Malaysia has intensified its push to build an AI-ready workforce, with Huawei pledging to train 30,000 local professionals under a new initiative. The plan aligns with Malaysia’s National Cloud Computing Policy, balancing sovereignty and digital economy competitiveness.
Digital Minister Gobind Singh Deo stressed that AI adoption must benefit all Malaysians, highlighting applications from small business platforms to AI-assisted diagnostics in remote clinics. He urged collaboration across industries to ensure inclusivity as the country pursues its digital future.
Huawei’s Gartner recognition for container management highlights its cloud-native strength. Its Pangu models and container products will support Malaysia’s AI goals in manufacturing, healthcare, transport, and ASEAN industries.
The programme will target students, officials, industry leaders, and associations while supporting 200 local AI partners. Huawei’s network of availability zones in ASEAN provides low-latency infrastructure, with AI-native innovations designed to accelerate training, inference, and industrial upgrades.
The government of Malaysia views AI as crucial to achieving its 2030 goals, which aim to balance infrastructure, security, and governance. With Huawei’s backing and a new policy framework, the country seeks to establish itself as a regional hub for AI expertise.
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A new workplace trend known as ‘quiet cracking’ describes employees who stay in their roles while feeling increasingly disengaged and emotionally drained.
Unlike quitting, where workers reduce effort, quiet cracking refers to those who continue to meet expectations yet feel like they are breaking inside.
Experts say the phenomenon usually develops gradually, with workers reporting fatigue, stress and frustration instead of open dissatisfaction. Many feel unable to speak up for fear of losing their job or facing uncertainty in the broader labour market, leaving them silent.
Critics argue that labelling such behaviour risks encouraging weakness instead of resilience, but supporters warn that ignoring the issue may worsen mental health challenges.
Some workers are turning to AI for support instead of seeking human assistance. Generative AI tools offer low-cost and constant access for advice and empathetic responses.
Advocates suggest AI could expand mental health support where professionals are scarce, while opponents caution that relying on AI instead of qualified therapists could carry significant risks.
Whether quiet cracking becomes a lasting workplace concern or fades as a passing trend remains uncertain, for now, it highlights the growing debate about how technology might play a role in addressing modern mental health struggles.
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Parag Agrawal, the former Twitter chief executive removed after Elon Musk’s takeover in 2022, has re-entered the technology sector with a new venture.
His company, Parallel Web Systems, is developing AI tools designed to help AI agents gather and analyse information online without human input.
The company’s first product, Deep Research API, outperforms human researchers and advanced models such as OpenAI’s GPT-5 on specific benchmarks.
Agrawal revealed that the system already supports millions of tasks daily and is used by coding agents to locate documents and fix errors. Parallel has secured 30 million dollars in funding and employs around 25 staff.
Agrawal had been Twitter’s chief technology officer before succeeding Jack Dorsey as chief executive in late 2021. After leaving the company, he returned to academic research and coding instead of joining other struggling firms.
He has argued that the internet will eventually be dominated by AI agents rather than human users, predicting that individuals may soon rely on dozens of agents to act on their behalf.
His views echo predictions from Coinbase developers, who recently suggested that AI agents could become the most significant users of Ethereum.
They propose that autonomous systems can handle stablecoin transfers and e-commerce transactions, enabling services from self-driving taxis to AI-powered content platforms.
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OpenAI recently unveiled GPT-5, a significant upgrade praised for its advances in accuracy, reasoning, writing, coding and multimodal capabilities. The model has also been designed to reduce hallucinations and excessive agreeableness.
Chief executive Sam Altman has admitted that OpenAI has even more powerful systems that cannot be released due to limited capacity.
Altman explained that the company must make difficult choices, as existing infrastructure cannot yet support the more advanced models. To address the issue, OpenAI plans to invest in new data centres, with spending potentially reaching trillions of dollars.
The shortage of computing power has already affected operations, including a cutback in image generation earlier in the year, following the viral Studio Ghibli-style trend.
Despite criticism of GPT-5 for offering shorter responses and lacking emotional depth, ChatGPT has grown significantly.
Altman said the platform is now the fifth most visited website worldwide and is on track to overtake Instagram and Facebook. However, he acknowledged that competing with Google will be far harder.
OpenAI intends to expand beyond ChatGPT with new standalone applications, potentially including an AI-driven social media service.
The company also backs Merge Labs, a brain-computer interface rival to Elon Musk’s Neuralink. It has partnered with former Apple designer Jony Ive to create a new AI device.
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Zoom has patched a critical Windows vulnerability that could let attackers fully take control of devices without needing credentials. The flaw, CVE-2025-49457, stems from the app failing to use explicit paths when loading DLLs, allowing malicious files to be executed.
Attackers could exploit this to install malware or extract sensitive data such as recordings or user credentials, even pivoting deeper into networks. The issue affects several Zoom products, including Workplace, VDI, Rooms, and Meeting SDK, all before version 6.3.10.
Zoom urges users to update their app immediately, as the flaw requires no advanced skill and can be triggered with minimal access. However, this highlights the increasing cybersecurity concerns associated with the digital world.
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Enterprise employees are increasingly building their own AI tools, sparking a surge in shadow AI that raises security concerns.
Netskope reports a 50% rise in generative AI platform use, with over half of current adoption estimated to be unsanctioned by IT.
Platforms like Azure OpenAI, Amazon Bedrock, and Vertex AI lead this trend, allowing users to connect enterprise data to custom AI agents.
The growth of shadow AI has prompted calls for better oversight, real-time user training, and updated data loss prevention strategies.
On-premises deployment is also increasing, with 34% of firms using local LLM interfaces like Ollama and LM Studio. Security risks grow as AI agents retrieve data using API calls beyond browsers, particularly from OpenAI and Anthropic endpoints.
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The cybersecurity market is consolidating as AI reshapes defence strategies. Platform-based solutions replace point tools to cut complexity, counter AI threats, and ease skill shortages. IDC predicts that security spending will rise 12% in 2025 to $377 billion by 2028.
Vendors embed AI agents, automation, and analytics into unified platforms. Palo Alto Networks’ Cortex XSIAM reached $1 billion in bookings, and its $25 billion CyberArk acquisition expands into identity management. Microsoft blends Azure, OpenAI, and Security Copilot to safeguard workloads and data.
Cisco integrates AI across networking, security, and observability, bolstered by its acquisition of Splunk. CrowdStrike rebounds from its 2024 outage with Charlotte AI, while Cloudflare shifts its focus from delivery to AI-powered threat prediction and optimisation.
Fortinet’s platform spans networking and security, strengthened by Suridata’s SaaS posture tools. Zscaler boosts its Zero Trust Exchange with Red Canary’s MDR tech. Broadcom merges Symantec and Carbon Black, while Check Point pushes its AI-driven Infinity Platform.
Identity stays central, with Okta leading access management and teaming with Palo Alto on integrated defences. The companies aim to platformise, integrate AI, and automate their operations to dominate an increasingly complex cyberthreat landscape.
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OpenAI’s GPT-5 launched last week to immense anticipation, with CEO Sam Altman likening it to the iPhone’s Retina display moment. Marketing promised state-of-the-art performance across multiple domains, but early user reactions suggested a more incremental step than a revolution.
Many expected transformative leaps, yet improvements mainly were in cost, speed, and reliability. GPT-5’s switch system, which automatically routes queries to the most suitable model, was new, but its writing style drew criticism for being robotic and less nuanced.
Social media buzzed with memes mocking its mistakes, from miscounting letters in ‘blueberry’ to inventing US states. OpenAI quickly reinstated GPT-4 for users who missed its warmer tone, underlining a disconnect between expectations and delivery.
Expert reviews mirrored public sentiment. Gary Marcus called GPT-5 ‘overhyped and underwhelming’, while others saw modest benchmark gains. Coding was the standout, with the model topping leaderboards and producing functional, if simple, applications.
OpenAI emphasised GPT-5’s practical utility and reduced hallucinations, aiming for steadiness over spectacle. At the same time, it may not wow casual users, its coding abilities, enterprise appeal, and affordability position it to generate revenue in the fiercely competitive AI market.
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Germany’s Seedbox.AI is betting on re-training large language models (LLMs) rather than competing to build them from scratch. Co-founder Kai Kölsch believes this approach could give Europe a strategic edge in AI.
The Stuttgart-based startup adapts models like Google’s Gemini and Meta’s Llama for medical chatbots and real estate assistant applications. Kölsch compares Europe’s role in AI to improving a car already on the road, rather than reinventing the wheel.
A significant challenge, however, is access to specialised chips and computing power. The European Union is building an AI factory in Stuttgart, Germany, which Seedbox hopes will expand its capabilities in multilingual AI training.
Kölsch warns that splitting the planned EU gigafactories too widely will limit their impact. He also calls for delaying the AI Act, arguing that regulatory uncertainty discourages established companies from innovating.
Europe’s AI sector also struggles with limited venture capital compared to the United States. Kölsch notes that while the money exists, it is often channelled into safer investments abroad.
Talent shortages compound the problem. Seedbox is hiring, but top researchers are lured by Big Tech salaries, far above what European firms typically offer. Kölsch says talent inevitably follows capital, making EU funding reform essential.
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Google has released Gemma 3 270M, an open-source AI model with 270 million parameters designed to run efficiently on smartphones and Internet of Things devices.
Drawing on technology from the larger Gemini family, it focuses on portability, low energy use and quick fine-tuning, enabling developers to create AI tools that work on everyday hardware instead of relying on high-end servers.
The model supports instruction-following and text structuring with a 256,000-token vocabulary, offering scope for natural language processing and on-device personalisation.
Its design includes quantisation-aware training to work in low-precision formats such as INT4, reducing memory use and improving speed on mobile processors instead of requiring extensive computational power.
Industry commentators note that the model could help meet demand for efficient AI in edge computing, with applications in healthcare wearables and autonomous IoT systems. Keeping processing on-device also supports privacy and reduces dependence on cloud infrastructure.
Google highlights the environmental benefits of the model, pointing to reduced carbon impact and greater accessibility for smaller firms and independent developers. While safeguards like ShieldGemma aim to limit risks, experts say careful use will still be needed to avoid misuse.
Future developments may bring new features, including multimodal capabilities, as part of Google’s strategy to blend open and proprietary AI within hybrid systems.
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