Key takeaways:

• Solana perpetual futures funding rates flipped negative, signaling excess demand for bearish positions.
• Rival networks like Base and Hyperliquid pose direct threats to Solana by aggressively capturing DEX market volume.

Solana’s native token SOL (SOL) faced a 15% correction following a rejection at $98 on May 11. A retest of the $83 level on Tuesday was followed by negative futures funding rates, indicating increased demand for short SOL positions. 

While declining network activity contributed to the price drop, competition among rival blockchain networks has picked up. 

SOL perpetual futures annualized funding rate. Source: Laevitas

The SOL perpetual futures funding rate stood at -3% on Tuesday, down considerably from the +8% on Saturday. During neutral market conditions, this indicator hovers near +9% to account for the cost of capital and exchange risk. Demand for bullish leverage has been largely absent since Saturday, when SOL price slipped below $90.

Solana DEX activity has declined by 56% since January

Declining activity on Solana’s decentralized exchanges (DEXs) has reduced ecosystem revenue and demand for SOL. This reduced appetite for decentralized applications (DApps) was not exclusive to Solana, but growing competition poses a major threat, as investors fear that demand for memecoins has faded for good.

Solana weekly DEX volumes, DApps revenue, USD. Source: DefiLlama

Solana DApp revenue stabilized near $20 million per week, down from an average of $35 million in January. This movement closely mirrors the network’s DEX activity trend, which currently stands at $11 billion per week, compared to January’s average of $25 billion. The 30-day DApp revenue leaders on Solana are Pump, Axiom Pro, Phantom, and Jupiter, which command a combined 65% market share.

Blockchain ranked by weekly DApps revenue market share. Source: DefiLlama

Solana remained the top blockchain for DApp revenue despite intensifying competition. Hyperliquid created a direct threat due to its dominance in perpetual contracts, offering a high-throughput solution with core trading features built directly into the consensus layer. Meanwhile, the Ethereum layer-2 network Base offered seamless integration into the Coinbase ecosystem.

In terms of total value locked (TVL), Solana secured second place with $5.9 billion, followed by BNB Chain at $5.5 billion and Base at $4.5 billion. DEX platforms and staking DApps like Jupiter, Kamino, Sanctum, and Raydium lead Solana’s TVL. Still, no blockchain threatens Ethereum’s $43.2 billion TVL, which relies heavily on collateralized lending and liquid staking.

Potential spoofing activity on Solana network DApps

Solana’s footprint in the DApp industry cannot be understated, but the network’s low fees offer a perfect opportunity for maximal extractable value (MEV) botting and inflated activity.

Related: Goldman Sachs exits XRP, Solana ETF exposure in Q1 2026

Source: X/lukecannon727

X user lukecannon727 noted that 1,600 addresses were reportedly responsible for nearly 63% of volumes on PreStocks, a synthetic asset trading platform that runs on the Solana network. According to the analysis, those entities presented balanced trading activity, high execution frequency, and small net losses. These findings are highly consistent with arbitrage activity, but they could also indicate volume spoofing.  

Recent weakness in SOL prices can be partially attributed to the broader decline in DApp demand and increased competition, especially from Hyperliquid and Base. An eventual bull run seems highly dependent on a pickup in DEX activity, particularly in memecoin trading. But, at the same time, there is no indication that SOL should retest the $78 level last seen in early April.

The U.S. Commodity Futures Trading Commission (CFTC) has moved to block Minnesota’s new restriction on prediction markets, filing a lawsuit in the District of Minnesota that challenges Senate File (SF) 4760 as an overreach of state authority. The suit centers on the state’s prohibition of advertising, creating, operating, or otherwise facilitating prediction-market platforms, with a specific focus on event contracts tied to sporting events, military conflicts, and weather—essentially banning platforms such as Kalshi and Polymarket from listing these products within Minnesota’s borders.

In its filing, the CFTC argues that Minnesota’s law conflicts with federal regulation of derivatives and event contracts under the Commodity Exchange Act (CEA), asserting exclusive federal jurisdiction over such products. The agency seeks to block the Minnesota statute on both preliminary and permanent grounds, asserting that Minnesota’s law would criminalize exchanges the CFTC has approved and event contracts that have been self-certified to the Commission. The filing frames the state action as prejudicing the federal government’s ability to enforce federal law.

The Minnesota bill was signed into law by Governor Tim Walz and is slated to take effect on August 1. It amended state statutes to ban the advertising, creation, operation, or facilitation of prediction-market platforms, effectively constraining the listing of event contracts on platforms like Kalshi and Polymarket. The law’s text specifies that event contracts tied to various categories, including sports outcomes and other contingencies, would be treated as wagers under Minnesota law.

The CFTC’s position is that it holds “exclusive jurisdiction” to regulate prediction markets under the CEA, and it argues that Minnesota’s ban would interfere with the federal framework for these products. The agency asked the court to issue both a preliminary injunction and a permanent injunction to prevent the law from taking effect, emphasizing that the state action would undermine the federal government’s enforcement of federal law.

According to Cointelegraph, the CFTC has, in recent episodes, aligned with Kalshi in multiple state-level challenges to prediction-market constraints and has pursued similar actions against authorities in states such as Connecticut, Illinois, New York, and Ohio. The current Minnesota case is presented as the first outright state legislative ban in the United States, contrasting with prior regulatory-focused actions at the state level. The Commission’s stance has been supported by statements from the agency’s leadership, who have signaled that state restrictions on prediction markets would be challenged in court. In response to Minnesota’s move, Kalshi described the law as unenforceable and constitutionally and federally unlawful, while Polymarket did not immediately respond to inquiries for comment.

Key takeaways

• Federal overreach argument: The CFTC asserts exclusive federal jurisdiction over event contracts under the Commodity Exchange Act, challenging Minnesota’s outright ban on prediction-market activities.
• State law and effective date: Minnesota’s SF 4760, signed by the governor, will prohibit advertising, creation, operation, or facilitation of prediction-market platforms when it takes effect on August 1.
• Judicial remedy sought: The CFTC requests both preliminary and permanent injunctions to halt the Minnesota law from taking effect and to prevent enforcement actions against exchanges listing event contracts.
• Affected entities and responses: The suit directly implicates platform operators such as Kalshi and Polymarket; Kalshi has argued the law is unenforceable, while Polymarket has not issued an immediate public statement.
• Broader crypto policy context in Minnesota: Separately, Minnesota enacted a crypto custody services bill for banks and credit unions, set to take effect August 1, and also passed a ban on crypto kiosks and ATMs in a bid to curb scams—reflecting a broader regulatory approach to crypto activity within the state.

Legal framework and the Minnesota challenge

The CFTC’s legal argument rests on the premise that event contracts—for example, contractual bets on sports results or other future contingencies—fall under the purview of regulated derivatives and swaps, which the federal regulator oversees. By labeling Minnesota’s prohibition on listing or facilitating these contracts as incompatible with federal law, the CFTC contends that the state cannot criminalize exchanges that have received federal approval or the contracts that have been self-certified under federal oversight. The complaint emphasizes the risk that Minnesota’s statute would interfere with the federal government’s ability to enforce federal law governing these markets.

State action and institutional implications for markets

Minnesota’s SF 4760 marks a notable instance of state lawmakers choosing to curtail prediction-market activity outright, moving beyond regulatory restrictions or licensing frameworks seen in other jurisdictions. The CFTC’s challenge highlights a core tension in the U.S. market structure: whether state capitals may expand restrictions on a federally regulated derivative product, potentially creating a patchwork of compliance requirements for exchanges that aspire to operate nationwide. This legal dynamic has immediate implications for platform operators seeking to serve multiple states and for banks or custodians that may consider exposure to or integration with these markets.

From an enforcement and compliance perspective, the case underscores several practical considerations for exchanges and financial institutions:

• Licensing and registration: If the CFTC prevails on jurisdictional grounds, platforms may need to reassess multi-state listing strategies and ensure alignment with federal registration requirements to avoid inadvertent violations.
• Compliance program design: Firms must ensure KYC/AML controls, contract disclosures, and listing procedures meet federal standards for traded products and that cross-border or cross-state listings do not create legal exposure.
• Cross-state regulatory risk: The Minnesota action illustrates how state-level action can complicate a platform’s risk and compliance posture, even when federal preemption is invoked, potentially affecting regulatory anticipation and capital planning.
• Operational certainty: The outcome could influence the timing of product launches, self-certifications, and listing decisions, particularly for platforms seeking to operate with broad access across the United States.

Commentary from platform representatives indicates divergent views on the enforceability and legality of Minnesota’s approach. Kalshi described the law as unenforceable and a constitutional overstep, while Polymarket did not immediately provide a public reaction to the lawsuit. The CFTC’s broader stance in related cases—where it has supported Kalshi in other state actions—adds a layer of strategic tension between federal and state authorities over the governance of prediction markets. These dynamics are being tracked not only by market participants but also by compliance and legal teams evaluating the risk landscape for regulated financial products tied to real-world outcomes.

Regulatory context and policy implications

The Minnesota dispute arrives amid ongoing national and global debates about how prediction markets should be treated within financial regulatory frameworks. The CFTC’s aggressive posture toward state restrictions aligns with a broader trend of asserting federal authority over novel derivatives markets, especially those that could intersect with commodities and securities laws. The case also sits within a larger policy dialogue about how such markets should be regulated in light of anti-fraud, consumer protection, and risk-management concerns.

On the international side, policy makers frequently contrast U.S. approaches with evolving European frameworks, such as MiCA, to illustrate different model outcomes for market integrity, licensing, and cross-border service provision. While MiCA governs crypto-asset service providers within the European Union, cases like Minnesota’s SF 4760 serve as a reminder that cross-jurisdictional coherence remains a critical objective for global market participants seeking to minimize legal and operational risk. For U.S. market participants, the current litigation could influence legislative debates about preemption, federal licensing norms, and the boundaries of state intervention in federally regulated product categories.

Overall, the dispute signals potential near-term attention for exchanges, banks, and investors as courts weigh the balance between state policy experimentation and federal regulatory prerogatives. The court’s ruling will have immediate relevance for the status of prediction-market platforms in Minnesota and could set a precedent for similar challenges in other states that may consider restrictive measures or outright bans. Analysts and compliance teams will be watching for how the court addresses the CFTC’s allegations of exclusive jurisdiction and what that implies for the governance of event contracts in a federated regulatory environment.

Looking ahead, the August 1 effective date of Minnesota’s law remains a critical milestone. The court’s decision on the CFTC’s injunction request will shape the practical viability of prediction-market platforms within Minnesota’s borders and illuminate the broader legal framework governing the intersection of federal derivatives regulation and state policy. As enforcement actions unfold, a clearer picture should emerge on how the federal government will enforce preemptive authority in this space and how state legislators might approach similar issues in the future.

As coverage continues, observers should monitor filings for any narrowing of claims, potential settlements, or interim court orders that could affect product listings, platform operations, or custody arrangements tied to prediction-market activities. In the near term, the Minnesota development reinforces the need for robust regulatory reporting, comprehensive compliance controls, and strategic risk assessments for entities operating or considering entry into federally regulated prediction markets.

Source notes: The CFTC’s press materials and related regulatory filings are publicly accessible, and Minnesotan legislative text can be reviewed through the state’s official repository. For context on related rulings and positions, Cointelegraph has reported on the CFTC’s stance in other state actions, including Kalshi-related matters referenced in this coverage.

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.