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Decoding the Upcoming Waves of Innovation in AI

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Decoding the Upcoming Waves of Innovation in AI

Introduction

As we approach 2024, Artificial Intelligence (AI) expectations reach new heights. This year emerges as a pivotal point at the intersection of technology and our daily lives, signifying technological advancements and a fundamental redefinition of our relationship with AI. In this article, we will delve into the key innovations expected in 2024 and how these are shaping a future where AI is not just a tool but a companion redefining our reality.

 

Evolution of AI: From GPT-3 to GPT-4 and Beyond

The journey from GPT-3 to the eagerly awaited arrival of GPT-4 represents more than a mere technical upgrade. It is a revelation that redefines how we interact with AI. GPT-4’s ability to comprehend and generate texts of unprecedented complexity and context immerses us in a new era where AI becomes not just a tool but an intelligent collaborative agent.

The quantum leap in GPT-4’s information processing capability reflects a shift towards deeper coexistence between humans and machines. What once seemed like science fiction is now an everyday reality: engaging in profound and meaningful conversations with a machine. This advancement impacts how we interact with technology and how businesses and industries harness this intelligence to drive innovation.

In this new paradigm, AI ceases to be a mere tool and transforms into a collaborator actively generating ideas, solutions, and content. This transformation not only enhances efficiency but raises fundamental questions about how society approaches the integration of AI into our daily lives. We are crossing the threshold into an era where AI is, more than ever, an intelligent and collaborative companion on our journey toward the future.

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Generative AI and its Transformative Impact:

Generative artificial intelligence is reshaping entire industries, anticipating an unprecedented wave of innovation in 2024. This technology transcends simple chatbots and image generators that amazed and, at times, unsettled in 2023. We are now witnessing the emergence of generative creators for video and music, proving to be increasingly powerful and accessible.

The integration of these capabilities into creative platforms and productivity tools, as seen this year with ChatGPT technology, foreshadows the arrival of fascinating new applications. Generative design tools and voice synthesisers loom on the horizon, and distinguishing between the real and computer-generated becomes an invaluable skill in the arsenal of critical abilities.

 

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Ethical Challenges in the Era of AI

Ethical challenges in this dynamic innovation landscape stand out as a fundamental consideration. With its disruptive potential, artificial intelligence demands responsible development and use to minimise potential negative impacts. Issues such as bias, lack of transparency, and the possible loss of human jobs require constant attention.

The case of Sam Altman, following his departure and quick return to OpenAI, underscores the importance of transparency and responsibility in AI development. In 2024, ethics in AI will take centre stage as a critical area, and the demand for ethical AI specialists is set to grow. Companies are striving to demonstrate compliance with ethical standards and the implementation of appropriate safeguards.

 

AI-Enhanced Applications:

Throughout 2023, there was a rush to incorporate generative AI features into various programs and applications. From search engines like Bing and Google to productivity tools like Office and social platforms like Snapchat, the integration of chatbot features emerges as an effective strategy to enhance the next-generation customer experience. Providers have been cautious due to uncertainties regarding data protection and customer privacy issues. Still, these are expected to be resolved as AI providers adapt their services to meet market needs.

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Low-Code and No-Code Software Engineering:

As predicted by Gartner in 2019, where 65% of application development was expected to be done with low-code/no-code tools by 2024, the trend continues to gain momentum. While traditional programming and software engineering roles may not vanish entirely, the rise of generative AI tools like ChatGPT enables anyone to create and test applications in minutes.

 

 

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Augmented Work through Artificial Intelligence:

Understanding how we can enhance our human capabilities through artificial intelligence to perform our work faster, more efficiently, and safely becomes a crucial skill in the 2024 workplace. From quickly summarising relevant legal precedents for legal professionals to accelerating contract drafting, artificial intelligence becomes an ally. In the medical field, it aids in drafting patient notes and analysing medical images. Programmers use it to streamline software writing and test results. Even students find assistance in organising notes and research, while job seekers can leverage it to craft resumes and cover letters.

 

Quantum AI:

While quantum computing may not immediately impact everyone, its ability to massively speed up specific heavy computational workloads increasingly finds applications in artificial intelligence. Unlike traditional computer bits, Quantum algorithms process data using qubits, which exist in more than one state at a time. This feature makes them much more efficient for problems like optimisation, commonly addressed with machine learning.

In 2024, further advances are expected in applying quantum computing to power increasingly more significant and complex neural networks and algorithms.

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Refinement for the AI Revolution:

While it’s often said that artificial intelligence won’t take away jobs, those using AI may displace those who don’t. In 2024, understanding how AI impacts your work or profession and developing the ability to adapt the right tool to the task is a smart idea. Forward-thinking companies will seek to assist workers in this transition by integrating AI skills into education and training programs. For those whose companies are not taking this initiative, numerous free online resources are available to dive into and enhance job prospects.

 

AI Legislation:

Legislators have historically struggled to keep pace with technology, but the revolutionary nature of AI is starting to catch their attention. In 2024, lawmakers from various jurisdictions, including the European Union, the United States, the United Kingdom, and India, are expected to craft regulations addressing the impact of AI on employment, privacy, and other aspects. This legislative process aims to strike a balance between citizen protection and the promotion of innovation and trade. The debate over where to draw ethical and legal lines will be a prominent theme in political discourse during 2024.

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Conclusion

In the transformative landscape 2024, AI emerges as a dynamic force, evolving from a tool to a collaborative partner. The journey from GPT-3 to GPT-4 marks a profound shift, ushering in ethical considerations, workplace augmentation, and legislative endeavours. As we navigate these waves of innovation, the principles of responsibility and adaptation guide our trajectory into an AI-driven future.

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What’s Happening With Ripple ETFs as XRP Struggles at $1.30?

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Ripple (XRP) ETF Flows. Source: SoSoValue


Here are the possible reasons behind XRP’s daily correction to under $1.35 and what’s next.

The cryptocurrency market is in retreat once again as of the start of the current business week, with BTC dumping to a new local low of under $63,000. Most altcoins have followed suit, and Ripple’s cross-border token is no exception.

The broader ecosystem’s state, in which over $150 billion left the total market cap in 36 hours, is the most apparent reason behind XRP’s 4.5% correction to $1.33. However, there might be another one lurking.

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ETFs See No Action

Data from SoSoValue shows that investors who opt to gain XRP exposure through the spot Ripple ETFs in the US have seemingly disappeared. Half of the trading days last week saw no reportable net inflows, and the streak continued on February 23.

As of now, three of the last five trading days have seen an emphatic “$0.00” next to the total daily net inflow number. Consequently, the cumulative net inflows since the first such product saw the light of day in mid-November have remained flat at $1.23 billion.

The current investor behavior is entirely different than the products’ initial days, in which they surpassed the $1 billion mark in precisely a month.

Ripple (XRP) ETF Flows. Source: SoSoValue
Ripple (XRP) ETF Flows. Source: SoSoValue

XRP Price Down but Not Out

As mentioned above, XRP has declined by over 4.5% in the past 24 hours. It’s also down 8% weekly and a whopping 30% monthly. As such, it currently fights to stay above $1.30, prompting prominent analyst CryptoWZRD to conclude that the asset had, as expected, closed bearish yesterday.

However, they explained that the XRP/BTC trading pair “printed bullish,” and predicted more gains for Ripple’s token against the market leader. This, in turn, would help XRP “turn bullish.”

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Merlijn The Trading said yesterday that the cross-border token was “holding structure while alts bleed.” He outlined the significance of the $1.36 support, but the asset has since broken below it.

Nevertheless, he added that the more macro XRP behavior is different than what people expect, as it’s trading less than a speculative altcoin at this point. In fact, it shows more signs of an infrastructure token as it’s being supported by “real utility narratives.”

“We are talking about payments, tokenization, on-chain settlement rails, and growing real-world activity on XRP.”

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AI agents can’t run wild without on-chain identity

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Chandler Fang

Disclosure: The views and opinions expressed here belong solely to the author and do not represent the views and opinions of crypto.news’ editorial.

While you read this piece, countless AI agents are furiously negotiating contracts, initiating payments, managing treasury functions, and accessing sensitive data. Their remit is expanding from advisory tools to autonomous economic actors at a frenetic pace, yet there is still no standardized way to prove who they are, what they are authorized to do, or who is accountable when something goes wrong. 

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Summary

  • AI agents are becoming economic actors: Autonomous systems are already executing payments, reallocating capital, and managing treasury functions, but lack standardized identity and accountability.
  • The identity gap is a systemic risk: API keys and cloud credentials weren’t built for autonomous decision-makers. Without verifiable onchain identity, trust in AI-driven finance will fracture.
  • Blockchain as the trust layer: Verifiable, programmable agent identity (KYA) could anchor authorization, liability, and auditability — or centralized platforms will fill the void.

As AI agents begin to transact at scale, blockchain-based identity and authorization infrastructure will become a crucial trust layer for the digital economy, not an optional enhancement. This argument may not sit comfortably with everyone, as some folks in crypto argue that decentralized identity has failed to gain traction and that enterprises will default to centralized cloud credentials and private APIs. Others firmly believe AI agents remain experimental and years away from meaningful financial autonomy. 

Both views underestimate how quickly autonomous systems are integrating into enterprise workflows and how unprepared the current infrastructure is to manage the associated risk. Centralized infrastructure is too slow to keep pace with the unprecedented speed of AI adoption, underscoring the crucial need for decentralized infrastructure to bridge the gap.

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AI agents are becoming economic actors

According to Gartner, more than 40% of enterprise workflows will involve autonomous agents in 2026. This near-term projection reflects a shift already visible across fintech, supply chain management, and treasury operations, where AI systems are increasingly authorized to execute transactions rather than merely recommend them. 

As tokenization initiatives expand across global banks and asset managers, AI agents are being positioned to rebalance portfolios, route payments, and optimize liquidity in real time. Consumer behavior signals a similar shift. 

A recent YouGov study found that 42% of US consumers would allow an AI agent to purchase on their behalf if it ensured the lowest price. At the same time, research from Keyfactor shows that 86% of cybersecurity professionals believe autonomous systems should have unique, dynamic digital identities. While demand for AI-powered commerce is accelerating, trust frameworks remain inadequate.

The missing identity and accountability layer

The core problem is not intelligence but verification. As AI agents begin to manage treasury operations, process payroll, or transact on decentralized exchanges, there is still no standardized way to verify an agent’s identity, evaluate its risk profile, or assign accountability if it misallocates funds. Traditional API keys and static credentials were designed for software tools, not for autonomous systems capable of independent decision-making.

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This gap is particularly acute in blockchain environments, where transactions are irreversible and pseudonymous by design. If an AI agent interacts with tokenized assets, executes trades across DeFi protocols, or manages stablecoin flows, counterparties need cryptographic assurance about the agent’s authority and constraints. Blockchain-based identity frameworks, anchored in verifiable credentials and programmable permissions, offer a path forward by allowing agents to prove who issued their mandate, what limits apply, and how liability is structured.

Skeptics may argue that embedding identity into onchain systems risks undermining decentralization or increasing regulatory oversight. Others will contend that centralized identity providers can solve the same problem more efficiently. Yet centralized credentials do not provide the transparency, portability, or composability required for agents operating across multiple blockchains and jurisdictions.

Tokenization and AI demand new infrastructure

As ever, institutional skepticism remains strong. Many executives still treat AI agents as experimental, even as adoption accelerates across payments, treasury, and procurement. The same institutions are aggressively pursuing tokenization of real-world assets, stablecoin settlement rails, and automated compliance systems. The infrastructure supporting tokenized securities and programmable money cannot rely on ad hoc identity models if autonomous agents are expected to manage billions in digital assets.

The convergence of AI and tokenization creates a new market structure in which machine-driven actors may outnumber human traders in certain domains. Without standardized KYA (Know Your Agent) frameworks — verifying an agent’s identity, who it acts for, and what it’s authorized to do — the result will be fragmented trust silos and increased systemic vulnerability. With them, a new class of verifiable, accountable AI agents could transact across decentralized networks with clearly defined permissions and audit trails.

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Looking ahead, payment providers that fail to integrate verifiable AI identity risk being sidelined as autonomous commerce scales. DeFi protocols that embed agent-level permissions and dynamic credentials may attract institutional capital seeking compliance-compatible automation. Conversely, a major failure involving an unverified AI agent could trigger regulatory backlash that slows tokenization and autonomous finance for years.

The debate now confronting the industry is not whether AI agents will transact, but how they will be trusted when they do. Blockchain’s most durable contribution may not be speculative tokens or memecoin cycles, but the ability to anchor machine identity, authorization, and accountability in tamper-resistant infrastructure. As autonomous systems begin executing payments and reallocating capital at machine speed, trust cannot remain an afterthought.

The next phase will test whether code can also carry identity, mandate, and responsibility for non-human actors. If blockchain fails to provide that foundation, centralized platforms will fill the void. If it succeeds, decentralized networks could become the default trust layer for an economy increasingly powered by autonomous agents.

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Chandler Fang

Chandler Fang

Chandler Fang is the co-founder of t54. Prior to t54, Chandler was the Lead Product Manager of Payments at Ripple. Before Ripple, as VP of Product Management, he was in charge of JP Morgan’s Cash Flow Forecasting AI product. He also served as a Venture Partner at FoundersX Ventures, investing in DeepTech and FinTech for close to a decade. Chandler holds an MS in Financial Engineering from UC Berkeley Haas.

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Factors affecting the cost of Web3 game development in 2026

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The overall cost of Web3 game development is rarely about the game itself. It is about the ecosystem behind it. The cost can typically range between $40,000 and $500,000+, depending on complexity, blockchain integration, NFT systems, multiplayer architecture, smart contracts, security requirements, and production quality. A practical Web3 game development cost breakdown is as follows:

  • A simple Web3-enabled game can start around $40,000
  • A competitive mid-scale Web3 game often lands between $150,000 and $300,000
  • Large-scale, multiplayer, token-driven ecosystems frequently exceed $400,000 to $700,000+

However, these numbers are meaningless without understanding what is being built. The cost of Web3 games is usually determined by five structural layers:

  1. Game architecture
  2. Blockchain architecture
  3. Economic design
  4. Infrastructure scalability
  5. Security and compliance depth

Let us now dive deeper into understanding each layer and typically what percentage of cost it involves. 

Detailed Web3 Game Development Cost Breakdown

Let’s break down cost drivers more specifically.

Layer 1: Gameplay & Core Game Architecture (20–30%)

Before blockchain enters the conversation, it is to be kept in mind that you are still building a game. Game development cost varies based on:

  • Engine selection (Unity vs Unreal)
  • Visual fidelity (2D vs stylized 3D vs high-end 3D)
  • Gameplay complexity (casual loop vs real-time multiplayer combat)
  • AI logic systems
  • Cross-platform compatibility

A simple 2D Web3 game may require a small team of:

  • 1–2 game developers
  • 1 designer
  • 1 UI/UX resource

A 3D multiplayer Web3 game may require:

  • Gameplay engineers
  • Network engineers
  • Technical artists
  • Environment artists
  • QA specialists

This is exactly where the cost of Web3 game development tends to jump significantly.

Layer 2: Blockchain Integration Complexity & Smart Contract Development (20–35%)

Web3 is not a plug-in. It changes how data flows. Traditional games store the following on centralized servers:

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  • Inventory
  • Rewards
  • Points
  • Assets

On the other hand, Web3 games must decide:

  • What goes on-chain?
  • What stays off-chain?
  • How frequently transactions occur?
  • Who pays gas fees?
  • How are assets validated?

Every blockchain decision affects:

  • Development time
  • Infrastructure cost
  • Transaction efficiency
  • User experience

Smart contract development alone can range from $20,000 to $80,000, depending on:

  • Token complexity
  • NFT minting rules
  • Staking mechanisms
  • Vesting logic
  • Governance integration

Security audits can add another $15,000 to $60,000, depending on the overall scope of the project. However, many tend to underestimate this layer entirely.

Layer 3: Tokenomics & Economic Engineering (10–20%)

This is where Web3 projects either survive or collapse. Tokenomics design includes:

  • Emission rates
  • Reward balancing
  • Inflation control
  • Sink mechanisms
  • Marketplace fee structure
  • Liquidity strategy

Designing a sustainable economy is not “whitepaper work.” It directly affects:

  • Backend logic
  • Reward distribution
  • Smart contract rules
  • Player retention
  • Long-term viability

Improperly designed token systems destroy ecosystems quickly. Professional economic modeling often adds $10,000 to $40,000 to total project cost. However, skipping it can cost millions later.

Layer 4: Infrastructure & Scalability (15–25%)

Web3 games often operate with a hybrid architecture:

  • On-chain asset ownership
  • Off-chain game logic
  • Cloud-based state management
  • API layers connecting wallet systems

Infrastructure must handle:

  • Concurrent users
  • Real-time gameplay (if multiplayer)
  • Transaction logging
  • Fraud detection
  • Analytics pipelines

Initial backend setup may cost $25,000 to $100,000, depending on the complexity involved. In addition to this, ongoing cloud costs can range from:

  • $3,000/month for moderate usage
    • $15,000+/month for large-scale operations

This is exactly where enterprise-grade projects differ from hobby builds.

Layer 5: Security & Fraud Prevention (10–20%)

Web3 games attract exploit attempts. Attack vectors include:

  • Smart contract vulnerabilities
  • Reward manipulation
  • Wallet exploitation
  • Bot farming
  • Marketplace abuse

Security engineering includes:

  • Smart contract testing
  • Load testing
  • Anti-bot systems
  • Activity anomaly detection
  • Secure wallet session management

Skipping serious security is one of the fastest ways to destroy trust and lose credibility. 

Want the Best Quote for Your Next Web3 Game Development Project?

Web3 Game Development Cost by Project Scale

Tier 1: Web3 MVP (Startup-Level Build)

Estimated Cost: $40,000 – $80,000

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This tier includes:

  • Basic gameplay loop
  • Simple NFT asset structure
  • Wallet integration (MetaMask or similar)
  • Basic smart contract for rewards
  • Limited backend infrastructure
  • Minimal multiplayer support

This build is ideal for:

  • Concept validation
    • Token pre-launch engagement
    • Community building
    • Early-stage Web3 startups

What it does not include:

  • Advanced tokenomics modeling
  • Complex PvP systems
  • Real-time multiplayer scaling
  • In-game marketplace with high liquidity
  • Multi-chain integration

Most early-stage founders fall into this category.

Tier 2: Mid-Scale Web3 Game (Growth Stage)

Estimated Cost: $100,000 – $250,000

At this level, you’re building a scalable product. This includes:

  • Advanced gameplay mechanics
  • NFT minting and trading
  • In-game marketplace
  • Token reward logic
  • Multiplayer features
  • Backend cloud infrastructure
  • Security testing
  • Analytics dashboard
  • Admin control panels

This is suitable for:

  • Venture-backed startups
    • Web3-native gaming studios
    • Token-launch ecosystems
    • Projects targeting 50K+ users

At this stage, blockchain development and backend engineering significantly impact the budget.

Tier 3: Enterprise / AAA Web3 Game

Estimated Cost: $300,000 – $500,000+

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This includes:

  • AAA-level graphics
  • Unreal/Unity advanced rendering
  • Complex multiplayer networking
  • Cross-chain asset compatibility
  • Advanced tokenomics & staking
  • DAO governance integration
  • Fraud prevention systems
  • High-scale backend architecture
  • Full smart contract auditing
  • LiveOps infrastructure

This is not just a game; it’s a Web3 platform. This tier is typical for enterprises or well-funded Web3 projects.

Timeline Correlation with Cost

Web3 game development timelines typically look like:

  • 3–4 months: Basic Web3 MVP
  • 6–9 months: Scalable mid-tier game
  • 9–15 months: Enterprise-grade ecosystem

Shorter timelines require larger teams. Larger teams increase short-term budget burn. Time compression always increases cost.

Ongoing Operational Costs

It is to be always kept in mind that only development is not the final expense. You can expect:

  • Smart contract audit: $10,000 – $50,000
    • Cloud hosting: $2,000 – $15,000 monthly
    • Security monitoring
    • LiveOps management
    • Token economy balancing

Web3 games require continuous maintenance for flawless performance.

Should You Hire Web3 Game Developers In-House or Outsource?

If you try to hire Web3 game developers in-house, it involves:

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  • Higher fixed cost
  • Long hiring cycles
  • Web3 talent scarcity

On the other hand, outsourcing the task to a trusted Web3 game development company often provides:

  • Faster deployment
  • Cross-domain expertise
  • Scalable team allocation
  • Lower operational overhead
  • Reduced recruitment risk

It is exactly the reason as to why many startups as well as enterprises prefer outsourcing.

The Real Risk Behind “Cheap Web3 Game Development”

Cheap Web3 builds usually mean:

  • No smart contract audit
  • Weak backend
  • Poor token balancing
  • Inadequate security
  • Limited scalability

Initial savings often lead to:

  • Token collapse
  • Security breach
  • User churn
  • Rebuild costs

This, in turn, can ultimately lead to doubling total expenditure and hence not recommended.

So How Much Should You Budget?

If you are a:

  • Startup founder
    Minimum realistic serious Web3 game development budget can range between: $75,000 and $150,000.
  • Mid-scale company
    The budget can lie anywhere between $150,000 and $300,000.
  • Enterprise-scale vision
    For enterprise-level game development, where the vision is crafting a sustainable Web3 economy, the budget can range from $300,000 to $700,000+. 

Why Choosing the Right Web3 Game Development Company Matters

Choosing solely based on lowest bid can result in increasing the long-term cost. Antier, a capable Web3 game development company ensures:

  • Secure smart contracts
  • Sustainable tokenomics
  • Scalable infrastructure
  • Audit readiness
  • Optimized gas usage
  • Long-term viability

Ultimately, it is the overall development quality that determines ecosystem survival.

Final Thoughts

If you want to understand how much does it cost to develop a Web3 game, the answer varies dramatically based on ambition and scale. A realistic starting budget can be something around $40,000 for MVP-level builds and can exceed half a million dollars for enterprise-grade ecosystems. The difference lies in:

  • Blockchain architecture
    • Multiplayer complexity
    • NFT systems
    • Security measures
    • Infrastructure scalability

If your goal is long-term sustainability and ecosystem growth, structured engineering investment is non-negotiable. You need to understand that Web3 game development is not simply about adding NFTs or tokens to a game. It is about building:

  • A functioning digital economy
  • A secure blockchain architecture
  • A scalable multiplayer environment
  • A sustainable reward system

The cost reflects the complexity of these systems working together. Working with a reliable Web3 game development company helps you clearly understand where the money goes allows you to invest intelligently instead of underfunding critical layers.

Frequently Asked Questions

01. What is the typical cost range for Web3 game development?

The cost of Web3 game development typically ranges from $40,000 to over $500,000, depending on factors like complexity, blockchain integration, and production quality.

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02. What are the main cost drivers in Web3 game development?

The main cost drivers include game architecture, blockchain integration complexity, economic design, infrastructure scalability, and security and compliance depth.

03. How does the complexity of a Web3 game affect its development cost?

The complexity of a Web3 game affects its development cost significantly, with simple games starting around $40,000, mid-scale games ranging from $150,000 to $300,000, and large-scale games often exceeding $400,000 to $700,000+.

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Russia Reportedly Investigates Telegram CEO Over Facilitating Terror

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Russia Reportedly Investigates Telegram CEO Over Facilitating Terror

Russian authorities have initiated a criminal investigation into Telegram co-founder and CEO Pavel Durov, according to state media reports.

Durov is being investigated in Russia as part of a criminal case involving allegations of facilitation of terrorist activities, official state publication Rossiyskaya Gazeta reported on Tuesday, citing the Federal Security Service (FSB).

Kremlin spokesman Dmitry Peskov reportedly confirmed the investigation, saying the news reports were based on materials from the FSB, which was “carrying out its functions.”

The latest news adds to an ongoing pressure campaign against Telegram in Russia since state media regulator Roskomnadzor tightened messenger restrictions in early February.

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Telegram had not responded to the reports by the time of publication. Cointelegraph contacted Telegram for comment but did not immediately receive a response.

Telegram refuses to cooperate with Russian authorities

The reported investigation builds on Telegram’s refusal to comply with Roskomnadzor’s demands to remove what it said was extremist-linked content.

According to the state-linked Komsomolskaya Pravda, Telegram has not removed almost 155,000 channels, chats and bots flagged for illegal or harmful content locally.

The largest categories include 104,093 channels containing false information, 10,598 promoting extremism, 4,168 justifying extremist activity and 3,771 related to drugs.

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The investigation could lead to the entire platform being labeled as extremist, former Russian presidential internet adviser German Klimenko reportedly warned. He said that could criminalize payments for Telegram Premium subscriptions and advertising on the platform.

Durov accuses Russia of attacking Telegram to promote state-owned messenger

Durov has previously said the pressure is aimed at steering users toward a new state-backed messenger called MAX.

Source: Pavel Durov

He added that other countries, including Iran, have attempted similar strategies and failed. “Despite the ban, most Iranians still use Telegram and prefer it to surveilled apps,” Durov wrote on his Telegram channel on Feb. 10.

“Restricting citizens’ freedom is never the right answer. Telegram stands for freedom of speech and privacy, no matter the pressure,” Durov added.

Related: TON Pay aims to turn Telegram into a crypto checkout layer for TON

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The Russian investigation comes as Durov remains under scrutiny abroad. Durov is also part of an ongoing inquiry in France since his arrest in August 2024.

French authorities lifted Durov’s travel ban in November 2025 after previously saying he could face up to 10 years in prison.

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