Tools & Platforms

Shanghai tech conference showcases AI in action

Published

4 days ago

September 11, 2025

Robbyant”s R1 robot chef ChefZ is on display at the 2025 Inclusion Conference on the Bund in Shanghai. [Provided to chinadaily.com.cn]

The 2025 Inclusion Conference on the Bund, which spotlighted the real-world application of artificial intelligence, embodied intelligence, and advanced technologies across various industries and aspects of daily life, kicked off on Wednesday in the Huangpu World Expo Park in Shanghai.

Industry leaders, researchers, and enthusiasts gathered to explore the latest advancements and discuss the future of technology.

Xeonova, a Hefei-based commercial fusion company, aims to accelerate fusion energy development through AI, according to Wang Ge, chief scientist at the firm.

“We are working to integrate AI into our current fusion engineering process,” Wang said. The company aims to use AI to build digital twins of fusion reactors, enabling rapid iteration and optimization in a virtual environment.

In addition to energy, AI applications in robotics garnered significant attention. Boulhol Clement from France, working in social media in Shanghai, said he was excited about the future and impressed by the AI and robot technology.

“I really like all the technology stuff with AI and with robots, and I think some robots are very impressive,” Clement said, highlighting the potential of robots in various fields, including rescue operations.

Source link

Tools & Platforms

Why the Future of AI in the Arab World Must Begin with the Basics

Published

16 minutes ago

September 15, 2025

Stars of Science

Why the Future of AI in the Arab World Must Begin with the Basics

Accessibility Statement
Skip Navigation

As AI reshapes everything around us, Qatar is doubling down on the vital role of core scientific disciplines—led by programs like Stars of Science—to make regional innovations achieve universal impact.

DOHA, Qatar, Sept. 15, 2025 /PRNewswire/ — Across Qatar and the Arab world, the race to harness artificial intelligence is heating up. Governments, universities, and startup incubators are aligning to transform the region into an AI hub. Yet amid this momentum, leading voices in science and technology are urging a return to fundamentals – especially as studies like MIT’s reveal that students who relied on ChatGPT showed the lowest brain engagement and consistently underperformed compared to peers using search engines or no tools at all.

As the longest-serving juror on Stars of Science, Prof. Fouad Mrad returns in Season 17, bringing decades of expertise to the next generation of Arab innovators.

Dr. Ahmad Nabeel, acclaimed innovator and season 9 finalist, returns for the fourth time as a guest juror in Stars of Science Season 17, bringing his journey from innovator to mentor full circle.

Stars of Science alumnus Mohammed Al-Qassabi captures a celebratory moment with contestants during the casting of Stars of Science Season 17.

Nada Elkharashi, finalist on Stars of Science Season 16, working in the lab as she was refining her project during the development phase.

Watch Arab innovators take the stage in Season 17 of Stars of Science, competing for the title of Top Arab Innovator.

This vision is embodied by Stars of Science, now in its seventeenth season. The edutainment show captures the innovation journey of young Arab innovators who transform their ideas into real-world solutions rooted in scientific principles. Far from treating AI as a buzzword, the program emphasizes the importance of grounding breakthroughs in tested, data-backed experimentation, already generating 14 AI-powered innovations.

“AI is applied science at its core,” said Prof. Fouad Mrad, one of the show’s longest-serving jurors and its science advisor. “What you learned two years ago might already be outdated. But the basics? Those stay with you.”

This belief is tightly woven into Qatar’s broader agenda to build a diversified, knowledge-based economy. Under the Qatar National Vision 2030, the country continues to invest in scientific research and science, technology, engineering, mathematics, and medicine (STEMM) education across all levels. Hamad Bin Khalifa University’s launch of ‘Fanar’, an Arabic-language generative AI platform, empowers Arabic-speaking innovators to apply AI in ways grounded in science and context.

Even on the global stage, this view is taking hold. Demis Hassabis, CEO of Google DeepMind and a 2024 Nobel laureate in Chemistry, recently emphasized that success in AI still depends on mastering fundamental disciplines like mathematics, physics, and biology. His reasoning is simple: AI is a powerful amplifier of knowledge, not a replacement for it.

This approach is already shaping the work of Stars of Science alumni who are showing that AI, when paired with scientific principles, can transform entire fields.

Dr. Ahmad Nabeel, the Kuwaiti finalist from Season 9, created ‘Klens’, a self-cleaning laparoscope that addresses a long-standing challenge in minimally invasive surgery: lens obstruction. The device uses predictive AI, trained on surgical data, to detect when fog or fluids may impair vision and trigger a cleaning mechanism before the view is compromised.

Rather than reinventing a solution, Nabeel’s innovation builds on proven medical practices enhanced through AI. Today, he leads Gulf Medical Technologies. In 2024, his company partnered with Mayo Clinic to further develop and commercialize ‘Klens’. Through this work, Nabeel exemplifies how AI becomes most impactful when it strengthens, not shortcuts, the scientific process.

This alignment of education, innovation, and mentorship is also visible in Qatar Foundation’s wider ecosystem. Qatar Science & Technology Park (QSTP), a global hub for deep tech with impact, and a member of Qatar Foundation, has continued to support Stars of Science and other startups, as part of its mission to create a future where technology and science positively impact humanity and the natural world. At Web Summit Qatar 2025, QSTP launched programs like the Shell.ai Futures Pitch to support AI-focused sustainability ventures, reinforcing the country’s commitment to science-backed innovation.

Looking ahead, Mrad believes that future success in AI across the Arab world will be defined by those who use scientific fundamentals as their springboard.

“The most impactful ideas we see are those that fuse AI with deep domain knowledge,” he said. “In the coming seasons, I expect even more projects that don’t just use AI but elevate it through science.”

By investing in education, building AI tools, and celebrating innovators who use AI responsibly, Qatar is not only keeping pace with global change – it is helping define it.

To follow the contestants’ journeys as they build impactful AI on Stars of Science, find the latest broadcast details on starsofscience.com.

About Stars of Science:

Throughout 17 years of success, Stars of Science – the edutainment TV initiative of Qatar Foundation (QF) – has leveraged its position as the premier innovation show in the Arab world to empower Arab innovators to successfully transform innovative ideas into tangible solutions, strengthening the culture of innovation among Arab youth. In its sustained journey that started in 2009, the show has demonstrated how young Arab innovators develop technological solutions for their communities, aiming to improve people’s well-being, provide financial opportunities to their local citizens, and advance sustainable development.

Over a 12-week process, the contestants develop their solutions experimentally in a shared innovation space, competing against time with the mentorship and support of a team of experienced engineers and product developers.

An expert panel of jurors assesses and selects more promising innovators and their projects every week across several prototyping and testing rounds until three finalists remain to compete for a share of the Grand Prize. Jury deliberation and online voting from the public determine the rankings of the two top winners.

To know more about Stars of Science, please visit: Website, Facebook, Twitter, Youtube, Instagram, Tiktok, and LinkedIn

For media inquiries, please contact: Oussama Rahal – [email protected]

Photo – https://mma.prnewswire.com/media/2772478/Photo_01.jpg
Photo – https://mma.prnewswire.com/media/2772479/Photo_02.jpg
Photo – https://mma.prnewswire.com/media/2772480/Photo_03.jpg
Photo – https://mma.prnewswire.com/media/2772481/Photo_04.jpg
Photo – https://mma.prnewswire.com/media/2772482/Photo_05.jpg

SOURCE Stars of Science

WANT YOUR COMPANY’S NEWS FEATURED ON PRNEWSWIRE.COM?

440k+
Newsrooms &
Influencers

9k+
Digital Media
Outlets

270k+
Journalists
Opted In

Source link

Tools & Platforms

Is AI Going to Replace Nurses?

Published

39 minutes ago

September 15, 2025

HealthLeaders

AI will redefine nursing practice, not replace it, says this CNE.

People all over the country are holding their breath to see how AI will impact the workforce, and in healthcare it’s no different.

AI comes with many promises of care efficiency and cost savings, with the side effect of anxiety about job security and potential displacement. In nursing, the stakes are even higher, with concerns about patient safety and privacy at the forefront.

In 2025 alone, there have been several nursing strikes that have centered concerns about AI, including a National Nurses United march involving 100,000 members who were calling for safe staffing and protections against AI and other untested technologies.

However, from one leader’s perspective, AI will be additive in nursing, not a replacement.

“The hope is that it’s going to be a plus one, and I think that we as nursing leaders really need to ensure that we are at the front of all of this,” said Terry McDonnell, senior vice president and chief nurse executive at Duke University Health System. “We need to be vetting, developing, engaging with industry partners, engaging with operational partners, and we also have to make sure that we bring our staff along with us and have them as part of the conversation.”

The reality of AI in nursing

According to McDonnell, the biggest misconception about AI is that it’s going to replace nursing jobs.

“The reality is that AI has been in healthcare for a very long time, but now it’s to a point where it’s accelerating at a pace that we need to keep up with,” McDonnell said, “and I think we’re always going to need human interaction and high-level human processing.”

One of the primary ways that nurses will use AI is for decision support.

“Gone will be the days of searching long for policies and literature,” McDonnell said. “AI actually helps us sift through a lot of information very quickly.”

AI also allows nurses to be proactive with things like computer vision and algorithms that help notify nurses if a patient is at risk of falling while getting out of bed. With AI in use, nurses won’t have to be physically in the room to know what’s going on with their patients.

“Imagine a world where there’s cameras in a room. It’s part of the normal care setting, and based on algorithms, the nurse will get a notification that a patient might be trying to get out of bed, and they might be at risk for a fall,” McDonnell said. “The nurse can then intervene long before the patient’s on the floor.”

Redefined, not replaced

For CNOs who want to help quell fears among nurses that AI might replace their jobs, McDonnell recommends education and including nurses in the process.

“We’re doing a lot of development here at Duke and we’re letting our frontline nurses be part of the vetting, the development, and the creation of those solutions,” McDonnell said. “It’s really about making sure that people understand what we’re talking about when we talk about AI solutions and tools, and having them be a part of the conversation and not having it be something that gets imposed upon them.”

As AI progresses in the industry, there is plenty of potential for developing nurse-led models of care, McDonnell explained. AI will change care delivery, improve outcomes, and decrease falls and infections.

“It’s going to be interesting to see how we adapt these tools,” McDonnell said, “and how these tools can then help care providers, nurses, physicians, nurse practitioners, and PAs actually be able to focus more and give more of that human interaction that everybody’s been missing as we’ve been trying to do more with the same amount of resources.”

AI also has a bright future in the preventative care space, according to McDonnell, especially when paired with remote patient monitoring and hospital at home technology.

“We know that people do better from infection risk and from recovery when they’re in their home setting,” McDonnell said. “I think with these tools, we’re going to be able to keep people safe in their homes and get them through with remote monitoring.”

For CNOs who are feeling intimidated by implementing AI in their health systems, McDonnell recommends avoiding the narrative that AI is going to take away nursing jobs.

“Embrace [AI], be curious, and learn what the capability is,” McDonnell said, “and most importantly, ensure that your staff and your patients are part of the discussion.”

G Hatfield is the CNO editor for HealthLeaders.

Source link

Tools & Platforms

Why Qwen3 Next Is the Most Efficient AI Model Yet

Published

1 hour ago

September 15, 2025

Julian Horsey

What if the future of artificial intelligence wasn’t just about being smarter, but also leaner, faster, and more adaptable? Enter Qwen3 Next, a new AI model that challenges the notion that bigger is always better. With an astonishing 80 billion parameters at its core, it achieves high-performance results while activating just a fraction of its potential during inference. This isn’t just a technical feat, it’s a paradigm shift. Imagine an AI capable of rivaling the giants while consuming a fraction of the computational resources. In a world where efficiency often feels like an afterthought, Qwen3 Next flips the script, proving that innovation and practicality can go hand in hand.

In this feature, Sam Witteveen pulls back the curtain on what makes Qwen3 Next a true fantastic option. From its hybrid attention mechanisms to its sparse inference architecture, every design choice reflects a bold vision for the future of AI. You’ll discover how this model not only redefines benchmarks but also sets the stage for scalable, multilingual, and agentic capabilities that adapt to the demands of a rapidly evolving world. Whether you’re intrigued by its ability to predict multiple tokens simultaneously or its promise of cost-effective performance, Qwen3 Next offers a glimpse into what’s next for artificial intelligence. After all, the future isn’t just about building bigger, it’s about building smarter.

Qwen3 Next Overview

TL;DR Key Takeaways :

Qwen3 Next is an 80-billion-parameter mixture-of-experts (MoE) AI model that activates only 3 billion parameters during inference, achieving high performance with reduced computational demands.
Key innovations include a hybrid attention mechanism, sparse inference activating just 3.7% of parameters, and a 512-expert architecture for precision and adaptability across tasks.
The model supports multi-token prediction and speculative decoding, allowing faster and more efficient inference for time-sensitive applications.
Trained on 15 trillion tokens from a 36 trillion token corpus, Qwen3 Next delivers scalable performance while minimizing resource usage, with potential for further optimization.
It offers multilingual and agentic capabilities, excelling in reasoning, tool use, and multi-step workflows, while setting new benchmarks in the global AI landscape with its innovative design.

Core Innovations That Define Qwen3 Next

Qwen3 Next introduces a suite of new features that distinguish it from other AI models. These innovations not only enhance its functionality but also set new benchmarks for the design and application of future AI systems.

Hybrid Attention Mechanism: This advanced mechanism optimizes how the model processes information, improving its ability to handle complex tasks efficiently. It also serves as a blueprint for future proprietary AI systems.
Sparse Inference: By activating only 3.7% of its parameters during inference, Qwen3 Next achieves remarkable speed and resource efficiency without compromising on performance, making it a cost-effective solution for diverse applications.
Mixture-of-Experts Architecture: With 512 specialized experts, the model excels at managing a wide variety of tasks, offering unparalleled precision and adaptability across different domains.

These features collectively ensure that Qwen3 Next not only meets but exceeds expectations for efficiency, scalability, and performance, making it a standout in the competitive AI landscape.

Enhanced Inference with Multi-Token Prediction

A defining feature of Qwen3 Next is its ability to predict multiple tokens simultaneously, significantly accelerating the inference process. This capability allows for faster and more efficient generation of results, making it particularly valuable in time-sensitive applications. Additionally, the model incorporates speculative decoding, a innovative technique that improves decoding efficiency while maintaining high levels of accuracy. These advancements align with the latest research trends, making sure that Qwen3 Next remains at the forefront of AI development and continues to deliver practical benefits for users.

Qwen3 Next : Behind the Curtain

Here are more detailed guides and articles that you may find helpful on Qwen AI models.

Efficient Training for Scalable Performance

Qwen3 Next was trained on 15 trillion tokens derived from a 36 trillion token corpus, achieving exceptional performance while minimizing computational costs. This efficient training process not only reduces resource usage but also leaves room for further optimization. Extending the training to the full corpus could unlock even greater potential, making Qwen3 Next a scalable and future-ready solution. For you, this translates to a model that is both powerful and adaptable, capable of evolving to meet increasingly complex demands.

Benchmark Excellence and Versatility

Qwen3 Next consistently outperforms its predecessors and rivals larger models across a wide range of benchmarks. It is available in two distinct versions—“thinking” and “instruct”—each tailored to specific use cases. The “thinking” version excels in advanced reasoning tasks, while the “instruct” version is optimized for task-specific instructions. This dual approach ensures that Qwen3 Next delivers consistent, reliable results, offering the flexibility to address diverse requirements effectively.

Multilingual and Agentic Capabilities

Designed with global applications in mind, Qwen3 Next is capable of processing and generating responses in multiple languages. While its internal reasoning primarily occurs in English, its multilingual capabilities make it adaptable to various linguistic contexts. This versatility is further enhanced by its agentic abilities, which include tool use, function calling, and multi-step reasoning. These features empower you to tackle complex workflows with confidence, allowing efficient problem-solving and decision-making in diverse scenarios.

Redefining the Global AI Landscape

The development of Qwen3 Next underscores the innovation and openness of Chinese AI labs, setting a new benchmark in the global AI ecosystem. Its design choices, such as sparse inference and multi-token prediction, challenge competitors to rethink their strategies and adapt to the rapidly evolving landscape. For example, organizations like Meta may need to incorporate similar advancements to remain competitive. By pushing the boundaries of what AI can achieve, Qwen3 Next not only redefines current standards but also shapes the trajectory of future AI development.

A Vision for the Future

Qwen3 Next is more than just an AI model, it represents a forward-thinking vision for the future of artificial intelligence. By combining innovation, efficiency, and performance, it sets a new standard for what AI systems can accomplish. Whether you are exploring multilingual processing, using agentic capabilities, or optimizing computational resources, Qwen3 Next offers a robust and adaptable solution. It addresses today’s challenges while anticipating the demands of tomorrow, making sure that you remain at the forefront of technological progress.

Media Credit: Sam Witteveen

Filed Under: AI, Top News

Latest Geeky Gadgets Deals

Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.

Source link