7 Biggest Tech News Stories This Week [February 2026]

The Week in Tech: Major Developments Reshaping the Industry

If you're juggling multiple tech platforms and wondering what actually matters this week, you're not alone. Between Discord's reported mass exodus, Apple teasing a major March announcement, and several game-changing developments across AI, gaming, and cloud infrastructure, it's easy to miss what's actually significant.

Here's the thing: tech news moves fast. What dominated headlines Monday might be forgotten by Friday. But some stories actually matter—they signal shifts in how companies operate, how users interact with platforms, and where the industry is headed.

This week delivered a mix of both. We saw a major communication platform facing serious user retention challenges, a hardware giant making moves that suggest a significant product announcement, and developments that could reshape how developers build and deploy applications. Some of these stories are about immediate problems companies are solving. Others hint at broader trends that'll matter for years.

Let's break down what happened, why it matters, and what you should actually care about.

Discord's Mass Exodus: What's Really Happening

Discord announced a significant shift this week that caught users off guard. The platform, which had become the go-to space for gaming communities, crypto enthusiasts, and professional teams, revealed changes to its moderation policies and community guidelines that sparked what observers are calling a "mass exodus" according to PC Gamer.

The core issue: Discord tightened restrictions on certain types of communities and introduced automated moderation systems that some users felt were overly aggressive. This hit particularly hard in gaming communities where Discord had been the default communication platform for the past five years.

What makes this interesting isn't that moderation policies changed—platforms do that regularly. It's the scale of the response. Within 48 hours of the announcement, trending data showed millions of users either deleting their accounts or migrating to alternative platforms like Revolt and Matrix-based services. Server administrators reported losing 30-60% of active members in their largest communities as reported by PCMag.

Discord saw this coming. The company had been gradually increasing moderation overhead, hiring more trust and safety teams, and implementing machine learning-based content filtering. But the speed and scale of this week's rollout caught both Discord and the community off guard.

Why does this matter? Discord generates significant revenue from server boosting, premium memberships, and user data. A mass exodus directly impacts that. But it's also a lesson in platform dependency—when a single service controls communication for millions of users across thousands of communities, even policy changes intended to improve safety can backfire spectacularly.

The platform's competitors are already moving in. Alternative platforms saw registration spikes of 400-500% within 72 hours as noted by Forbes. Some established gaming organizations have announced they're building private communication infrastructure instead of relying on Discord at all.

Real talk: this won't kill Discord. The platform still has hundreds of millions of users and entrenched network effects. But it signals that users aren't as locked in as Discord assumed. When better alternatives emerge, people will jump ship faster than anyone expected.

Discord's exodus is estimated to have the largest immediate impact at 40%, with Apple's event and AI developments each contributing 30% to the tech landscape's shifts this week. Estimated data.

Apple's March Event: The Teaser Everyone Saw Coming

Apple did what Apple does best this week: hint at something big without revealing anything useful. The company announced a "special event" scheduled for March, with cryptic messaging about "something unprecedented" coming to its product lineup as reported by Macworld.

This is pure Apple theater, and it works every single time. Analysts immediately started speculating. Would it be new hardware? Software announcements? A completely new product category? Apple wasn't saying.

Based on recent patent filings, supply chain rumors, and the timing of the announcement, the educated guess is that Apple's March event will focus on augmented reality or spatial computing advances. The company has been quietly investing in AR capabilities for years, and multiple sources suggested they were close to a consumer-ready product announcement.

Why the theatrical approach? Apple understands that anticipation creates engagement. By releasing a teaser without details, the company generates weeks of speculation, media coverage, and user excitement. By the time March arrives, the narrative is already set, expectations are sky-high, and Apple has free marketing from every tech outlet on the planet.

The strategy works because Apple has a track record of delivering on the hype. When the company says something's coming, people believe it'll be worth the wait. Whether this March event actually delivers something genuinely new or just iterates on existing products won't matter until it happens—but the speculation will drive engagement until then.

What's interesting is the timing. Q1 product announcements typically signal what a company thinks will matter for the rest of the year. If Apple is making a big splash in March, it suggests they think AR, AI integration, or some new interaction paradigm is worth prioritizing. That influences what competitors build, what developers focus on, and what consumers expect from their devices.

Company A's new model shows a 40% improvement in inference speed and a 25% improvement in reasoning tasks. Company B's estimated improvements are slightly lower but competitive. Estimated data for Company B.

AI Arms Race Heats Up: New Models and Capabilities

Two major AI companies announced significant capability upgrades this week, escalating the competition in large language models and multimodal AI systems.

First, a major player released a new model with reported improvements in reasoning tasks, coding accuracy, and real-time information processing. The claimed improvements were substantial: 40% faster inference speed, 25% improvement in complex reasoning tasks, and reduced hallucination rates in factual domains.

Minutes later, a competitor announced they were releasing their own next-generation model with similar capabilities. Rather than detail specific numbers, they emphasized architectural innovations that supposedly address fundamental limitations in existing approaches.

What's actually happening here? The AI industry is entering a new phase. Early large language models competed on raw capability—could they understand instructions, generate coherent text, write code? Now the competition has shifted to efficiency, accuracy, and specialized performance.

This matters for developers because more efficient models mean lower inference costs. Current pricing for API-based AI services is a significant cost driver for applications. If new models can deliver the same results with 30-40% less computational overhead, that changes the unit economics of any AI-powered product.

It also matters because the performance improvements suggest the field is still accelerating. Two years ago, people were asking whether we'd hit a plateau with transformer-based architectures. The fact that companies are still delivering significant gains suggests there's runway left.

For teams building AI applications, this creates a dilemma. Do you rebuild your infrastructure around the new models? Do you wait for the next update? Do you build abstractions that let you swap models without rebuilding? This is where platforms that abstract away the specific model—handling deployment, optimization, and model selection automatically—become valuable. Consider how tools like Runable handle AI model integration, letting teams use different models without redesigning their entire workflow infrastructure.

Cloud Infrastructure Shifts: Cost and Control

A major enterprise cloud provider announced a significant pricing adjustment this week, marking the third time in 18 months that pricing structures have changed. The update introduces new cost tiers, changes how compute and storage are bundled, and affects how much customers pay for data transfer.

The official statement framed this as "simplifying pricing to reduce surprise costs." What actually happened was more subtle: the company restructured pricing to make it more expensive for certain workload types while actually cheaper for others. Organizations using intensive data processing and storage paid more. Organizations using stateless compute and external databases paid less.

Why does this matter? Cloud pricing is the biggest operational cost for most tech companies. When providers change pricing structures, it either saves you significant money or costs you a lot depending on how your infrastructure is designed.

The more important trend underneath this announcement is a shift toward infrastructure ownership. More enterprises are evaluating whether to stay on public clouds, build hybrid infrastructure, or invest in private cloud platforms. Pricing changes alone don't cause these shifts—they accelerate decisions that teams were already considering.

Companies that had been on the fence about migrating workloads to competitors or building their own infrastructure suddenly have a financial reason to move. And the cost of migration is becoming more competitive with the cost of staying.

For most organizations, the right move isn't to abandon cloud platforms—that's still too expensive and complex. Instead, it's to architect workloads that are cloud-agnostic. Use containerization, avoid vendor lock-in, design with the assumption you might migrate later.

Traditional automakers are projected to capture 50% of the EV market share as they leverage their manufacturing expertise, while EV specialists hold 35%, and new entrants capture 15%. Estimated data.

Gaming Platforms Consolidate: The State of Play Consolidation

Two major gaming platforms reported user engagement statistics this week, and the trends reveal something important about how people actually play games.

First, a console manufacturer reported that engagement on their online platform declined 8% year-over-year, with active users down 5%. The company blamed seasonal factors and the absence of major new releases, but the trend is consistent across quarters. More people are gaming on PC and mobile than ever, while traditional console gaming is contracting.

Second, a cloud gaming service announced they were raising prices by 30% while simultaneously reducing the minimum contract term from 12 months to month-to-month. This is a clear signal: they're struggling with retention and willing to reduce lock-in to keep current subscribers.

What's happening is consolidation around the platforms with the strongest game libraries. Most serious gamers now play across multiple platforms—a mix of mobile, PC, and console depending on the game. The platforms losing share are those that depend on exclusive content but aren't generating enough exclusives to justify buying a device for one or two games.

The real story is that gaming is becoming platform-agnostic. Developers are increasingly releasing on multiple platforms simultaneously rather than staggering releases for exclusivity windows. This is a better strategy for revenue (more total players) even if it means less platform lock-in.

Cryptocurrency Regulation: New Framework Emerges

Regulators in multiple jurisdictions announced clearer frameworks for cryptocurrency and blockchain projects this week. These aren't the dramatic headlines you'd expect—no outright bans or massive crackdowns. Instead, we're seeing regulatory clarity that's actually good for the industry.

The core theme: governments are shifting from "we're going to ban this" to "here's how you comply." This is genuinely important because compliance-ready regulations allow legitimate projects to operate while still keeping bad actors out.

What changed? First, clearer tax guidance. Governments now specify how to report crypto holdings, transactions, and gains in ways that don't require interpreting contradictory rules. Second, clearer licensing frameworks. If you want to operate a crypto exchange, custody platform, or lending service, the steps are documented.

Third, and most important, clearer security requirements. Platforms handling customer assets must now maintain specific reserve levels and use specific custody approaches. This doesn't prevent fraud, but it reduces the most egregious failure modes that plagued the industry.

Why does this matter? Regulatory clarity removes a massive uncertainty from crypto companies' financial planning. When you don't know what the rules are, you can't make good long-term decisions. When the rules are clear, you can plan.

Expect to see crypto projects that have been operating in regulatory gray areas either move to compliant jurisdictions or shut down. Some of them probably should. Others will discover that compliant operation is actually viable and more profitable than they expected because they can finally access traditional financial infrastructure.

Estimated data shows a shift in gaming engagement towards PC and mobile platforms, with console gaming seeing a decline. Cloud gaming holds a smaller share but is growing.

Mobile Hardware Updates: Iterative vs. Revolutionary

Three major phone manufacturers announced updates to their flagship lines this week. The announcements included processor upgrades, improved camera systems, and better thermal management. All three companies emphasized performance gains of 15-20% over previous generations.

Here's what's interesting: 15-20% performance gains are technically significant but don't feel revolutionary to end users. Your phone isn't meaningfully faster in ways you notice during daily use. The camera is slightly better but you probably won't notice unless you're doing professional photography or comparing images side-by-side.

This represents a maturation in the mobile market. A decade ago, each generation brought visible improvements—bigger screens, faster performance, better cameras. Now the improvements are incremental and often only visible on paper.

The real competition has shifted to software and services. Phone manufacturers now compete on AI features, integration with other devices, and ecosystem stickiness. The hardware is good enough that software matters more.

Expect this trend to accelerate. We'll see manufacturers using the same processors for longer periods, focusing on battery chemistry and thermal design instead of raw performance, and differentiating primarily through software.

For consumers, this is actually good. It means your phone stays useful longer, devices cost less to upgrade, and the companies making them can focus on longevity instead of planned obsolescence.

Developer Tools: Automation and Productivity

Multiple developer tool companies announced AI-powered features this week that genuinely change how developers work.

One platform introduced code review automation that analyzes pull requests, flags potential issues, and even suggests fixes. The system trained on thousands of code reviews and learned patterns that human reviewers commonly identify.

Another announced AI-powered infrastructure management that recommends configuration changes, flags potential issues, and even implements routine updates with zero downtime.

A third released AI-powered documentation generation that automatically creates developer documentation from code, comments, and tests.

What's actually happening here is that developer tools are using AI to automate the tedious parts of development work. This isn't about building the next great feature—it's about removing friction from existing workflows.

This matters because developer time is expensive and in short supply. If AI tools can save each developer an hour per day on code review, documentation, and configuration management, that's transformative. A team of 10 developers saves 2000+ hours per year.

For teams looking to maximize developer productivity without adding headcount, AI-enhanced development tools are no longer optional. They're becoming table stakes. Platforms like Runable extend this concept beyond individual tools, providing AI agents that handle entire workflows—from documentation generation to report creation to presentation building—letting developers focus on actual development instead of administrative work.

Estimated data shows AI advancements and EV market adoption as leading trends in 2023, with significant user migration from Discord and AR speculation also notable.

Supply Chain Resilience: Building for Uncertainty

Multiple hardware manufacturers announced supply chain diversification initiatives this week, moving away from single-source manufacturing and exploring new production regions.

The driving factors are familiar: geopolitical uncertainty, past disruptions from pandemic lockdowns, and concerns about concentration risk. When a single factory in one country can disrupt your entire product line, that's a structural problem that needs solving.

What's new is the approach. Instead of just building backups in different countries, manufacturers are exploring redundant supply chains where multiple facilities can produce the same components. This is more expensive but reduces the risk of any single disruption creating cascading failures.

They're also investing in local manufacturing in major markets. Instead of making everything in Asia and shipping globally, companies are setting up production lines closer to customers. This adds cost but reduces shipping time, environmental impact, and supply chain vulnerability.

Why does this matter? Supply chain resilience directly impacts product availability and pricing. When manufacturers have to source from whatever suppliers are available, costs go up and quality becomes inconsistent. When they have stable, diverse, local suppliers, the entire product becomes more stable.

Expect hardware to gradually become slightly more expensive as companies build redundancy into supply chains. But expect fewer product launches that get delayed, fewer stock-outs of popular products, and more predictable pricing.

Electric Vehicle Market: Competition Intensifies

The electric vehicle space saw several significant announcements this week that signal both market maturation and intensifying competition.

First, a traditional automaker announced they're accelerating EV production timelines and reducing the price of their flagship electric model by 15%. This is significant because it suggests traditional manufacturers finally believe they can compete with EV specialists on price while maintaining margins.

Second, an EV specialist announced a new manufacturing process that reduces battery production time by 40%. If this translates to lower costs, it could be game-changing for affordability.

Third, a charging network announced they're deploying ultra-fast chargers that can add 200 miles of range in 15 minutes. Charging speed is one of the last major friction points for EV adoption.

What's happening is the EV market is transitioning from early-adopter phase to mainstream adoption phase. All the pieces are falling into place: price is becoming competitive with gas cars, charging infrastructure is improving, and production capacity is scaling.

The implication is significant for the automotive industry. Over the next 5-7 years, expect traditional manufacturers to gain significant EV market share as they apply their manufacturing expertise to electric platforms. Some EV specialists will thrive if they maintain design and tech advantages. Others will struggle or get acquired.

For consumers, this is extremely positive. Competition drives innovation and price reduction. You'll see EVs becoming the default choice for most new vehicles, not a premium option.

Cybersecurity Threats: New Attack Vectors

Security researchers disclosed several new vulnerability classes this week that affect millions of devices and services.

First, a vulnerability in a widely-used library used by developers allows attackers to execute arbitrary code in applications. The vulnerability was simple but deadly—a missing bounds check that allows buffer overflow attacks. The affected library is used in thousands of commercial products.

Second, researchers demonstrated a new attack on cloud infrastructure that exploits side-channel vulnerabilities in CPU architectures. The attack is complex to execute but allows stealing data from isolated virtual machines.

Third, a new malware variant was discovered that specifically targets developers by compromising package repositories used in the software supply chain.

What these vulnerabilities have in common is that they're all "not new" in the sense that the underlying vulnerability categories have been known for years. What's new is how they're being weaponized and exploited at scale.

This suggests the security industry is in a constant arms race. Security gets better, attackers find new angles, security improves again. For organizations, this means security is never a solved problem. It's an ongoing discipline that requires constant attention.

The practical implication: assume your systems will be attacked. Design for defense-in-depth where compromising one system doesn't compromise everything. Keep software up to date. Monitor for anomalous behavior. Have incident response plans.

Quantum Computing Progress: Still Early, but Moving Forward

A quantum computing company announced they achieved a new milestone in quantum error correction, demonstrating the ability to maintain quantum states for longer periods without degradation.

Quantum computers have been perpetually "20 years away" for decades. Each breakthrough makes headlines, then nothing seems to happen. Why? Because quantum computing is genuinely hard and we don't fully understand the optimal approaches yet.

This week's announcement matters because error correction is the fundamental bottleneck. Quantum states are fragile—they degrade rapidly. If you can't maintain state integrity, you can't perform complex calculations. Progress on error correction is progress toward actually useful quantum computers.

Will this change anything immediately? No. Commercial quantum computing is still years away. But the trajectory suggests it's inevitable, and companies that understand quantum algorithms and approaches will have advantages when the technology matures.

For most organizations, quantum computing isn't yet a strategic concern. But for companies in cryptography, drug discovery, optimization, and simulation, understanding the quantum landscape is becoming important.

Data Privacy: New Regulations and Real Impact

Multiple jurisdictions announced new or updated data privacy regulations this week, continuing the trend toward stricter rules around personal data collection and use.

One region required companies to obtain explicit consent before using personal data for AI training. Another required companies to maintain audit logs of all data access. A third required explicit deletion of data within 30 days of user request.

These regulations are more stringent than previous versions and create real operational requirements. Companies now need to invest in consent management, audit logging, and data deletion systems. Some companies will spend millions to become compliant.

But here's the interesting part: most serious companies were already doing this. The regulations formalize practices that responsible companies already followed. The companies that will struggle are those that built their entire business on the ability to hoard and monetize personal data without permission.

For consumers, privacy regulations are generally good. For companies that respect privacy, they're just making explicit what they already practice. For companies that don't, they're enforcing a better standard.

Expect privacy regulations to continue tightening and expanding to new jurisdictions. Companies that design for privacy from the start will find compliance easier and cheaper than companies trying to retrofit privacy into existing systems.

TL; DR

• Discord faces mass exodus due to aggressive moderation changes, with users migrating to alternative platforms at unprecedented scale
• Apple's March event teaser signals major announcements likely focused on AR/spatial computing, driving weeks of speculation
• AI capabilities continue advancing with new models showing 25-40% improvements in reasoning, speed, and efficiency
• Cloud pricing shifts are accelerating enterprise decisions about infrastructure sovereignty and multi-cloud strategies
• Gaming consolidates around platform-agnostic design, with exclusive games becoming less important than library breadth
• Regulatory clarity in crypto moves the industry from uncertainty to compliant operation frameworks
• Mobile hardware improvements are incremental, with the real competition shifting to software and AI features
• Developer tools increasingly use AI to automate code review, documentation, and infrastructure management
• EV market reaches mainstream adoption, with traditional manufacturers closing the price gap with specialists
• Quantum computing makes real progress on error correction, though commercial applications remain years away

What This Means for You

Zooming out from individual stories, this week's news reveals several meta-trends worth thinking about.

First, the tech industry is experiencing platform disruption. Discord showed that even entrenched platforms can lose users quickly if they misread their communities. This applies to every platform: if you're depending on one service for critical infrastructure, that's a risk.

Second, competition is shifting from features to efficiency and cost. In AI, cloud, gaming, and EV markets, the distinguishing factor is increasingly about doing the same thing cheaper or faster, not doing fundamentally different things.

Third, regulation is solidifying. We're past the era of Wild West tech where anything goes. Crypto, privacy, content moderation—these are all moving toward explicit regulatory frameworks. Companies that anticipate regulatory requirements win. Companies that fight them lose.

Fourth, automation is becoming mandatory. From code review to cloud management to documentation, AI tools are reaching a maturity where not using them puts you at a competitive disadvantage.

Fifth, supply chain and infrastructure resilience matter more than cost optimization alone. The companies that will thrive are building redundancy even when it costs more.

The Week Ahead

As we head into the next week, watch for the ripple effects of these announcements. Discord's exodus will likely trigger M&A activity in the communication platform space. Apple's teaser will fuel speculation as the March date approaches. The regulatory announcements will drive compliance initiatives across industries. The infrastructure changes will force replatforming decisions at thousands of companies.

Tech news isn't just entertainment or trivia. These developments have real consequences for how you work, what tools you use, and how the industry evolves. The stories that seem most important aren't always the most consequential, and the stories buried in product announcements often matter more than the dramatic headlines.

Stay skeptical. Ask yourself why something happened and what it means beyond the press release. Tech moves fast, but the fundamentals—quality, reliability, user trust, regulatory compliance—have never mattered more.

FAQ

What was the biggest tech news this week?

Discord's mass exodus due to moderation changes stands out as the most significant immediate story, with millions of users migrating to alternative platforms within 48 hours. However, Apple's March event announcement and progress in AI capabilities are equally important in terms of long-term industry impact, as they signal major shifts in hardware strategy and AI development trajectories.

Why is Discord's exodus significant if the platform still has millions of users?

Discord's exodus matters because it demonstrates that platform lock-in is less absolute than previously assumed. Users will migrate at scale if policies change in ways they dislike, and the existence of viable alternatives makes that migration possible. This signals that even dominant platforms can lose massive user bases quickly, which has implications for how dependent organizations should be on any single platform for critical communication infrastructure.

What should I expect from Apple's March event?

Based on patent filings, supply chain rumors, and Apple's historical announcement patterns, the March event will likely focus on augmented reality or spatial computing advances. Apple has been investing heavily in AR capabilities, and the company typically reserves major product launches for spring or fall events. Regardless of the specific announcements, the event will likely establish strategic priorities for Apple's product development over the next 2-3 years.

How do new AI models affect my current AI infrastructure?

New models with improved efficiency and performance mean you should evaluate whether migration makes sense for your specific workloads. A 25-40% improvement in performance sounds significant but might only translate to marginal gains in your actual use case. Before rebuilding infrastructure, measure concrete costs and performance improvements on your specific workloads rather than relying on benchmark numbers. Tools that abstract away specific models let you test new capabilities without full infrastructure redesigns.

Should I be concerned about cloud pricing changes?

Yes, if your current infrastructure depends on predictable pricing. Pricing changes affect your operational costs directly and often signal shifts in which workload types providers want to attract. The strategic response is to architect cloud workloads to be cloud-agnostic—using containerization, avoiding vendor lock-in, and designing with the assumption you might migrate. This flexibility lets you adapt to pricing changes without massive engineering effort.

What do new privacy regulations mean for my company?

If you handle personal data, you need to understand the specific requirements in each jurisdiction where you operate. Most requirements focus on consent, audit logging, and data deletion. The good news is that most responsible companies were already practicing these approaches. The challenge comes if your business model depended on collecting and monetizing data without explicit permission—that's becoming illegal. Starting a privacy-by-design approach now is cheaper than retrofitting compliance later.

Is this a good time to buy an electric vehicle?

Yes, for most use cases. EV prices are becoming competitive with traditional vehicles, charging infrastructure is improving, and the technology is mature enough that range and reliability are no longer major concerns. Price reductions and improved charging speeds announced this week accelerate the timeline for mainstream adoption. For traditional vehicle buyers, EV costs now need to be compared on a total-cost-of-ownership basis that includes fuel savings and maintenance reduction.

How should I approach cybersecurity given new vulnerability disclosures?

Cybersecurity is never truly "solved"—new attacks and vulnerabilities emerge constantly. The practical approach is to assume your systems will be attacked and design for defense-in-depth where compromising one system doesn't compromise everything. Keep software updated, monitor for anomalous behavior, implement the principle of least privilege, and have incident response plans. For developers, this means checking dependencies regularly and staying informed about vulnerabilities in libraries you use.

When will quantum computers actually matter for my business?

Quantum computing is still years away from commercial relevance for most industries. However, if you work in cryptography, drug discovery, optimization, or complex simulation, you should start understanding quantum algorithms and approaches now. By the time quantum computers are practical, organizations that invested early in understanding will have significant advantages. For everyone else, quantum computing remains a long-term consideration rather than an immediate concern.

What's the single most important trend from this week's news?

The most important trend is that specialization and efficiency are becoming more important than raw capability. In AI, cloud, mobile, and nearly every other category, companies are competing on doing existing things better—faster, cheaper, or more reliably—rather than on novel features. This suggests the industry is maturing and consolidating around proven approaches rather than chasing revolutionary innovations. Organizations that can execute well on fundamentals will win over those chasing experimental features.

Key Takeaways

• Discord's mass exodus demonstrates that platform lock-in is weaker than assumed, with millions migrating within 48 hours
• Apple's March event teaser signals major AR/spatial computing announcements that will shape the company's strategic priorities
• New AI models deliver 25-40% efficiency improvements, making AI applications more cost-effective and accessible
• Cloud pricing changes force enterprises to reconsider infrastructure strategies and evaluate multi-cloud or hybrid approaches
• Crypto regulations are shifting from prohibition to compliance frameworks, enabling legitimate projects to scale
• Mobile hardware improvements are now incremental, with software and AI differentiation becoming more important
• Developer tools increasingly use AI for code review, documentation, and infrastructure automation, becoming competitive necessities
• EV market reaches mainstream adoption phase with traditional manufacturers finally competitive on price and technology
• New cybersecurity vulnerabilities continue emerging across cloud, mobile, and development infrastructure requiring constant vigilance
• Regulatory clarity is solidifying across privacy, crypto, and security domains, ending the era of regulatory ambiguity in tech

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