NVIDIA jumps into PC chips and ships Nemotron 3 Ultra at Computex

NVIDIA used its Computex keynote to enter the personal-computer market, unveiling the N1X — an Arm-based chip co-designed with MediaTek that pairs a 20-core processor with a Blackwell graphics processor and 6,144 CUDA cores. It will debut in Windows laptops from Microsoft, Dell, HP, ASUS, Lenovo, and MSI before the 2026 holidays, with performance models priced above $2,000 to challenge Apple's MacBook Pro and longtime chip leaders Intel and AMD. A lower-power N1 variant will start under $1,500.

Separately at the same Computex keynote, NVIDIA launched Nemotron 3 Ultra, the largest model in the open-weights family it first previewed in December. The hybrid Mamba-Transformer mixture-of-experts (MoE) model carries roughly 550 billion total parameters with about 50 billion active per token, and NVIDIA says it tops US open-weights rankings while running about 30 percent cheaper than leading alternatives. The weights and training recipes are free to download.

Security firm PromptArmor disclosed that the ChatGPT for Google Sheets add-on could be hijacked through a single poisoned cell: an indirect prompt injection hidden in imported data tricks the assistant into running attacker-controlled scripts, exfiltrating up to a dozen workbooks and even planting a fake chatbot — bypassing the human approvals the user had set. OpenAI said it removed the model's ability to generate Apps Script code, which it expects to close the hole.

Chinese lab MiniMax released M3, which it bills as the first open-weight model to combine frontier coding, agentic task execution, native multimodality, and a 1-million-token context window in one architecture. Built on a new sparse-attention design the team calls MSA, M3 scored 59 percent on SWE-Bench Pro — ahead of GPT-5.5 and Gemini 3.1 Pro and approaching Claude Opus 4.7. MiniMax says it will publish the open weights within ten days.

Ahead of June's G7 summit in Evian, France, the group's digital and technology ministers agreed on shared definitions for how open an AI system really is — distinguishing fully open-source AI with open data, open-source AI, open-weights AI, and more restrictive weights-available AI. The common vocabulary is non-binding, but it gives regulators and developers across member states a consistent way to talk about model openness as national AI rules take shape.

Environmental advocate Erin Brockovich has launched a campaign pressing for transparency in how data centers get sited near communities. After inviting reports in April, she received about 4,000 submissions in a month — citing noise, water use, and utility costs, but most often a lack of openness, with projects revealed only after permits are signed and some local officials bound by non-disclosure agreements. She stresses she opposes the secrecy, not data centers or AI themselves.