Bitcoin miners are increasingly positioning themselves as pivotal players in the AI infrastructure supply chain, leveraging their control of sizable power capacity and data-center real estate to support surging demand for AI workloads. A fresh Bernstein analysis shows publicly traded miners collectively plan more than 27 gigawatts of power capacity and have disclosed AI-related agreements totaling over $90 billion, covering about 3.7 gigawatts with hyperscalers, neocloud providers and chipmakers. The finding adds a new dimension to the industry’s post-halving trajectory, suggesting energy and site access could become the true bottlenecks in scaling AI computing, even as crypto mining undergoes a notable pivot toward AI-focused data centers and high-performance computing facilities.

Meanwhile, a RAND research brief released last week estimates the United States could add roughly 82 gigawatts of net available capacity by 2030, underscoring a broader backdrop of expanding demand for data-center-grade power. Bernstein emphasizes that the real constraint now is electricity access—grid interconnections and approvals can take years, complicating plans to scale AI infrastructure at pace. In practice, the wait times for securing a gigawatt of power can stretch to about 50 months across states, with even growth-friendly jurisdictions such as Texas applying batch-review processes to manage interconnection queues and resource loads. The combination of regulatory scrutiny and local opposition to large-scale data centers further compounds these delays, in Bernstein’s view giving miners an edge due to their existing, grid-connected sites and experience running high-density computing facilities.

With AI demand rising, the report frames Bitcoin miners as potential accelerants for AI infrastructure rather than mere participants in a crypto cycle. The authors note that the bottleneck has shifted from silicon to electricity, a change that could reshape strategies across the crypto and broader tech infrastructure sectors.

The analysis arrives amid a broader narrative that the so-called AI supercycle is not only about chip technology or cloud-scale compute, but also about who can reliably provide the energy and real estate required to run demanding AI workloads at scale. The piece links to prior coverage on how miners are moving beyond traditional Bitcoin production to build data-center ecosystems capable of hosting AI-related infrastructure and computing workloads.

Key takeaways

• Miners control a planned power portfolio exceeding 27 GW and have disclosed more than $90 billion in AI-related agreements covering about 3.7 GW with hyperscalers, neocloud providers and chipmakers, according to Bernstein.
• Access to electricity has become the primary scaling constraint for AI data centers, with grid interconnection queues and permitting delays stretching into multi-year timelines in several states.
• RAND projects a significant growth path for US capacity, estimating around 82 GW of net available capacity could be added by 2030, highlighting a larger macro backdrop for AI infrastructure expansion.
• The regulatory environment and local opposition to large data centers are contributing to delays, reinforcing the advantage for miners already operating grid-connected facilities.
• Miner economics are evolving: after the 2024 halving reduced mining rewards, several players are expanding into AI data centers and high-performance computing, with Soluna Holdings reporting a substantial rise in data-center hosting earnings, while IREN is cited as a prime pivot candidate thanks to Microsoft-backed AI agreements.

AI infrastructure takes the lead, while electricity remains the hurdle

Bernstein’s analysis paints a picture of miner-turned-AI infrastructure players extending beyond their core Bitcoin mining activities. After the 2024 halving compressed mining margins, the sector has increasingly pursued revenue diversification through AI data centers and high-performance computing facilities. The emphasis is shifting from raw hashing power to the ability to secure reliable power and proximity to robust data-center ecosystems—assets that miners already command through long-standing grid connections and experience managing complex, dense computing environments.

The practical implication for investors and builders is clear: the value proposition for miners hinges less on the price of Bitcoin and more on their capacity to unlock and monetize AI-ready energy and real estate. The interconnection bottleneck is no longer a theoretical risk but a real choke point that can slow or derail expansion plans. In this context, utility providers’ approval processes, capacity queues and the pace of grid upgrades become material factors shaping the pace of AI infrastructure deployment. This dynamic helps explain why miners with established infrastructure networks may enjoy a structural advantage as AI workloads proliferate across industries.

Real-world pivots: from mining to AI clouds and data centers

The Bernstein study spotlights concrete examples of diversification beyond traditional crypto mining. Soluna Holdings, for instance, reported a meaningful uptick in first-quarter revenue, driven largely by its data-center hosting business rather than crypto mining. The shift mirrors a broader pattern among miners seeking recurring, sizable revenue streams tied to AI-ready facilities rather than volatile mining rewards alone.

Another prominent example cited by Bernstein is IREN, which is viewed as well-positioned to pivot toward AI infrastructure following multibillion-dollar agreements with Microsoft. The premise is simple: if miners can leverage existing sites and operational expertise to house AI compute and related services, they may unlock new growth channels that complement, or even supplant, traditional mining economics over time.

These moves are not merely opportunistic. They reflect a strategic recalibration in response to both market pressures and regulatory realities. By leveraging grid-connected sites and building AI-capable data centers, miners could become essential partners in AI value chains—providing power, cooling, and space for AI cloud services, while also contributing to the resilience and redundancy of AI compute ecosystems.

For investors, the takeaway is that AI infrastructure demand is not a standalone trend but a potential economic expansion path for miners with the scale and site access to support large, power-intensive deployments. It also underscores a broader market shift: the traditional crypto cycle may increasingly ride on AI-driven demand for compute and data-center capacity, rather than price dynamics alone.

What remains uncertain, however, are the policy and regulatory trajectories across different geographies and how quickly grid operators can modernize the interconnection process. The RAND projection of 82 GW of additional capacity by 2030 provides a bullish backdrop, but the pace at which administrators authorize new connections will be crucial. The coming years could determine whether the mining-to-AI infrastructure pivot achieves its intended scale or encounters persistent friction in the form of permitting delays and local opposition.

Beyond the headline figures, the evolving economic model invites a closer look at how specific players balance energy costs, capital expenditure for data-center facilities, and revenue from AI-related services. The Soluna and IREN cases illustrate how diversified revenue streams—from hosting to cloud-style AI offerings—may become a backbone for miner profitability, particularly as traditional block rewards continue to adjust post-halving cycles.

Additionally, the broader AI hardware supply chain remains a critical factor. As miners court partnerships with hyperscalers, cloud providers and chipmakers, the question becomes not only who can secure the most power but who can integrate seamlessly with AI platforms and meet reliability standards essential for enterprise-grade compute workloads. In this sense, the Bernstein analysis casts miners as potential accelerants for AI infrastructure growth, provided they can navigate energy and regulatory complexities with the same efficiency they apply to data-center management.

In short, the convergence of Bitcoin mining and AI infrastructure signals a meaningful shift in how digital asset infrastructure assets are valued. It points to a future where energy access, site strategy and long-term power commitments may determine which players lead in AI-enabled compute—and which ones struggle to scale in the face of interconnection bottlenecks and policy headwinds.

Readers should watch how grid operators, regulators and utility providers respond to this evolving landscape, as well as how mining firms optimize their asset portfolios to capitalize on growing AI demand while managing the risk profile that comes with long interconnection timelines and the complex economics of data-center deployments.

TLDR

• BlackRock transferred 5,847 Bitcoin worth about $450 million to Coinbase Prime through 20 separate transactions.
• The transfer occurred as Bitcoin prices fluctuated near $77,000 after a recent dip earlier in the week.
• Coinbase Prime serves as the custody and trading platform for BlackRock’s iShares Bitcoin Trust ETF.
• The movement likely reflects ETF operations such as redemptions, rebalancing, or internal fund management.
• IBIT has grown to nearly $63 billion in assets since its launch in January 2024.

BlackRock transferred 5,847 Bitcoin worth about $450 million to Coinbase Prime on Tuesday through multiple transactions. The movement occurred as Bitcoin prices fluctuated near $77,000 after a recent dip. Market data shows institutional activity continues alongside shifting price trends.

BlackRock Shifts Bitcoin to Coinbase Prime Accounts

BlackRock executed 20 separate transactions to move 5,847 Bitcoin into Coinbase Prime custody accounts. The transfers drew attention from traders tracking institutional wallet activity.

Coinbase Prime serves as the custody and trading platform for BlackRock’s iShares Bitcoin Trust, known as IBIT. The platform handles asset storage and transaction processing for institutional clients.

The asset manager uses Coinbase Prime to manage Bitcoin, backing its exchange-traded fund holdings. Therefore, such transfers often relate to fund operations rather than direct market sales.

Market participants observed the timing as Bitcoin hovered near $77,000 after dropping to $76,000 earlier. Price data from CoinGecko confirmed the short-term fluctuation.

Analysts stated that transfers to Coinbase Prime may signal ETF redemptions or internal portfolio adjustments. Others added that operational needs also drive these transactions.

One market analyst said, “Movements like these often reflect fund mechanics rather than immediate selling pressure.” The statement reflects common interpretations of institutional transfers.

IBIT launched in January 2024 after regulatory approval for spot Bitcoin ETFs in the United States. The fund has since grown to nearly $63 billion in assets.

Bitcoin Whale Wallets Rise as Accumulation Continues

Data from Santiment shows wallets holding at least 100 Bitcoin increased to 20,229 over the past year. The figure rose from 18,191 wallets recorded during the same period.

These wallets typically belong to institutional investors, large holders, and high-net-worth individuals. Each wallet holds Bitcoin valued at roughly $7.7 million based on current prices.

The steady rise occurred despite price volatility across the past year. Bitcoin experienced several swings, yet large wallet counts continued to grow.

Santiment reported that the increase represents an 11% rise in whale wallet numbers. The data highlights continued accumulation by larger holders.

Smaller traders showed mixed sentiment during recent market movements. However, large holders maintained consistent accumulation patterns.

A market observer said, “Large wallets tend to expand holdings during uncertain periods.” The comment reflects ongoing accumulation trends.

Bitcoin’s price remained close to $77,000 at the time of reporting. Market data showed recovery following the brief dip earlier in the week.

The Polkadot price prediction is getting attention again as DOT trades near $1.25, which is 97% below its all-time high of $55 and close to the lowest price the token has ever hit.

Polkadot launched Bulletin Chain earlier this month, a new storage system that replaces the central servers most Web3 apps still use.

But even with that upgrade, a 300% move from here only turns $1,000 into $4,000, while a single listing event from a presale entry can deliver that kind of return in one day.

Polkadot Launches Bulletin Chain as DOT Trades Near All-Time Low

Polkadot announced Bulletin Chain on May 4 as a storage layer for Web3 apps that still run on central servers, according to CoinDesk. Developer activity has not turned into real user growth, with total DeFi value locked still below $300 million.

A bridge exploit in April showed a weak spot per Crypto.com. The DOT outlook for 2026 still depends on whether real users follow the builders who are already there.

Where the Biggest Returns Are Being Built Before Exchange Listing

Pepeto Collects $10.08 Million as a Working Protocol Delivers Before Listing Day

The gap between builders and real users on big chains is exactly why presale money keeps going to Pepeto, a project made by a PEPE cofounder that has pulled in more than $10.08 million because the tools work today and not on some future date.

The bridge moves tokens between blockchains so holders save on gas fees, the swap runs trades through the Pepeto official website so money never sits with a third party, and the AI scanner checks contracts before traders go near them, so every tool feeds demand back into one place from the very first trade.

Staking at 172% APY grows the value of every token bought at $0.0000001871 before any exchange opens, and because SolidProof ran the full audit and all 420 trillion tokens are locked at launch with nothing new added after, the free float keeps dropping with each holder who stakes.

A Binance listing is expected when presale funding fills up, and that is the moment where a fixed supply meets exchange volume for the first time.

The Pepeto site shows the product running right now, and that proof is why Pepeto keeps pulling in wallets faster every week while large caps like DOT sit 97% below their highs waiting for a recovery that could take years.

Polkadot Price Prediction Targets Through 2026 and 2027

Polkadot trades at $1.25 with a market cap around $2.12 billion according to CoinMarketCap, ranked 43rd. Analysts see a possible 2026 high of $5.29 according to PricePrediction, while Changelly sees $1.89 by December.

The 2027 range goes from $1.01 to $2.35. A $1,000 buy at $1.25 growing to $5.29 returns about $3,266, strong for a large cap but still a fraction of what a presale entry before listing day can bring in one session.

Conclusion

The entry in Pepeto today at $0.0000001871 will not be here next week, because every person who made real money in crypto made one choice that set them apart from everyone else, and that choice was to act before the listing instead of planning to come back later.

The Polkadot price prediction may show DOT climbing from $1.25 toward $5 over many months, and that would be a good gain, but the wallets that changed lives in every cycle found presale entries where one listing event turned years of waiting into one price move.

The presale already passed $10.08 million, the staking pool at 172% APY grows every day, and a PEPE cofounder running the project with a Binance listing on the way is what makes this different from everything else in the market.

The presale ends when the listing opens, and every day of waiting is one day less to get in at this price. Missing this by one day could be the gap between collecting the listing gain and reading about the wallets that did.

Click To Visit Pepeto Website To Enter The Presale

FAQs

What is the Polkadot price prediction for 2026?

The Polkadot price prediction for 2026 shows DOT could reach $5.29 at the top, while Changelly sees $1.89 by December. DOT trades at $1.25, down 97% from its $55 high.

What is the best presale to buy alongside the Polkadot price prediction?

The best presale to buy is Pepeto because it can deliver from one listing event what DOT at $1.25 would take years to match, with $10.08 million raised and a Binance listing on the way.

Disclaimer: This is a Press Release provided by a third party who is responsible for the content. Please conduct your own research before taking any action based on the content.

TLDR

• Google introduced a redesigned Search experience powered by Gemini 3.5 Flash at I O 2026.
• The new interface supports longer and more conversational user queries instead of short keywords.
• Google added an AI-powered autocomplete that suggests refined and follow-up questions in real time.
• AI Overviews now appear more consistently and provide summarized answers at the top of results.
• Users can move between AI summaries and chatbot-style interactions without leaving the search page.

Google introduced a redesigned Search platform powered by Gemini 3.5 Flash at I/O 2026. The update blends traditional search with AI-generated responses and conversational features. The company confirmed that the rollout aims to shift user behavior toward natural language queries.

Google presented the updated interface as part of its broader Gemini strategy across products and Android systems. The company emphasized faster responses and improved context handling through the new model. Robby Stein said users will “reliably” see AI Overviews for conversational queries.

Google Expands Conversational Search and AI Summaries

Google redesigned the search box to support longer and more detailed user queries. The interface now encourages full questions instead of short keyword searches. As a result, users can ask complex queries like protocol explanations and receive structured answers.

The company also introduced AI-powered autocomplete that suggests refined questions in real time. This system builds on user intent and offers follow-up prompts during typing. Google stated that this feature helps guide users toward more complete and relevant searches.

AI Overviews remain central to the new experience and appear at the top of results pages. These summaries compile information from multiple sources into a single response. Stein explained that the system connects directly to AI Mode for extended conversations.

Users can now transition between summaries and chatbot interactions without leaving the search page. This integration allows continuous dialogue powered by Gemini 3.5 Flash. Google positioned the model as faster and more efficient than earlier versions.

Gemini Model Powers Deeper Integration Across Devices

Google confirmed that Gemini 3.5 Flash supports both cloud and on-device processing. Some AI tasks will now run locally on Android devices. This approach reduces latency and improves performance for certain features.

The company linked this update to its broader Gemini Intelligence initiative. It aims to embed AI capabilities across mobile ecosystems and services. Google also highlighted ongoing work on open models for developers.

The search redesign aligns with Google’s focus on unified AI experiences across platforms. The company plans to expand these capabilities in future updates. Current deployments began following the I/O announcement.

Google did not disclose exact rollout timelines for all regions. However, it confirmed gradual availability across devices and markets. The company continues to test features through limited releases.

Changes in Search Structure Affect Information Visibility

Google confirmed that AI Overviews synthesize content from multiple indexed sources. The system selects key data points and presents a summarized response. This process reduces reliance on traditional link-based navigation.

The company acknowledged that users may interact less with individual websites. AI-generated answers often provide direct responses without requiring clicks. Google did not provide specific metrics on traffic changes.

Platforms that provide structured data may still contribute to AI summaries. However, their visibility depends on how Gemini selects information. Google continues refining its ranking and synthesis systems.