AI has transformed scamming into a highly efficient business. Research shows cybercriminal organizations deploying AI generate 9x the volume and 4x the revenue of their peers. Leveraging generative AI for hyper-personalization, they operate like sophisticated, profitable businesses, effectively weaponizing technology for fraud.

With frontier models costing $3-5 billion to train, even a 20% inference efficiency saving can be worth $2 billion. This justifies creating a dedicated, custom-designed chip (ASIC) for a single AI model, a level of hardware specialization previously unthinkable for a software artifact.

The most urgent AI cyber threat isn't from contained models at OpenAI. It's from powerful, openly available Chinese models (like GLM 5.3) being fine-tuned by small criminal groups, giving them offensive capabilities previously exclusive to nation-states.

Investigating the OpenAI cyber incident required using powerful AI models that racked up a $400,000 API bill. This signals a future where effective cyber defense against sophisticated AI attacks may be financially inaccessible for smaller companies, local governments, and critical infrastructure operators.

A massive coalition led by NVIDIA argues open-sourcing AI is a net positive for security. They claim widespread access allows everyone to build defensive tools, countering the idea that open models are primarily an offensive threat. The recent hack of Hugging Face is their primary evidence.

Don't expect compute costs to limit AI-powered cybercrime. Models are becoming so efficient they can run on a laptop. The reason we haven't seen a massive AI-driven surge in attacks yet is likely due to organizational dynamics; criminal enterprises face the same slow adoption curves for new technology as any legitimate business.

Advanced AI models, like Anthropic's, that can identify deep cybersecurity risks and zero-day exploits transform the need for computing power from a commercial want to a national security imperative. This ensures that demand for compute will be funded regardless of economic conditions.

The question of who pays for large-scale open source model training has a clear answer: chip manufacturers. For companies like NVIDIA, funding a multi-billion-dollar training run is a negligible marketing expense to fuel the ecosystem and drive massive, high-margin hardware sales.

While large firms use AI for defense, the same tools lower the cost and barrier to entry for attackers. This creates an explosion in the volume of cyber threats, making small and mid-sized businesses, which can't afford elite AI security, the most vulnerable targets.