AI News

AI News Brief: On September 2 Taipei time, Rani Borkar, President of Microsoft’s Azure Hardware Systems and Infrastructure division, said in a keynote at SEMICON Taiwan 2026 that simply ramping up memory chip production capacity won’t solve the supply chain bottlenecks currently holding back AI infrastructure buildout. She called on the industry to ease the shortage of key components through technological innovation rather than relying solely on capacity expansion.

AI news brief: AfterQuery, a startup specializing in AI training data, is reportedly valued at $3.2 billion after a new funding round — just five months after announcing a $30M Series A at a $300M valuation in April. That’s a valuation jump of more than 10x in under half a year, and according to Y Combinator partner Gustaf Alströmer, it’s the fastest a startup has ever gone from founding to unicorn in the accelerator’s history.

AI news brief: Google is speeding up the development and rollout of its custom AI chips to stay ahead in the AI race, with AI infrastructure chief Amin Vahdat saying at Semicon Taiwan 2026 on September 2 that Google is compressing its chip generation cycle from once every two years to two new chips per year, with plans to go even faster, while also boosting R&D investment in Taiwan.

AI News Brief: Japan’s airports are set to roll out artificial intelligence to detect anomalies in runways, lighting, and other infrastructure, aiming to double maintenance efficiency as inbound foreign travelers keep rising while staffing stays tight. The initiative is led by Japanese trading house Sumitomo Corporation, targeting hub airports short on manpower to strengthen infrastructure inspection and maintenance with AI.

AI news flash: Google’s August 2026 AI updates focus on bringing intelligence into everyday life, spanning hardware, models, education, and search. The headline is Gemini 3.7 Flash, currently the best efficient model for coding and agentic tasks, launched just three weeks after 3.6 Flash with major gains in software engineering, knowledge work, and web dev workflows, plus a price cut to half of 3.6 Flash’s per-million-token rate.

AI News Brief: BenchMIRT is a new method for breaking down what LLM benchmarks actually measure, auditing them at the individual question level. Traditional benchmarks usually claim to measure a single capability (like safety, general reasoning, or instruction following), but individual questions often involve multiple capabilities at once. For example, BBQ, a benchmark that tests whether models rely on social stereotypes, has a question about a grandparent and grandchild booking an Uber that looks like it’s testing age bias, but actually also requires the model to correctly track character roles and reason from evidence rather than assumptions.

AI News Brief: Astra is the first model that OpenAI’s Preparedness Framework has rated as crossing the ‘Critical’ threshold for cybersecurity capability, putting its risk rating above every previous OpenAI release and among the framework’s highest tiers. In response, OpenAI says it’s rolling out stronger safeguards for Astra’s release to cut the risk of misuse or spillover. The original summary doesn’t give more detail on the specific mechanisms, testing methods, or release timeline — see the original link for more.

AI News Brief: Gemini today announced ‘agentic video understanding,’ a new capability for its Gemini 3.7 Flash, 3.6 Flash, and 3.5 Flash-Lite models, available through the Gemini API (Google AI Studio and Gemini Ent…

AI news brief: Three real-world examples of AI-native workflows — Basis, Clay, and Exa Labs have all deployed AI agents to optimize internal operations, covering onboarding, account management, and developer integration.

AI news brief: Nvidia announced a $3.5 billion investment in Taiwanese chipmaker MediaTek, and as part of the deal, MediaTek will use Nvidia’s technology to help design custom chips for AI companies and hyperscalers, chips that plug directly into Nvidia-centric data center architecture. The move comes as more AI companies and cloud providers—including Amazon, Google, Microsoft, OpenAI, and Anthropic—invest in building their own chips to cut their reliance on Nvidia GPUs.