Archived edition · Bangkok time
This edition covers Terence Tao's Math 2.0 keynote addressing AI formal alignment in mathematics, Qualcomm's disclosure of frontier lab targets for continuous 100B on-device models by 2028, reverse engineering workflows with Claude Opus 5.5, and a fact-check confirming Alibaba's Qwen 4 27B remains in pre-training.
4 unique stories
As enterprises increasingly automate complex decision-making and verification pipelines with AI, Tao's Math 2.0 thesis demonstrates that formal verification without underlying human explanatory comprehension creates hidden systemic risks in high-stakes domains.
If achieved, enterprises could run state-of-the-art language models directly on mobile edge silicon, slashing recurring cloud inference bills and resolving data sovereignty constraints under local privacy regulations.
Automating matching decompilation compresses years of human reverse-engineering into compute hours, demonstrating powerful legacy system migration workflows while sparking debates over IP security and client-side binary protection.
Distinguishing strategic roadmaps from production weight releases prevents enterprise engineering teams in Thailand from making misallocated local hardware investments before model specifications and real-world architectures finalize.