AI Weekly Malaysia

AWS CEO Matt Garman said Amazon has stopped using NDAs in its dealings with government agencies, as part of a blog post pushing back on data center opposition while Amazon seeks approval to build new data centers. The post cites New York's one-year moratorium on permits for large data centers and claims more than 100 data center moratoriums are being considered across the US. Garman also argues data centers are not major water users, saying direct data center water consumption is 0.5% of all US industrial water usage, less than golf courses and almond farming.

Why: The concrete change is Amazon's NDA policy for government agencies, so builders should not expect any immediate AWS product, region, or pricing change from this post. The actionable signal is the 100+ proposed US data center moratoriums: if they advance, they could affect where and how fast cloud/AI capacity expands, which matters to teams making multi-year compute or data-residency plans. The article provides no Malaysia-specific detail, so treat it as a global cloud-infrastructure policy signal rather than a local announcement.

Tom's Hardware reports that the UK government has issued draft guidance telling staff to stop thanking AI chatbots, and to favour lightweight models and shorter prompts in order to cut environmental impact. Beyond the headline and URL, the supplied page content is only Tom's Hardware navigation, membership and newsletter boilerplate — no named department, effective date, model names, or measured energy figures are present.

Why: There is not enough in this text to change a build decision. The one usable signal is directional: a large public-sector employer is treating prompt length and model choice as an efficiency lever rather than a politeness or UX question. If your team ships AI features or agents, this is a prompt to check whether your default model tier and prompt sizes are justified — but this item gives you no numbers, no policy text, and no Malaysian equivalent, so do not cite it as evidence of anything specific.