Artificial intelligence Archives | Page 385 of 689

South Korea’s new Science Minister pledges AI-led national transformation

South Korea’s new Science and ICT Minister, Bae Kyung-hoon, has pledged to turn the nation into one of the world’s top three AI powerhouses.

Instead of following outdated methods, Bae outlined a bold national strategy centred on AI, science and technology, aiming to raise Korea’s potential growth rate to 3 per cent and secure a global economic leadership position.

Bae, a leading AI expert and former president of LG AI Research, officially assumed office on Thursday.

Drawing from experience developing hyperscale AI models like LG’s Exaone, he emphasised the need to build a unique competitive advantage rooted in AI transformation, talent development and technological innovation.

Rather than focusing only on industrial growth, Bae’s policy agenda targets a broad AI ecosystem, revitalised research and development, world-class talent nurturing, and addressing issues affecting daily life.

His plans include establishing AI-centred universities, enhancing digital infrastructure, promoting AI semiconductors, restoring grassroots research funding, and expanding consumer rights in telecommunications.

With these strategies, Bae aims to make AI accessible to all citizens instead of limiting it to large corporations or research institutes. His vision is for South Korea to lead in AI development while supporting social equity, cybersecurity, and nationwide innovation.

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EU confirms AI Act rollout and releases GPAI Code of Practice

The European Commission has confirmed it will move forward with the EU AI Act exactly as scheduled, instead of granting delays requested by tech giants and businesses.

On 10 July 2025, it published the final General-Purpose AI (GPAI) Code of Practice alongside FAQs to guide organisations aiming to comply with the new law.

Rather than opting for a more flexible timetable, the Commission is standing firm on its regulatory goals. The GPAI Code of Practice, now in its final form, sets out voluntary but strongly recommended steps for companies that want reduced administrative burdens and clearer legal certainty under the AI Act.

The document covers transparency, copyright, and safety standards for advanced AI models, including a model documentation form for providers.

Key dates have already been set. From 2 August 2025, rules covering notifications, governance, and penalties will come into force. By February 2026, official guidelines on classifying high-risk AI systems are expected.

The remaining parts of the legislation will take effect by August 2026, instead of being postponed further.

With the publication of the GPAI Code of Practice, the EU takes another step towards building a unified ethical framework for AI development and deployment across Europe, focusing on transparency, accountability, and respect for fundamental rights.

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Meta faces fresh EU backlash over Digital Markets Act non-compliance

Meta is again under EU scrutiny after failing to fully comply with the bloc’s Digital Markets Act (DMA), despite a €200 million fine earlier this year.

The European Commission says Meta’s current ‘pay or consent’ model still falls short and could trigger further penalties. A formal warning is expected, with recurring fines likely if the company does not adjust its approach.

The DMA imposes strict rules on major tech platforms to reduce market dominance and protect digital fairness. While Meta claims its model meets legal standards, the Commission says progress has been minimal.

Over the past year, Meta has faced nearly €1 billion in EU fines, including €798 million for linking Facebook Marketplace to its central platform. The new case adds to years of tension over data practices and user consent.

The ‘pay or consent’ model offers users a choice between paying for privacy or accepting targeted ads. Regulators argue this does not meet the threshold for genuine consent and mirrors Meta’s past GDPR tactics.

Privacy advocates have long criticised Meta’s approach, saying users are left with no meaningful alternatives. Internal documents show Meta lobbied against privacy reforms and warned governments about reduced investment.

The Commission now holds greater power under the DMA than it did with GDPR, allowing for faster, centralised enforcement and fines of up to 10% of global turnover.

Apple has already been fined €500 million, and Google is also under investigation. The EU’s rapid action signals a stricter stance on platform accountability. The message for Meta and other tech giants is clear: partial compliance is no longer enough to avoid serious regulatory consequences.

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Broadcom challenges Nvidia with Tomahawk Ultra AI networking chip

Broadcom has introduced a new networking chip designed to boost AI data centre performance, positioning itself against Nvidia in the AI hardware race.

Called Tomahawk Ultra, the chip helps link hundreds of processors within close range, ensuring fast communication vital for large AI models.

Instead of using Nvidia’s proprietary NVLink system, Broadcom’s Tomahawk Ultra operates on an accelerated version of Ethernet and connects up to four times more chips within a server rack.

The chip acts as a traffic controller, enabling what the industry refers to as ‘scale-up’ computing — where AI models tap into combined computing power from tightly grouped chips.

According to Broadcom senior vice president Ram Velaga, it took engineers around three years to design the Tomahawk Ultra, which was originally aimed at high-performance computing but adapted for AI workloads as demand surged.

Taiwan Semiconductor Manufacturing Company (TSMC) is producing the processors using its five-nanometre process, and the chips are already shipping to customers.

Rather than requiring major hardware overhauls, the Tomahawk Ultra offers a scalable, Ethernet-based alternative for AI firms looking to build faster, more flexible data centres.

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UK customer‑experience leaders champion human‑centred AI

Marketing Week’s CX50 2025 accolades spotlight ten individuals who are redefining customer experience by putting people before pixels.

These leaders are harnessing AI thoughtfully, augmenting frontline staff with tools that personalise service without eroding the human touch.

Their work spans retail, hospitality, financial services and the public sector, showcasing how AI-driven systems can streamline operations while nurturing empathetic engagement.

Strategies include using automation for routine tasks and intelligent routing, freeing teams to focus on empathy, insight and dialogue.

Partners Cognizant, Google Cloud and Salesforce helped assemble the CX50 list. The initiative underscores a growing movement: top-performing brands blend algorithmic precision with human warmth to build trust and loyalty in increasingly digital markets.

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AI system screens diabetic eye disease with near-perfect accuracy

A new AI programme is showing remarkable accuracy in detecting diabetic retinopathy, a leading cause of preventable blindness. The SMART system, short for Simple Mobile AI Retina Tracker, can scan retinal images using even basic smartphones and has achieved over 99% accuracy.

Researchers at the University of Texas Health Sciences Center in the US trained the AI using thousands of retinal images from diverse populations across six continents. The system processes images in under a second and can distinguish diabetic retinopathy from other eye diseases.

Experts say the technology could dramatically expand access to eye screenings, particularly in areas lacking specialist care. By integrating the tool into regular check-ups, both primary care providers and ophthalmologists could streamline early diagnosis.

Researchers highlighted that the tool’s mobile accessibility allows for global reach, potentially screening billions. The findings were presented at the annual meeting of The Endocrine Society, though they have yet to be peer-reviewed.

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Tech giants work to avert an AI‑driven energy crisis

The AI boom is triggering alarms in the energy sector, with data centres expected to consume 3% of the world’s electricity by 2030, double today’s share. This projection has spurred tech firms to pursue aggressive efficiency strategies.

Control systems powered by AI regulate cooling more precisely, while liquid cooling systems replace inefficient air-based approaches. Cutting-edge chips and more innovative software have already yielded energy savings of 20–30% per workflow.

Infrastructure improvements mean data-centre support systems now consume just 10% of the energy that powering the servers does. Despite these advances, the total energy demand continues to rise, prompting investments in technology upgrades and low-carbon power sources.

A global race is underway as US and Chinese companies push for increasingly efficient AI chips. Still, experts warn that overall consumption will grow, so efficiency alone won’t be enough. Broad energy planning and sustainable strategies are critical to avoid a looming power crunch as AI proliferates.

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Pennsylvania criminalises malicious deepfakes under new digital forgery law

Governor Shapiro has enacted a new statute enhancing Pennsylvania’s legal stance on AI-generated content by defining deceptive deepfakes as digital forgery.

The law criminalises creating and distributing such content, mainly when used for deceit, highlighting a proactive response to deepening online threats.

The legislation differentiates between uses of deepfakes: non-consensual impersonation will result in misdemeanour charges, while cases involving fraudulent intent, such as financial scams or political manipulation, are now classified as third-degree felonies.

Support for the bill was bipartisan and overwhelming in the state legislature. Its sponsors emphasised that while it deters harmful digital impersonation, it also carefully safeguards legitimate speech, including parody, satire, and artistic expression.

With Pennsylvania now among the growing number of states implementing deepfake regulations, this development aligns with a national trend to regulate AI-generated digital forgeries. It complements earlier state-level laws and federal initiatives to curb AI’s misuse without stifling innovation.

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AI tool uses walking patterns to detect early signs of dementia

Fujitsu and Acer Medical are trialling an AI-powered tool to help identify early signs of dementia and Parkinson’s disease by analysing patients’ walking patterns. The system, called aiGait and powered by Fujitsu’s Uvance skeleton recognition technology, converts routine movements into health data.

Initial tests are taking place at a daycare centre linked to Taipei Veterans Hospital, using tablets and smartphones to record basic patient movements. The AI compares this footage with known movement patterns associated with neurodegenerative conditions, helping caregivers detect subtle abnormalities.

The tool is designed to support early intervention, with abnormal results prompting follow-up by healthcare professionals. Acer Medical plans to expand the service to elderly care centres across Taiwan by the end of the year.

Fujitsu’s AI was originally developed for gymnastics scoring and adapted to analyse real-world gait data with high accuracy using everyday mobile devices. Both companies hope to extend the technology’s use to paediatrics, sports science, and rehabilitation in future.

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South Korean firm unveils faster AI data centre architecture with CXL-over-Xlink

South Korean company Panmnesia has introduced a new architecture for AI data centres aimed at improving speed and efficiency.

Instead of using only PCIe or RDMA-based systems, its CXL-over-Xlink approach combines Compute Express Link (CXL) with fast accelerator links such as UALink and NVLink.

The company claims this design can deliver up to 5.3 times faster AI training and reduce inference latency sixfold. By allowing CPUs and GPUs to access large shared memory pools via the CXL fabric, AI workloads are no longer restricted by the fixed memory limits inside each GPU.

It will enable data centres to scale compute and memory independently, adapting to changing workload demands without hardware overprovisioning.

Panmnesia’s system also reduces communication overhead using accelerator-optimised links for CXL traffic, helping maintain high throughput with sub-100ns latency.

The architecture incorporates a hierarchical memory model blending local high-bandwidth memory with pooled CXL memory, alongside scalable CXL 3.1 switches that connect hundreds of devices efficiently without bottlenecks.

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