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Editor's Pick

Why Social Media Bans for Kids Are Turning Into a Global Policy Wave

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  For a long time, the politics of child safety online stayed comfortably vague. Governments issued warnings, schools promoted media literacy, and platforms promised better tools. But the underlying assumption remained the same: parents were supposed to manage the problem at home. That assumption is now breaking. On April 9, 2026, Greece unveiled plans for a total social media ban for children 15 and under, with enforcement aimed at the platforms themselves. According to AP, the proposal would require companies to reverify users’ ages and could expose them to penalties that reach as high as 6% of global turnover for noncompliance. A month earlier, on March 6, 2026, Indonesia said it would ban social media accounts for children under 16 on high-risk platforms including YouTube, TikTok, Instagram, Facebook, Threads, X, Roblox, and others, with implementation beginning on March 28. The important shift is not just that more countries are restricting minors’ access. It is that regulator...
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GitHub's VS Code BYOK move matters more than it looks

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Bring-your-own-key support can look like a small settings change until you view it through procurement, governance, and model volatility. GitHub's new BYOK option for Copilot Business and Enterprise users in VS Code signals a larger shift in developer tooling. Teams increasingly want the convenience of an integrated AI surface without surrendering model choice, billing control, or policy flexibility to a single vendor path. Three Things to Know GitHub now lets organizations use their own model-provider keys inside VS Code Chat and agent workflows, including built-in and custom agents. That matters because enterprise teams want portability across providers, cleaner cost accounting, and the option to use local or regional models. Viewed alongside GitHub's recent interaction-data policy update, BYOK also reads as a trust feature for organizations that care deeply about data boundaries. A small product change with a real governance message GitHub's April 22 changelog entry...
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Google's TPU split shows what the agent era really needs

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The clearest message in Google's new TPU announcement is that the agent era is forcing infrastructure to specialize. Google's new TPU 8i and TPU 8t are not just faster chips. They express a deeper market belief: agentic AI puts constant low-latency inference and giant training jobs under the same roof, but they are no longer the same infrastructure problem. Three Things to Know Google is separating inference-first and training-first TPU roles because agent systems create different performance and cost pressures. TPU 8i is framed around low latency and large-scale concurrent inference, while TPU 8t is framed around training with a massive shared memory pool. The strategic lesson is that AI infrastructure is becoming less about one best chip and more about matching the right compute shape to the right workload. Google is splitting the infrastructure job in two Google's April 2026 TPU announcement is notable not only because the numbers are large, but because the product ...
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OpenAI's workspace agents turn ChatGPT into team software

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The important part of OpenAI's new workspace agents is not that they are stronger bots. It is that they are built to live inside team process. OpenAI's workspace agents push ChatGPT beyond the one-person assistant model. By combining shared agents, cloud execution, approvals, analytics, and admin controls, the launch turns ChatGPT into something closer to organizational software than a consumer chat interface. Three Things to Know Workspace agents are designed around shared context, approvals, and handoffs instead of one-off personal prompts. The cloud runtime matters because agents can keep working across tools and Slack even when nobody is actively watching the chat. The real adoption question is governance: which tools an agent can touch, what actions need approval, and how teams review runs over time. This is how ChatGPT stops being a solo tool OpenAI's April 22 launch of workspace agents is easy to summarize as another agent release, but that framing misses the bi...
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GitHub's small CodeQL update matters because security teams still lose on local framework knowledge

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A lot of security tooling looks smart until it meets your company's own helper functions. GitHub's latest CodeQL update looks minor on the surface, but it solves a real adoption pain: many teams know their own sanitizers and validation guards better than the scanner does, and the cost of encoding that knowledge has often been high enough that they simply never do it. Three Things to Know GitHub now lets teams define sanitizers and validators declaratively in YAML data extensions instead of custom CodeQL logic. That matters because local framework knowledge is one of the biggest reasons static analysis results drift from developer trust. The feature also pushes CodeQL model packs closer to a maintainable workflow artifact instead of a specialist-only customization layer. Why this change is easy to miss On the surface, GitHub's latest CodeQL note looks like a small changelog item for security specialists. In practice, it touches one of the most frustrating problems in sta...
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OpenAI and Cloudflare are betting that enterprise agents win with distribution, not demos

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The most important agent launch this month may not be a new model. It may be a new default place to run one. OpenAI's expansion inside Cloudflare Agent Cloud and Cloudflare's broader Agent Cloud push signal a deeper market bet: enterprise agents will not scale through isolated demos, but through platforms that collapse model access, runtime, storage, security, and deployment into one operational surface. Three Things to Know OpenAI is using Cloudflare Agent Cloud to put GPT-5.4 and Codex inside an environment already framed for production workloads. Cloudflare is pitching agents as long-running infrastructure workloads that need new compute, storage, and security defaults. The market implication is that agent adoption may hinge more on distribution and operating environment than on headline model benchmarks. This is really a distribution story The OpenAI and Cloudflare announcement is easy to misread as another partnership post in a season full of them. But the important p...
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Meta's agent training plan shows why interactive data may become the next labor fight

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The next AI data bottleneck may not be text. It may be the ordinary human act of using a computer. Meta's reported decision to collect employee mouse movement, clicks, keystrokes, and periodic screenshots for agent training matters because it exposes a deeper shift: frontier agent systems increasingly need real interactive behavior, and that turns workers into both operators and data sources. Three Things to Know Reported internal Meta tracking is notable because interactive training data is much harder to source than public text or images. The move blurs the line between workplace telemetry and product development, even if the company says the data is not for employee evaluation. If agent builders keep chasing higher-quality computer-use data, labor, consent, and regional regulation will become product constraints rather than side issues. Why this report matters more than it first appears The Meta report is easy to read as a surveillance story, and it is one. But it is also a ...
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GitHub's fake star economy is turning open-source popularity into a due-diligence risk

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A star used to feel like a cheap trust signal. Now it increasingly looks like a metric that can import legal and supply-chain risk into early decisions. The current fake-star conversation is important not because vanity metrics are new, but because peer-reviewed evidence now says GitHub stars are being manipulated at scale, often in ways that overlap with phishing, spam, and weak repository quality. Three Things to Know CMU researchers found roughly six million suspected fake GitHub stars across 18,617 repositories and 301,000 accounts, with sharp growth in 2024. The paper argues fake stars help only in the short term and become a liability over time, especially when stars are used as a high-stakes quality shortcut. The FTC's fake social influence rule turns star manipulation into more than an ethics issue when the metric is used for commercial signaling. Why this story caught fire The fake-star economy is resonating right now because it sits at the intersection of three anxiet...
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