New Global Ovarian Cancer Research Consortium Joins Forces with Microsoft's AI For Good Lab To Launch First-Of-Its-Kind $1M+ Global Grant To Improve Survival Rates
TORONTO, May 8, 2025 /CNW/ - Today marks World Ovarian Cancer Day and the launch of the Global Ovarian Cancer Research Consortium — a first-of-its-kind alliance uniting four leading ovarian cancer research organizations across the United States, Australia, Canada, and the United Kingdom.
Together, the Consortium is announcing its inaugural initiative: a game-changing $1 million grant, with an additional $1 million in compute support from Microsoft's AI for Good Lab, to address the global challenge in ovarian cancer survival rates. Globally, 324,000 women are diagnosed with ovarian cancer and 207,000 women die from the disease each year. The Consortium's groundbreaking AI Accelerator Grant is a bold new effort that will ignite a wave of innovation in AI-powered ovarian cancer research — bringing hope, and potentially life-saving breakthroughs, to women around the world.
The Consortium, formed in 2024, brings together leading ovarian cancer organizations from the United States, Australia, Canada, and the United Kingdom. Their mission: to combine forces, resources, and determination to accelerate progress where it's desperately needed. Now, with the support of Microsoft's technology and expertise, the Consortium is poised to rewrite the future of ovarian cancer care.
Progress in ovarian cancer research is lagging dangerously behind other diseases. It's predicted that by 2050 the number of women around the world diagnosed with ovarian cancer will rise over 55% to 503,448 and the number of women dying from ovarian cancer is projected to increase to 350,956 each year.
"The complexity of ovarian cancer, with its vague symptoms and many types, makes it difficult to diagnose early and treat at advanced stages. Yet these are accomplishments we know we need to save lives. This is why the $1 million collaborative investment in AI-powered ovarian cancer research is critically needed," shares Tania Vrionis, CEO of Ovarian Cancer Canada. "Through this AI Accelerator Grant, we can harness AI to understand ovarian cancer and its impact on women faster than ever. Our global philanthropic partnership, support from Microsoft's AI for Good Lab, and international research collaboration are key to accelerating change. After decades without real progress, women facing ovarian cancer deserve breakthroughs as quickly as we can make them."
AI is already revolutionizing cancer diagnoses—from breast to brain, skin to thyroid—with stunning advances. But ovarian cancer has yet to feel the full power of this transformation. That changes now.
With this urgent call to action, the Consortium is summoning the world's brightest minds to harness AI and tip the scales toward survival.
"When I heard my treatment options, I was not happy. To treat my cancer, they had to remove my uterus, my ovaries, and I knew I could no longer have a child on my own. But I also knew that I wanted to live so I had no choice," shares Julia, a 38-year-old Canadian woman diagnosed with advanced low-grade serous ovarian cancer, a rare form of the disease. Despite undergoing life-altering treatment options when diagnosed with advanced ovarian cancer, women still face a high chance of their cancer returning, just as Julia's did in 2023. To improve their treatment options and disease outcomes, innovative research is urgently required. "We need to make ovarian cancer a top priority. It doesn't have the same visibility and awareness that other cancers have but women like me have limited options when facing the disease," adds Julia. "The truth is that change will only happen if research funding increases in a significant way. Ovarian Cancer Canada has helped me a lot through my journey. They support me, share information, and most importantly, with research investments like this, they gave me what I was missing most - hope."
Researchers will be asked to form teams that will include a representative from each of the four countries to compete for the new grant. The successful grant will support any area of research that will improve survival rates. It must have a multi-jurisdictional team from across the grant-funded countries and a multidisciplinary team, including an AI expert. To learn more about the grant, visit https://ocrahope.org/research/information-for-researchers/grant-programs/
Microsoft is generously partnering on this grant to donate up to $1m of in-kind Azure compute credits to the successful project through Microsoft's AI for Good Lab-partnership with OCRA. Microsoft's cloud computing power will enable the successful applicants to accelerate progress against ovarian cancer.
"New discoveries are needed to find lifesaving treatments for ovarian cancer, a cancer that tragically still has a low survival rate. Equipping leading researchers around the globe with powerful AI tools and computing resources will help accelerate their critical work, hopefully leading to breakthroughs that save women's lives. Microsoft's AI for Good Lab is proud to support ovarian cancer research through this grant." said Juan Lavista Ferres, Microsoft Chief Data Scientist and Director of Microsoft's AI for Good Lab.
ABOUT OVARIAN CANCER CANADAWe are the only national health charity in Canada focused on uncovering key discoveries that can change the reality of an ovarian cancer diagnosis. We are building research capacity, unlocking insights into rarer forms of the disease, addressing urgent needs, and bringing hope to people across the country. After decades without real change, improved outcomes are finally possible.
The 3,000 Canadians diagnosed with ovarian cancer every year deserve our attention . They deserve our focus on demanding action, delivering change, and transforming their lives. We will not rest until women are able to live freely, fully, and uninhibited by ovarian cancer. Towards this goal, we are relentless. Learn more at ovariancanada.org.
SOURCE Ovarian Cancer Canada
View original content to download multimedia: http://www.newswire.ca/en/releases/archive/May2025/08/c4537.html
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
21 minutes ago
- Yahoo
Chinese AI firms form alliances to build domestic ecosystem amid US curbs
SHANGHAI (Reuters) -China's artificial intelligence companies have announced two new industry alliances, aiming to develop a domestic ecosystem to reduce dependence on foreign tech as they seek to cope with U.S. export restrictions on advanced Nvidia chipsets. The announcements were timed to coincide with the three-day World Artificial Intelligence Conference in Shanghai ending on Monday. The conference also showcased a slew of new products, such as an AI computing system from Huawei that experts believe rivals Nvidia's most advanced offering, as well as consumer-friendly products such as several kinds of digital AI glasses. The "Model-Chip Ecosystem Innovation Alliance" brings together Chinese developers of large language models (LLMs) and AI chip manufacturers. "This is an innovative ecosystem that connects the complete technology chain from chips to models to infrastructure," said Zhao Lidong, CEO of Enflame, one of the participating chipmakers. Other manufacturers of graphics processing units (GPUs) in the alliance include Huawei, Biren, and Moore Threads, which have been hit by U.S. sanctions that block them from purchasing advanced tech made with U.S. know-how. The alliance was announced by StepFun, an LLM developer. A second alliance, the Shanghai General Chamber of Commerce AI Committee, aims to "promote the deep integration of AI technology and industrial transformation." Participants include SenseTime, also sanctioned by the U.S. and which has pivoted from facial recognition technology to LLMs. Others are StepFun and another LLM developer, MiniMax, as well as chipmakers Metax and Iluvatar CoreX. One of the most talked about products at the conference was Huawei's CloudMatrix 384 which incorporates 384 of its latest 910C chips and outperforms Nvidia's GB200 NVL72 on some metrics, according to U.S. research firm SemiAnalysis. Huawei's system design capabilities have meant that it has been able to use more chips and system-level innovations to compensate for weaker individual chip performance, SemiAnalysis said. At least six other Chinese computing firms showcased similar "clustering" chip technology. Metax demonstrated an AI supernode featuring 128 C550 chips designed to support large-scale liquid-cooled data centre requirements. Other events included Tencent's unveiling of its open-source Hunyuan3D World Model 1.0, which the company said enables users to generate interactive 3D environments through text or image prompts. Baidu announced what it said was next-generation "digital human" technology that helps businesses to create virtual livestreamers. It features "cloning technology" that can replicate a human's voice, tone, and body language from just 10 minutes of sample footage. Alibaba was among those announcing AI glasses. Its Quark AI Glasses are powered by its Qwen AI model and are due to be released in China by the end of 2025. They will allow users to access the tech giant's map service for easy navigating and to use Alipay by scanning QR codes with voice commands. Connectez-vous pour accéder à votre portefeuille
Axios
22 minutes ago
- Axios
Musk announces Tesla, Samsung Electronics chip supply deal
Tesla CEO Elon Musk said late Sunday the automaker has signed a deal to obtain semiconductor chips from Samsung Electronics. The big picture: Samsung had announced Saturday that it had struck a $16.5 billion supply agreement, but it didn't name the company. The announcement comes after Samsung, one of the world's largest memory chip makers, acknowledged last year that it had fallen behind in the AI chips war. Driving the news: "Samsung's giant new Texas fab will be dedicated to making Tesla's next-generation AI6 chip. The strategic importance of this is hard to overstate," Musk wrote on his platform X. "Samsung currently makes AI4. TSMC will make AI5, which just finished design, initially in Taiwan and then Arizona," Musk added. "Samsung agreed to allow Tesla to assist in maximizing manufacturing efficiency. This is a critical point, as I will walk the line personally to accelerate the pace of progress. And the fab is conveniently located not far from my house."
Forbes
an hour ago
- Forbes
Mistral AI's Environmental Audit Puts Spotlight On AI's Hidden Costs
Mistral AI Mistral AI has quantified the environmental price of artificial intelligence with unprecedented transparency, releasing what appears to be the first comprehensive lifecycle assessment of a large language model. The French AI startup's detailed analysis of its Mistral Large 2 model reveals that training alone generated 20,400 metric tons of carbon dioxide equivalent and consumed 281,000 cubic meters of water over 18 months. This disclosure comes as enterprises face dual pressures - implementing AI to stay competitive while fulfilling sustainability commitments. The audit provides decision-makers with concrete data points that were previously hidden behind industry opacity, enabling more informed technology adoption strategies. The numbers from Mistral's assessment illustrate the resource intensity of AI. Training the 123 billion parameter model required energy equivalent to 4,500 gasoline-powered cars operating for a year, while water consumption matched filling 112 Olympic-sized swimming pools. Each individual query through Mistral's Le Chat assistant generates 1.14 grams of CO2 equivalent and consumes 45 milliliters of water, roughly equivalent to growing a small radish. Mistral AI More significantly, the analysis reveals that operational phases have a greater impact on the environment. Training and inference account for 85% of water consumption, far exceeding the environmental cost of hardware manufacturing or data center construction. This operational dominance means that environmental costs accumulate continuously as model usage scales up. Mistral's research identifies actionable strategies for reducing environmental impact. Geographic location has a significant influence on carbon footprint, with models trained in regions with renewable energy and cooler climates exhibiting markedly lower emissions. The study demonstrates a strong correlation between model size and environmental cost, with larger models generating impacts roughly one order of magnitude higher for equivalent token generation. These findings suggest specific optimization approaches. Enterprises can reduce environmental impact by selecting appropriately sized models for specific use cases rather than defaulting to larger, general-purpose systems. Continuous batching techniques that group queries can minimize computational waste, while deploying models in regions with clean energy grids substantially reduces carbon emissions. Mistral's disclosure strategy differs significantly from that of its competitors. While OpenAI CEO Sam Altman recently claimed ChatGPT queries consume just 0.32 milliliters of water per request, the lack of a detailed methodology makes meaningful comparison difficult. This transparency gap presents opportunities for companies willing to provide comprehensive environmental data, allowing them to differentiate themselves competitively. The audit establishes environmental transparency as a key differentiator in the enterprise AI market. As sustainability metrics increasingly influence procurement decisions, vendors providing detailed environmental impact data gain advantages in enterprise sales cycles. This transparency enables more sophisticated vendor evaluations that balance performance requirements against environmental costs. For technology executives, Mistral's audit provides decision-making criteria previously unavailable. Organizations can now factor environmental impact into AI procurement decisions, alongside traditional metrics such as performance and cost. The data enables more sophisticated total cost of ownership calculations that include environmental externalities. Looking ahead, environmental performance may become as critical as computational performance in selecting AI vendors. Organizations that establish environmental accounting practices now position themselves advantageously as regulatory requirements expand and stakeholder scrutiny intensifies. The Mistral audit demonstrates that detailed environmental measurement is feasible, potentially making opacity from other vendors increasingly untenable in enterprise markets.
