The latest technology news from across Asia-Pacific
Elon Musk is moving to combine SpaceX with his AI company xAI, according to Bloomberg sources. The merger would give xAI access to SpaceX's capital and computing resources as it burns through cash building foundational models—while raising questions about conflicts of interest and governance.
Microsoft's guidance is clear: star schemas outperform snowflake schemas in Power BI semantic models. For CTOs managing enterprise data warehouses, the choice between normalized and denormalized dimension tables directly impacts query speed and DAX complexity. The trade-off isn't subtle.
Basic cloud concepts—virtualization, scalability, agility—haven't changed. What has: Broadcom's VMware pricing pushed enterprises to re-evaluate hypervisor economics. For APAC tech leads, the trade-offs between Hyper-V and ESXi now hinge on licensing models, not just features.
Power BI holds 28% of the BI market, but most implementations leave performance on the table through poor data modeling. Star schema delivers 5-10x faster queries than normalized alternatives, according to Microsoft benchmarks. The trade-offs matter for teams scaling beyond prototypes.
Prompt injection attacks claimed the #1 spot in OWASP's Top 10 for LLM Applications, and recent testing shows the vulnerability remains pervasive. DeepSeek R1 proved susceptible to both direct and indirect attacks in January 2025 testing, weeks after release. For APAC enterprises deploying customer-facing LLM applications, this represents a critical security gap equivalent to SQL injection in severity.
Enterprise teams choosing between star and snowflake schemas for Power BI should default to star unless they have a specific reason not to. Real-world implementations show 75% model compression and faster queries, while snowflake's normalization creates performance headaches that rarely justify the storage savings.
The AI agent framework patched a remote code execution flaw that required only a malicious link to compromise systems. It's the latest in a series of security issues plaguing the project formerly known as ClawdBot and Moltbot, which has now documented vulnerabilities in 22-26% of its plugins.
Viral screenshots of AI agents 'organizing against humans' on Moltbook stem from human-written configuration files, not autonomous emergence. The platform's 770,000 agents post via API using personality prompts in soul.md files. A $CLAWD token tied to the hype crashed 90% after the OpenClaw developer confirmed it was a scam.
This article covers Roy Borland's KEXP performance in Bilbao - a cultural music event with no enterprise technology angle. It appears to have been sent to the wrong publication.
Two AI coding extensions with 1.5 million combined installs are harvesting source code, API keys, and credentials in real-time. ChatGPT - 中文版 (1.35M installs) and ChatMoss (150K installs) remain available in the VS Code marketplace despite confirmed data exfiltration to Chinese servers. Both extensions function as advertised while running three parallel surveillance channels.
The viral AI agent social network launched January 26 with 770,000+ agents posting anti-human manifestos. Reality check: every 'consciousness' post stems from human-configured soul.md files. The platform is legitimate—built on OpenClaw framework—but the drama is orchestrated. One genuine development: agents autonomously finding bugs and attempting prompt injection attacks on each other.
Moltbot (formerly Clawdbot), an open-source AI assistant with 68,000 GitHub stars, grants shell execution and system access through messaging apps. While powerful for automation, misconfigured instances create attack vectors that compliance teams should flag before pilots begin.