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Category: robotics/AI – Page 10

Triple cardiovascular disease detection with an artificial intelligence-enabled stethoscope (TRICORDER): design and rationale for a decentralised, real-world cluster-randomised controlled trial and implementation study

Introduction Early detection of cardiovascular disease in primary care is a public health priority, for which the clinical and cost-effectiveness of an artificial intelligence-enabled stethoscope that detects left ventricular systolic dysfunction, atrial fibrillation and cardiac murmurs is unproven but potentially transformative.

Methods and analysis TRICORDER is a pragmatic, two-arm, multi-centre (decentralised), cluster-randomised controlled trial and implementation study. Up to 200 primary care practices in urban North West London and rural North Wales, UK, will be randomised to usual care or to have artificial intelligence-enabled stethoscopes available for use. Primary care clinicians will use the artificial intelligence-enabled stethoscopes at their own discretion, without patient-level inclusion or exclusion criteria.

GPT-5 prompting guide

GPT-5, our newest flagship model, represents a substantial leap forward in agentic task performance, coding, raw intelligence, and steerability.

While we trust it will perform excellently “out of the box” across a wide range of domains, in this guide we’ll cover prompting tips to maximize the quality of model outputs, derived from our experience training and applying the model to real-world tasks. We discuss concepts like improving agentic task performance, ensuring instruction adherence, making use of newly API features, and optimizing coding for frontend and software engineering tasks — with key insights into AI code editor Cursor’s prompt tuning work with GPT-5.

We’ve seen significant gains from applying these best practices and adopting our canonical tools whenever possible, and we hope that this guide, along with the prompt optimizer tool we’ve built, will serve as a launchpad for your use of GPT-5. But, as always, remember that prompting is not a one-size-fits-all exercise — we encourage you to run experiments and iterate on the foundation offered here to find the best solution for your problem.

Tesla Masterplan Part 4: Coming Soon

Questions to inspire discussion.

🇦🇺 Q: How was Tesla’s FSD supervised launch received in Australia? A: Tesla’s FSD supervised launch in Australia received fair coverage from mainstream media, including a 4.5-minute segment on national news, without Tesla paying for advertising.

🚘 Q: What are the key features of Tesla’s FSD supervised system? A: Tesla’s FSD supervised system uses cameras and advanced software to autonomously accelerate, brake, and steer, but requires the driver to be responsible and ready to take control at any time.

FSD Safety Concerns.

⚠️ Q: What safety issues have been reported with Tesla’s FSD supervised system? A: Tesla’s FSD supervised system has been involved in multiple accidents overseas, but in most cases, the driver was distracted and tried to blame the car, highlighting the need for drivers to take full responsibility.

🇺🇸 Q: What legal challenges has Tesla faced with FSD in the US and Canada? A: Tesla’s FSD supervised system has been slapped with lawsuits in the US and Canada due to multiple crashes, with Tesla stating that in most cases, the driver was distracted and not using the system properly.

Continue reading “Tesla Masterplan Part 4: Coming Soon” | >

Transferrin receptor–targeted anti-amyloid antibody enhances brain delivery and mitigates ARIA

Paper on a promising Alzheimer’s immunotherapy: engineered asymmetric anti-amyloid-β antibody with a transferrin receptor binding domain for crossing the blood-brain-barrier and a mutation which mitigates harmful side effects seen in past versions of this type of treatment. #immunotherapy #alzheimers

Amyloid-related imaging abnormalities (ARIA), side effects of anti-amyloid drugs seen in magnetic resonance imaging of the brain, are a major safety concern in patients with Alzheimer’s disease. We developed an antibody transport vehicle (ATV) targeting transferrin receptor (TfR) for brain delivery of anti-amyloid-β protein (anti-Aβ) using asymmetrical Fc mutations (ATVcisLALA) that mitigates TfR-related liabilities and retains effector function when bound to Aβ. Administration of ATVcisLALA:Aβ in mice exhibited broad brain distribution and enhanced parenchymal plaque target engagement. This biodistribution reduced ARIA-like lesions and vascular inflammation. Taken together, ATVcisLALA has the potential to improve the next generation of Aβ immunotherapy through enhanced biodistribution mediated by transport across the blood-brain barrier.

Artificial neuron merges DRAM with MoS₂ circuits to better emulate brain-like adaptability

The rapid advancement of artificial intelligence (AI) and machine learning systems has increased the demand for new hardware components that could speed up data analysis while consuming less power. As machine learning algorithms draw inspiration from biological neural networks, some engineers have been working on hardware that also mimics the architecture and functioning of the human brain.

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