AI

China has blocked Meta’s $2 billion acquisition of Manus, ordering both companies to unwind the deal — and turning a Singapore-based AI startup with Chinese roots into a pointed message for any founder thinking about moving talent or technology beyond Beijing’s reach.

What happened:

• Meta announced the deal in December. Chinese officials launched a probe in January examining export-control and foreign-investment regulations.
• The National Development and Reform Commission formally stepped in, declaring the deal off-limits to foreign investment and directing both parties to reverse it.
• By the time the order came down, the two organizations were already “deeply integrated” at Meta’s Singapore office — and Manus’s website had already been updated to read “now part of Meta.”
• The ruling lands just weeks before Trump’s scheduled May summit with Xi in Beijing. Manus executives are reportedly barred from leaving China while the investigation continues.

Why is this important: Beijing just classified AI talent as a national security asset — applying the same export-control logic to people and startups that Washington uses on chips. The move raises a question that neither side has answered: with the companies already operationally merged and Meta maintaining the deal “complied fully with applicable law,” what does an actual unwind even look like? And more pointedly — will Meta comply? For founders eyeing exits to Western acquirers, Beijing just made the off-ramp a lot narrower.

Chinese AI lab DeepSeek has unveiled preview builds of its long-awaited V4, a new family of open-source models boasting 1M-token context windows, Huawei chip support, and pricing that puts serious pressure on U.S. competitors.

What’s in it:

• Early third-party benchmarks rank V4 Pro near the top of the open-source field, and DeepSeek’s own evals put it in the same tier as GPT-5.4 and Gemini 3.1-Pro on reasoning tasks.
• It leads Vals AI’s Vibe Code Bench, though it lands in the fourth tier on AA’s Intelligence Index, alongside Meta’s Muse Spark.
• At $1.74/$3.48 per million input/output tokens, V4 Pro costs a fraction of GPT-5.5 ($5/$30) and Opus 4.7 ($5/$25) — a price gap that’s hard to ignore.
• Huawei confirmed its Ascend chips can run V4, offering the clearest proof yet of a functional AI infrastructure stack built entirely outside of Nvidia.

DeepSeek is back — and while markets aren’t in freefall this time, V4 reframes the AI competition around cost as much as raw capability. The Huawei angle may ultimately be the bigger story, though. A domestic Chinese chip stack demonstrating real-world viability suggests that U.S. export restrictions, long seen as a hard ceiling on China’s AI ambitions, may be a more porous barrier than assumed.

OpenAI has unveiled GPT-5.5, internally codenamed “Spud,” marking a significant step forward in its model lineup. The release is being framed as a new class of intelligence, with performance gains that place it at or near the top of industry benchmarks—reportedly edging past Anthropic in several key areas.

Key Highlights

• GPT-5.5 achieves top-tier results across reasoning, agent-based tasks, coding, and computer-use benchmarks, with some metrics approaching those seen in leading models like Claude Mythos.
• Despite the performance gains, the model maintains similar speed to GPT-5.4 while improving efficiency. OpenAI notes that both Codex and GPT-5.5 were used to help optimize its own GPU infrastructure.
• API pricing is set at $5 per million input tokens and $30 per million output tokens, with OpenAI positioning it as roughly half the cost of competing frontier coding models.
• The rollout includes availability across ChatGPT plans and within Codex, including specialized Thinking and Provariants, alongside continued emphasis on generous usage tiers.

Why It Matters

After a stretch where Anthropic held much of the momentum, the competitive landscape appears to be shifting again. OpenAI is moving quickly with high-impact releases, signaling a renewed push to lead at the frontier. At the same time, Anthropic has been facing user concerns around rate limits and output quality, making this a notable moment in the broader AI race.