Twin Health Secures $53M to Expand AI Digital Twin for Metabolic Health
Twin Health has announced a $53 million investment led by Maj Invest of Denmark to accelerate the expansion of its AI digital twin technology, announced in a press release. This funding aims to enhance Twin Health's reach among health plans and Fortune 500 clients across various sectors, including retail, healthcare, and technology.
The company has also shared results from a study published in the New England Journal of Medicine Catalyst, highlighting the effectiveness of its AI digital twin in treating diabetes and promoting weight loss without the need for high-cost medications. The digital twin technology provides personalized insights into metabolism, nutrition, sleep, and physical activity, offering continuous care for metabolic health.
Twin Health focuses on reducing healthcare costs by eliminating the reliance on medications and extreme diets. The company offers performance-based care, where clients only pay when members achieve significant clinical outcomes, such as A1C reduction or weight loss. This approach aligns with the growing demand for responsible GLP-1 strategies and long-term cost reduction in healthcare.
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Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
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