Taiwanese prosecutors on Monday indicted a former deputy manager at Taiwan Semiconductor Manufacturing Company (TSMC) for allegedly stealing trade secrets involving technologies designated as national core technologies, with the intent to use them in China.

The defendant, identified by the surname Chen, faces charges under Taiwan’s National Security Act and the Trade Secrets Act. Prosecutors are seeking a seven-year prison sentence.

According to the indictment, Chen conspired with a Hong Kong national between 2023 and 2024 to establish CSMAC, a semiconductor materials analysis company in China. He is accused of copying 21 TSMC documents containing national core technologies and other proprietary trade secrets for use in the new venture.

TSMC, the world’s largest contract chipmaker and a key supplier to companies such as Nvidia and Apple, detected the unauthorized copying through an internal investigation and successfully recovered all duplicated documents. The Hong Kong co-conspirator was not prosecuted because he had died. Chen remains in custody, and Reuters was unable to reach him for comment. TSMC declined to comment on the case.

Prosecutors described this as Taiwan’s first indictment involving the alleged theft of trade secrets related to technologies officially designated as national core technologies for intended use in China.

The case underscores heightened concerns in Taiwan over China’s efforts to recruit Taiwanese semiconductor talent and acquire advanced chip know-how. In response, Taiwan has significantly tightened protections for technologies deemed critical to its economic and national security.

MacDailyNews Take: TSMC clearly plays a central role in the global semiconductor supply chain, making the protection of its intellectual property a matter of strategic importance far beyond Taiwan’s borders.

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The post Taiwan indicts former TSMC deputy manager for alleged theft of national core technology trade secrets intended for China appeared first on MacDailyNews.

Apple is quietly shopping for AI chip companies. According to a new report from The Information, the company has been approaching chip startups and consulting with bankers about potential acquisitions — a notable shift for a firm long known for its reluctance to make big hardware buys.

The move comes as Apple grapples with limitations in its current AI infrastructure. Its Private Cloud Compute servers, which power parts of Apple Intelligence, currently rely on internally designed M2 Ultra chips. These have proven insufficient for handling larger, more demanding AI models.

The Siri Overhaul Problem

One concrete example stands out: Apple has been working on a major Siri overhaul powered in part by Google’s Gemini models through a partnership. When engineers tried running these advanced models on Apple’s own servers, the M-series hardware fell short. As a result, more complex Siri tasks are now routing through Nvidia GPUs hosted in Google’s cloud infrastructure.

This dependency clashes with Apple’s long-standing preference for controlling its own silicon and protecting user privacy through on-device and Private Cloud Compute processing.

Baltra Delayed

Internally, Apple has been developing its first dedicated AI server chip, codenamed Baltra. The company had originally targeted a 2026 launch, but the timeline has slipped. Baltra is designed as a purpose-built server ASIC (with Broadcom contributing key networking and interconnect technology) to reduce reliance on third-party GPUs for cloud AI workloads.

The reported pursuit of acquisitions suggests Apple wants to accelerate progress on its next-generation server silicon — either by bringing in specialized talent and IP or by acquiring teams that have already solved similar challenges.

A Rare Shift in M&A Approach

Apple has historically avoided large acquisitions, preferring to build technology in-house. Its most recent notable deal was the January 2026 acquisition of Israeli audio AI startup Q.ai (reportedly valued around $2 billion). With roughly $45.6 billion in cash and cash equivalents as of late March 2026, Apple certainly has the financial firepower if it chooses to move.

This new interest in chip startups marks a pragmatic acknowledgment that the AI hardware race — particularly in data center-scale inference and training — moves extremely fast. While Apple excels at designing efficient mobile and laptop chips, scaling specialized AI accelerators for servers is a different challenge that hyperscalers like Google, Amazon, and Meta have been tackling for years.

Broader Context

This development comes just days after Apple announced a major multi-year expansion of its partnership with Broadcom, worth more than $30 billion. The deal includes custom silicon components and supports U.S. manufacturing expansion in Colorado. It underscores Apple’s broader push to strengthen its custom silicon capabilities while also highlighting how much it still relies on external partners for certain advanced technologies.

What It Means

If Apple follows through on acquisitions, it could help close the gap in its cloud AI infrastructure faster than organic development alone would allow. Success here would support more ambitious on-device and private-cloud AI features without heavy dependence on external clouds and GPUs.

It would also represent a meaningful evolution in Apple’s strategy: from a company that largely designs its own chips from scratch to one willing to acquire specialized expertise to stay competitive in the AI era.

The coming months will reveal whether these discussions lead to actual deals — and whether they can meaningfully accelerate Apple’s ability to run sophisticated AI models on its own terms.

MacDailyNews Take: The mad scramble to catch up continues. Hopefully, new Apple CEO John Ternus can quickly kick things back into high gear after far too many years of coasting along in neutral.

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Após atingir três valores recordes só nesta semana, as ações da Apple [$AAPL] mantiveram a ascensão nesta sexta-feira e, graças a uma alta de 0,14%, elas valem agora US$333,74 — US$0,48 a mais do que o valor registrado ontem e um novo recorde histórico.

Já o pico do pregão foi de US$334,98, o que também representa um recorde em relação ao penúltimo valor máximo registrado (US$334,68).

Com relação ao ranking das empresas de capital aberto mais valiosas do mundo, a Apple segue na segunda posição, agora com um market cap de US$4,902 trilhões. Porém, algo interessante aconteceu hoje: ela ultrapassou brevemente a NVIDIA [$NVDA] durante o pregão, assumindo a posição de empresa mais valiosa do mundo por algum tempo; no fechamento da Nasdaq, porém, ela acabou voltando ao segundo lugar.

Isso foi facilitado após mais um dia de queda nas ações da fabricante de GPUs (o segundo seguido), desta vez de -2,21%, o que fez com que os papéis da empresa fechassem valendo US$202,81. Já o market cap está agora em US$4,912 trilhões — ou seja, apenas US$10 bilhões a mais do que o da Apple.

A Alphabet [$GOOG], empresa-mãe do Google, segue na terceira posição desse ranking, agora um market cap de US$4,224 trilhões. Assim como a NVIDIA, as ações da gigante de Mountain View também recuaram hoje, fechando o dia valendo US$346,12 (-2,17%).

Shift in pecking order illustrates that investors are reassessing outlook for artificial intelligence

Apple overtook Nvidia on Friday to become the world’s most valuable company, reshuffling the top ranks of tech heavyweights as investors reassess the outlook for artificial intelligence.

Apple was last valued at $4.88tn as ⁠its shares held steady, while Nvidia ⁠was roughly at $4.86tn, ​after a 3.5% decline.

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© Photograph: Michael M Santiago/Getty Images

© Photograph: Michael M Santiago/Getty Images

© Photograph: Michael M Santiago/Getty Images

Em 1995, a SEGA investiu 5 milhões de dólares na Nvidia e salvou a empresa da falência. Três décadas depois, Jensen Huang e o CEO da SEGA celebraram a parceria em Akihabara, anunciando que jogos clássicos e novos títulos como o Virtua Fighter Crossroads chegarão aos novos PCs RTX Spark.

The post RTX Spark volta a unir Nvidia com a SEGA 30 anos depois do NV1 appeared first on Tek Notícias.

Apple momentarily surpasses Nvidia to reclaim the title of world’s most valuable company but ends the week at No. 2 on the list.

(via Cult of Mac - Your source for the latest Apple news, rumors, analysis, reviews, how-tos and deals.)

Japan Wires AI Into Medicine Japan built the world’s most trusted names in medical hardware and biopharma. This

US regulators cleared ZTE and Maginfra to buy Nvidia H200 chips, while a Kingsoft Cloud subsidiary received approval for AMD chips.

A indústria da beleza está a evoluir para um modelo mais preditivo, centrando-se na capacidade de antecipar as necessidades da pele através de dados, diagnóstico e IA. Ao TEK Notícias, Guive Balooch explica como esta mudança impacta o desenvolvimento de novos produtos e a relação com os consumidores.

The post O mundo da beleza está cada vez mais tecnológico. Futuro passa por “ouvir” as necessidades da pele antes de reagir appeared first on Tek Notícias.

A Nvidia continua a apostar no ecossistema de robótica e apresentou o primeiro sistema de segurança que prepara o ambiente para os robots agirem em ambientes dinâmicos, ao lado de trabalhadores humanos.

The post Nvidia lança o Halos para colocar robots a trabalhar ao lado de humanos em segurança appeared first on Tek Notícias.

Nvidia’s “Halos for Robotics” system brings autonomous vehicle safety tools to humanoid robots designed to work near people in factories.

Groq raised $650 million to expand its AI inference cloud after a Nvidia licensing deal, as demand for production AI compute grows.

Nvidia and telecom partners including SoftBank Corp and NTT Data plan to demonstrate a stack of data, models, simulation tools and secure runtimes at DTW Ignite 2026, aimed at helping operators move from task-based automation to fully autonomous network operations.

The company argues while generative AI has delivered strong returns in network management, customer care and back-office automation, most of the impact has been limited to speeding up predetermined steps while humans still correlate insights and direct next actions.

Nvidia’s claims automation is now “the launchpad to autonomy” rather than the end goal, with AI agents expected to proactively monitor for problems and coordinate changes across network, IT and business systems while keeping humans in control of policy.

Nvidia cites figures showing 54% of telecom operators view data-related issues as their biggest obstacle to building telecom-specific AI models, largely because the most valuable network and customer data is too sensitive to use directly for training.

SoftBank Corp is tackling the problem by using Nvidia’s NeMo Safe Synthesizer and NeMo Anonymizer tools to generate privacy-preserving synthetic datasets which mirror the structure of real network performance and configuration datasets.

Those datasets are being used to fine-tune its Large Telecom Model (LTM) and build specialised network agents.

On the runtime side, Nvidia stated its NemoClaw blueprints and OpenShell secure runtime are designed to give long-running agents policy-based guardrails and sandboxed access to telecom systems, allowing operators to expand agent responsibilities while keeping behaviour auditable and governed.

NTT Data is applying Nvidia’s open Nemotron models alongside NemoClaw to build agents which track long-term network performance trends and escalate anomalies to specialised research agents for deeper telemetry analysis.

Other partners building on the same framework include: AdaptKey, which is piloting self-healing 5G agents with operators; ServiceNow, which is bringing its Project Arc incident-response tooling to telecom network operations centres; and Tata Consultancy Services, which is developing a multi-fidelity AI sensor architecture for faster anomaly detection.

Simulation is the third pillar of the effort, intended to let agents test recommendations in near-real-time digital environments before acting on live systems.

Software company Forsk stated its GPU-accelerated radio propagation model now achieves ray-tracing-level accuracy up to 200 times faster than CPU-only systems, while Viavi Solutions reports order-of-magnitude gains in RAN simulation throughput after shifting workloads to Nvidia’s RTX Pro 6000 Blackwell GPUs.

KDDI and KDDI Research, working with Nvidia, Keysight and Samsung Research America, are building a high-fidelity RAN digital twin aimed at the 6G era, allowing multiple autonomous agents to simulate scenarios for future radio conditions and traffic shifts.

The TM Forum’s DTW Ignite conference runs 23–25 June 2026 in Copenhagen.

The post Nvidia rallies telcos around AI agents at DTW Ignite appeared first on Mobile World Live.

Nvidia unveiled what it described as the industry’s first full-stack safety platform for physical AI designed to accelerate the deployment of humanoid robots in industrial environments.

The company said its expanded Halos platform combines AI compute, system software, sensors and inspection tools into a single safety architecture aimed at helping robotics companies build and certify autonomous systems operating alongside human workers.

The chipmaker explained as robots become more autonomous and increasingly rely on AI foundation models, distributed sensors and accelerated computing, “scaling these systems requires a full-stack safety architecture” before they can be trusted to work alongside humans in factories, warehouses and logistics operations.

The stack includes Nvidia’s IGX Thor industrial computing platform, Holoscan Sensor Bridge for sensor connectivity and Halos OS software stack.

Nvidia also opened its Halos AI Systems Inspection Lab to robotics partners, aiming to help them complete pre-certification testing and validate safety systems before approaching regulators.

Digit
Humanoid robotics company Agility Robotics is the first partner to adopt elements of the platform into the proprietary safety system for its Digit humanoid robot, which is already being deployed for industrial applications with customers including Amazon, Schaeffler and Toyota Motor Manufacturing Canada.

The robotics player will also use Nvidia’s Inspection Lab to validate Digit’s safety-related software, AI components and cybersecurity protections against strict standards.

Agility Robotics CEO Peggy Johnson said: “For humanoids to deliver value at scale, safety has to be built into the robot and validated across the entire system.”

She added the partnership with Nvidia “extends our leadership in responsible automation”, describing it as “a non-negotiable requirement for bringing humanoids safely into industrial workflows”.

Deepu Talla, VP of robotics and edge AI at Nvidia said: “Physical AI is transforming how factories, warehouses and logistics operations work. He added developers will be able to “harness Nvidia’s proven autonomous vehicle safety foundation to develop safer robots faster” and deploy systems “alongside workers with greater confidence”.

The post Nvidia rolls out robot safety platform appeared first on Mobile World Live.

Does a thought-experiment about US ascendancy in the technology say as much about AI jitters as it does about the reality?

It’s 2031 and the US and China are about to tear Europe into pieces.

The US ploughed vast sums into datacentres and the EU did not. China built robots and Europe did not. American companies “restructured” their workflows around AI and fired people, while EU workers went on long lunch breaks and handed over administrative tasks to the AI model Claude.

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© Photograph: Hannibal Hanschke/EPA

© Photograph: Hannibal Hanschke/EPA

© Photograph: Hannibal Hanschke/EPA

AWS is in talks to sell its chips to other data centers. CEO Andy Jassy has said this represents a $50 billion opportunity for the company.