Vietnam’s Prime Minister Pham Minh Chinh has launched a strategic initiative to enhance the country’s capabilities in semiconductors, AI, and cloud computing. The initiative, outlined in Dispatch No. 83/CD-TTg, aims to develop a skilled workforce through targeted education and training in these critical technology sectors. The initiative calls for collaboration among various government bodies, including ministers and local authorities, to implement measures to drive these industries’ advancements.
The Ministry of Education and Training (MoET) leads this effort by guiding public and private universities to establish specialised units focused on semiconductor technology, AI, and cloud computing. The project includes creating new schools and departments dedicated to advancing research and training. The MoET will also modernise curricula by integrating cutting-edge technologies and AI into teaching methodologies while fostering partnerships with businesses and research institutions.
In addition, the Ministry of Planning and Investment will develop a strategic project for nurturing human resources in the semiconductor industry, with a long-term vision extending to 2050. The plan will also encompass AI and cloud computing, emphasising the establishment of innovation ecosystems. Meanwhile, the Ministry of Science and Technology will prioritise scientific research in these fields and create mechanisms to attract international talent.
Local government leaders are encouraged to attract investments to build semiconductors, AI, and cloud computing ecosystems. Deputy Prime Minister Le Thanh Long will oversee the implementation of this initiative, which aims to position Vietnam as a leader in these technology sectors, leveraging education and innovation to drive economic growth in the digital age.
Chinese AI developers are finding innovative ways to circumvent US export controls on advanced chips by leveraging foreign computing resources. The strategy allows them to access high-performance chips, such as Nvidia’s A100 and H100, which are restricted under US regulations. As the demand for AI capabilities grows, these developers employ various methods to remain competitive in the tech landscape.
One key approach is using cloud computing services from major American providers like Amazon Web Services (AWS) and Microsoft Azure. This method is legally permissible under current US regulations, which focus on directly exporting physical technologies rather than cloud-based computing power.
Additionally, Chinese AI developers are collaborating with brokers and using identity-mapping techniques from the cryptocurrency industry. These brokers help facilitate access to AI servers in countries like Australia, allowing companies to deploy advanced chips without importing them directly into China. For example, entrepreneur Derek Aw has arranged for over 300 servers equipped with Nvidia’s H100 chips to be housed in Australia and utilised by firms in Beijing.
Despite the challenges posed by export controls, many Chinese companies have stockpiled chips and invested in domestic semiconductor manufacturing. While local suppliers often need to catch up to US technologies, this dual approach helps maintain momentum in AI research and development. Legal experts note that as long as technology is not used for military purposes, cloud services to access advanced computing power remain unregulated, highlighting the complexities of enforcing technology trade restrictions.
The ongoing situation illustrates the US government’s challenges in enforcing its trade policies. As Chinese companies continue to adapt and innovate, the US may need to tighten regulations to address emerging loopholes.
A key player in the development of plant-based proteins is generative AI. Paris-based start-up AI Bobby is at the forefront, using AI to enhance protein functionality in meat and dairy alternatives. The company believes this technology can accelerate research, increasing efficiency and accuracy in protein design, which is essential for replicating the qualities of animal proteins.
The functionality of plant-based proteins, such as gelling, nutritional value, and mouthfeel, has often been criticised for falling short of their animal-based counterparts. AI Bobby’s founder, Dominik Grabinski, emphasises that improving these functionalities is crucial to making plant-based products more appealing to consumers. Generative AI, according to Grabinski, has the potential to speed up research by up to ten times and improve the success rate of finding solutions.
One area of focus for AI Bobby is gelation, which is vital for texture and ease of formulation in plant-based meats. By refining this process, the start-up aims to reduce the need for additional ingredients, lowering production costs. AI Bobby aspires to link function to structure in the future, helping producers design proteins that meet specific needs more precisely.
AI Bobby envisions a future where plant-based proteins can surpass animal-derived proteins in functionality. The company aims to empower producers to create alternatives to key animal proteins like collagen, gelatin, and egg white, all through plant-based sources.
BigCommerce is bolstering its AI capabilities through collaboration with Google, aiming to enhance online store performance and drive customer growth. The Austin-based company introduced a suite of new AI-focused solutions during its recent product launch, including tools for personalised product recommendations and AI-generated quote proposal emails, with plans for more features like semantic search and predictive analytics.
These enhancements build on BigCommerce’s partnership with GoogleCloud’s AI technology, which was formed about a year ago. The company is positioning itself against competitors like Shopify and Amazon, which have also integrated AI to improve their platforms. BigCommerce believes these updates will benefit merchants significantly, particularly in terms of efficiency and customer experience.
Despite a challenging journey since going public in 2020, BigCommerce is making substantial investments in AI, and it is already showing positive results. Recent earnings reports indicate an 11% increase in revenue, driven partly by the success of these AI tools, and a reduction in net losses compared to the previous year.
The company remains optimistic that its AI strategy will pay off, helping it compete more effectively in e-commerce. BigCommerce is committed to providing merchants with various AI-powered tools, enabling them to choose the best solutions for their unique needs.
TikTok has unveiled a groundbreaking AI voiceover tool, empowering content creators with the ability to craft personalised voiceovers effortlessly. The new feature allows affiliates to enhance their content by aligning voiceovers with their brand’s tone, making it more engaging and authentic. The ease of use ensures even those with minimal technical skills can produce high-quality voiceovers, streamlining the content creation process.
Affiliate marketers are expected to benefit significantly from this innovation. The tool’s ability to produce custom voiceovers quickly allows marketers to focus more on strategy and less on time-consuming tasks. The AI-generated voices can be tailored to different audiences, enabling affiliates to reach a broader demographic and experiment with various accents and languages.
TikTok’s AI tool provides a cost-effective solution for those working with limited budgets, levelling the playing field between smaller affiliates and larger competitors. The enhanced engagement metrics with personalised content can lead to higher conversion rates, giving affiliates a competitive edge in the market.
As TikTok continues to innovate, staying informed and adaptable will be crucial for affiliates looking to maximise their success. Early adopters of the AI voiceover tool may find themselves ahead of the curve, reaping the benefits of increased audience engagement and improved performance metrics.
FuriosaAI has launched its latest AI inference chip, RNGD, which promises to be a significant accelerator for data centres handling large language models (LLMs) and multimodal model inference. Founded in 2017 by former AMD, Qualcomm, and Samsung engineers, FuriosaAI has rapidly developed cutting-edge technology, culminating in the RNGD chip.
The RNGD chip, developed with the support of TSMC, has demonstrated impressive performance in early tests, particularly with models such as GPT-J and Llama 3.1. The chip’s architecture, featuring a Tensor Contraction Processor (TCP) and 48GB of HBM3 memory, delivers high efficiency and programmability, achieving token throughput of 2,000 to 3,000 tokens per second for models with around 10 billion parameters.
FuriosaAI’s approach to innovation is evident in its quick development and optimisation cycles. Within weeks of receiving silicon for their first-generation chip in 2021, the company achieved notable results in MLPerf benchmarks, with performance improvements reaching 113% in subsequent submissions. The RNGD chip is the next step in their strategy, offering a sustainable solution with a lower power draw than leading GPUs.
The RNGD chip is sampled by early access customers, with a broader release anticipated in early 2025. FuriosaAI’s CEO, June Paik, expressed pride in the team’s dedication and excitement for the future as the company continues to push the boundaries of AI computing.
Elon Musk has urged California to pass the AI bill requiring tech companies to conduct safety testing on their AI models. Musk, who owns Tesla and the social media platform X, has long advocated for AI regulation, likening it to rules for any technology that could pose risks to the public. He specifically called for the passage of California’s SB 1047 bill to address these concerns.
This is a tough call and will make some people upset, but, all things considered, I think California should probably pass the SB 1047 AI safety bill.
For over 20 years, I have been an advocate for AI regulation, just as we regulate any product/technology that is a potential risk…
California lawmakers have been busy with AI legislation, attempting to introduce 65 AI-related bills this season. These bills cover a range of issues, including ensuring algorithmic fairness and protecting intellectual property from AI exploitation. However, many of these bills have yet to advance.
The push for AI regulation comes when countries representing a broader portion of the global population are holding elections, raising concerns about the potential impact of AI-generated content on political processes.
OpenAI, the developer behind ChatGPT, is backing a new California bill, AB 3211, to ensure transparency in AI-generated content. The proposed bill would require tech companies to label content created by AI, which ranges from innocuous memes to deepfakes that could potentially mislead voters in political campaigns. The legislation has gained attention as concerns grow over the impact of AI-generated material, especially in an election year.
The bill has somewhat been overshadowed by another California AI bill, SB 1047, which mandates safety testing for AI models and has faced resistance from the tech industry, including OpenAI. This resistance highlights the complexity of regulating AI while balancing innovation and public safety.
California lawmakers have introduced 65 AI-related bills in this legislative session, covering algorithmic fairness and protecting intellectual property from AI exploitation. However, many of these proposals have yet to advance, leaving AB 3211 as one of the more prominent measures still in play.
OpenAI has expressed the importance of transparency for AI-generated content, especially during elections, advocating for measures like watermarking to help users identify the origins of what they see online. Considering that AI-generated content is a global issue, there are strong concerns that it could influence the upcoming elections in the USA and in other countries.
AB 3211 has already passed the state Assembly with unanimous support and recently cleared the Senate Appropriations Committee. The bill requires a full Senate vote before the legislative session ends on 31 August. If it passes, it will go to Governor Gavin Newsom for approval or veto by 30 September.
Researchers from the Universities of Edinburgh and Dundee are pioneering an AI tool designed to detect early signs of dementia through routine brain scans. Utilising a large dataset of CT and MRI scans from Scottish patients, the team aims to analyse these images with linked health records to identify patterns that may indicate a heightened risk of dementia.
The ultimate goal is to create a digital healthcare tool for radiologists to assess dementia risk during routine scans. Early identification of high-risk patients could lead to the development of more effective treatments, particularly for Alzheimer’s and vascular dementia. The project, known as SCAN-DAN, is part of a larger global collaboration called NEURii, which focuses on advancing digital health tools.
The research is supported by NEURii, which brings together international expertise and funding to overcome barriers to commercialisation. By collaborating with partners like the NHS and the Scottish National Safe Haven, the project ensures the secure handling of patient data, aiming to integrate AI tools into everyday clinical practice.
Experts believe that early diagnosis is crucial for managing dementia effectively. With costly and limited treatments, projects like SCAN-DAN offer hope for more accessible and reliable solutions. The researchers are confident that this initiative could significantly impact how dementia is diagnosed and treated.
A recent study reveals that nearly half of AI-based medical devices approved by the US Food and Drug Administration (FDA) have not been trained on real patient data. Of 521 devices examined, 43% lacked published clinical validation, raising concerns about their effectiveness in real-world settings.
The study highlights that only 22 of these devices were validated through randomised controlled trials, considered the ‘gold standard’ for clinical testing. Some devices relied on ‘phantom images’ instead of real patient data, while others used retrospective or prospective validation methods. Researchers emphasise the importance of conducting proper clinical validation to ensure these technologies are safe and effective.
Researchers hope their findings will prompt the FDA and the medical industry to improve the credibility of AI devices by conducting and publishing clinical validation studies. They believe enhancing these processes’ transparency and rigour will significantly impact patient care.
In Australia, similar regulations exist, with the Therapeutic Goods Administration (TGA) requiring AI-based software to provide information about its training data and suitability for the Australian population. Medical devices must also meet general clinical evidence guidelines to ensure safety and effectiveness.
