Nvidia is revolutionising its chip design process by leveraging large language models (LLMs) and autonomous AI agents. These innovations are being used to speed up the development of GPUs, CPUs, and networking chips, significantly enhancing design quality and productivity. The models include prediction, optimisation, and automation tools, which help engineers improve designs, generate code, and debug issues more efficiently.
The company has trained an LLM specifically on Verilog, a hardware description language, to accelerate the creation of its systems. This model assists in speeding up the design and verification processes while automating manual tasks, supporting Nvidia’s goal of maintaining a yearly product release cycle. As Nvidia continues to develop increasingly complex architectures, such as the Blackwell architecture, these AI tools are vital in meeting the challenges of next-generation designs.
At the Hot Chips conference in the US, Mark Ren, Nvidia’s director of design automation research, will provide insights into these AI models. He will highlight their applications in chip design, focusing on how agent-based systems powered by LLMs transform the field by autonomously completing tasks, interacting with designers, and learning from experience.
The use of AI agents for tasks like timing report analysis and cell cluster optimisation has already gained recognition, with a recent project winning best paper at the IEEE International Workshop on LLM-Aided Design. Nvidia’s advancements demonstrate the critical role of AI in pushing the boundaries of chip design.
China’s ambition to lead in humanoid robot development was evident at the recent World Robot Conference in Beijing, where companies showcased innovative and cost-effective solutions. Wisson Technology, known for its flexible robotic arms powered by pneumatic artificial muscles, showed its ability to produce these at a fraction of the cost of traditional robotic arms, signalling a shift in production methods.
Despite the advancements, challenges remain in the supply chain. Yi Gang, founder of Ti5 Robot, pointed out product reliability issues, particularly in motion-control components like harmonic gears. These concerns limit production volumes, underscoring the need for further improvements in the industry.
China’s efforts in robotics are bolstered by President Xi Jinping’s push for technological advancement, with smart driving advancements contributing to progress in the field. The country’s robotics market, the largest globally, is reshaping traditional industries, from manufacturing to education and healthcare. Speaking at the close of the conference, Premier Li Qiang emphasised the need to stabilise the supply chain and expand robot usage across various sectors. Describing robots as a feature of technological innovation, he underscored their importance in China’s high-end manufacturing goals.
Despite its declining quarterly revenue, Baidu, in its statement, assured people that its leading position in AI in China will position it to navigate the increasingly competitive market. The comment comes from an AI price war in China, where companies are increasingly lowering the prices of large language models powering generative AI technologies.
Ernie, Baidu’s large language model, has been integrated into various applications to enhance user experience and is touted to be a competitor to OpenAI’s GPT. According to Baidu CEO Robin Li, the company’s Ernie platform processes over 600 million AI requests daily, the highest volume among Chinese firms. Li added, ‘Competition will be fierce over the next 2 to 3 years.’
As China’s dominant search engine, most revenue comes from ads. However, the company has strategically pivoted to AI by investing significantly in the sector to position itself as an ‘AI company’. The company has expanded its AI offerings by introducing a paid version of its Ernie-powered chatbot for public use and offering API services to developers via cloud computing. “Our advertising business is currently facing pressure caused by a combination of external factors and our proactive efforts to accelerate the AI-driven renovation of search,” Li said during a conference call with analysts.
Why does this matter?
The dipped revenue indicates Baidu’s difficulty in transitioning from search ads to AI as China faces an economic slump. Baidu’s news of prioritising AI as its search revenue stalls can be located as a part of the broader tech trend where, with the AI gold rush, companies increasingly look to increase their AI portfolios to ensure they retain their competitiveness and don’t fall behind in the AI market that is expected to accrue massive business value.
Perplexity AI, backed by Jeff Bezos and Nvidia, has announced its intention to initiate advertisement on its AI-based search engine platform by the fourth quarter of the year. Last month, the company rolled out a publisher’s program with partners comprising IME, Der Spiegel, Fortune, Entrepreneur, The Texas Tribune, and WordPress.
The AI-powered search engine space is still in its infancy, opening a massive market for new players. Among the big tech giants, Google has integrated AI in its search by providing AI-generated summaries or overviews for each search request. Meanwhile, its rival Microsoft has integrated OpenAI technology and launched the AI-powered Bing.
Why does it matter?
This move can potentially threaten Google’s dominant position in the industry. Through its search engine supremacy for two decades, Google became one of the world’s most valuable companies through its ad-based revenue model. Since ChatGPT launched, existing and upcoming search engines have attempted to integrate AI into web search and bring about a new business model in the search engine space.
Several Chinese state-linked entities are turning to cloud services to access restricted US technology, according to recent public tender documents. By using cloud platforms like Amazon Web Services (AWS), these entities gain access to advanced chips and AI capabilities that would otherwise be unavailable due to US trade restrictions.
Entities like Zhejiang Lab and the National Center of Technology Innovation for EDA have expressed interest in using AWS for AI development. Others, such as Shenzhen University and Fujian Chuanzheng Communications College, have reportedly utilised Nvidia chips through cloud services, circumventing US export bans.
Microsoft’s Azure platform has also attracted attention from Chinese institutions like Chongqing Changan Automobile Co and Sichuan University, which are exploring generative AI technology. The ability to integrate these advanced tools into their systems is seen as critical for maintaining competitiveness.
Concerns remain over the use of US technology by Chinese organisations, especially those with potential military applications. Universities such as Southern University of Science and Technology and Tsinghua University have pursued cloud access to Nvidia chips, despite US efforts to restrict such technology transfers.
Google has appointed Noam Shazeer, a former Google researcher and co-founder of Character.AI, as co-lead of its main AI project, Gemini. Shazeer will join Jeff Dean and Oriol Vinyals in overseeing the development of AI models at DeepMind, Google’s AI division, which are set to enhance products like Search and Pixel smartphones.
Shazeer rejoined Google after founding Character.AI in 2021. The tech giant secured his return by paying billions and striking a licensing agreement with his former company. Shazeer expressed excitement in a memo to staff, praising the team he has rejoined.
Originally joining Google in 2000, Shazeer was instrumental in the 2017 research that ignited the current AI boom. Character.AI, which leverages these advancements, has attracted significant venture capital, reaching a $1 billion valuation last year.
Google’s decision to bring Shazeer back echoes similar strategies by other tech giants, although these moves have drawn regulatory scrutiny. In related news, a US judge recently ruled that Google’s search engine violated antitrust laws by creating an illegal monopoly.
Tensions are rising within Google’s AI research division, DeepMind, as over 200 employees have expressed concerns regarding the company’s involvement in defence contracts. The discontent stems from Google’s reported agreements to provide AI and cloud computing services to military organisations, including the Israeli military.
In an internal letter circulated in May, the employees voiced their unease, emphasising that such contracts contradict Google’s mission to lead in ethical AI development. The letter argues that any association with military activities could undermine the company’s commitment to responsible AI, as stated in Google’s AI Principles.
Why does this matter?
The dissent highlights a growing cultural divide between DeepMind and Google, particularly regarding the ethical implications of their technologies. DeepMind, acquired by Google in 2014, had previously been assured that its AI developments would not be used for military or surveillance purposes, a promise now seemingly in jeopardy.
The situation underscores the ongoing ethical debates within tech companies about the application of AI in military contexts, raising questions about the balance between innovation and ethical responsibility.
California’s revised bill on AI regulation, SB 1047, has drawn significant attention from tech companies, including San Francisco-based Anthropic, a competitor to OpenAI. The bill, introduced by State Senator Scott Wiener, seeks to mandate safety testing for advanced AI models that are costly to develop and establish a ‘kill switch’ for malfunctioning AI.
While the bill has faced opposition from major tech players like Google, Meta, and OpenAI, Anthropic’s CEO, Dario Amodei, has noted that recent amendments have improved the bill, making its benefits potentially outweigh its costs, though some concerns remain. Tech companies have largely opposed the bill, arguing that it could hinder AI development in California and create an uncertain legal environment.
Meta, in particular, warned that the bill could make the state less attractive for AI innovation. OpenAI has advocated for federal rather than state regulation, citing the bill’s potential to complicate the legal landscape for AI developers.
Despite these concerns, the revised version of SB 1047 has been seen as a step forward by some in the tech community. Amodei acknowledged that while the bill’s initial version raised fears of stifling innovation, the amendments have alleviated many of those worries. However, he still sees some aspects of the bill as potentially problematic.
D-ID has recently launched an innovative AI video translation tool that allows creators to automatically translate their videos into multiple languages while simultaneously cloning the speaker’s voice and synchronising lip movements to match the translated audio. This groundbreaking feature enhances video content accessibility for a global audience, making it easier for creators to connect with viewers across language barriers.
The tool supports translations into 30 languages, including widely spoken languages such as Arabic, Mandarin, Japanese, Hindi, Spanish, and French, enabling creators to reach diverse audiences and expand their global footprint effectively. By automating the translation and dubbing process, D-ID aims to reduce localisation costs for businesses and content creators, facilitating the scaling of video marketing and communication strategies worldwide.
Additionally, the tool enters a competitive landscape where other companies, such as YouTube and Vimeo, are improving video translation capabilities as video continues dominating digital communication. D-ID’s technology targets individual creators and enterprise customers looking to enhance global outreach through effective video localisation strategies.
By combining voice cloning and lip-syncing, D-ID’s AI Video Translate creates a seamless multilingual viewing experience, positioning the company as a key player in the future of AI-driven content creation.
South Tyneside and Sunderland NHS Foundation Trust will continue using AI technology after a successful trial demonstrated its effectiveness in identifying bowel lesions. The trial involved 2,032 patients across 10 centres in the UK and used the GI Genius AI device during colonoscopies. After a while, this technology detected an additional 0.36 adenomas per procedure, helping to prevent potential cancer development.
Professor Colin Rees, a consultant gastroenterologist at the trust, highlighted the significance of the AI device in saving lives by increasing the detection of bowel abnormalities. The AI was particularly effective in identifying small or flat polyps often missed by the human eye, which can be crucial in early cancer prevention.
Bowel cancer remains a significant health concern in the UK, with 43,000 new cases and 16,000 deaths annually. The AI’s ability to detect adenomas in an extra eight out of 100 people without increasing complications is a promising advancement for medical professionals.
The trial, led by South Tyneside and Sunderland NHS Foundation Trust and Newcastle University, has encouraged the trust to integrate AI technology into routine practice. As the AI continues to learn from images, its performance is expected to improve further, offering hope for wider adoption in the future.
