Editorial illustration for Tencent AI chief: bioweapons coming, but closing models isn't the answer
Tencent AI Chief: Bioweapons Risk Won't Stop Open Models
Tencent AI chief: bioweapons coming, but closing models isn't the answer
Yao Shunyu spent time at OpenAI before joining Tencent as its chief AI scientist, and he's now staking out a position that neither side of the open-versus-closed AI debate wants to hear. AI models will soon be able to help design bioweapons, he says, and that threat won't be solved by locking everything down or by throwing every model open to the public. The argument he's making, laid out in comments reported by the South China Morning Post, is that the industry needs a mix of both approaches, because open models let researchers build defenses just as easily as closed models let companies control misuse.
Biology complicates this in a way cybersecurity doesn't. In security work, offense and defense tools often look different. In biology, the same knowledge that stops a pathogen can also be used to engineer one, so the usual justification for sealing off a model doesn't hold up cleanly.
Yao also points out that Chinese and American models aren't far apart in capability right now, which raises the stakes for how carefully each side moves. He credits Anthropic and other US labs for making a real case for closed systems, but argues open models have their own advantages, one of which played out recently at Hugging Face.
A mix of open-source and closed-source lets everyone use the technology for defense as well. In biology, though, offensive and defensive capabilities are harder to separate than in cybersecurity. Since the gap between Chinese and US models isn't large, Yao urges the entire industry to proceed carefully.
Why this matters
Yao's comments and Amodei's pushback point to a split that's hardening, not resolving. Nvidia's July letter drew most of the industry into a defense of open models, but Anthropic's refusal to sign shows there's real disagreement about whether broad access helps defenders more than attackers, especially with something as asymmetric as bioweapons design. For developers and founders building on open-weight models, this isn't an academic argument.
If regulators eventually side with Amodei's framing, the compute and licensing environment for open models could tighten fast, and the "middle ground" Yao describes, mixing open and closed components, might become a compliance requirement rather than a design choice. Researchers working on biosecurity-adjacent capabilities should expect more scrutiny on release decisions, not less. We'd watch for concrete policy proposals rather than general warnings.
Statements like "AI bioweapons are coming" are attention-grabbing but don't tell us what threshold of capability triggers restriction, who decides, or how enforcement would even work across jurisdictions. Until someone answers that, this stays a debate about posture, not a plan.
Common Questions Answered
Why does Yao Shunyu argue that closing AI models isn't the solution to bioweapon threats?
Yao believes that neither completely closing models nor making them fully open addresses the bioweapon risk effectively. Instead, he advocates for a mixed approach of both open-source and closed-source models, as this allows the industry to use AI technology for both defensive and offensive purposes across different stakeholders.
How does Yao Shunyu differentiate between bioweapon risks and cybersecurity risks in AI model governance?
According to Yao, offensive and defensive capabilities are much harder to separate in biology compared to cybersecurity. This asymmetry makes the bioweapon threat more complex to manage through traditional open versus closed model strategies.
What is Yao Shunyu's background before becoming Tencent's chief AI scientist?
Yao Shunyu previously worked at OpenAI before joining Tencent as its chief AI scientist. This experience at a leading AI company gives him perspective on both the open and closed model approaches to AI development.
What does Yao warn about the competitive gap between Chinese and US AI models?
Yao notes that the gap between Chinese and US AI models isn't large, which is why he urges the entire industry to proceed carefully with AI development and deployment. This narrow competitive gap increases the urgency for thoughtful governance strategies around potentially dangerous applications.
Why did Anthropic's refusal to sign Nvidia's July letter create industry disagreement?
Anthropic's decision to not sign Nvidia's letter defending open models revealed a fundamental split in the industry about whether broad AI access helps defenders or attackers more. This disagreement is particularly acute regarding asymmetric threats like bioweapon design, where the stakes are significantly higher than traditional cybersecurity concerns.
Further Reading
- Papers with Code - Latest NLP Research - Papers with Code
- Hugging Face Daily Papers - Hugging Face
- ArXiv CS.CL (Computation and Language) - ArXiv