of trade executions by institutional investors. How to calculate VWAP VWAP works a bit differently. Instead of treating each price equally, it gives more weight to prices where more trading volume occurs. Here is the formula to calculate VWAP:In plain terms, the formula is:VWAP = (Price × Volume at each point, all added up) ÷ Total VolumeLet’s go through an example.Say you have this data for BTC:90,000 at 10 trades90,100 at 20 trades89,900 at 5 trades90,050 at 15 tradesFirst, multiply each price by its volume:90,000 × 10 = 900,00090,100 × 20 = 1,802,00089,900 × 5 = 449,50090,050 × 15 = 1,350,750Now add those results:900,000 1,802,000 449,500 1,350,750 = 4,502,250Then calculate the total volume:10 20 5 15 = 50Finally, divide the total value by the total volume:VWAP = 4,502,250 ÷ 50 = 90,045 When to use TWAP vs. VWAP? It really comes down to what kind of trade you’re making and what the market looks like at the time.If you’re trading during busy hours and want to make sure you’re not overpaying — or underselling — compared to where most of the action is happening, VWAP is your friend. It gives you a sense of the market’s “true” average price by factoring in volume, so it’s great for benchmarking your trades or timing your entry and exit in line with market momentum. If you’re buying below VWAP, you’re likely getting a solid deal.TWAP, on the other hand, is better when you’re trying to stay under the radar. Maybe you’re dealing with a less liquid coin, or you’re trading at a quieter time of day when volume is all over the place. In that case, TWAP helps you slowly work your way into or out of a position without spooking the market. It doesn’t care about volume — it just paces your trade out over time in equal chunks.So, big picture: Use VWAP when you’re following the crowd and want to time things smartly. Use TWAP when you’d rather move quietly and keep things simple. TWAP vs. VWAP: Key differences to be aware of TWAP and VWAP in crypto trading Traders and institutions use TWAP and VWAP to minimize market impact and secure better execution prices. Let’s look at two real-world examples that show how these algorithms perform when the stakes are high.1. Strategy’s $250-million Bitcoin buy with TWAPBack in August 2020, Strategy (called MicroStrategy at the time) made headlines by announcing a $250-million investment in Bitcoin (BTC) as a treasury reserve asset. Rather than entering the market all at once — and risking a sharp price jump — they partnered with Coinbase and used a TWAP strategy. By spreading the purchase out over several days, Strategy was able to blend into market activity, minimizing slippage and securing a favorable average price.2. Definitive’s TWAP strategy for Instadapp (INST)A major crypto VC firm used TWAP to handle a large position in Instadapp (INST), a decentralized finance token known for its low liquidity. Over two weeks in July 2024, it executed the trade in small chunks using Definitive’s TWAP algorithm. The result was a 7.5% improvement over what it would’ve paid using VWAP, and gas fees made up just 0.30% of the $666,000 order. It was a clear win in terms of both cost-efficiency and stealth execution.3. Kraken Pro and the use of VWAPKraken offers advanced trading capabilities through its Kraken Pro platform, which includes VWAP as a built-in technical indicator for traders. On Kraken Pro, users can access VWAP directly in the charting interface, powered by TradingView integration, to analyze crypto assets across various timeframes.For instance, a trader on Kraken Pro might use VWAP to optimize a Bitcoin trade. They could set up an order to buy BTC when the price dips below the daily VWAP — indicating it’s trading below the volume-weighted average and potentially undervalued — and sell when it rises above, suggesting overvaluation or profit-taking opportunities. Institutional clients and high-volume traders, in particular, rely on Kraken’s VWAP functionality for precision in the fast-moving crypto market.Whether you’re managing a big order or just trying to get a fair entry, knowing when and how to use both TWAP and VWAP can give you a serious edge in the market.Happy crypto trading!
Bitcoin miner Bit Digital acquires $53M facility as AI, HPC push continues
Bitcoin mining company Bit Digital has acquired an industrial building in Madison, North Carolina, upping the ante in a business diversification strategy that includes strategic pivots into AI and high-performance computing. Bit Digital agreed to buy the property for $53.2 million through Enovum Data Centers Corp., the company’s wholly owned Canadian subsidiary, regulatory filings show. The investment includes a $2.25 million initial deposit, with $1.2 million being non-refundable. The transaction is expected to close on May 15.Bit Digital disclosed the acquisition in a Form 8-K filed with the US Securities and Exchange Commission. Source: SECBit Digital’s regulatory filing was submitted around the same time that it announced a new Tier 3 data center site in Quebec, Canada, which will support the company’s 5 megawatt colocation agreement with AI infrastructure provider Cerebras Systems. The Quebec facility is being retrofitted with roughly $40 million in upgrades to meet Tier 3 standards — strict requirements that ensure high reliability for critical systems and continuous operation.Bit Digital CEO Sam Tabar said at the time that the Quebec operation “represents continued momentum in our strategy to deliver purpose-built AI infrastructure at scale.”Related: Auradine raises $153M, debuts business group for AI data centersMiners under pressure to diversifyFaced with volatile crypto prices and a quadrennial Bitcoin halving cycle that squeezes revenues, several mining firms have leveraged their existing infrastructure to pivot to other data-intensive workloads. Mining companies like Hive Digital say AI data centers offer potentially higher revenue streams than crypto mining. In the latest sign of economic pain, public Bitcoin miners sold more than 40% of their Bitcoin (BTC) holdings in March, according to data from TheMinerMag publication. Public miners that can’t keep their costs under control struggle the most in maintaining their Bitcoin operations, placing more pressure on executives to seek out alternative revenue streams.An October report by CoinShares suggested that the least profitable miners are more likely to shift gears to AI and other workloads. The cost per Bitcoin is an important metric for mining companies, which have struggled to remain profitable in a post-halving environment. Source: CoinSharesRelated: SEC says proof-of-work mining does not constitute securities dealing
How Mantra’s OM token collapsed in 24 hours of chaos
Mantra’s OM token collapsed by more than 90% overnight, and the crypto world can’t agree on why. On April 13, OM’s price plummeted from over $6 to below $0.50, wiping out more than $5 billion in market cap and triggering widespread panic across the crypto industry.The sudden crash drew comparisons to Terra’s LUNA implosion as traders scrambled for answers. Unverified rumors of insider dumping, forced liquidations, mislabeled wallets and exchange manipulation quickly spread — but Mantra insists it was caught in the middle.Mantra had built a strong position in the real-world asset tokenization narrative heading into April 13, backed by a $1-billion deal to tokenize Dubai-based Damac Group’s real estate and data centers. It secured a Virtual Assets Regulatory Authority (VARA) license in Dubai and launched a $108-million ecosystem fund with support from heavyweights such as Laser Digital, Shorooq, Amber Group and Brevan Howard Digital. In February 2025, the OM token hit an all-time high of nearly $9.But on April 13, that momentum was violently interrupted. The hours that followed painted a messy picture of token transfers, insider speculation and shifting blame. Here’s a detailed look at how the OM collapse played out.24 hours of the Mantra OM fiascoApril 13 (16:00–18:00 UTC)Mantra’s OM token was trading sideways throughout the day. It dropped from $6.14 to $5.52 during this two-hour window.April 13 (18:00–20:00 UTC)The token suddenly fell to $1.38 in the first hour, then to as low as $0.52 in the next — losing over 90% of its value in a single day. Social media erupted with theories, including a rug pull, insider dumping, forced liquidation or exchange manipulation.Mantra’s OM loses over 90% of its value in just a few hours. Source: CoinGeckoApril 13 (20:00–22:00 UTC)Early speculation surrounded a rug pull, sparked by a screenshot of a deleted Telegram channel. This was later debunked, as the deleted group was not Matra’s official channel. Cointelegraph has confirmed that the project’s Telegram is active at the time of writing.Mantra shared its first statement on X, but the brief update was met with immediate backlash from the community.Mantra says OM’s crash was due to “reckless liquidations.” Source: Mantra/ExyApril 13 (22:00–00:00 UTC)Mantra co-founder and CEO John Patrick Mullin posted a more detailed statement on X, claiming OM’s market action was triggered by “reckless forced closures initiated by centralized exchanges on OM account holders.”“The timing and depth of the crash suggest that a very sudden closure of account positions was initiated without sufficient warning or notice,” Mullin said.“That this happened during low-liquidity hours on a Sunday evening UTC (early morning Asia time) points to a degree of negligence at best, or possibly intentional market positioning taken by centralized exchanges.”Related: Atkins becomes next SEC chair: What’s next for the crypto industryApril 14 (00:00–02:00 UTC)In the days leading up to the crash, at least 17 wallets had deposited a total of 43.6 million OM (worth $227 million) into Binance and OKX, according to blockchain tracker Lookonchain.Two of these wallets were labeled as belonging to Laser Digital, a strategic Mantra investor, by blockchain data platform Arkham Intelligence. The label triggered further speculation and allegations against Laser Digital. At the time of writing, the accuracy of Arkham’s labels has not been confirmed, and the platform has not responded to Cointelegraph’s request to clarify.Laser Digital is still tagged on Arkham’s platform. Source: Arkham IntelligenceMeanwhile, Mullin replied to community questions under his X post, suggesting internal findings pointed to one exchange as the main cause of the collapse while stating that it was not Binance.April 14 (02:00–05:00 UTC)Both Binance and OKX responded to the situation. Binance said, “Binance is aware that $OM, the native token of MANTRA, has experienced significant price volatility. Our initial findings indicate that the developments over the past day are a result of cross-exchange liquidations.”OKX CEO Star Xu posted on X, “It’s a big scandal to the whole crypto industry. All of the onchain unlock and deposit data is public, all major exchanges’ collateral and liquidation data can be investigated. OKX will make all of the reports ready!”OKX stated, “Following the incident, we have conducted investigations and identified major changes to the MANTRA token’s tokenomics model since Oct 2024, based on both publicly available on-chain data and internal exchange data.“Our investigation also uncovered that several on-chain addresses have been executing potentially coordinated large-scale deposits and withdrawals across various centralized exchanges since Mar 2025.”April 14 (05:00–12:00 UTC)Laser Digital denied ownership of the wallets tagged by Arkham and reported by Lookonchain, calling them mislabeled.“We want to be absolutely clear: Laser has not deposited any OM tokens to OKX. The wallets being referenced are not Laser wallets,” the company said on X, sharing three token addresses to support its claim that no sales had occurred.Lookonchain also identified another wallet using Arkham data that had remained dormant for a year before becoming active just hours before the crash. The wallet was labeled as belonging to Shane Shin, a founding partner of Shorooq Partners, and received 2 million OM shortly before the collapse.Source: Lookonchain/Shae ShinApril 14 (12:00–13:00 UTC)Mullin joined Cointelegraph’s Chain Reaction show and denied reports that key Mantra investors dumped OM before the collapse. He dismissed allegations that the team controlled 90% of the supply.“I think it’s baseless. We posted a community transparency report last week, and it shows all the different wallets,” Mullin said, noting the dual-token setup across Ethereum and the Mantra mainnet. Additionally, he reassured users that OM token recovery is the team’s primary concern. “We’re still in the early stages of putting together this plan for a potential buyback of tokens,” he said. Related: The whale, the hack and the psychological earthquake that hit HEXApril 14 (13:00–16:00 UTC)More theories started emerging. Onchain Bureau claimed market makers at FalconX were responsible for the price crash. They blamed it on the loan option model — a service allowing market makers to borrow tokens and execute guaranteed purchases at contract expiry.“Instead of paying the market maker with a monthly retainer fee, they had a contract signed saying that they would be able to enforce a buy of, for example, 1M tokens at $1 by contract expiry. Clearly, when the contract expired, they enforced the contract and made their bags,” Onchain Bureau said in a now-deleted X post.Shortly afterward, Onchain Bureau followed up, saying FalconX had reached out and denied being Mantra’s market maker. Mullin also responded to the post, stating that FalconX was not the project’s market maker. He described them instead as a trading partner.Meanwhile, crypto detective ZachXBT weighed in, claiming that individuals linked to Reef Finance had allegedly been seeking massive OM-backed loans in the days leading up to the crash.Source: ZachXBTWhat we know of the OM crashSeveral theories have been thrown around. Initial fears ranged from a rug pull to insider trading, which Mantra has denied in several instances by sharing wallet addresses. The team has responded to online comments and media inquiries to assure that they haven’t run away.Mantra has also denied that the price collapse was a result of an expiring deal with market maker FalconX. Some fingers were pointed toward Laser Digital, which said it is a result of mislabeling at Arkham Intelligence. Arkham Intelligence has not responded to Cointelegraph’s request to clarify its labels. However, the Laser Digital tags on Arkham are a low-confidence prediction made by an AI model, not a verified entity with a blue checkmark.Magenta-colored labels on Arkham Intelligence are low-confidence AI predictions, not verified wallets. Source: Arkham IntelligenceIn the days following the OM crash, Mullin stated that he would burn all of his team’s tokens. He later said that he would start by putting his own allocation on the line.Mullin announced that Mantra would publish a post-mortem and followed with a “statement of events” on April 16. The team reiterated that no project-led token sales occurred and that all team allocations remain locked. The statement doubled down on Mantra’s plan to introduce a token buyback and burn program but lacked new information on the cause of the crash.Mullin told Cointelegraph that Mantra has tapped an unnamed blockchain analyst to investigate the underlying cause of the crash, though details remain confidential at this time.Magazine: Memecoin degeneracy is funding groundbreaking anti-aging research
Eliza Labs launches auto.fun, a no-code AI spin on Pump.Fun
Eliza Labs, the developer behind the AI agent framework ai16z, announced the launch of auto.fun, a new no-code platform allowing users to launch AI agents on Web3 applications.Auto.fun allows for the creation, deployment and monetization of AI agents by non-developers without programming knowledge, according to an April 17 announcement.The platform supports the creation of AI agents that interact with social media, decentralized finance (DeFi) apps and other Web3 services.“The vision for auto.fun is to democratize access to both AI and Web3 technologies by creating agents that can execute tasks autonomously on behalf of users,” said Shaw Walters, founder of Eliza Labs and the open-source elizaOS.The animated ASCII art shown to auto.fun visitors ahead of launch. Source: auto.funWalters said the agents could automate yield farming strategies, manage social media accounts or trade on behalf of users. The platform is focused on X support, with DeFi, gaming and other application support promised in the future.Related: AI takes nearly 60% of global venture capital dollars in Q1: PitchbookAI agents with no coding requiredEliza Labs said auto.fun will allow users to create agentic AI systems that both respond to queries and perform tasks. Users will purportedly be able to tell their AI agents what to do with their funds in DeFi through simple commands. “Find me the best staking opportunities with at least 12% APY and automatically allocate funds.”An Eliza Labs spokesperson told Cointelegraph that the product’s focus is accessibility, with some user education in place:“While the platform makes it possible for users to spin up agents in a few clicks, key educational prompts and user experience guardrails are embedded throughout the process to help users make informed choices.Token launch mechanicsAuto.fun also introduces what Eliza Labs calls “fairer than fair” token launches. The company is employing a bonding curve mechanism that “combines the benefits of a fair launch with enough flexibility for project teams to secure up to 50% of their tokens before market listing.”Related: Ethereum could be AI’s key to decentralization, says former core devA bonding curve is a smart contract-based algorithmic pricing model in DeFi that dynamically adjusts a token’s price based on its circulating supply. When tokens are bought or sold, the bonding curve automatically adjusts the price according to predefined mathematical relationships, ensuring continuous liquidity without relying on traditional order books.The Eliza Labs spokesperson said (RAY) purportedly allows for “a more sustainable alternative.”that traditional token launches often leave core teams with little in terms of resources and allow for easier token dumps. The hybrid bonding curve approach developed in partnership with Raydium The system allows project teams to pre-reserve up to 50% of the supply, which supposedly ensures “they have meaningful skin in the game and resources for post-launch development.” The remaining tokens are sold through a bonding curve that should limit the advantages of bot-driven purchases.Walters also highlighted that auto.fun is open source. This “ensures users can verify exactly how their agents operate and what happens with their data.”Agents that will operate on the platform include FightFi, a collection of social media agents that compete with each other with agent-specific tokens providing token-gated access to higher-level functions.Other agents include Secret, which launches Solana (SOL) tokens, and Sigma Music Agent, which connects musicians and fans with AI agents. Another agent on the platform is Astra, which manages crosschain payments between Ethereum Virtual Machine (EVM) blockchains, Solana, and the Bitcoin (BTC) layer-2 Lightning Network.Magazine: ‘Chernobyl’ needed to wake people to AI risks, Studio Ghibli memes: AI Eye
Bitcoin price levels to watch as Fed rate cut hopes fade
Bitcoin’s (BTC) price failed another attempt at breaking above resistance at $86,000 on April 16 as Fed Chair Jerome Powell dashed hopes of early rate cuts, citing the impact of Trump’s tariffs.Since April 9, BTC price has formed daily candle highs between $75,000 and $86,400, but has been unable to produce a close above $86,000.BTC/USD daily chart. Source: Cointelegraph/TradingViewMany analysts and traders ask, “Where is Bitcoin price headed next?” as the asset remains stuck in a tight range on the lower time frame (LTF) of the 4-hour chart.88% chance interest rates unchangedPolymarket bettors say there is an 88% chance that the current interest rates will remain between 4.25% and 4.50%, leaving just a 10% probability of a 0.25% rate cut.Interest rate expectations. Source: PolymarketHowever, a common market belief is that any bearish price action from unchanged interest rates is already priced in.On April 16, US Federal Reserve Chair Jerome Powell indicated that the Fed is not rushing to cut interest rates. Speaking in Chicago, he emphasized a “wait-and-see” approach, needing more economic data before adjusting policy. Powell highlighted risks from President Trump’s tariffs, which could drive inflation and slow growth, potentially creating a “challenging scenario” for the Fed’s dual mandate of stable prices and maximum employment. “The level of the tariff increases announced so far is significantly larger than anticipated,” said Powell in a speech, adding: “The same is likely to be true of the economic effects, which will include higher inflation and slower growth.”He stressed maintaining a restrictive policy to ensure inflation doesn’t persist, suggesting any immediate rate cuts despite market volatility and tariff uncertainties.Related: Bitcoin gold copycat move may top $150K as BTC stays ‘impressive’As a result, President Trump has threatened Powell with termination, arguing that he is “always too late and wrong” and that his April 16 report was a typical and complete “mess.”“Powell’s termination cannot come fast enough!”Meanwhile, Polymarket now says there’s a 46% chance that Bitcoin’s price will hit $90,000 on April 30, with less than 5% possibility of hitting new all-time highs above $110,000.Key Bitcoin price levels to watchBitcoin must flip the $86,000 resistance level into support to target higher highs at $90,000.For this to happen, BTC/USD must first regain its position above the 200-day exponential moving average (purple line) at $87,740. This trendline was lost on March 9 for the first time since August 2024.Above that, there is a major supply zone stretching all the way to $91.240, where the 100-day SMA sits. Bulls will also have to overcome this barrier in order to increase the chances of BTC’s run to $100,000.Bitcoin daily chart. Source: Cointelegraph/TradingViewConversely, the bears will attempt to keep the $86,000 resistance in place, increasing the likelihood of new lows under $80,000. A key area of interest lies between $76,000 and the previous range lows at $74,000, i.e., the previous all-time high from March 2024.Below that, the next move would be a retest of the US election day price of $67,817, erasing all the gains made from the so-called Trump pump.Onchain analyst James Check points out that Bitcoin’s true bottom lies at its “true market mean” — the average cost basis for active investors — around the $65,000 area. “The $75,000 zone is an area where you want the bulls to mount a defense,” check said in an interview on the TFTC podcast, adding:“If they don’t, the next step is we go back to the chop consolidation range, we find out how deep into that we go, and the flag in the sea of sand is $65,000.”Interestingly, this price level aligns closely with Michael Saylor’s Strategy cost basis, which sits around $67,500. This article does not contain investment advice or recommendations. Every investment and trading move involves risk, and readers should conduct their own research when making a decision.
How Meta’s antitrust case could dampen AI development
Meta, the parent company of Facebook, Instagram, WhatsApp and Messenger, is facing antitrust proceedings that could limit its ability to develop AI amid a field of competitors.First filed in 2021, the Federal Trade Commission (FTC) alleges that Meta’s strategy of absorbing firms — rather than competing with them — violates antitrust laws. If the court rules against Meta, it could be forced to spin out its various messenger services and social media sites into independent companies.The loss of its stable of social media companies could harm Facebook’s competitiveness not only in the social media industry but also in its ability to train and develop its proprietary Llama AI models with data from those sites.The trial could take anywhere from a couple of months to a year, but the outcome will have lasting consequences on Meta’s standing in the AI race.Meta’s antitrust case and its effect on AIThe FTC first opened its complaint against Meta in 2020 when the firm was still operating as Facebook. The agency’s amended complaint a year later alleges that Meta (then Facebook) used an illegal “buy-or-bury” scheme on more creative competitors after its “failed attempts to develop innovative mobile features for its network.” This resulted in a monopoly of the “friends and family” social media market.Meta founder and CEO Mark Zuckerberg had the chance to address these allegations on April 14, the first day of the official FTC v. Meta trial. He testified that only 20% of user content on Facebook and some 10% on Instagram was generated by users’ friends. The nature of social media has changed, Zuckerberg claimed.“People just kept on engaging with more and more stuff that wasn’t what their friends were doing,” he said — meaning that the nature of Meta’s social media holdings was sufficiently diverse.The FTC alleges that Meta identified potential threat competitors and bought them up. Source: FTCAt the time of the FTC’s initial complaint, Meta called the allegations “revisionist history,” a claim it repeated on April 13 when it stated the agency was “ignoring reality.” The company has argued that the purchases of Instagram and WhatsApp have benefited users and that competition has appeared in the form of YouTube and TikTok. If the District of Columbia Circuit Court rules against Meta, the global social media giant will be forced to unwind these services into independent firms. Jasmine Enberg, vice president and principal analyst at eMarketer, told the Los Angeles Times that such a ruling could cost Meta its competitive edge in the social media market. “Instagram really is its biggest growth driver, in the sense that it has been picking up the slack for Facebook for a long time, especially on the user front when it comes to young people,” said Enberg. “Facebook hasn’t been where the cool college kids hang out for a long time.”Such a ruling would also affect the pool of data from which Meta can draw to train its AI models. In July 2024, Meta halted the rollout of AI models in the European Union, citing “regulatory uncertainty.” The pause came after privacy advocacy group None of Your Business filed complaints in 11 European countries against Meta’s use of public data from its platforms to train its AI models. The Irish Data Protection Commission subsequently ordered a pause on the practice until it could conduct a review. Related: Meta’s Llama 4 puts US back in lead to ‘win the AI race’ — David SacksOn April 14, Meta got the go-ahead to use public data — i.e., posts and comments from adult users across all of its platforms — to train the model. If these firms dissolved into separate companies, with their own organizational structures and data protection policies and practices, Meta would be cut off from an ocean of data and human communication with which its AI could be improved. Andrew Rossow, a cyberspace attorney with Minc Law and CEO of AR Media Consulting, told Cointelegraph that in such an event, “companies would most likely control their own user data, and Meta would be restricted from using it unless new data-sharing agreements were negotiated, which would be subject to regulatory scrutiny and user/consumer privacy laws.”However, Rossow noted that it wouldn’t be a total loss for Meta. Zuckerberg’s firm would retain the wealth of data from Facebook and Messenger. It could continue to use “opt-in” data from consumers who allow their posts to be used for AI training, and it could also employ synthetic data sets as well as third-party and open data.Meta, the AI race and data protectionsThe race to unseat OpenAI and its ChatGPT model from AI dominance has grown more competitive in the last year as DeepSeek joined the fray and Meta launched the fourth iteration of its open-source Llama model. In addition to training new models, major AI development firms are investing billions in new data centers to accommodate new iterations. In January 2025, Meta announced the construction of a 2-gigawatt data center with more than 1.3 million Nvidia AI graphics processing units. Zuckerberg wrote in a post on Threads, “This will be a defining year for AI. In 2025, I expect Meta AI will be the leading assistant serving more than 1 billion people […] To power this, Meta is building a 2GW+ datacenter that is so large it would cover a significant part of Manhattan.”Illustration of the data map coverage. Source: Mark ZuckerbergHis announcement followed the $500-billion Stargate project, which would see massive investment in AI development led by OpenAI and SoftBank, with Microsoft and Oracle as equity partners. Related: Trump announces $500B AI infrastructure venture ‘Stargate’Amid this competition, AI firms are looking for broader and more varied sources of data to train their AI models — and have turned to dubious practices in order to get the data they need. In order to stay competitive with OpenAI when developing its Llama 3 model, Meta harvested thousands of pirated books from the site LibGen. According to court documents in a case pending against Meta, Llama developers harvested data from pirated books because licensing them from sources like Scribd seemed “unreasonably expensive.” Time was another perceived motivator for using pirated works. “They take like 4+ weeks to deliver data,” one engineer wrote about services through which they could purchase book licenses.The practice is not limited to Meta. OpenAI has also been accused of mining data from pirated work hosted on LibGen. Rossow suggested that, “to ensure lasting impact — beyond short-term profit,” Meta would do well to “prioritize investment in advanced data collection, rigorous auditing and the implementation of privacy-preserving and encryption-based technologies.”By focusing on transparency and responsible practices, “Meta can continue to genuinely advance AI capabilities, rebuild and nurture long-term user trust, and adapt to evolving legal and ethical standards, regardless of changes to its platform portfolio.”What a ruling for the FTC would meanLitigation is now hitting tech firms from all sides as they face allegations of privacy violations, copyright law infringement and stifling competition. Major cases like those facing Google, Amazon and Meta that have yet to play out will decide how and whether these firms can proceed as they have, defining the guardrails for AI development as well. Rossow said that the current antitrust case against Meta could decide how courts interpret antitrust law for tech firms, spanning tech mergers, data usage and market competition. It would also signal that courts are “willing to break up tech conglomerates” when issues of smothering competition are involved, while at the same time, “taking current precedent a step further in harmonizing it with the laws of cyberspace.”Magazine: Memecoin degeneracy is funding groundbreaking anti-aging research