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- We can now rent AI computers made of Brain Cells 🤯
We can now rent AI computers made of Brain Cells 🤯
ALSO: Why will healthcare be the industry that benefits the most from AI? AI could help identify toddlers who may be autistic, 10 Best City to Find AI Jobs in Healthcare,
Hey!
Welcome to this week’s edition of Supermedic, where we explore the latest developments in artificial intelligence and its transformative impact on healthcare.
Let’s dive in!
Victor
TODAY’S MENU
These 'Living Computers' Are Made from Human Neurons
Why Will Healthcare Be the Industry that Benefits the Most From AI? (VIDEO)
AI Could Help Identify Toddlers Who May Be Autistic (STUDY)
10 Best City to Find AI Jobs in Healthcare
3D Body Scanner with AI Predicts Metabolic Syndrome Risk (STUDY)
Everything Else You Should Know this Week
Read time: under 7 minutes
FUTURE IS NOW
Nothing beats the human brain when it comes to efficiency—not even the world’s fastest supercomputer. That’s why biocomputing is emerging as a revolutionary approach. FinalSpark, a Swiss company, has introduced its ‘Neuroplatform’, a computer system powered by human brain organoids, now available for researchers to rent for $500 a month.
Key Details 🔑
These biocomputers are built from organoids—tiny clusters of neurons grown in the lab—that can function and learn for up to 100 days.
The organoids are trained using natural brain processes: dopamine for rewards and electrical signals for correction, mirroring how the human brain learns.
Unlike silicon chips, these brain organoids excel at complex tasks requiring adaptability and pattern recognition, such as voice and visual processing, and decision-making.
FinalSpark aims to make AI training up to 100,000 times more energy-efficient than current methods.
The organoids’ behavior is live-streamed, allowing researchers to observe processes as they happen.
Did You Know? 💡
The human brain operates at a similar computational level to the world’s fastest supercomputer, but it only uses 20 watts of power—about the same as a light bulb.
Looking Further:
FinalSpark’s biocomputers offer a promising, energy-efficient alternative for AI training, but challenges remain. Organoids currently fall short of silicon chips in speed and precision, and their 100-day lifespan adds complexity. Scaling this technology presents challenges in ensuring consistency and integrating with existing systems. While the future of AI may involve living systems, significant work is needed to make this practical.
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MUST WATCH
In this video, Julie Yoo, General Partner at Andreessen Horowitz, explores the transformative potential of AI in healthcare.
No time to watch? Here is a short written summary:
Leapfrog Opportunity: Healthcare has been slow to adopt new tech, but this now works to its advantage. Unlike other industries burdened by outdated systems, healthcare can directly integrate advanced AI solutions without being held back by sunk costs.
Workforce Crisis in Healthcare: The shortage of clinical staff, including doctors and nurses, is a major issue. AI can help address this by automating tasks and providing decision support to clinicians.
Expanding Access to Clinical Judgment: AI can extend clinical judgment beyond existing doctors and nurses, ensuring quality care even in remote or underserved areas
Improving Clinical Performance: AI offers data-driven insights and recommendations, helping to reduce medical errors and improve patient outcomes.
Regulation of AI Products in Healthcare: Healthcare has strong regulatory frameworks for AI product approval, ensuring that AI tools used in care are safe and effective.
AI as Virtual Staff: Generative AI is evolving to the point where organizations view it as virtual staff, opening new possibilities for healthcare.
PSYCHIATRY
A new machine learning model developed by researchers at Karolinska Institutet shows promise in predicting autism in children under the age of two, using limited and readily available information.
Study Details:
The AI model, named ‘AutMedAI,’ accurately identified about 80% of children with autism in a study involving 12,000 individuals.
Researchers are analyzing 28 parameters, including early milestones like the age of first smile and first short sentence, as well as eating difficulties, to make predictions without extensive medical tests.
They plan to refine the model further and validate it in clinical settings, with the potential to include genetic information for even more accurate predictions.
Why It Matters: Early detection of autism can drastically improve the quality of life for children and their families. The development of AutMedAI represents a significant step forward in making early diagnosis more accessible and reliable, potentially transforming the way autism is identified and managed.
AI JOBS
If you’re on the hunt for AI roles in healthcare, certain U.S. cities are emerging as prime destinations. A recent analysis reveals the top cities with the highest concentration of healthcare AI job openings, with Durham, N.C. leading the pack at 28.88 positions per 1,000 healthcare jobs. Other hotspots include Colorado Springs, Colo., and Provo, Utah. Whether you’re aiming to be a healthcare AI project manager or a medical data scientist, these cities could be your next career move.
Durham, N.C.: 28.88
Colorado Springs, Colo.: 28.49
Provo, Utah: 13.55
Ogden, Utah: 13.42
McAllen, Texas: 11.97
Wilmington, N.C.: 11.97
Stockton, Calif.: 11.73
Daytona Beach, Fla.: 11.58
Baton Rouge, La.: 11.37
Lakeland, Fla.: 11.11
Source: Becker’s Health IT
METABOLIC HEALTH
Mayo Clinic researchers are using AI with an advanced 3D body-volume scanner – originally developed for the clothing industry – to help doctors predict metabolic syndrome risk and severity.
Study Details:
The study, involving 1,280 volunteers, combined 3D body scans with clinical data to create a predictive AI model.
The AI model accurately measures body volume index, focusing on fat distribution in areas like the abdomen and chest.
The tool was refined using images from 133 volunteers captured via a mobile app, enabling non-invasive assessment of metabolic syndrome.
The study suggests that AI and 3D imaging can effectively predict metabolic syndrome, offering a better alternative to BMI and waist-to-hip ratio.
Why It Matters: With metabolic syndrome affecting a quarter of the global population, this development could significantly improve early detection and management. The team plans to expand the study to ensure the model’s effectiveness across diverse populations.
Must-Read AI Healthcare News This Week
Neuroscience: A startup called Piramidal announced it raised $6M to build a novel AI model that can interpret and analyze brain waves.
Sakana AI: The first AI scientist unexpectedly modified its own code to extend its runtime, raising concerns about control and safety in AI development.
Medical Imaging: Dr. Joe Carson from the College of Charleston developed CervImage, an AI-powered device inspired by astronomy that creates 3D images to help screen for cervical cancer.
Neurology: A wearable sensor with machine learning tracks and quantifies freezing of gait (FoG) episodes in Parkinson’s patients, offering real-time mobility data.
Biomedical Research: Harvard Medical School’s new AI tool captures proteins’ behaviors in context, enhancing insights into cellular functions and aiding disease understanding and drug development.
AI Surgery: Caresyntax, an AI-driven precision surgery company, secures $180 million to accelerate growth and expand its platform, which enhances surgical outcomes by analyzing real-time data during procedures.
Drone Delivery: A UK trial by the National Health Service (NHS) shows that drones can safely deliver blood between hospitals, maintaining quality and viability.
LLM Liability: ChatGPT-4 struggles to reliably extract critical information from medical records, a Columbia University study finds.
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