Google Moves to Outbuild OpenAI in the Workplace AI Race
Image Credit: Google
Google has launched Gemini Enterprise, a full-scale AI platform for businesses to build and deploy autonomous agents across teams. It’s the company’s boldest move yet in the competition with OpenAI’s ChatGPT Enterprise and AgentKit, both of which target similar automation across corporate systems.
Here’s what’s inside the rollout:
Platform scope: Built under Google Cloud, Gemini Enterprise links with Workspace, Microsoft 365, Salesforce, and SAP for secure data access.
Early adopters: Companies including Figma, Klarna, Macquarie Bank, and Virgin Voyages are already using the system, with Virgin deploying more than 50 internal agents.
Tool access: Integrates with Google’s Code Assist and Deep Research tools to analyze internal data and automate repetitive workflows.
Google calls Gemini Enterprise “the new front door for AI in the workplace,” framing it as a secure hub for internal agents and automation. The timing is unmistakable. OpenAI’s new ChatGPT updates are moving in the same direction. The race now hinges on reliability, integration, and trust across the board.
University Used AI to Detect AI and Wrongly Accused 6,000 Students
Image: ABC News: Danielle Bonica)
Australian Catholic University (ACU) used AI tools to flag nearly 6,000 students for academic misconduct in 2024, most for alleged use of generative AI. Many were later cleared, revealing how flawed detection systems can upend real lives when used without oversight or context.
How did this affect staff and students?
Scale of accusations: About 90% of misconduct cases involved AI, though many students had done nothing wrong.
Student impact: Some students lost internships and job offers while transcripts were marked “results withheld.”
Faulty tools: ACU relied on Turnitin’s AI detector, which later admitted its reports “may misidentify” human writing.
Course correction: The university dropped the detector and introduced training on ethical AI use for students and staff.
AI detectors are notoriously unreliable, often flagging human writing as machine output including content from the U.S. Constitution and the Bible. Turnitin’s AI feature uses deep-learning models to spot content “likely” written or paraphrased by LLMs. The next step for universities is not policing algorithms with more algorithms, but teaching digital literacy, transparency, and fairness.
China is Building a Rival AI Chip Stack. Nvidia’s Lead Faces Real Pressure
Image Credit: Getty Images
China is racing to close the technology gap with the United States, pouring billions into artificial intelligence, robotics, and chip manufacturing. Nvidia’s Jensen Huang recently said China is now only “nanoseconds behind,” as Chinese firms rapidly expand into advanced semiconductor design and production.
Where is China gaining ground?
DeepSeek’s launch: Released a ChatGPT rival in 2024 using fewer chips and less funding.
Huawei and Alibaba: Announced processors said to match Nvidia’s H20 in power and efficiency.
Cambricon’s rise: Shares more than doubled as China pushes domestic chip use.
Trade pressure: US export bans have accelerated Beijing’s push for chip independence.
“You cannot underestimate China’s ability to catch up,” as Prof Yang put it, and the incentives now align across funding, talent, and procurement. The next phase demands transparent tests, software maturity, and supply chains that can deliver at scale, since leadership in AI will track whoever can prove reliability under real workloads rather than claims alone.
OpenAI’s Low-Cost ChatGPT Plan Reaches New 16 Asian Countries
Image Credit: Android Authority
An under-$5 ChatGPT Go tier has rolled out to 16 countries across Asia, with local currency billing in several markets and USD pricing elsewhere. The company reports rapid user growth in the region and a push to turn engagement into paid adoption while it scales costly infrastructure.
Who gains and what changes now?
Coverage: Sixteen markets across South and Southeast Asia, local payments in several, USD in others.
Price: Under five dollars per month, with final cost shaped by local taxes.
Capacity: Higher daily limits and doubled memory enable longer sessions and richer context.
Risks: Card access, patchy connectivity, and low digital literacy could widen usage gaps.
Cheaper access is a start, not an endpoint, and the next step is clear consumer safeguards, local-language literacy, and simple billing options that include the unbanked. If those pieces land, low-cost AI can serve classrooms, shops, and households without deepening the divide.
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