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Semiconductor design set for AI revolution with new Synopsys tool

Synopsys has introduced AgentEngineer, an AI-powered technology designed to streamline semiconductor design by automating complex engineering tasks.

The company, which provides software for chip design, aims to help engineers cope with increasing demands as semiconductor firms like Nvidia build advanced AI server systems with thousands of chips.

CEO Sassine Ghazi highlighted the growing pressure on engineers to manage complexity, meet tight deadlines, and control costs.

The AI-driven tool will initially assist human engineers by handling specific tasks, such as verifying circuit designs. Over time, it is expected to coordinate the development of intricate systems comprising multiple chips and components, ensuring efficient project delivery.

The company’s technology and development lead, Shankar Krishnamoorthy, emphasised that AI will be crucial in expanding research and development capacity without requiring larger engineering teams.

With the pace of AI computing accelerating, semiconductor companies face mounting challenges in chip design. Synopsys believes AI will play a critical role in overcoming these difficulties, making the process faster and more efficient.

The new technology is part of a broader industry shift toward AI-driven automation in engineering.

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Ampere Computing joins SoftBank in AI-focused expansion

SoftBank has announced a $6.5 billion acquisition of US chip startup Ampere Computing, marking a major step in its investment in AI infrastructure.

The deal, paid entirely in cash, reflects founder Masayoshi Son’s growing focus on AI as a transformative technology. Ampere produces data centre CPUs based on an architecture from SoftBank’s majority-owned Arm Holdings, with customers including Oracle.

The acquisition follows a series of multi-billion-dollar AI investments by SoftBank, including funding for OpenAI, the Stargate AI data centre project, and Cristal, an AI services joint venture in Japan.

Ampere, founded in 2018 by former Intel president Renee James, developed its own custom CPU cores—an approach typically seen in larger firms like Apple and Qualcomm.

Under SoftBank’s ownership, the company will operate alongside Arm, strengthening SoftBank’s growing collection of AI-focused chip technology firms.

Masayoshi Son described the move as part of his vision for ‘artificial super intelligence,’ highlighting the need for advanced computing power.

While SoftBank has seen mixed results in past investments, such as its troubled backing of WeWork, the company continues to place high-stakes bets on emerging technologies.

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AI-powered robot dog mimics human learning process

Swedish AI startup IntuiCell has introduced Luna, a robot dog with a functional digital nervous system that enables it to learn and adapt like humans and animals.

Unlike traditional AI models that rely on vast datasets and pre-training, Luna learns through real-world interactions.

The company has even hired a professional dog trainer to teach Luna how to walk, mimicking the way neurons process information in biological systems.

CEO Viktor Luthman described Luna as a breakthrough in AI, allowing machines to learn without requiring high-powered data centres or offline simulations.

The technology, he says, could eventually lead to advanced autonomous robots capable of operating in unpredictable environments such as space and deep-sea exploration.

Future iterations could assist in disaster response or even contribute to constructing habitats on Mars.

Founded as a spin-off from Lund University in 2020, IntuiCell has received funding from Sweden’s Navigare Ventures, Norway’s SNÖ Ventures, and the European Union.

The company believes that Luna’s capabilities could mark a significant step forward in the development of humanoid and autonomous robots, with applications far beyond current AI-powered machines.

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Nvidia CEO predicts humanoid robots will revolutionise manufacturing

Nvidia CEO Jensen Huang believes that humanoid robots will soon be widely used in manufacturing, possibly within the next five years.

Speaking at the company’s annual developer conference, Huang unveiled new software tools designed to improve robots’ ability to navigate the world.

Huang stated that the manufacturing industry would likely lead the way in adopting humanoid robots, due to its controlled environment and well-defined tasks.

He emphasised the economic value, with robots potentially costing around $100,000 to rent, making them a good investment.

The CEO’s predictions highlight the growing role of AI in automation, with Huang confident that humanoid robots will soon be an integral part of factory operations.

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Microsoft invests $2.2 billion in Malaysian cloud expansion

Microsoft is set to launch its first cloud region in Malaysia, featuring three data centres in the greater Kuala Lumpur area.

The centres, known as Malaysia West, will begin operations by mid-year, marking a significant step in the company’s $2.2 billion investment in the country.

However, this move is part of Microsoft’s broader plan to expand its cloud and AI services in Southeast Asia. Microsoft estimates the investment will generate $10.9 billion in revenue and create over 37,000 jobs in Malaysia over the next four years.

Laurence Si, managing director of Microsoft Malaysia, stated that the company’s operations in Malaysia remain on track despite concerns over US export controls on semiconductor chips.

Microsoft remains confident in its relationships with stakeholders and its ability to meet its investment commitments.

Local businesses are expected to benefit from enhanced cloud and AI capabilities, with the country aiming to become a leading hub for technological innovation in the region.

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AI firm Prezent aims for global expansion after securing fresh investment

AI startup Prezent has raised $20 million in fresh funding to refine its AI-powered slide deck creation platform and expand into new markets.

The Los Altos-based company, which also operates in Bengaluru, aims to help businesses create high-quality presentations tailored to industry-specific language and terminology.

Founded in 2021 by Rajat Mishra, Prezent combines generative AI with proprietary data from millions of slide decks to offer customised business communication solutions.

The company’s AI assistant, Astrid, enables users to upload documents such as Excel files and PDFs while providing relevant company-specific context. Prezent’s technology suggests layouts and formats for presentations, helping users streamline their workflow.

For those on tight deadlines, an expedited service combines AI with human reviewers to deliver polished, professional-grade decks overnight. The platform currently serves around 150 Fortune 2000 companies, particularly in biopharma and tech, and is now targeting financial services and manufacturing.

With plans to expand into Europe, Japan, and Singapore, Prezent is also developing APIs to allow developers to generate presentations directly from chatbots, apps, and search engines.

Last year, the company reported over $10 million in annual recurring revenue and now has nearly 200 employees, most of whom work remotely from India.

The latest investment, led by Greycroft with participation from Zoom Ventures and others, values Prezent at well over $100 million.

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OpenAI and Google face lawsuits while advocating for AI copyright exceptions

OpenAI and Google have urged the US government to allow AI models to be trained on copyrighted material under fair use.

The companies submitted feedback to the White House’s ‘AI Action Plan,’ arguing that restrictions could slow AI progress and give countries like China a competitive edge. Google stressed the importance of copyright and privacy exceptions, stating that text and data mining provisions are critical for innovation.

Anthropic also responded to the White House’s request but focused more on AI risks to national security and infrastructure rather than copyright concerns.

Meanwhile, OpenAI and Google are facing multiple lawsuits from news organisations and content creators, including Sarah Silverman and George R.R. Martin, who allege their works were used without permission for AI training.

Other companies, including Apple and Nvidia, have also been accused of improperly using copyrighted material, such as YouTube subtitles, to train AI models.

As legal challenges continue, major tech firms remain committed to pushing for regulations that support AI development while navigating the complexities of intellectual property rights.

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New AI model by Stability AI creates 3D videos from images

Stability AI has unveiled its latest AI model, Stable Virtual Camera, designed to convert 2D images into dynamic 3D video scenes. Announced in a company blog post, the model enables users to create immersive videos with realistic depth and perspective using up to 32 input images. It generates ‘novel views’ of a scene, offering various preset camera movements, including Spiral, Dolly Zoom, Move, and Pan.

The tool is currently available as a research preview and allows users to generate videos in square (1:1), portrait (9:16), and landscape (16:9) formats, with a maximum length of 1,000 frames. However, Stability AI warns that certain images, such as those with people, animals, or complex textures like water, may produce lower-quality results. Highly ambiguous or irregularly shaped objects may also lead to visual artifacts.

Stable Virtual Camera is available for research use under a non-commercial license and can be downloaded from AI development platform Hugging Face. The launch follows a turbulent period for Stability AI, which has recently undergone leadership changes, secured new investments, and expanded into new AI applications, including generative audio. With this latest innovation, the company aims to solidify its position in the competitive AI market.

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Nvidia holds back on optical technology for GPUs

Nvidia’s CEO, Jensen Huang, has stated that a promising new chip technology, co-packaged optics, is not yet reliable enough for use in the company’s flagship GPUs.

The technology, which uses laser beams to transfer data via fiber optic cables instead of traditional copper, is more energy-efficient and faster.

However, Huang emphasized that copper connections remain ‘orders of magnitude’ more reliable than today’s optical alternatives, making them the preferred choice for now.

Speaking at Nvidia’s annual developer conference in San Jose, Huang announced that the company will use co-packaged optics in two upcoming networking chips designed for server switches, increasing their energy efficiency by three and a half times.

These switch chips will be released later this year and into 2026, marking a gradual technological step forward. However, Huang clarified that Nvidia currently has no plans to implement optical connections between GPUs, as reliability remains a key priority for its AI-focused customers like OpenAI and Oracle.

Silicon Valley startups such as Ayar Labs, Lightmatter, and Celestial AI have invested heavily in co-packaged optics, seeing it as essential for building more powerful AI systems. Nvidia itself has backed some of these ventures, despite Huang’s cautious approach.

While optical connections could eventually help AI models process complex tasks more efficiently, Nvidia is prioritizing proven technology for its near-term roadmap, ensuring stability in an industry preparing to invest hundreds of billions in AI infrastructure.

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Tencent sees surge in profits and revenue

Tencent, a leading Chinese tech giant, has reported impressive financial results for the fourth quarter and full year, boosted by its strategic investment in AI.

For the three months ending December 31, Tencent’s net profits soared by 90% year-on-year to 51.3 billion yuan ($7.1 billion), while its revenue increased by 11% to 172.4 billion yuan, surpassing analyst expectations.

The company’s strong performance was attributed to AI-driven enhancements in its advertising platform, growing video account engagement, and solid results from its gaming division.

For the full year, Tencent’s revenue reached 660.3 billion yuan, up 8% from the previous year, with net profits jumping 68% to 194.1 billion yuan.

CEO Pony Ma highlighted the role of AI in driving innovation, noting that Tencent had reorganized its AI teams to focus on fast product development and advanced model research.

The company’s stock price has surged to its highest in nearly four years, reflecting strong investor confidence.

The increased AI interest follows the unexpected global success of DeepSeek, a Chinese startup whose chatbot development caught the attention of investors, positioning China as a competitor to Western tech leaders like OpenAI.

Ma expressed Tencent’s admiration for DeepSeek and confirmed its active integration of their technology. Tencent has also started testing its own AI model, ‘Hunyuan Thinker’, which aims to offer more professional and human-like responses.

Despite its financial successes, Tencent faces ongoing challenges, including a sluggish domestic economy and political tensions, particularly with the US.

In January, the US added Tencent to a list of firms linked to China’s military, a move the company and the Chinese government have criticized as unjustified.

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