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Bitcoin Price Crashes To Two-Week Low Near $66,000

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Bitcoin price fell below $66,500 on Friday, hitting its lowest level in more than two weeks as a wave of long liquidations and mounting macroeconomic stress weighed on the crypto market..

Data shows nearly $300 million in long positions were liquidated over the past 24 hours, according to Bitcoin Magazine Pro data, compared with roughly $50 million in short liquidations, pointing to an unwind of crowded bullish positioning in crypto futures. The imbalance reflects a market that had leaned heavily long and is now adjusting as sentiment shifts.

The bitcoin price selloff coincided with a broader risk-off move across global markets. Nasdaq 100 futures have fallen about 10% from their January highs, while oil prices climbed near $100 per barrel amid escalating geopolitical tensions tied to the ongoing conflict involving Iran. 

Earlier today, Israel said it will escalate strikes on Iran after renewed waves of Iranian missile attacks, while both sides continue exchanging fire despite ongoing diplomatic efforts. 

President Trump has paused U.S. strikes on Iranian energy infrastructure for 10 more days to allow negotiations, even as reports suggest the Pentagon is considering deploying up to 10,000 additional troops to the Middle East.

Meanwhile, the conflict is widening regionally, with shipping disruptions reported in the Strait of Hormuz, Gulf states on alert after strikes, and Iranian casualties reportedly nearing 2,000 as international talks continue in Europe.

The surge in crude has renewed inflation concerns and pressured risk assets, including cryptocurrencies.

Bitcoin price dynamics

Bitcoin price briefly approached $71,500 this week on optimism tied to a potential diplomatic breakthrough in the Middle East. Those gains reversed as uncertainty around negotiations resurfaced, pushing prices lower and reinforcing sensitive market conditions.

Despite the recent decline, bitcoin price continues to trade within a defined range between $60,000 and $75,000 that has held for several weeks, even months. The asset remains well below its October 2025 peak above $126,000 following a broader market correction.

Institutional flows present a mixed picture. U.S.-listed spot bitcoin exchange-traded funds recorded sustained inflows earlier in March, totaling about $2.5 billion over five weeks. That momentum has slowed in recent sessions, with net outflows emerging and signaling a pause in accumulation as investors respond to macro uncertainty.

At the same time, on-chain data indicates continued withdrawals of bitcoin from centralized exchanges over the past month. This trend suggests longer-term holders are moving assets into self-custody, a pattern often associated with accumulation rather than distribution.

Despite this, Morgan Stanley is a step closer to launching its spot Bitcoin ETF, MSBT, after the New York Stock Exchange posted a listing notice — signaling an imminent debut that could make it the first such product from a major U.S. bank, alongside offerings from BlackRock and Fidelity.

Options markets add another layer of complexity. Roughly $14 billion in bitcoin price options are set to expire, representing a significant share of open interest. 

Hedging activity tied to these contracts has contributed to subdued volatility, with price action gravitating toward key strike levels near $75,000.

As these contracts roll off, the stabilizing effect from derivatives positioning may fade, leaving bitcoin more exposed to external catalysts. 

With geopolitical risks elevated and macro conditions tightening, the market faces a period where price movements may become more reactive and less constrained by structural flows.

LayerZero Goes Live on Institution-Focused Canton as Its First Interop Protocol

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The LayerZero integration gives assets tokenized on Canton access to over 165 public blockchains.

LayerZero has integrated with the institution-focused blockchain Canton (CC), becoming the first interoperability protocol to go live on the network, per a press release shared with The Defiant.

The integration, announced today, March 26, lets traditional financial institutions on Canton route tokenized assets, including securities, digital bonds, and equities, across the more than 165 public blockchains supported by LayerZero, while maintaining their compliance and confidentiality requirements, according to the release.

Also part of the integration, investors can now use stablecoins on external public chains to fund primary purchases of Canton-based tokenized real-world assets (RWAs), while Canton-native tokenized instruments can move into other ecosystems for secondary market trading.

“Canton has already built the rails for traditional finance, processing more than $350B in daily U.S. Treasury repo volume,” LayerZero CEO Bryan Pellegrino said in the release. “LayerZero’s job is to make sure those assets are available in every global market, across blockchains.”

The deal extends LayerZero’s already notable institutional push. In February, LayerZero unveiled its own Layer 1 blockchain, Zero, backed by strategic investments from Citadel Securities and Tether.

The Depository Trust & Clearing Corporation (DTCC) and the New York Stock Exchange’s parent Intercontinental Exchange both said they are evaluating the network for tokenized securities and settlement workflows.

More recently, LayerZero partnered with Centrifuge to expand multichain access for tokenized funds including nearly $861 million in tokenized U.S. Treasuries, as The Defiant reported last week.

For its part, Canton positions itself as the L1 blockchain network for TradFi institutions, with configurable privacy features. Per data from RWAxyz, Canton currently has $342.7 billion in represented asset value from tokenized RWAs, all of which is attributed to Broadridge’s Distributed Ledger Repo (DLR) platform.

Canton’s native CC token now carries a market cap of roughly $5.2 billion, ranking it #21 on CoinGecko. Last June, Digital Asset, the firm behind Canton, raised $135 million in a round that included Goldman Sachs, Citadel Securities, BNP Paribas, the DTCC, and Paxos, with CEO Yuval Rooz saying the capital would accelerate adoption for tokenized bonds, money-market funds, and commodities, as The Defiant reported at the time.

Just yesterday, Visa announced that it has become a Super Validator on the Canton network, becoming the first global payments company to do so, and is set to introduce privacy-preserving payments to the network.

This article was written with the assistance of AI workflows. All our stories are curated, edited and fact-checked by a human.

Bitcoin price (BTC) slides alongside software stocks following leak of new Anthropic model

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Anthropic, the artificial intelligence company behind Claude, has begun testing a new AI model more capable than any it has released previously, Fortune reported.

The company said the model represents “a step change” in performance and is “the most capable we’ve built to date.” It is currently being tested with a small group of early access customers as Anthropic evaluates its behavior and risks.

Among the names moving sharply lower on the news: Palo Alto Networks (PANW), Crowdstrike (CRWD) and Fortinet (FTNT) are all down 4%-6%. The broader iShares Expanded Tech-Software Sector ETF (IGV) is off 2.5%.

The overnight leak likely contributed to bitcoin’s tumble back to $66,000 after flirting with $70,000 hours earlier.

Details about the model surfaced after internal materials were accidentally exposed in a publicly accessible data store, according to Fortune. Around 3,000 assets linked to Anthropic’s blog were available online, including draft announcements and internal content that had not yet been released.

Among the files was a draft blog post referring to the model as “Claude Mythos.” The document warned that the system could pose serious cybersecurity risks, pointing to its ability to identify and exploit software vulnerabilities.

Anthropic currently offers three tiers of models — Opus, Sonnet and Haiku — which vary in size, cost and capability. The leaked materials suggest the company is developing a new tier called “Capybara,” which would be even larger and more intelligent than Opus, the company’s most advanced model to date.

How Content Creators Use Image to Video AI to Boost Social Media Engagement

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Social media has become highly competitive, and content creators are always looking for ways to increase engagement. Static images still work, but video content consistently performs better across platforms like Instagram, TikTok, and YouTube Shorts.

This is where Image to Video AI tools are becoming very useful. They allow creators to turn simple images into animated videos that attract more attention, improve watch time, and increase engagement without requiring advanced editing skills.

In this article, we will explore how content creators are using this technology, why it works, and how you can apply it to your own social media strategy.

What Is Image to Video AI?

Image to Video AI is a technology that converts static images into animated videos using artificial intelligence. It analyzes the image and adds motion effects like zoom, pan, depth changes, and cinematic transitions.

You can use tools like ImageMover to turn photos into engaging videos without needing any video editing experience.

The system uses machine learning to understand image structure and then generates motion frames to create smooth video output.

Why Content Creators Use Image to Video AI

Content creators are under pressure to produce consistent, engaging content. AI tools help solve several challenges:

Faster Content Creation

Videos can be created in minutes instead of hours.

No Editing Skills Required

Beginners can produce professional-looking videos easily.

Better Engagement

Videos usually perform better than static posts.

More Content Output

Creators can turn old images into new video content.

How Image to Video AI Improves Engagement

Engagement depends on how users interact with content. Image to video AI helps increase engagement in several ways:

1. Adds Motion to Static Content

Motion naturally attracts attention on social media feeds.

2. Increases Watch Time

Even short animations increase how long users stay on a post.

3. Improves Storytelling

Images combined into video form tell a stronger story.

4. Boosts Algorithm Reach

Platforms prioritize video content in recommendations.

How Content Creators Use Image to Video AI in Real Life

Let’s look at how creators actually use these tools in daily content production.

1. Turning Photos into Reels and Shorts

Creators take existing images and convert them into short video clips for Instagram Reels, TikTok, and YouTube Shorts.

Using Image to Video AI, they can quickly generate motion-based content that looks fresh and engaging.

2. Repurposing Old Content

Many creators already have thousands of photos sitting unused.

Instead of letting them go to waste, they convert them into videos and repost them as new content.

This helps maintain consistency without creating new material every day.

3. Creating Product Showcases

Influencers and business creators use image to video AI to promote products.

A simple product image can be turned into a short animated advertisement with zoom and motion effects.

4. Enhancing Personal Branding

Creators use animated photos to build a stronger personal brand.

For example:

  • Profile pictures with motion effects
  • Lifestyle photos turned into storytelling videos
  • Behind-the-scenes images converted into reels

5. Educational Content Creation

Teachers and educators also use AI tools to turn diagrams and slides into short visual videos for better understanding.

This improves learning engagement and clarity.

How Image to Video AI Works Behind the Scenes

The process is simple for users but advanced in the background.

Step 1: Image Upload

The creator uploads a photo or set of images.

Step 2: AI Analysis

The system identifies objects, faces, and background layers.

Step 3: Motion Mapping

AI determines how movement should be applied.

Step 4: Frame Generation

Multiple frames are created to simulate motion.

Step 5: Video Output

The final video is generated and ready to download.

This automated workflow makes content creation fast and accessible.

Step-by-Step Guide for Creators

If you want to use Image to Video AI for social media, follow these steps:

Step 1: Choose a Tool

Start with a reliable platform like ImageMover, which provides simple access to AI video generation.

Step 2: Upload Your Image

Upload a clear and high-quality image for best results.

Tips:

  • Use sharp images
  • Avoid cluttered backgrounds
  • Ensure subject visibility

Step 3: Select Animation Style

Choose motion effects such as:

  • Zoom in/out
  • Pan movement
  • Cinematic motion
  • Depth-based animation

Step 4: Generate Video

Let the AI process your image and create motion frames.

Step 5: Preview and Download

Check the output and download the final video if satisfied.

Step 6: Post on Social Media

Share your video on platforms like:

  • Instagram
  • TikTok
  • Facebook
  • YouTube Shorts

Benefits for Content Creators

Using Image to Video AI offers several advantages:

Saves Time

Content creation becomes faster and easier.

Improves Consistency

Creators can post regularly without extra effort.

Boosts Engagement

Videos get more likes, shares, and comments.

Expands Creativity

New content styles become possible.

Works for All Niches

Suitable for lifestyle, business, education, and entertainment creators.

Common Mistakes to Avoid

Even though the tool is simple, creators should avoid:

  • Using low-resolution images
  • Ignoring preview results
  • Overusing motion effects
  • Posting without optimization

Avoiding these improves video performance.

Why Image to Video AI Is Growing in 2026

This technology is becoming more popular because:

  • Social media is video-first
  • Creators need faster workflows
  • AI reduces technical barriers
  • Audiences prefer short-form video content

As a result, more creators are switching to AI-powered tools.

Real Impact on Social Media Growth

Creators using Image to Video AI often see:

  • Higher engagement rates
  • Increased reach on reels and shorts
  • Better audience retention
  • More content output with less effort

It helps both beginners and professionals grow faster.

Final Thoughts

Image to Video AI is changing how content creators produce and share content. It simplifies video creation and allows users to turn simple images into engaging social media videos.

Tools like ImageMover make this process easy, even for beginners. With just a few clicks, creators can generate videos that improve engagement and reach.

As social media continues to evolve, Image to Video AI will play an even bigger role in content creation strategies. For creators looking to stay competitive, this technology is becoming essential rather than optional.







NYSE owner doubles down on Polymarket with fresh $600 million investment

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Intercontinental Exchange (ICE), the parent company of the New York Stock Exchange (NYSE), said it added another $600 million to its investment in prediction market platform Polymarket, closing out a previously announced funding agreement between the two firms.

The new capital comes on top of a $1 billion investment ICE made in October. ICE also plans to buy up to $40 million in additional shares from existing holders, bringing its total commitment close to $2 billion. The company said the investment will not materially affect its financial results.

Polymarket runs a marketplace where users trade on the outcome of real-world events, from elections to economic data releases. A trader, for example, might buy shares that pay out if inflation rises above a specified level. Prices shift in real time, reflecting crowd expectations.

The backing from ICE gives Polymarket more than capital. It ties the platform to one of the upcoming names in global markets. Rival platform Kalshi recently raised more than $1 billion at a $22 billion valuation, roughly double its previous mark. The company is already generating an estimated $1.5 billion in annual revenue, highlighting strong demand for event-based trading.

Investor interest has grown even as lawmakers question whether prediction markets are vulnerable to manipulation or insider activity. These concerns could shape how regulators treat both Polymarket and its peers in the coming years.

Polymarket has taken steps to position itself for that scrutiny. It acquired a licensed exchange and clearinghouse earlier this year while expanding its political and financial ties. It also recently announced a partnership with Palantir and TWG AI to build a surveillance system aimed at detecting suspicious trading and manipulation in its sports prediction markets.

ICE’s investment signals that large, traditional market operators see potential in the sector. If prediction markets gain broader approval, they could sit alongside stocks and futures as another way for traders to express views on the forthcoming events.

BlackRock sends $181 million in Bitcoin, Ether to Coinbase amid crypto sell-off

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BlackRock deposited $181 million in digital assets on Coinbase Prime today during a slump in crypto markets that pushed Bitcoin and altcoins lower.

According to Arkham Intel data, 612 BTC, worth around $41 million, and 68,567 Ethereum, worth approximately $140 million, were transferred from a wallet owned by the leading asset manager.

While BlackRock’s transfers may not involve selling and could be part of a dip-buying strategy, they have caught notice amid mixed demand for exchange-traded products and ongoing geopolitical uncertainty.

The deposit took place amid a sharp crypto market retreat, with Bitcoin sliding from above $68,000 to approximately $66,300 and Ether dipping to $1,982, below the $2,000 mark, per CoinGecko.

Total market capitalization fell 3% over 24 hours to $2.4 trillion.

Flows into and out of BlackRock’s spot crypto ETFs

The iShares Bitcoin Trust (IBIT) attracted roughly $117 million in outflows in the last three days, but those losses were more than offset by $161 million in inflows recorded on Monday alone, leaving net inflows for the week at $44 million, according to data tracked by Farside Investors.

Cumulative net inflows into IBIT since its January 2024 launch have nonetheless topped $63 billion.

On the Ether side, BlackRock’s iShares Ethereum Trust (ETHA) suffered approximately $214 million in withdrawals this week, a steep figure that contrasts with consistent inflows into the recently launched iShares Staked Ethereum Trust (ETHB), which offers holders an annualized staking reward.

Disclosure: This article was edited by Vivian Nguyen. For more information on how we create and review content, see our Editorial Policy.

Bitcoin Slides Below $69,000 as Iran Stalemate Fuels Global Selloff

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Major altcoins plunge, with ETH, SOL, and XRP dropping 5%.

Crypto markets sold off sharply on Thursday as oil surged back above $93 per barrel after U.S.-Iran peace talks stalled, dragging risk assets lower across the board.

Bitcoin (BTC) is trading at around $68,400, down 3.5% over the past 24 hours. ETH and SOL slipped 5% to $2,050 and $87, respectively. Meanwhile, Ripple (XRP) dropped 4.5%.

BTC Chart

Total crypto market capitalization decreased 3.2% to $2.43 trillion, according to Coingecko.

ETF Flows

Spot Bitcoin ETFs posted net inflows of $7.8 million on Wednesday, with Fidelity’s FBTC leading the charge with $83 million. However, that was mostly offset by $70 million in outflows from BlackRock’s IBIT, according to SoSoValue.

Ethereum ETFs continued to underperform, recording net outflows of $8 million, led by BlackRock’s ETHA, with $33 million in withdrawals.

Big Movers

All of the Top 100 digital assets posted gains over the last 24 hours.

SIREN and MemeCore (M) are today’s biggest losers, plunging 30% and 13%, respectively.

Around 97,000 leveraged traders were liquidated for $305 million in the past 24 hours, according to CoinGlass. Bitcoin accounted for $93 million, while ETH made up $104 million.

Looking ahead, two catalysts loom on Friday: the PCE inflation report and the expiration of Trump’s five-day window for diplomacy with Iran.

AAVE drops 3.2% as nearly all constituents decline

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CoinDesk Indices presents its daily market update, highlighting the performance of leaders and laggards in the CoinDesk 20 Index.

The CoinDesk 20 is currently trading at 1912.59, down 2.4% (-47.98) since 4 p.m. ET on Thursday.

One of 20 assets is trading higher.

Leaders: BCH (+0.8%) and CRO (-0.7%).

Laggards: APT (-4.6%) and AAVE (-3.2%).

The CoinDesk 20 is a broad-based index traded on multiple platforms in several regions globally.

Anthropic Auto Mode Means No More Babysitting Claude

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Enterprise developers looking to give agents more autonomy can now do so safely with a new auto mode capability introduced in Claude Code, which allows the AI agent to perform tasks such as editing files and running commands without needing to ask for permission at every step.

The AI lab revealed on March 24 that the new auto mode provides a safer alternative to the somewhat risky permission-skip setting, which allows the large language model (LLM) to bypass all permissions without any safety checks. However, it does not require enterprise developers to supervise the LLM and approve every single permission, making auto mode a balanced setting that is palatable for times when developers are using the LLM for long-running tasks.

Auto mode is another instance of how AI technology is continuously shifting and changing the coding process and role of the enterprise developer. It also shows that the current top value application of AI continues to be coding. While Anthropic’s Claude is considered a strong coding model, the coding opportunity has led other AI vendors, notably OpenAI, to try to demonstrate that their models can code well too. For example, OpenAI highlighted high-level coding skills when it released GPT-5.4 mini and nano last week.

Related:OpenAI Rethinks ChatGPT Shopping Strategy

The Benefit of Auto Mode

In auto mode, specifically, Anthropic has provided another illustration of how humans will become more supervisors of what AI is doing.

“It’s more of a guidance, a shepherding process,” said Bradley Shimmin, an analyst at Futurum Group. 

The feature helps reduce the time enterprise developers spend monitoring the LLM, and it also helps manage costs, said Lian Jye Su, an analyst at Omdia, a division of Informa TechTarget.

“There’s not so much back and forth, which means time can be saved, so a quicker time to market, and cost can be saved as well,” Su said. He added that allowing Claude to run longer without needing to stop to ask for certain permission could mean users have to expend fewer tokens.

Lower Quality Code

Despite the upside of auto mode, it could also lead to “a greater risk of introducing hallucination and running into context degradation and decoherence, wherein the model gets lost and confused and starts doing stuff that you don’t want it to do,” Shimmin said.

It is also possible that giving Claude the option to run for longer without asking for permission could degrade code quality, because the model might have decided on one course of action, but safeguards and permissions already predetermined by the system lead it to another.

Related:Anthropic’s Claude Can Now Take Control of Your Computer

“Risk theory is producing long-term technical debt in the form of perhaps having to maintain code that is not doing what you really expect it to do, or code that is somehow not as performant, dependable, or stable,” Shimmin said. 

Despite the possibility of leading to lower coding quality levels, auto mode will force enterprise developers to evaluate the results, Su said.

“You still need a human in the process of evaluation and verification,” he said. “A human now becomes more of an evaluator and a lot more passive in the active coding process.”

Garlinghouse Reveals Why Ripple Pivoted To Its Own Stablecoin

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Ripple’s decision to launch RLUSD was not a sudden expansion beyond XRP so much as a move to internalize a business it was already helping power at scale. Speaking at FII Priority Miami 2026, Ripple CEO Brad Garlinghouse said the company’s role in stablecoin flows had grown large enough that building its own product became the logical next step.

Why Ripple Entered the Stablecoin Market

Garlinghouse said the turning point came well before RLUSD’s launch 13 months ago. “Two years ago, we were minting 20% of all USDC,” he said, tying that activity directly to Ripple’s payments business. With more than $100 billion in payment flows already processed, Ripple concluded that if it was already a major engine behind stablecoin usage, it made sense to bring that function in-house.

He also linked the decision to a moment of stress in the stablecoin market. Garlinghouse pointed to USDC’s temporary depeg during the Silicon Valley Bank collapse as a reminder that institutional users care about balance-sheet strength as much as blockchain rails.

“Circle came out and said, hey, we’ll stand in the gap. We’ll guarantee the peg. And it didn’t move because at that point, Circle didn’t have a balance sheet,” he said. “Ripple has on our balance sheet, you know, 60, 70 billion dollars of crypto. We have about four billion dollars of US dollars. And so I think we’re in a position to really have a very compliant, very institutional focused stablecoin.”

According to Garlinghouse, stablecoins are increasingly adopted not because companies want exposure to crypto branding, but because they want a better way to solve treasury, settlement and cross-border transfer problems. That broader shift, he argued, is already reshaping how the sector is perceived.

Garlinghouse compared the current state of crypto to the internet industry in the late 1990s, when companies led with the technology rather than the use case. “We don’t talk about anything as an internet company now because it’s just prevalent in the background,” he said. “And I think that’s where some of the blockchain and crypto based solutions are heading”. Companies, he added, “just want to solve a payments problem. They want to solve a custody problem.”

On market structure, Garlinghouse expects the stablecoin field to get more crowded before it gets smaller. He said the biggest banks are already evaluating whether they should issue their own stablecoins, but questioned whether the market benefits from too many dollar-backed instruments that ultimately serve the same economic function. “We don’t need, you know, 50 US dollar stablecoins. Like, why? Like, they’re all, it’s still, at the end of the day, a U.S. dollar,” he said.

That does not mean he sees no room for differentiation. Instead, he argued that trust, licensing and reserve transparency will become the real competitive variables as the market matures. Ripple, he said, has deliberately taken a compliance-first route, pursuing not just a New York Department of Financial Services license but also an OCC license.

He added that the sector as a whole needs more regulatory verification and disclosure, pointing even to Tether’s renewed push for an audit as evidence that transparency is becoming harder to avoid.

Garlinghouse was similarly upbeat on the US policy backdrop. He described passage of the Genius Act as a major unlock for demand and said corporate executives are now actively asking whether stablecoins should be part of their operations. While he said follow-on legislation around asset classification has been slower, he argued the tone in Washington has already shifted sharply, citing recent coordination between the SEC and CFTC and predicting further progress by the end of May.

“So I think we already have made huge progress in this administration to provide some of that structure and Clarity [Act]. I think clarity will still pass. I was in Washington two days ago, and I think we’ll still get something. […] I’ll predict by the end of May we’ll get something across,” Garlinghouse said.

At press time, XRP traded at $1.36.

XRP price chart
XRP drops below the 200-week EMA again, 1-week chart | Source: XRPUSDT on TradingView.com

Featured image from YouTube, chart from TradingView.com

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